Special Issue "10th Anniversary of Information—Emerging Research Challenges"

A special issue of Information (ISSN 2078-2489).

Deadline for manuscript submissions: closed (31 December 2019).

Special Issue Editor

Prof. Dr. Willy Susilo
Website
Guest Editor
School of Computer Science and Software Engineering, University of Wollongong, Northfields Avenue, Wollongong NSW 2522, Australia
Interests: cryptography; computer security; design of signature schemes
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Information marks its 10th anniversary in 2019. Over the past decade, Information has published nearly 800 papers on the development of information science and technology, as well as their application in a broad variety of areas. Moreover, in the last few years, the journal has grown dramatically. Without the continuous support of our authors, reviewers, editors, and readers, the growth of Information would not have been possible.

To celebrate this anniversary, we are launching this Special Issue, entitled “10th Anniversary of Information—Emerging Research Challenges”. The aim of this Special Issue is to collect a set of high-quality papers that cover a broad scope of information. Particularly, we encourage researchers to present comprehensive review papers that highlight the most recent advances in the field of information science.

Prof. Dr. Willy Susilo
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (14 papers)

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Research

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Open AccessArticle
TwiFly: A Data Analysis Framework for Twitter
Information 2020, 11(5), 247; https://doi.org/10.3390/info11050247 - 02 May 2020
Cited by 1 | Viewed by 1106
Abstract
Over the last decade, there have been many changes in the field of political analysis at a global level. Through social networking platforms, millions of people have the opportunity to express their opinion and capture their thoughts at any time, leaving their digital [...] Read more.
Over the last decade, there have been many changes in the field of political analysis at a global level. Through social networking platforms, millions of people have the opportunity to express their opinion and capture their thoughts at any time, leaving their digital footprint. As such, massive datasets are now available, which can be used by analysts to gain useful insights on the current political climate and identify political tendencies. In this paper, we present TwiFly, a framework built for analyzing Twitter data. TwiFly accepts a number of accounts to be monitored for a specific time-frame and visualizes in real time useful extracted information. As a proof of concept, we present the application of our platform to the most recent elections of Greece, gaining useful insights on the election results. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessArticle
A Self-Operating Time Crystal Model of the Human Brain: Can We Replace Entire Brain Hardware with a 3D Fractal Architecture of Clocks Alone?
Information 2020, 11(5), 238; https://doi.org/10.3390/info11050238 - 27 Apr 2020
Viewed by 2016
Abstract
Time crystal was conceived in the 1970s as an autonomous engine made of only clocks to explain the life-like features of a virus. Later, time crystal was extended to living cells like neurons. The brain controls most biological clocks that regenerate the living [...] Read more.
Time crystal was conceived in the 1970s as an autonomous engine made of only clocks to explain the life-like features of a virus. Later, time crystal was extended to living cells like neurons. The brain controls most biological clocks that regenerate the living cells continuously. Most cognitive tasks and learning in the brain run by periodic clock-like oscillations. Can we integrate all cognitive tasks in terms of running clocks of the hardware? Since the existing concept of time crystal has only one clock with a singularity point, we generalize the basic idea of time crystal so that we could bond many clocks in a 3D architecture. Harvesting inside phase singularity is the key. Since clocks reset continuously in the brain–body system, during reset, other clocks take over. So, we insert clock architecture inside singularity resembling brain components bottom-up and top-down. Instead of one clock, the time crystal turns to a composite, so it is poly-time crystal. We used century-old research on brain rhythms to compile the first hardware-free pure clock reconstruction of the human brain. Similar to the global effort on connectome, a spatial reconstruction of the brain, we advocate a global effort for more intricate mapping of all brain clocks, to fill missing links with respect to the brain’s temporal map. Once made, reverse engineering the brain would remain a mere engineering challenge. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessArticle
Improving Power and Resource Management in Heterogeneous Downlink OFDMA Networks
Information 2020, 11(4), 203; https://doi.org/10.3390/info11040203 - 10 Apr 2020
Cited by 1 | Viewed by 879
Abstract
In the past decade, low power consumption schemes have undergone degraded communication performance, where they fail to maintain the trade-off between the resource and power consumption. In this paper, management of resource and power consumption on small cell orthogonal frequency-division multiple access (OFDMA) [...] Read more.
In the past decade, low power consumption schemes have undergone degraded communication performance, where they fail to maintain the trade-off between the resource and power consumption. In this paper, management of resource and power consumption on small cell orthogonal frequency-division multiple access (OFDMA) networks is enacted using the sleep mode selection method. The sleep mode selection method uses both power and resource management, where the former is responsible for a heterogeneous network, and the latter is managed using a deactivation algorithm. Further, to improve the communication performance during sleep mode selection, a semi-Markov sleep mode selection decision-making process is developed. Spectrum reuse maximization is achieved using a small cell deactivation strategy that potentially identifies and eliminates the sleep mode cells. The performance of this hybrid technique is evaluated and compared against benchmark techniques. The results demonstrate that the proposed hybrid performance model shows effective power and resource management with reduced computational cost compared with benchmark techniques. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessArticle
Logic-Based Technologies for Intelligent Systems: State of the Art and Perspectives
Information 2020, 11(3), 167; https://doi.org/10.3390/info11030167 - 22 Mar 2020
Cited by 7 | Viewed by 1735
Abstract
Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at [...] Read more.
Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessFeature PaperArticle
Triadic Automata and Machines as Information Transformers
Information 2020, 11(2), 102; https://doi.org/10.3390/info11020102 - 13 Feb 2020
Viewed by 873
Abstract
Algorithms and abstract automata (abstract machines) are used to describe, model, explore and improve computers, cell phones, computer networks, such as the Internet, and processes in them. Traditional models of information processing systems—abstract automata—are aimed at performing transformations of data. These transformations are [...] Read more.
Algorithms and abstract automata (abstract machines) are used to describe, model, explore and improve computers, cell phones, computer networks, such as the Internet, and processes in them. Traditional models of information processing systems—abstract automata—are aimed at performing transformations of data. These transformations are performed by their hardware (abstract devices) and controlled by their software (programs)—both of which stay unchanged during the whole computational process. However, in physical computers, their software is also changing by special tools such as interpreters, compilers, optimizers and translators. In addition, people change the hardware of their computers by extending the external memory. Moreover, the hardware of computer networks is incessantly altering—new computers and other devices are added while other computers and other devices are disconnected. To better represent these peculiarities of computers and computer networks, we introduce and study a more complete model of computations, which is called a triadic automaton or machine. In contrast to traditional models of computations, triadic automata (machine) perform computational processes transforming not only data but also hardware and programs, which control data transformation. In addition, we further develop taxonomy of classes of automata and machines as well as of individual automata and machines according to information they produce. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
Open AccessArticle
A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G
Information 2020, 11(2), 89; https://doi.org/10.3390/info11020089 - 07 Feb 2020
Cited by 3 | Viewed by 1720
Abstract
Energy efficiency is a major concern in the emerging mobile cellular wireless networks since massive connectivity is to be expected with high energy requirements from the network operators. Non-orthogonal multiple access (NOMA) being the frontier multiple access scheme for 5G, there exists numerous [...] Read more.
Energy efficiency is a major concern in the emerging mobile cellular wireless networks since massive connectivity is to be expected with high energy requirements from the network operators. Non-orthogonal multiple access (NOMA) being the frontier multiple access scheme for 5G, there exists numerous research attempts on enhancing the energy efficiency of NOMA enabled wireless networks while maintaining its outstanding performance metrics such as high throughput, data rates and capacity maximized optimally.The concept of green NOMA is introduced in a generalized manner to identify the energy efficient NOMA schemes. These schemes will result in an optimal scenario in which the energy generated for communication is managed sustainably. Hence, the effect on the environment, economy, living beings, etc is minimized. The recent research developments are classified for a better understanding of areas which are lacking attention and needs further improvement. Also, the performance comparison of energy efficient, NOMA schemes against conventional NOMA is presented. Finally, challenges and emerging research trends, for energy efficient NOMA are discussed. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessArticle
Coreference Resolution: Toward End-to-End and Cross-Lingual Systems
Information 2020, 11(2), 74; https://doi.org/10.3390/info11020074 - 30 Jan 2020
Cited by 1 | Viewed by 998
Abstract
The task of coreference resolution has attracted considerable attention in the literature due to its importance in deep language understanding and its potential as a subtask in a variety of complex natural language processing problems. In this study, we outlined the field’s terminology, [...] Read more.
The task of coreference resolution has attracted considerable attention in the literature due to its importance in deep language understanding and its potential as a subtask in a variety of complex natural language processing problems. In this study, we outlined the field’s terminology, describe existing metrics, their differences and shortcomings, as well as the available corpora and external resources. We analyzed existing state-of-the-art models and approaches, and reviewed recent advances and trends in the field, namely end-to-end systems that jointly model different subtasks of coreference resolution, and cross-lingual systems that aim to overcome the challenges of less-resourced languages. Finally, we discussed the main challenges and open issues faced by coreference resolution systems. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessArticle
Which Are the Most Influential Cited References in Information?
Information 2019, 10(12), 395; https://doi.org/10.3390/info10120395 - 17 Dec 2019
Cited by 1 | Viewed by 778
Abstract
This bibliometric study presents the most influential cited references for papers published in the journal Information by using reference publication year spectroscopy (RPYS). A total of 30,960 references cited in 996 papers in the journal Information, published between 2012 and 2019, were [...] Read more.
This bibliometric study presents the most influential cited references for papers published in the journal Information by using reference publication year spectroscopy (RPYS). A total of 30,960 references cited in 996 papers in the journal Information, published between 2012 and 2019, were analyzed in this study. In total, 29 peaks with 48 peak papers are presented and discussed. The most influential cited references are related to set theory and machine learning which is consistent with the scope of the journal. A single peak paper was published in the journal Information. Overall, authors publishing in the journal Information have drawn from many different sources (e.g., journal papers, books, book chapters, and conference proceedings). Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Review

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Open AccessReview
Analysis of Facial Information for Healthcare Applications: A Survey on Computer Vision-Based Approaches
Information 2020, 11(3), 128; https://doi.org/10.3390/info11030128 - 26 Feb 2020
Cited by 8 | Viewed by 1484
Abstract
This paper gives an overview of the cutting-edge approaches that perform facial cue analysis in the healthcare area. The document is not limited to global face analysis but it also concentrates on methods related to local cues (e.g., the eyes). A research taxonomy [...] Read more.
This paper gives an overview of the cutting-edge approaches that perform facial cue analysis in the healthcare area. The document is not limited to global face analysis but it also concentrates on methods related to local cues (e.g., the eyes). A research taxonomy is introduced by dividing the face in its main features: eyes, mouth, muscles, skin, and shape. For each facial feature, the computer vision-based tasks aiming at analyzing it and the related healthcare goals that could be pursued are detailed. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessFeature PaperReview
On the Integration of Knowledge Graphs into Deep Learning Models for a More Comprehensible AI—Three Challenges for Future Research
Information 2020, 11(2), 122; https://doi.org/10.3390/info11020122 - 22 Feb 2020
Cited by 2 | Viewed by 2463
Abstract
Deep learning models contributed to reaching unprecedented results in prediction and classification tasks of Artificial Intelligence (AI) systems. However, alongside this notable progress, they do not provide human-understandable insights on how a specific result was achieved. In contexts where the impact of AI [...] Read more.
Deep learning models contributed to reaching unprecedented results in prediction and classification tasks of Artificial Intelligence (AI) systems. However, alongside this notable progress, they do not provide human-understandable insights on how a specific result was achieved. In contexts where the impact of AI on human life is relevant (e.g., recruitment tools, medical diagnoses, etc.), explainability is not only a desirable property, but it is -or, in some cases, it will be soon-a legal requirement. Most of the available approaches to implement eXplainable Artificial Intelligence (XAI) focus on technical solutions usable only by experts able to manipulate the recursive mathematical functions in deep learning algorithms. A complementary approach is represented by symbolic AI, where symbols are elements of a lingua franca between humans and deep learning. In this context, Knowledge Graphs (KGs) and their underlying semantic technologies are the modern implementation of symbolic AI—while being less flexible and robust to noise compared to deep learning models, KGs are natively developed to be explainable. In this paper, we review the main XAI approaches existing in the literature, underlying their strengths and limitations, and we propose neural-symbolic integration as a cornerstone to design an AI which is closer to non-insiders comprehension. Within such a general direction, we identify three specific challenges for future research—knowledge matching, cross-disciplinary explanations and interactive explanations. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessReview
Still Minding the Gap? Reflecting on Transitions between Concepts of Information in Varied Domains
Information 2020, 11(2), 71; https://doi.org/10.3390/info11020071 - 29 Jan 2020
Cited by 3 | Viewed by 1238
Abstract
This conceptual paper, a contribution to the tenth anniversary Special Issue of Information, gives a cross-disciplinary review of general and unified theories of information. A selective literature review is used to update a 2013 article on bridging the gaps between conceptions of [...] Read more.
This conceptual paper, a contribution to the tenth anniversary Special Issue of Information, gives a cross-disciplinary review of general and unified theories of information. A selective literature review is used to update a 2013 article on bridging the gaps between conceptions of information in different domains, including material from the physical and biological sciences, from the humanities and social sciences including library and information science, and from philosophy. A variety of approaches and theories are reviewed, including those of Brenner, Brier, Burgin and Wu, Capurro, Cárdenas-García and Ireland, Hidalgo, Hofkirchner, Kolchinsky and Wolpert, Floridi, Mingers and Standing, Popper, and Stonier. The gaps between disciplinary views of information remain, although there has been progress, and increasing interest, in bridging them. The solution is likely to be either a general theory of sufficient flexibility to cope with multiple meanings of information, or multiple and distinct theories for different domains, but with a complementary nature, and ideally boundary spanning concepts. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
Open AccessReview
Formal Ontologies in Information Systems Development: A Systematic Review
Information 2020, 11(2), 66; https://doi.org/10.3390/info11020066 - 27 Jan 2020
Cited by 1 | Viewed by 1195
Abstract
Computational ontologies are machine-processable structures which represent particular domains of interest. They integrate knowledge which can be used by humans or machines for decision making and problem solving. The main aim of this systematic review is to investigate the role of formal ontologies [...] Read more.
Computational ontologies are machine-processable structures which represent particular domains of interest. They integrate knowledge which can be used by humans or machines for decision making and problem solving. The main aim of this systematic review is to investigate the role of formal ontologies in information systems development, i.e., how these graphs-based structures can be beneficial during the analysis and design of the information systems. Specific online databases were used to identify studies focused on the interconnections between ontologies and systems engineering. One-hundred eighty-seven studies were found during the first phase of the investigation. Twenty-seven studies were examined after the elimination of duplicate and irrelevant documents. Mind mapping was substantially helpful in organising the basic ideas and in identifying five thematic groups that show the main roles of formal ontologies in information systems development. Formal ontologies are mainly used in the interoperability of information systems, human resource management, domain knowledge representation, the involvement of semantics in unified modelling language (UML)-based modelling, and the management of programming code and documentation. We explain the main ideas in the reviewed studies and suggest possible extensions to this research. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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Open AccessCreative
A Short Note on the History of the Concept of Information
Information 2019, 10(10), 305; https://doi.org/10.3390/info10100305 - 29 Sep 2019
Cited by 2 | Viewed by 1481
Abstract
This paper deals with the Arabic translation taṣawwur in Averroes’ Great Commentary of the term τῶν ἀδιαιρέτων νόησις (“ton adiaireton noesis”, thinking of the indivisibles) in Aristotle’s De anima and the Latin translation from Arabic with (in-)formatio, as quoted by Albertus Magnus [...] Read more.
This paper deals with the Arabic translation taṣawwur in Averroes’ Great Commentary of the term τῶν ἀδιαιρέτων νόησις (“ton adiaireton noesis”, thinking of the indivisibles) in Aristotle’s De anima and the Latin translation from Arabic with (in-)formatio, as quoted by Albertus Magnus [...] Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
Open AccessEssay
Understanding Humans: The Extensions of Digital Media
Information 2019, 10(10), 304; https://doi.org/10.3390/info10100304 - 29 Sep 2019
Cited by 2 | Viewed by 1221
Abstract
With digital media, not only are media extensions of their human users, as McLuhan posited, but there is a flip or reversal in which the human users of digital media become an extension of those digital media as these media scoop up their [...] Read more.
With digital media, not only are media extensions of their human users, as McLuhan posited, but there is a flip or reversal in which the human users of digital media become an extension of those digital media as these media scoop up their data and use them to the advantage of those that control these media. The implications of this loss of privacy as we become “an item in a data bank” are explored and the field of captology is described. The feedback of the users of digital media become the feedforward for those media. Full article
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
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