Special Issue "Information Technology: New Generations (ITNG 2019)"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (31 January 2020).

Special Issue Editors

Prof. Dr. Shahram Latifi
Website
Guest Editor
Department of Electrical & Computer Engineering, University of Nevada, 4505 Maryland Parkway, Las Vegas, NV 89154-4026, USA
Interests: image processing; data and image compression; gaming and statistics; information coding; sensor networks; reliability; applied graph theory; biometrics; bio-surveillance; computer networks; fault tolerant computing; parallel processing; interconnection networks
Special Issues and Collections in MDPI journals
Dr. Doina Bein
Website
Guest Editor
Department of Computer Science, California State University, Fullerton, CA 92834, USA
Interests: automatic dynamic decision-making; computational sensing; distributed algorithms; energy-efficient wireless networks; fault tolerant data structures; fault tolerant network coverage; graph embedding; multi-modal sensor fusion; randomized algorithms; routing and broadcasting in wireless networks; secure network communication; self-stabilizing algorithms; self-organizing ad-hoc networks; supervised machine learning; urban sensor networks; wireless sensor networks
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Information proposes a Special Issue on “Information Technology: New Generations”. This Special Issue intends to contain a selection of carefully revised and extended papers to be presented at the ITNG 2019, to be held in Las Vegas, Nevada, USA, 1–3 April 2019.  Contributors are invited to submit original papers dealing with state-of-the-art technologies pertaining to digital information and communications for publication in this Special Issue of the journal. The papers need to be submitted to the Guest Editor by email: [email protected] (or the Information Editorial Office: [email protected]). Please follow the instructions available here regarding the number of pages and the page formatting. The research papers should reach us latest by October 31, 2019.

Prof. Dr. Shahram Latifi
Dr. Doina Bein
Guest Editors

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 1000 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.

Keywords

  • Networking and wireless communications
  • Internet of Things (IoT)
  • Software Defined Networking
  • Cyber Physical Systems
  • Machine learning
  • Robotics
  • High performance computing
  • Software engineering and testing
  • Cybersecurity and privacy
  • Big Data
  • High performance computing
  • Cryptography
  • E-health
  • Sensor networks
  • Algorithms
  • Education

Published Papers (2 papers)

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Research

Open AccessArticle
A Framework for Detecting Intentions of Criminal Acts in Social Media: A Case Study on Twitter
Information 2020, 11(3), 154; https://doi.org/10.3390/info11030154 - 12 Mar 2020
Abstract
Criminals use online social networks for various activities by including communication, planning, and execution of criminal acts. They often employ ciphered posts using slang expressions, which are restricted to specific groups. Although literature shows advances in analysis of posts in natural language messages, [...] Read more.
Criminals use online social networks for various activities by including communication, planning, and execution of criminal acts. They often employ ciphered posts using slang expressions, which are restricted to specific groups. Although literature shows advances in analysis of posts in natural language messages, such as hate discourses, threats, and more notably in the sentiment analysis; research enabling intention analysis of posts using slang expressions is still underexplored. We propose a framework and construct software prototypes for the selection of social network posts with criminal slang expressions and automatic classification of these posts according to illocutionary classes. The developed framework explores computational ontologies and machine learning (ML) techniques. Our defined Ontology of Criminal Expressions represents crime concepts in a formal and flexible model, and associates them with criminal slang expressions. This ontology is used for selecting suspicious posts and decipher them. In our solution, the criminal intention in written posts is automatically classified relying on learned models from existing posts. This work carries out a case study to evaluate the framework with 8,835,290 tweets. The obtained results show its viability by demonstrating the benefits in deciphering posts and the effectiveness of detecting user’s intention in written criminal posts based on ML. Full article
(This article belongs to the Special Issue Information Technology: New Generations (ITNG 2019))
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Open AccessArticle
Analysis and Identification of Possible Automation Approaches for Embedded Systems Design Flows
Information 2020, 11(2), 120; https://doi.org/10.3390/info11020120 - 22 Feb 2020
Abstract
Sophisticated and high performance embedded systems are present in an increasing number of application domains. In this context, formal-based design methods have been studied to make the development process robust and scalable. Models of computation (MoC) allows the modeling of an application at [...] Read more.
Sophisticated and high performance embedded systems are present in an increasing number of application domains. In this context, formal-based design methods have been studied to make the development process robust and scalable. Models of computation (MoC) allows the modeling of an application at a high abstraction level by using a formal base. This enables analysis before the application moves to the implementation phase. Different tools and frameworks supporting MoCs have been developed. Some of them can simulate the models and also verify their functionality and feasibility before the next design steps. In view of this, we present a novel method for analysis and identification of possible automation approaches applicable to embedded systems design flow supported by formal models of computation. A comprehensive case study shows the potential and applicability of our method. Full article
(This article belongs to the Special Issue Information Technology: New Generations (ITNG 2019))
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