Special Issue "Data Analysis in Intelligent Communication Systems"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 25 May 2020.

Special Issue Editors

Prof. Dr. Naixue Xiong
E-Mail Website
Guest Editor
Northeastern State University, Oklahoma, USA
Interests: cloud computing; security and dependability; parallel and distributed computing; communication; optimization theory
Special Issues and Collections in MDPI journals
Prof. Dr. Hongju Cheng
E-Mail Website
Guest Editor
College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
Interests: mobile ad hoc networks, wireless sensor networks, and wireless mesh networks
Prof. Dr. Sajid Hussain
E-Mail Website
Guest Editor
Computer Science, Fisk University, Nashville, Tennessee, USA
Interests: energy efficient communication protocols and security techniques for mobile, Sensor Networks, and pervasive applications
Special Issues and Collections in MDPI journals
Prof. Dr. Victor S. Sheng
E-Mail Website
Guest Editor
Department of Computer Science, University of Central Arkansas, Conway, AR 72035, USA
Interests: crowdsourcing; data mining and machine learning; spatial information retrieval; data security; decision support; applications in business, health informatics, and software engineering
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Intelligent communication systems (ICS) have received increasing attention in both the academic and industry arenas because they can integrate technologies and expertise to create and provide innovative services, improve safety and mobility, and thus increase the efficiency of existing infrastructure. The appearance of new technologies, such as the Internet of Things and cloud computing, has brought opportunities for the development of ICS by revolutionizing the modern world of travel via the use of sensors, applications for mobile devices, and other technological advancements. These sensor and mobile devices can gather local information after deployment, and the collected data are very important to make correct decisions for motor drivers. Cloud computing is an extensive way to enjoy knowledge discovery, information sharing, and supported decision making when establishing a large, fully functioning, real-time, accurate, and efficient ICS. This new notion involves some key issues in which traditions are replaced by data analysis requiring manual discrimination and resolution to reach optimization.

The data generated from ICS devices turn out to be of value only if they are subjected to analysis, which brings data analytics and optimization into the picture. The emergence of data science and analytics will also provide new tools, using which, transportation systems and services will be managed in the future. Many of the most popular data process techniques, including data mining, machine learning, artificial intelligence, data fusion, and so on, can be used to build the ICS and optimize its performance. The confluence of this multitude of technologies and tools from different domains and the impact they will have in future transportation systems.

The aim of this Special Issue will be to feature articles on new technologies that will impact future ICS. They might span across data analysis and optimization, IOT (such as sensor networks), vehicular technologies (such as V2V and V2I), security mechanisms, and infrastructure-level technologies to support transportation. In addition to terrestrial transportation, cloud computing, network infrastructure, and network optimization as well as multimedia concerning ICS are also of interest.

Within the above dimensions, the scope of the Special Issue welcomes high-quality original research and review articles that cover a broad range of topics related to data analysis and optimization in the ICS. Potential topics include but are not limited to the following:

  • Data distribution platforms for ICS
  • Data optimization for ICS
  • Online optimization for real time traffic data
  • Spatiotemporal visual analysis for ICS
  • Internet of Things and Internet of Vehicles
  • Transportation data mining and exploration
  • Advanced driver assistance systems
  • Traffic estimation and prediction system
  • New paradigms for ICS/Vehicular communication
  • Cloud computing based big data mining
  • Fusion of multisource mobility data
  • Vehicle dynamics and control system

Prof. Dr. Naixue Xiong
Prof. Dr. Hongju Cheng
Prof. Dr. Sajid Hussain
Prof. Dr. Victor S. Sheng
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. Electronics 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 (2 papers)

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Research

Open AccessArticle
Expert Finding Considering Dynamic Profiles and Trust in Social Networks
Electronics 2019, 8(10), 1165; https://doi.org/10.3390/electronics8101165 (registering DOI) - 15 Oct 2019
Abstract
Recently, social network services that express individual opinions and thoughts have been significantly developed. As unreliable information is generated and shared by arbitrary users in social network services, many studies have been conducted to find users who provide reliable and professional information. In [...] Read more.
Recently, social network services that express individual opinions and thoughts have been significantly developed. As unreliable information is generated and shared by arbitrary users in social network services, many studies have been conducted to find users who provide reliable and professional information. In this paper, we propose an expert finding scheme to discover users who can answer users’ questions professionally in social network services. We use a dynamic profile to extract the user’s latest interest through an analysis of the user’s recent activity. To improve the accuracy of the expert finding results, we consider the user trust and response quality. We conduct a performance evaluation with the existing schemes through various experiments to verify the superiority of the proposed scheme. Full article
(This article belongs to the Special Issue Data Analysis in Intelligent Communication Systems)
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Open AccessArticle
Design and Analysis of the Task Distribution Scheme of Express Center at the End of Modern Logistics
Electronics 2019, 8(10), 1141; https://doi.org/10.3390/electronics8101141 - 09 Oct 2019
Abstract
With the rise and improvement of artificial intelligence technology, the express delivery industry has become more intelligent. At the terminal of modern logistics, each dispatch center has hundreds of express mail deliveries to be dispatched every day, and the number of dispatchers is [...] Read more.
With the rise and improvement of artificial intelligence technology, the express delivery industry has become more intelligent. At the terminal of modern logistics, each dispatch center has hundreds of express mail deliveries to be dispatched every day, and the number of dispatchers is far less than the number of express mail deliveries. How to assign scientific tasks to each courier dispatch is the main target of this paper. The purpose is to make the number of tasks between the various couriers in the express center roughly the same in each cycle, so that there is a more balanced income between the couriers. In the simulation experiment, the delivery addresses are clustered according to the balanced k-means algorithm. Then, the ant colony algorithm is used to plan the delivery order of the express items in each class. Then, the time cost model is established according to the delivery distance of the express items in each class and the delivery mode of the express items to calculate the delivery time cost. Through a large amount of experimental data, the standard deviation of delivery time cost of each courier gradually decreases and tends to stabilize, which suggests that this method has a good effect on the dispatching task assignment of the express center. It can effectively make the delivery workload between the distributors roughly the same, and improve the delivery efficiency of the courier, save energy, and promote sustainable development. Full article
(This article belongs to the Special Issue Data Analysis in Intelligent Communication Systems)
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