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Special Issue "Sensors for Information Technology, Electronics and Mobile Communication"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (15 January 2019)

Special Issue Editors

Guest Editor
Prof. Dr. Himadri Nath Saha

Institute of Engineering and Management Department of Electrical and Electronics Engineering , Gurukul, Y-12, Block -EP, Salt Lake Electronics Complex, Sector V, Kolkata, West Bengal 700091, India
Website | E-Mail
Interests: IoT; Machine Learning; Algorithm,Security; Wireless Communication; Robotics; Brain Computing Interface; MANET; Sensors; Computer Networking
Guest Editor
Prof. Dr. Victor C.M. Leung

The University of British Columbia, Department of Electrical & Computer Engineering, Vancouver, Canada
Website | E-Mail
Phone: +1-604-822-6932
Fax: +1-604-822-5949
Interests: design and analysis of architectures, protocols, and management, control and interworking strategies for telecommunication networks and information systems; applications to broadband, satellite, wireless, mobile, and personal communications networking and cloud computing
Guest Editor
Prof. Dr. Satyajit Chakrabarti

Institute of Engineering and Management Department of Computer Science Engineering , Gurukul, Y-12, Block -EP, Salt Lake Electronics Complex, Sector V, Kolkata, West Bengal 700091, India
E-Mail
Interests: Machine Learning; IoT; Big Data Analytics; Data Mining; Algorithms; Robotics; Sensors; Human Computer Interface; Networking & MANET; Wireless Communication
Guest Editor
Prof. Bob Gill

British Columbia Institute of Technology, Department of Electrical and Computer Engineering, 3700 Willingdon Ave, Burnaby, BC V5G 3H2, Canada
Website | E-Mail
Interests: electrical and computer engineering; DSP; network security; bio-medical engineering; computer systems

Special Issue Information

Dear Colleagues,

Continuing from the outstanding success of IEEE IEMCON 2017, we are proud to present IEEE IEMCON 2018 which will provide an opportunity for researchers, educators and students to discuss and exchange ideas on issues, trends, and developments in Information Technology, Electronics and Mobile Communication. The conference aims to bring together scholars from different disciplinary backgrounds to emphasize dissemination of ongoing research in the fields of in Information Technology, Electronics and Mobile Communication. Contributed papers are solicited describing original works in the above mentioned fields and related technologies. The conference will include a peer-reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions. Extended Version of accepted and presented paper will welcome to be submitted for publication at this Special Issue.

Topics and technical areas of interest include but are not limited to the following:

Information Technology

  • Computer Network
  • Evolutionary Computation and Algorithms
  • Intelligent Information Processing
  • Information System Integration and Decision Support
  • Image Processing and Multimedia Technology
  • Information Security and Encoding Technology; Information Retrieval
  • Signal Detection and Processing
  • Data Mining; Data Analytics and Big Data
  • Mobile Computing
  • Artificial Intelligence
  • Visualization and Computer Graphic
  • Natural Language Processing
  • Machine Learning
  • Internet of Things

Electronics

  • VLSI and Microelectronic Circuit Embedded Systems
  • System on Chip (SoC) Design
  • FPGA (Field Programmable Gate Array) Design and Applications
  • Electronic Instrumentations
  • Electronic Power Converters and Inverters
  • Electric Vehicle Technologies
  • Intelligent Control; Optimal Control; Robust Control
  • Linear and Nonlinear Control Systems
  • Complex Adaptive Systems
  • Industrial Automation and Control Systems Technology
  • Modern Electronic Devices

Mobile Communication

  • Ad hoc networks
  • Body and personal area networks
  • Cloud and virtual networks
  • Cognitive radio networks
  • Cooperative communications
  • Delay tolerant networks
  • Future wireless Internet
  • Green wireless networks
  • Local dependent networks; Location management
  • Mobile and wireless IP; Mobile computing
  • Multi-hop networks
  • Network architectures; Network Security
  • Routing, QoS and scheduling
  • Telecommunication Systems
  • Vehicular networks
  • Wireless multicasting, broadcasting and geocasting
  • Wireless sensor networks
Prof. Dr. Himadri Nath Saha
Prof. Dr. Victor C.M. Leung

Prof. Dr. Satyajit Chakrabarti
Prof. Bob Gill
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. Sensors is an international peer-reviewed open access bimonthly 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 1800 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 (3 papers)

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Research

Open AccessArticle Blind Estimation of the PN Sequence of A DSSS Signal Using A Modified Online Unsupervised Learning Machine
Sensors 2019, 19(2), 354; https://doi.org/10.3390/s19020354
Received: 26 November 2018 / Revised: 3 January 2019 / Accepted: 11 January 2019 / Published: 16 January 2019
PDF Full-text (433 KB)
Abstract
Direct sequence spread spectrum (DSSS) signals are now widely used in air and underwater acoustic communications. A receiver which does not know the pseudo-random (PN) sequence cannot demodulate the DSSS signal. In this paper, firstly, the principle of principal component analysis (PCA) for
[...] Read more.
Direct sequence spread spectrum (DSSS) signals are now widely used in air and underwater acoustic communications. A receiver which does not know the pseudo-random (PN) sequence cannot demodulate the DSSS signal. In this paper, firstly, the principle of principal component analysis (PCA) for PN sequence estimation of the DSSS signal is analyzed, then a modified online unsupervised learning machine (LEAP) is introduced for PCA. Compared with the original LEAP, the modified LEAP has the following improvements: (1) By normalizing the system state transition matrices, the modified LEAP can obtain better robustness when the training errors occur; (2) with using variable learning steps instead of a fixed one, the modified LEAP not only converges faster but also has excellent estimation performance. When the modified LEAP is converging, we can utilize the network connection weights which are the eigenvectors of the autocorrelation matrix of the DSSS signal to estimate the PN sequence. Due to the phase ambiguity of the eigenvectors, a novel approach which is based on the properties of the PN sequence is proposed here to exclude the wrong estimated PN sequences. Simulation results showed that the methods mentioned above can estimate the PN sequence rapidly and robustly, even when the DSSS signal is far below the noise level. Full article
Open AccessArticle A Method for Analyzing the Impact of Intra-System and Inter-System Interference on DME Based on Queueing Theory
Sensors 2019, 19(2), 348; https://doi.org/10.3390/s19020348
Received: 26 November 2018 / Revised: 1 January 2019 / Accepted: 14 January 2019 / Published: 16 January 2019
PDF Full-text (841 KB) | HTML Full-text | XML Full-text
Abstract
In order to use Distance Measuring Equipment (DME) properly, the impact of intra-system and inter-system electromagnetic interference must be analyzed firstly. However, the error of interference analysis using present methods based on pulse overlap is large when there are more aircraft. The aim
[...] Read more.
In order to use Distance Measuring Equipment (DME) properly, the impact of intra-system and inter-system electromagnetic interference must be analyzed firstly. However, the error of interference analysis using present methods based on pulse overlap is large when there are more aircraft. The aim of this article is to study a method of analyzing interference on DME whether the number of aircraft is small or not. According to the flow chart of DME signal, we studied the limitations of present methods; then constructed a model of analyzing the collision between duration of desired signal and dead time of receiver based on M/M/1/0 queueing system. Combing this model with other methods, we present a analytic model of analyzing intra-system and inter-system interference on DME. Using this analytic model, we analyzed reply efficiency (RE) and capacity of DME under intra-system and Joint Tactical Information Distribution System (JTIDS) interference. The result shows that the calculation for the probability of overlap between DME dead time and subsequent signals using queueing model agrees well with simulation. Consequently, the analytic model is more accurate than using a single method to analyze interference on DME. Full article
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Open AccessArticle Road Anomalies Detection System Evaluation
Sensors 2018, 18(7), 1984; https://doi.org/10.3390/s18071984
Received: 9 May 2018 / Revised: 13 June 2018 / Accepted: 19 June 2018 / Published: 21 June 2018
Cited by 1 | PDF Full-text (745 KB) | HTML Full-text | XML Full-text
Abstract
Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper
[...] Read more.
Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a “conditioned” and a real world setup, where the system performed worse compared to the “conditioned” setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities. Full article
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