Special Issue "Application of Advanced Computing, Control and Processing in Engineering"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Dr. Sudip Chakraborty
Website
Guest Editor
Department of Computer Engineering, Modeling, Electronics and Systems (D.I.M.E.S.), Laboratory of Transport Phenomena and Biotechnology, University of Calabria, Cubo-42a, Via P. Bucci, 87036 Rende, Italy
Interests: Photocatalysis; Membrane reactor; Energy Conversion; Nanomaterials; Waste valorization; Inorganic Catalyst; Plasmonics
Special Issues and Collections in MDPI journals
Dr. Robertas Damaševičius
Website SciProfiles
Guest Editor
Professor at Software Engineering Department, Kaunas University of Technology, K. Donelaičio g. 73, Kaunas 44249, Lithuania; Adjunct Professor at Institute of Mathematics, Silesian University of Technology, Akademicka 2A, 44-100 Gliwice, Poland
Interests: human–computer interface; robot programming; sustainable software engineering; assisted living; data mining and machine learning; smart learning
Special Issues and Collections in MDPI journals
Prof. Dr. Sergio Greco
Website
Guest Editor
Department of Computer Engineering, Modelling, Electronics and Systemics—DIMES, University of Calabria, Via P. Bucci Cubo 42/A, 87036 Arcavacata di Rende (CS), Italy
Interests: logic programing; artificial intelligence, data mining; cluster computing; sensor network

Special Issue Information

Dear friends and colleagues,

Computational concepts and techniques have always played a major role in control engineering since the first computer-based control systems were put into operation over twenty years ago. Today’s research discoveries at the confluence of theoretical, experimental, and computational science and engineering are enabled by the continuing availability of an ecosystem of advanced computational resources. The dramatic growth in practical applications for machine learning over the last twenty years has been accompanied by many important developments in the underlying algorithms and techniques. This role has, in fact, been accelerating over the intervening years as the sophistication of the computing methods and tools available—as well as the complexity of the control problems they have been used to solve—have also increased. In particular, the introduction of the microprocessor, nono-electronics, nanoprocessors, and their use as a low-cost computing element in a distributed computer control system has had a profound effect on the way in which the design and implementation of a advanced processing and control system is carried out and, to some extent, on the theory which underlies the basic design strategies.

Artificial intelligence and human–computer interactions is another area that is receiving increased attention day by day, due to their advanced ability to solved many previously unsolved problems The development of interactive computing has encouraged a substantial growth in the use of computer-aided design methods and robust and efficient numerical algorithms have been produced to support these methods. Major advances have also taken place in the languages used for control system implementation in terms of machine learning. The algorithms of human language and interaction with the system whose design is based on some very fundamental computer science concepts have been derived and developed over the past decade. With the extremely high rate of change in the field of computer science and electronics, the more recent developments have outpaced their incorporation into new control system design and implementation techniques. With wide adoption of new modalities of scientific and engineering discovery, the demand for computing and interface capabilities and services has increased significantly both in terms of the range of capabilities and overall capacity.

Concurrently, in this Special Issue, we hope to showcase the latest results from researchers, computer engineers, and electronics professionals in their attempts to explore new methods and algorithms while constantly adapting to rapid technological evolution, as well as in pursuing transformational discoveries across all processes and in engineering. In addition, we also encouraging submissions which attempt to solve various problems related to environmental sensing.

Dr. Sudip Chakraborty
Dr. Robertas Damaševičius
Prof. Dr. Sergio Greco
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 1500 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

  • nanotechnology
  • machine learning
  • artificial neural network
  • human–computer interaction
  • software engineering
  • artificial intelligence
  • environmental sensing
  • smart learning。

Published Papers (1 paper)

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Research

Open AccessArticle
Safety Risk Assessment of a Pb-Zn Mine Based on Fuzzy-Grey Correlation Analysis
Electronics 2020, 9(1), 130; https://doi.org/10.3390/electronics9010130 - 09 Jan 2020
Cited by 2
Abstract
Improving safety management and risk evaluation methods is important for the global mining industry, which is the backbone of the industrial development of our society. To prevent any accidental loss or harm to human life and property, a safety risk assessment method is [...] Read more.
Improving safety management and risk evaluation methods is important for the global mining industry, which is the backbone of the industrial development of our society. To prevent any accidental loss or harm to human life and property, a safety risk assessment method is needed to perform the continuous risk assessment of mines. Based on the requirements of mine safety evaluation, this paper proposes the Pb-Zn mine safety risk evaluation model based on the fuzzy-grey correlation analysis method. The model is compared with the risk assessment model based on the fuzzy TOPSIS method. Through the experiments, our results demonstrate that the proposed fuzzy-grey correlation model is more sensitive to risk and has less effect on the evaluation results under different scoring attitudes (cautious, rational, and relaxed). Full article
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