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Computers
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Theoretical and Applied Computer Science in Engineering and Decision Making
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Theoretical and Applied Computer Science in Engineering and Decision Making

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: closed (15 September 2018) | Viewed by 10830

Special Issue Editor

Dr. Achraf Jabeur Talmoudi

E-Mail Website
Guest Editor
Department of Electronics Engineering, University of Sousse, 4042 Sousse, Tunisia
Interests: identification and prediction; Petri Nets; control engineering; optimization

Special Issue Information

Dear Colleagues,

We invite submissions of novel research articles for a forthcoming Special Issue of Computers.

This Special Issue is associated with the 5th CODIT'18 International Conference on Control, Decision and Information Technologies, held in Thessaloniki (Greece), 10–13 April, 2018. However, it is also open to papers that have not been presented at the conference. High quality research papers are solicited to address theoretical as well as practical issues of computer tools applied in engineering and decision making.

The extended version of papers originally presented at CoDIT'18 must contain about 40% new material and the title of the extended version must clearly and unmistakably differ from the title of the article presented at the conference. Author(s) should cite the CoDIT'18 conference paper.

Topics of interest include all theoretical and practical issues of computer applied to: manufacturing systems, industrial processes, control, robotics, biomedical applications, transportation systems, renewable energy systems, distributed systems, supply chain management, telecommunication, information technology, software engineering, service systems, technology in education, applications in health care, etc. 

Dr. Achraf Jabeur Talmoudi
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 submissions that pass pre-check are 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. Computers 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 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

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12 pages, 1603 KiB  
Article
Model Structure Optimization for Fuel Cell Polarization Curves
by Markku Ohenoja, Aki Sorsa and Kauko Leiviskä
Computers 2018, 7(4), 60; https://doi.org/10.3390/computers7040060 - 9 Nov 2018
Cited by 6 | Viewed by 5618
Abstract
The applications of evolutionary optimizers such as genetic algorithms, differential evolution, and various swarm optimizers to the parameter estimation of the fuel cell polarization curve models have increased. This study takes a novel approach on utilizing evolutionary optimization in fuel cell modeling. Model [...] Read more.
The applications of evolutionary optimizers such as genetic algorithms, differential evolution, and various swarm optimizers to the parameter estimation of the fuel cell polarization curve models have increased. This study takes a novel approach on utilizing evolutionary optimization in fuel cell modeling. Model structure identification is performed with genetic algorithms in order to determine an optimized representation of a polarization curve model with linear model parameters. The optimization is repeated with a different set of input variables and varying model complexity. The resulted model can successfully be generalized for different fuel cells and varying operating conditions, and therefore be readily applicable to fuel cell system simulations. Full article
(This article belongs to the Special Issue Theoretical and Applied Computer Science in Engineering and Decision Making)
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Review

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19 pages, 1112 KiB  
Review
Extending NUMA-BTLP Algorithm with Thread Mapping Based on a Communication Tree
by Iulia Știrb
Computers 2018, 7(4), 66; https://doi.org/10.3390/computers7040066 - 3 Dec 2018
Cited by 1 | Viewed by 4480
Abstract
The paper presents a Non-Uniform Memory Access (NUMA)-aware compiler optimization for task-level parallel code. The optimization is based on Non-Uniform Memory Access—Balanced Task and Loop Parallelism (NUMA-BTLP) algorithm Ştirb, 2018. The algorithm gets the type of each thread in the source code based [...] Read more.
The paper presents a Non-Uniform Memory Access (NUMA)-aware compiler optimization for task-level parallel code. The optimization is based on Non-Uniform Memory Access—Balanced Task and Loop Parallelism (NUMA-BTLP) algorithm Ştirb, 2018. The algorithm gets the type of each thread in the source code based on a static analysis of the code. After assigning a type to each thread, NUMA-BTLP Ştirb, 2018 calls NUMA-BTDM mapping algorithm Ştirb, 2016 which uses PThreads routine pthread_setaffinity_np to set the CPU affinities of the threads (i.e., thread-to-core associations) based on their type. The algorithms perform an improve thread mapping for NUMA systems by mapping threads that share data on the same core(s), allowing fast access to L1 cache data. The paper proves that PThreads based task-level parallel code which is optimized by NUMA-BTLP Ştirb, 2018 and NUMA-BTDM Ştirb, 2016 at compile-time, is running time and energy efficiently on NUMA systems. The results show that the energy is optimized with up to 5% at the same execution time for one of the tested real benchmarks and up to 15% for another benchmark running in infinite loop. The algorithms can be used on real-time control systems such as client/server based applications which require efficient access to shared resources. Most often, task parallelism is used in the implementation of the server and loop parallelism is used for the client. Full article
(This article belongs to the Special Issue Theoretical and Applied Computer Science in Engineering and Decision Making)
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