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FACTS & FIGURES

JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: May 2020
Next issue: Aug 2020
Avg review time: 74 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
Starting on the 15th of June 2020 we wiil introduce a new policy for reviewers. Reviewers who provide timely and substantial comments will receive a discount voucher entitling them to an APC reduction. Vouchers (worth of 25 EUR or 50 EUR, depending on the review quality) will be assigned to reviewers after the final decision of the reviewed paper is given. Vouchers issued to specific individuals are not transferable.

2019-Dec-16
Starting on the 15th of December 2019 all paper authors are required to enter their SCOPUS IDs. You may use the free SCOPUS ID lookup form to find yours in case you don't remember it.

2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

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  1/2018 - 15

 HIGHLY CITED PAPER 

Optimization of Charge/Discharge Coordination to Satisfy Network Requirements Using Heuristic Algorithms in Vehicle-to-Grid Concept

DOGAN, A. See more information about DOGAN, A. on SCOPUS See more information about DOGAN, A. on IEEExplore See more information about DOGAN, A. on Web of Science, BAHCECI, S. See more information about  BAHCECI, S. on SCOPUS See more information about  BAHCECI, S. on SCOPUS See more information about BAHCECI, S. on Web of Science, DALDABAN, F. See more information about  DALDABAN, F. on SCOPUS See more information about  DALDABAN, F. on SCOPUS See more information about DALDABAN, F. on Web of Science, ALCI, M. See more information about ALCI, M. on SCOPUS See more information about ALCI, M. on SCOPUS See more information about ALCI, M. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,247 KB) | Citation | Downloads: 433 | Views: 2,777

Author keywords
electric vehicles, genetic algorithms, heuristic algorithms, smart grids, optimization

References keywords
grid(33), power(31), electric(28), vehicle(23), vehicles(21), energy(21), charging(18), plug(16), systems(14), smart(14)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 121 - 130
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01015
Web of Science Accession Number: 000426449500015
SCOPUS ID: 85043247244

Abstract
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Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.


References | Cited By

Cited-By ISI Web of Science

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Cited-By CrossRef

SCOPUS® Times Cited: 5
View record in SCOPUS®
[Free preview]

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Cited-By CrossRef

[1] Route Optimization of Electric Vehicle considering Soft Time Windows and Two Ways of Power Replenishment, Meng, Ming, Ma, Yun, Advances in Operations Research, ISSN 1687-9147, Issue , 2020.
Digital Object Identifier: 10.1155/2020/5612872
[CrossRef]

[2] Optimal Energy and Reserve Market Management in Renewable Microgrid-PEVs Parking Lot Systems: V2G, Demand Response and Sustainability Costs, Onishi, Viviani Caroline, Antunes, Carlos Henggeler, Trovão, João Pedro Fernandes, Energies, ISSN 1996-1073, Issue 8, Volume 13, 2020.
Digital Object Identifier: 10.3390/en13081884
[CrossRef]

[3] Comparative Optimization Analysis of Ramp Rate Constriction Factor Based PSO and Electro Magnetism Based PSO for Economic Load Dispatch in Electric Power System, Maharana, Himanshu Shekhar, Dash, Saroj Kumar, 2019 International Conference on Applied Machine Learning (ICAML), ISBN 978-1-7281-3908-1, 2019.
Digital Object Identifier: 10.1109/ICAML48257.2019.00020
[CrossRef]

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

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