https://ejece.org/index.php/ejece/issue/feedEuropean Journal of Electrical Engineering and Computer Science2024-11-20T18:04:10+01:00European Journal of Electrical Engineering&Computer Scienceeditor@ejece.orgOpen Journal Systems<table width="80%" cellpadding="10" align="center"> <tbody> <tr> <td rowspan="4" valign="top" width="20%"><img src="/public/site/images/zaratushtra/dergi_kapak2.jpg" alt="jets" align="left" border="0" hspace="10"> <button style="background: #10C9F5; cursor: pointer; font-size: 15px; font-style: bold; text-align: center; color: white; margin: 5px; padding: 5px 5px 5px 5px; border-radius: 15px; border: 2px solid #0D0A0A; width: 275px;" type="button"><strong>DOI</strong> : 10.240818/EJECE</button> <button style="background: #10C9F5; cursor: pointer; font-size: 15px; font-style: bold; text-align: center; color: white; margin: 5px; padding: 5px 5px 5px 5px; border-radius: 15px; border: 2px solid #0D0A0A; width: 275px;" type="button"><strong>ISSN</strong> : 2506-9853</button> <button style="background: #10C9F5; cursor: pointer; font-size: 15px; font-style: bold; text-align: center; color: white; margin: 5px; padding: 5px 5px 5px 5px; border-radius: 15px; border: 2px solid #0D0A0A; width: 275px;" type="button"><strong>Impact Factor</strong> : 0,69</button> <button style="background: #10C9F5; cursor: pointer; font-size: 15px; font-style: bold; text-align: center; color: white; margin: 5px; padding: 5px 5px 5px 5px; border-radius: 15px; border: 2px solid #0D0A0A; width: 275px;" type="button"><strong>Publication Frequency:</strong> Bimonthly</button> <button style="background: #10C9F5; cursor: pointer; font-size: 15px; font-style: bold; text-align: center; color: white; margin: 5px; padding: 5px 5px 5px 5px; border-radius: 15px; border: 2px solid #0D0A0A; width: 275px;" type="button"><strong>Country of Origin:</strong> Belgium</button></td> <td align="right" valign="bottom" width="20%" height="70px"> <img src="/public/site/images/zaratushtra/new10_e0.gif" alt="gif" border="0"></td> <td align="left" valign="bottom" height="125px"><button style="background: #A2E3FF; cursor: pointer; font-size: 15px; font-style: bold; text-align: center; color: blue; padding: 8px 16px; border-radius: 10px; border: 2px solid #4CAF50; width: 300px;" type="button">CALL FOR PAPER -VOL. 2/ ISSUE 7, 2018</button></td> </tr> <tr> <td rowspan="3" align="right" valign="top" width="20%"> </td> <td align="left" valign="top" height="75px"><button style="background: #A2E3FF; cursor: pointer; font-size: 15px; font-style: bold; text-align: center; color: blue; padding: 8px 16px; border-radius: 10px; border: 2px solid #4CAF50; width: 300px;" type="button">SUBMIT YOUR PAPER FOR PEER REVIEW</button></td> </tr> <tr> <td align="left" valign="top"> <p style="font-size: 17px; margin: 6px;">Submit <a href="/index.php/ejece/user/register"><span style="text-decoration: underline;"><strong>Online</strong></span></a> or by <span style="text-decoration: underline;"><a href="mailto:editor@europapublishing.org"><strong>E-mail</strong></a></span> to<br> <a href="mailto:editor@ejece.org">editor@ejece.org</a></p> </td> </tr> </tbody> </table> <table style="width: 100%;" cellpadding="7"> <tbody> <tr> <td> <iframe src="https://www.youtube.com/embed/jW1fB2qUlOU" width="450" height="250" frameborder="0"></iframe></td> <td valign="top" bgcolor="FAFAFA"> <p><span style="color: blue;"> <strong><span style="font-size: 140%; color: blue;"> ► </span> <span style="font-size: 140%; color: blue; text-decoration: underline;">What does EJECE do</span></strong></span> <strong><span style="font-size: 140%; color: blue;"> ?</span></strong><strong><em> </em></strong></p> <p><strong>European Journal of Electrical <strong>Engineering</strong> and Computer Science</strong> (EJECE) is a peer-reviewed international journal publishes <strong>bimonthly</strong> full-length state-of-the-art research papers, reviews, case studies related to <strong>all areas of <a href="/index.php/ejece/about/editorialPolicies#focusAndScope">Electrical Engineering and Computer Science</a></strong>. </p> <p>All submitted articles:</p> <ul> <li class="show">must be <strong>original</strong></li> <li class="show">must be<strong> previously unpublished research results</strong></li> <li class="show">must be <strong>experimental or theoretical</strong></li> <li class="show">and will be <strong>peer-reviewed</strong></li> <li class="show">may not be <strong>considered for publication elsewhere at any time during the review period</strong></li> </ul> <p><strong> </strong>EJECE is published by<strong> <a href="http://www.europapublishing.org">European Open Access Publishing (EUROPA Publishing)</a></strong> </p> </td> </tr> </tbody> </table> <table style="width: 100%;" cellpadding="3"> <tbody> <tr> <td valign="top" bgcolor="FAFAFA"> <p><strong>   <span style="font-size: 140%; color: blue;">► <span style="text-decoration: underline;">How do we do it</span></span> <span style="font-size: 140%; color: blue;"> ?</span>  </strong> </p> <p><strong>Open Access Policy</strong><br><br>EJECE provides immediate open access to its content on the principle that making research freely available after publication on the journal website to the public supports a greater global exchange of knowledge.</p> <p><img src="/public/site/images/zaratushtra/open_access.jpg" alt=""></p> <hr align="left" width="250px"> <p><strong>Zero Tolerance for Plagiarism </strong></p> <p>EJECEhas a policy of “Zero Tolerance on the Plagiarismâ€. We check the plagiarism issue through two methods: reviewer check and plagiarism prevention tool (iThenticate.com).</p> <p>All submissions will be checked by plagiarism prevention software before being sent to reviewers.</p> <p> <img src="/public/site/images/zaratushtra/no_plagiarism.jpg" alt=""></p> <hr align="left" width="250px"> <p><strong>Digital Archiving Policy </strong></p> <p>EJECEuses LOCKSS system as digital archiving policy. LOCKSS ensures the long-term survival of Web-based scholarly publications. Namely, your publication will remain digitally available forever for free under Creative Commons License.</p> <p><img src="/public/site/images/zaratushtra/clockss_lockss.png" alt=""></p> <hr align="left" width="250px"> <p>  <strong>Indexing </strong></p> <p><br><span class="auto-style5">All EJECE content is indexed with <a href="http://www.crossref.org/">CrossRef</a> and assigned a <a href="http://www.doi.org/">Digital Object Identifier (DOI)</a>. This means that all of our references are made available so that citations can be tracked by the publishing community.</span></p> <p><img src="/public/site/images/zaratushtra/indexing_policy21.jpg" alt=""></p> <hr align="left" width="250px"> <p>                                 </p> <p><strong>Paper Selection and Publishing Process</strong></p> <p><em>a) Submission Acknowledgement</em></p> <p>When you submit a manuscript online, you will receive a submission acknowledgement letter sent by the online system automatically. For email submission, the editor or editorial assistant sends an e-mail confirmation to the submission’s author within one to three working days. If you fail to receive this confirmation, please check your bulk email box or contact the editorial assistant.</p> <p><em>b) Basic Review</em></p> <p>The editor or editorial assistant determines whether the manuscript fits the journal’s focus and scope. Next, a check for the similarity rate is done using CrossCheck, powered by iThenticate. Any manuscripts out of the journal’s scope or containing plagiarism, including self-plagiarism, are rejected.</p> <p><em>c) Peer Review</em></p> <p>We use a double-blind system for peer review; both reviewers’ and authors’ identities remain anonymous to authors. The paper will be peer-reviewed by two or three experts; one is an editorial staff and the other two are external reviewers. The review process may take two to four weeks.</p> <p><em>d) Decision </em></p> <p>The decision (Acception, Revision or Decline) is based on the suggestions of reviewers. If there is a different opinion between reviewers, the editor will arrive to a balanced decision based on all the comments, or a second round of peer-reviewing may be initiated.<span style="background-color: #ffffff;"> </span></p> <p><em>e) Publication Fee</em></p> <p>In order to start copyediting process, <a href="/index.php/ejece/about/submissions#authorFees">Paper Publication Fee</a> must be paid. </p> <p><em>f) Copyediting Process-Step </em>1 :<em> Journal Template Adaptation</em></p> <p>The authors need to re-edit the paper, using the template. The re-edited paper should use the template provided by us and meet the formatting requirements outlined in the Author Guidelines.</p> <p>All accepted manuscripts are obligated to adapt the layout of the paper according to the journal's template. EJERS provides a<span class="Apple-converted-space"> </span><a href="https://www.ejece.org/upload/documents/EJECE_template.docx">.DOCX template format</a>, and also accepts<span class="Apple-converted-space"> </span><a href="https://www.ieee.org/conferences/publishing/templates.html">IEEE journal LaTeX template format</a>.</p> <p><em>g) Copyediting Process-Step 2</em></p> <p>After receiving the revised paper. Our editing staff will work on the layout and format. After the process, we will invite you to check the paper again.</p> <p><em>h) Online Publication & Indexing</em></p> <p>E-journal in .PDF  format will be available on the journal’s webpage free of charge for download. In addition, a DOI identifier will be assigned to your paper, and you will be informed regarding to the DOI number.</p> <p>  </p> <p> </p> </td> </tr> </tbody> </table>https://ejece.org/index.php/ejece/article/view/667Estimating Battery Life in Electric Vehicles using Deeper Long Short-Term Memory (DLSTM) Algorithm2024-11-20T18:04:10+01:00Le Viet Bachvothanhha.ktd@utc.edu.vnVo Thanh Havothanhha.ktd@utc.edu.vn<p>The paper estimates electric vehicle battery life using a deep, long-term memory algorithm (DLSTM). This algorithm employs a Forget Gate with a sigmoid function to retain or discard information from previous states. The Input Gate, also using a sigmoid function, determines new information to add, while a <em>tanh</em> function creates a new vector for updating the cell state. The Cell State Update combines inputs from the forget and input gates. The Output Gate uses a sigmoid function to select which part of the cell state to output. This AI algorithm analyses voltage, current, and temperature during charging to predict the lithium-ion battery’s state.</p>2024-11-16T00:00:00+01:00Copyright (c) 2024 Le Viet Bach, Vo Thanh Hahttps://ejece.org/index.php/ejece/article/view/654A Data-Driven Model for Classification of Traditional Chinese Medicine Materials2024-11-15T17:56:33+01:00Li Zhi-Jie20070946@dlnu.edu.cn<p>This paper proposes a data-driven classification model for traditional Chinese medicinal herbs based on mid-infrared spectral data. Addressing the limitations of traditional identification methods when the herbs’ appearance is damaged or incomplete, this study employs machine learning techniques to achieve accurate classification of medicinal herb types through spectral data preprocessing and feature extraction. Firstly, the Savitzky-Golay convolution smoothing method and Standard Normal Variate (SNV) transformation were used for denoising the spectral data. Then, Principal Component Analysis (PCA) was employed to reduce the dimensionality of the high-dimensional spectral data and extract the key features. Finally, the Gaussian Mixture Model (GMM) was applied to cluster the reduced data, categorizing the medicinal herbs into six classes. The results show that this method produces the accurate and stable classification. The constructed model is not only applicable to the classification and origin identification of medicinal herbs but also provides an important reference value for the classification and origin identification of other plant species.</p>2024-11-08T00:00:00+01:00Copyright (c) 2024 Li Zhi-Jiehttps://ejece.org/index.php/ejece/article/view/650Impact of Ad Blockers on Computer Power Consumption while Web Browsing: A Comparative Analysis2024-10-16T17:43:30+02:00Khan Awais Khankakhan@mun.caMohammad Tariq Iqbaltariq@mun.caMohsin Jamilmjamil@mun.ca<p>This study explores the impact of various ad blockers on power consumption during web browsing, focusing on different types of online content. By analyzing power use across ten popular websites, the study assesses the performance of five widely utilized ad blockers: AdBlock, AdBlock Plus, uBlock, uBlock Origin, and uBlock Origin Lite. Power consumption was measured under controlled conditions, comparing scenarios with and without ad blockers to gain insight into their efficiency. The findings indicate substantial differences in power savings, with some ad blockers significantly reducing power usage, particularly on media-heavy sites, while others unexpectedly increased consumption under certain conditions. The study underscores the potential of ad blockers to enhance power efficiency in digital environments, highlighting the importance of optimizing ad-blocking techniques to reduce the environmental impact of online activities. Through comprehensive analysis and comparison, this research offers insights into selecting effective ad blockers to minimize power consumption, promoting more sustainable web browsing practices.</p>2024-10-13T00:00:00+02:00Copyright (c) 2024 Khan Awais Khan, Mohammad Tariq Iqbal, Mohsin Jamilhttps://ejece.org/index.php/ejece/article/view/649A Comparative Analysis of Power Consumption While Using Open-Source and Proprietary Media Players2024-09-19T17:32:57+02:00Afzal Ahmedafzala@mun.caMohammad Tariq Iqbaltariq@mun.caMohsin Jamilmjamil@mun.ca<p>This study investigates the power consumption of various media player software applications, comparing open-source and proprietary options. The experiment measured the average power consumption of CPU, GPU, and memory usage of media players such as Kodi, MPC, MPV, SMP, VLC, Windows Media Player, ACG, ALLPlayer, GOM, KMPlayer, LAPlayer, POTPlayer, and RealPlayer while playing 4K video. The results revealed that proprietary media players generally consume less power compared to their open-source counterparts. Statistical analysis, including descriptive statistics and independent samples t-tests, confirmed these findings. Long-term power consumption projections indicated substantial energy savings with more efficient media players. These findings underscore the importance of considering energy efficiency in software selection for sustainable computing.</p>2024-09-18T00:00:00+02:00Copyright (c) 2024 Afzal Ahmed, Mohammad Tariq Iqbal, Mohsin Jamilhttps://ejece.org/index.php/ejece/article/view/648Implementation of Machine Learning in the Categorization of Improvement Areas for Kaizen Submissions2024-08-19T01:24:46+02:00Ricardo Burciaga Alarcónrburciaga@uadec.edu.mxLaura Cristina Vázquez de los Santoslaura_vazquez@uadec.edu.mx<p>This paper explores the synergy between Kaizen methodologies and Machine Learning, with the goal of improving the efficiency of categorizing areas of improvement. The implementation of Machine Learning algorithms, utilizing the ML.NET tool, has proven to be highly advantageous. These algorithms automate the categorization of Kaizen proposals based on structured data and predefined labels. This automation significantly reduces manual workload, expedites the classification process, and ultimately accelerates decision-making within the realm of continuous improvement. Furthermore, the application of machine learning has improved the categorization accuracy, reduced the risk of human errors, and ensured a more precise assignment to the relevant categories. This, in turn, enhances the quality of the collected information, facilitating well-informed decision-making. Additionally, the automated categorization has streamlined the process for users submitting Kaizen proposals, eliminating the need for manual category selection. This reduces cognitive load and promotes active engagement in the continuous improvement process. Furthermore, the system has introduced a category-based incentive structure, where users accrue points corresponding to the category assigned to their Kaizen proposals. These points can be exchanged for items provided by the company, acting as an additional incentive for active employee participation in the continuous improvement process. In conclusion, the integration of Machine Learning with the ML.NET tool has become a valuable tool for optimizing the management of improvement proposals, resulting in a marked enhancement in efficiency, accuracy, and user engagement in the categorization process.</p>2024-10-10T00:00:00+02:00Copyright (c) 2024 Ricardo Burciaga Alarcón, Laura Cristina Vázquez de los Santos