https://ejece.org/index.php/ejece/issue/feed European Journal of Electrical Engineering and Computer Science 2021-02-25T17:54:54-05:00 European Journal of Electrical Engineering&Computer Science editor@ejece.org Open 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">Â&nbsp;<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%">Â&nbsp;</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;">SubmitÂ&nbsp;<a href="/index.php/ejece/user/register"><span style="text-decoration: underline;"><strong>Online</strong></span></a>Â&nbsp;or byÂ&nbsp;<span style="text-decoration: underline;"><a href="mailto:editor@europapublishing.org"><strong>E-mail</strong></a></span> to<br>Â&nbsp;<a href="mailto:editor@ejece.org">editor@ejece.org</a></p> </td> </tr> </tbody> </table> <table style="width: 100%;" cellpadding="7"> <tbody> <tr> <td>Â&nbsp; <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;">Â&nbsp;<strong><span style="font-size: 140%; color: blue;"> â–ºÂ&nbsp;</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>Â&nbsp;</em></strong></p> <p><strong>European Journal of ElectricalÂ&nbsp;<strong>Engineering</strong> and Computer Science</strong>Â&nbsp;(EJECE) is a peer-reviewedÂ&nbsp;international journal publishes <strong>bimonthly</strong>Â&nbsp;full-length state-of-the-artÂ&nbsp;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>.Â&nbsp;</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>Â&nbsp;</strong>EJECE is published by<strong>Â&nbsp;<a href="http://www.europapublishing.org">European Open Access Publishing (EUROPA Publishing)</a></strong>Â&nbsp;</p> </td> </tr> </tbody> </table> <table style="width: 100%;" cellpadding="3"> <tbody> <tr> <td valign="top" bgcolor="FAFAFA"> <p><strong>Â&nbsp; Â&nbsp; Â&nbsp;<span style="font-size: 140%; color: blue;">â–ºÂ&nbsp;<span style="text-decoration: underline;">How do we do it</span></span> <span style="font-size: 140%; color: blue;"> ?</span>Â&nbsp;Â&nbsp;</strong>Â&nbsp;</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 PlagiarismÂ&nbsp;</strong></p> <p>EJECEhas a policy of “Zero Tolerance on the Plagiarism”. 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>Â&nbsp;<img src="/public/site/images/zaratushtra/no_plagiarism.jpg" alt=""></p> <hr align="left" width="250px"> <p><strong>Digital Archiving PolicyÂ&nbsp;</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>Â&nbsp;Â&nbsp;<strong>IndexingÂ&nbsp;</strong></p> <p><br><span class="auto-style5">All EJECE content is indexed withÂ&nbsp;<a href="http://www.crossref.org/">CrossRef</a>Â&nbsp;and assigned aÂ&nbsp;<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>Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp; Â&nbsp;Â&nbsp;</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 anonymousÂ&nbsp;to authors. The paper will be peer-reviewed by two or three experts;Â&nbsp;one is an editorial staff and the other two are external reviewers.Â&nbsp;The review process may take two to four weeks.</p> <p><em>d) DecisionÂ&nbsp;</em></p> <p>The decisionÂ&nbsp;(Acception, Revision or Decline)Â&nbsp;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;">Â&nbsp;</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>Â&nbsp;must be paid.Â&nbsp;</p> <p><em>f) Copyediting Process-Step </em>1 :<em>Â&nbsp;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">Â&nbsp;</span><a href="https://www.ejece.org/upload/documents/EJECE_template.docx">.DOCX template format</a>, and also accepts<span class="Apple-converted-space">Â&nbsp;</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 &amp; Indexing</em></p> <p>E-journal in .PDF Â&nbsp;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>Â&nbsp;Â&nbsp;</p> <p>Â&nbsp;</p> </td> </tr> </tbody> </table> https://ejece.org/index.php/ejece/article/view/268 Efficient Pneumonia Detection for Chest Radiography Using ResNet-Based SVM 2021-02-25T17:54:54-05:00 Marwa M. Eid marwa.3eeed@gmail.com Yasser H. Elawady yalawady@gmail.com <p class="Abstract"><span lang="EN-US">Chest radiography has a significant clinical utility in the medical imaging diagnosis, as it is one of the most basic examination tools. Pneumonia is a common infection that rapidly affects human lung areas. So, finding an advanced automated method to detect Pneumonia is assigned to be one of the most recent issues, which is still prohibitively expensive to mass adoption, especially in the developing countries. This article presents an innovative approach for distinguishing the residence of pneumonia by embedding computational techniques to chest x-rays images which eliminating the demands for single-image investigation and significantly decrease the total costs. Recent advances in deep learning achieved remarkable results in image classification on different domains; however, its application for Pneumonia diagnosis is still restricted. Hence, the main focus is to provide an investigation that will improve the research in this area, presenting a new proposal to the applications of pre-trained convolutional neural networks (CNNs) as a stage of features extraction to detect this disease. Specifically, we propose to combine deep residual neural networks (ResNets), which extract the hierarchical features from the individual x-ray images with the boosting algorithm to select the salient features, and support vector machine for classification (AdaBoost-SVM). After conducting the performance analysis on the available dataset, we have concluded that the precision of the introduced scheme in Pneumonia classification is superior to the most concurrent approaches, resulting in a great improvement in clinical outcomes. </span></p> 2021-01-12T09:12:58-05:00 Copyright (c) 2021 Yasser H. Elawady https://ejece.org/index.php/ejece/article/view/271 Prediction of Interpolants in Zero Diluted Images 2021-02-25T17:54:54-05:00 T. Kishan Rao kishanrao65@gmail.com M. Shankar Lingam shankumacharla@gmail.com Manish Prateek mprateek@ddn.upes.ac.in E. G. Rajan dr.rajaneg@gmail.com <p>This paper provides an algorithmic procedure to predict interpolants of zero diluted images. Given a digital image, one can zero dilute it by right adjoining a column consisting of ‘0s’ to every column except the last column and inserting a row consisting of ‘0s’ below every row except the last row. This yields a new image with a size (2W-1)×(2H-1), where W is the width and H is the height of the original image. Another way of zero diluting an image is by right adjoining a column consisting of ‘0s’ to every column and inserting a row consisting of ‘0s’ below every row. This yields a new image with a size (2W)×(2H), where W is the width and H is the height of the original image. Alternatively, subsampling of an image is carried out by forcing pixel values in the alternate columns and rows to zero. Thus, the size of the subsampled image is reduced to half of the size of the original image. This means 75% of the information in the original image is lost in the subsampled image. On the other hand, zero dilution of an image does not cause loss of information but increases the possibility of predicting more information. The question that arises here is whether it is possible to predict more pixel values, which are called interpolants so that the reconstructed image is an enhanced version of the original image in resolution. In this paper, two novel interpolant prediction techniques, which are reliable and computationally efficient, are discussed. They are (i) interpolant prediction using neighborhood pixel value averaging and (ii) interpolant prediction using extended morphological filtering. These techniques can be applied to predict interpolants in a subsampled image also.</p> 2021-01-12T09:25:15-05:00 Copyright (c) 2021 T. Kishan Rao, M. Shankar Lingam, Manish Prateek, E. G. Rajan https://ejece.org/index.php/ejece/article/view/265 EEG Channel Selection Using A Modified Grey Wolf Optimizer 2021-02-25T17:54:53-05:00 Hussien Rezk Hussien hussienrezk@students.mans.edu.eg El-Sayed M. El-Kenawy skenawy@ieee.org Ali I. El-Desouky prof.desoky@gmail.com <p>Consider an increasingly growing field of research, Brain-Computer Interface (BCI) is to form a direct channel of communication between a computer and the brain. However, extracting features of random time-varying EEG signals and their classification is a major challenge that faces current BCI. This paper proposes a modified grey wolf optimizer (MGWO) that can select optimal EEG channels to be used in (BCIs), the way that identifies main features and the immaterial ones from that dataset and the complexity to be removed. This allows (MGWO) to opt for optimal EEG channels as well as helping machine learning classification in its tasks when doing training to the classifier with the dataset. (MGWO), which imitates the grey wolves leadership and hunting manner nature and which consider metaheuristics swarm intelligence algorithms, is an integration with two modification to achieve the balance between exploration and exploitation the first modification applies exponential change for the number of iterations to increase search space accordingly exploitation, the second modification is the crossover operation that is used to increase the diversity of the population and enhance exploitation capability. Experimental results use four different EEG datasets BCI Competition IV- dataset 2a, BCI Competition IV- data set III, BCI Competition II data set III, and EEG Eye State from UCI Machine Learning Repository to evaluate the quality and effectiveness of the (MGWO). A cross-validation method is used to measure the stability of the (MGWO).</p> 2021-01-12T09:25:46-05:00 Copyright (c) 2021 hussien rezk hussien https://ejece.org/index.php/ejece/article/view/288 Improving Power Quality and Mitigation of Harmonic Distortion Impact at Photovoltaic Electric Vehicle Charging System 2021-02-25T17:54:53-05:00 Adel Elgammal adel_elgammal2000@yahoo.com Curtis Boodoo adel_elgammal2000@yahoo.com <p>This article offers a clear and realistic design for an active power filter to increase reliability and power quality of the photovoltaic charging system and a high-penetration electric vehicle distribution system<em>.</em> The MOPSO algorithm is used as the basis for problems with optimization and filter tuning. A typical regular load curve is used to model the warped power grid over a 24-hour cycle to estimate the total harmonic distortion (THD). For structures with high penetration of electric cars, the probability of minimizing THD (for example to five percent) is explored via optimum capacity active shunt filters and shunt capacitors. To maximize general performance of the charging system, the switching systems are re-scheduled. Moreover, to increase the current control accuracy of shunt active filter, the fuzzy logic controller is utilized. The major drawback to new system is that it would have unrestricted billing for entire day to cope with voltage interruption. In MATLAB / SIMULINK, detailed machine setup and control algorithm experiments are simulated. The simulation findings confirm the efficiency and viability of projected shunt active filter to enhance voltage profile and track power performance of photovoltaic charging system.</p> 2021-01-20T04:40:59-05:00 Copyright (c) 2021 Adel Elgammal, Curtis Boodoo https://ejece.org/index.php/ejece/article/view/287 E-Notice Board (ENB) for the Faculty Community 2021-02-25T17:54:53-05:00 Kingsley N. Omeje Kingsley.omeje.pg83243@unn.edu.ng Henry O. Osuagwu henry.osuagwu.pg68120@unn.edu.ng Chimezie F. Ugwu chimeziefederick@gmail.com <p>This research work developed Electronic Notice Board (ENB) for the faculty community. The purpose is to upgrade the already existing manual method of information dissemination, so as to improve the administrative work of the faculty, and to create an enabling environment for more efficient and friendly means of information delivery. It will improve the rate at which staff and students participate in faculty events and activities. The conventional notice board is one of the oldest methods used in information delivery and announcements to students. Students go to where the notice board is mounted in other to read updates or announcements. Use of wall notice board in every place is a tedious work since it needs to be updated regularly and with correct and right information manually. Few of the problems that necessitated the need for ENB are; inadequate time to read all the relevant information pasted newly on a notice board as a result of tight schedule since the copies are limited. Limited time-lag of newly pasted notice since people mutilate, remove or destroy the paper notices from the board leaving others uninformed. Some of the objectives are to enable individuals to view the update from their various devices from any location. To enable instant update to all users since notice is online. To allow individuals download and store copies of original information intact. Generally, it looks at the existing faculty notice boards, building a system that makes it run by the internet access or by local area network (LAN) so as to increase the rate at which relevant information is being disseminated to the faculty community with no location restriction. The user is kept updated each time the E-Notice Board is updated based on their categories through an SMS alert. This system intends to simplify and improve the University faculties to perform their daily activities since most of the school organs uses computerized system. This research work was designed using Object Oriented Analysis and Design Methodology (OOADM) and implemented using Hypertext Pre-Processor (PHP), Hypertext Markup Language (HTML), Bootstrap, Cascading Style Sheet (CSS) as front-end and My Structural Query Language (MYSQL) database as back-end.</p> 2021-01-20T08:46:25-05:00 Copyright (c) 2021 Kingsley N. Omeje, Henry O. Osuagwu, Chimezie F. Ugwu https://ejece.org/index.php/ejece/article/view/273 Remote Monitoring Technology for COVID-19 Patients 2021-02-25T17:54:51-05:00 Prakash Kanade kanade_prakash@yahoo.com Monis Akhtar monisakhtar0503@gmail.com Fortune David fortunekbz2009@gmail.com <p class="Abstract"><span lang="EN-US">Human beings have adapted to a new way of life, from an open society to a closed world. Covid19 has brought many changes to the way people live, social distance and minimal to no contact are our goals. This could have been impossible if we were not surrounded by technology. This Perspective offers a context for the implementation of Remote Technologies, demonstrating the forms in which pandemic preparation, monitoring, research, tracking, and Health Care Technologies are effectively implemented. Our research is focused on providing a solution for handling patients at health facilities with the help of remote technologies keeping in mind the importance of social distancing and minimum to no contact to minimize the spread of the virus. The strategy is to identify the two fronts where contact with a patient is to be made. The first front is the point at which a patient needs to be detected and classified as a potential risk, at this stage the technology needs to identify the patient's symptoms, gather relevant data, and help doctors build a portfolio. The second front is where an admitted patient needs to be monitored and taken care of with regular check-ups, the technology should also take good of the patient’s mental health. The paper proposes a solution to device remote technologies that could prove beneficial in the fight against the deadly coronavirus.</span></p> 2021-01-22T14:22:21-05:00 Copyright (c) 2021 Prakash Kanade, Monis Akhtar, Fortune David https://ejece.org/index.php/ejece/article/view/294 Optimal Design, Dynamic Modeling and Analysis of a Hybrid Power System for a Catamarans Boat in Bangladesh 2021-02-02T03:51:17-05:00 Mohammad Abu Abdullah Al Mehedi malmehedi@mun.ca M. Tariq Iqbal tariq@mun.ca <p class="Abstract" style="text-indent: 10.2pt;"><span lang="EN-US" style="color: #333333;">Bangladesh is a land of rivers, canals, and lakes where water transportation is an essential means of transport. The country use boats as one of the leading resources of a carrier in its widespread inland waterways. Most of the currently used boats use only diesel for fuel. Appropriate use of renewable energy sources, particularly solar energy with diesel generators, could reduce diesel consumption. In this paper, a typical boat energy requirement was calculated to be 42.10 kWh/day. A boat could be driven by a DC motor using electrical power generated using an onboard PV system, battery, and a small generator. The carrying capacity of the vessel is 20passenger for 8hours a day. The designed system consists of a 10.6 kW PV, 1.6kW rated small gas generator, onboard battery storage consists of 16 batteries, each placed 6V, 333 Ah, and a 48 V DC motor rated 5&nbsp;kW 3000 rpm with a speed controller. The paper includes system design details and sizing using HOMER Pro</span><span lang="EN-US"> and dynamic simulation using MATLAB Simulink. </span></p> 2021-02-02T03:51:16-05:00 Copyright (c) 2021 Mohammad Abu Abdullah Al Mehedi, M. Tariq Iqbal https://ejece.org/index.php/ejece/article/view/282 Procedure for the Contextual, Textual and Ontological Construction of Specialized Knowledge Bases 2021-02-02T04:08:05-05:00 François Achille Djontu Tajouo djontu.tajouo@gmail.com Thierry Noulamo thierry.noulamo@gmail.com Jean-Pierre Lienou lienou@gmail.com <p>Information Retrieval (IR) from data sources such as the web, databases, sensors, etc., and structuring it through ontologies is an ambitious research field that leads to the reduction of information search time, improvement of the quality of found information and the efficient decision making. In this work, we have proposed a system for extracting information from several data sources to enrich an ontology in the field of plant pathology. The objective of this work is to develop a knowledge base in the field of plant pathology, by structuring the data present in various data sources accessible mainly through the web. To do this, we first propose a modular development approach of a domain ontology. The construction of the ontology at first uses the text-based construction technique and then, we use the generic architecture of a web data extraction system technique from literature to propose a data extraction system for the enrichment of the different ontology modules of the domain. For each subsystem of our extraction system, we have developed the algorithms to be implemented.</p> 2021-02-02T04:08:05-05:00 Copyright (c) 2021 François Achille Djontu Tajouo, Thierry Noulamo, Jean-Pierre Lienou https://ejece.org/index.php/ejece/article/view/298 Big Data Analysis Proposal for Manufacturing Firm 2021-02-15T05:54:01-05:00 Alicia Valdez aliciavaldez@uadec.edu.mx Griselda Cortes griselda.cortes.morales@uadec.edu.mx Laura Vazquez laura_vazquez@uadec.edu.mx Adriana Martinez adrianaarmenta@uadec.edu.mx Gerardo Haces ghaces@uat.edu.mx <p>The analysis of large volumes of data is an important activity in manufacturing companies, since they allow improving the decision-making process. The data analysis has generated that the services and products are personalized, and how the consumption of the products has evolved, obtaining results that add value to the companies in real time.</p> <p>In this case study, developed in a large manufacturing company of electronic components as robots and AC motors; a strategy has been proposed to analyze large volumes of data and be able to analyze them to support the decision-making process; among the proposed activities of the strategy are: Analysis of the technological architecture, selection of the business processes to be analyzed, installation and configuration of Hadoop software, ETL activities, and data analysis and visualization of the results. With the proposed strategy, the data of nine production factors of the motor PCI boards were analyzed, which had a greater incidence in the rejection of the components; a solution was made based on the analysis, which has allowed a decrease of 28.2% in the percentage of rejection.</p> 2021-02-15T05:54:01-05:00 Copyright (c) 2021 Alicia Valdez, Griselda Cortes, Laura Vazquez, Adriana Martinez, Gerardo Haces https://ejece.org/index.php/ejece/article/view/299 The Global System for Mobile Communications (GSM) for Wireless Home Security with Arduino and Web CAM 2021-02-20T12:25:28-05:00 Abu Bakar Ibrahim abupsp@gmail.com Che Zalina Zulkifli chezalina@fskik.upsi.edu.my Hafizul Fahri Hanafi hafizul@fskik.upsi.edu.my Fatikah Anis Zakaria fatikahanis@yahoo.com.my <p>This project presents the global Mobile Communication System (GSM) for Wireless Home Security with Arduino and Web CAM. This study aims to expand the use of Arduino and GSM as one of the tools of home security system. The second is to develop a relatively inexpensive and easy-to-use home security system. The third is to develop a security system with the concept of self-monitoring. The fourth is to make it easier for users to be more sensitive to their home condition by simply receiving SMS. The methodology that has been used in developing this project is the Engineering Design Process model. Generally, this model has 9 phases. Each phase found in this model can help the researcher ensure that the product developed can achieve the set objectives. Researchers have analyzed all data and can conclude that 70 percent of respondents agree that the system designed can reduce theft and improve home security features. Respondents also agreed that this system could be applied in real situations. In addition, all respondents agreed that the system is safe to use, with a total percentage of 86 percent agree and 14 percent strongly agree. The final result could illustrate that this developed system can provide benefits and benefits to users.</p> 2021-02-20T12:24:27-05:00 Copyright (c) 2021 Abu Bakar Ibrahim, Che Zalina Zulkifli, Hafizul Fahri Hanafi, Fatikah Anis Zakaria https://ejece.org/index.php/ejece/article/view/300 Cellular Internet of Things Based Power Monitoring System for Networking Devices 2021-02-20T12:32:22-05:00 Olaide Ayodeji Agbolade oaagbolade@futa.edu.ng Fatai Olaoluwa Sunmola oaagbolade@futa.edu.ng <p class="Abstract"><span lang="EN-US">Voltage and frequency stability is critical for network devices like routers, switches and radios. Prolonged exposure of these devices to extreme voltage or frequency makes them susceptible to damage. Since these devices are usually operated round the clock and oftentimes in remote places, it becomes necessary to monitor the quality of the power delivered to them. In this work, we developed a power monitoring system to provide remote access to the supply voltage and frequency of network equipment powered by an uninterrupted power supply system. We develop an instrumentation system to monitor the grid frequency, grid voltage, as well as the UPSS output voltage. We equally present a complete system that processes sensors’ data and make them available to a remote server over a cellular network with a robust email and SMS notification system. Sensors data collated over one month show consistent results with correlation of 0.95 with an overall system power consumption of 83 mA.</span></p> 2021-02-20T12:32:22-05:00 Copyright (c) 2021 Olaide Ayodeji Agbolade, Fatai Olaoluwa Sunmola https://ejece.org/index.php/ejece/article/view/259 Expiry Date Digit Recognition using Convolutional Neural Network 2021-02-24T06:40:55-05:00 Tareq Khan tareq.khan@emich.edu <p>The expiry dates printed on the merchandise have a distinct background, font, alignment, and color in comparison with the available handwritten digit datasets. In this paper, an expiry date dataset is used, and also a convolutional neural network (CNN) model is proposed to recognize expiry dates out of images. This model may be employed together with our previously proposed smart expiry architecture to get an automated notification to the smartphone for the foods which are expiring soon. The suggested deep learning model is tested and has a classification accuracy of 90%.</p> 2021-02-24T06:40:55-05:00 Copyright (c) 2021 Tareq Khan