European Journal of Electrical Engineering and Computer Science 2020-08-04T03:42:07-04:00 European Journal of Electrical Engineering&Computer Science 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=""><strong>E-mail</strong></a></span> to<br>Â&nbsp;<a href=""></a></p> </td> </tr> </tbody> </table> <table style="width: 100%;" cellpadding="7"> <tbody> <tr> <td>Â&nbsp; <iframe src="" 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="">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 (</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="">CrossRef</a>Â&nbsp;and assigned aÂ&nbsp;<a href="">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="">.DOCX template format</a>, and also accepts<span class="Apple-converted-space">Â&nbsp;</span><a href="">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> Rumor Detection in Social Media with User Information Protection 2020-07-01T16:39:16-04:00 Md Rashed Ibn Nawab Kazi Md. Shahiduzzaman Titya Eng Md. Noor Jamal <p>Many researchers have already shown that only user-based or content-based features are not enough to detect rumor in social media and for better prediction we need to consider both. In our research, we argue that the word embedding feature and sentiment score with subjectivity can also play a vital role in this detection task. Moreover, to detect the rumor at a very early stage and debunk it we may need to make the detection framework portable to legitimate users. This critical situation demands a secure implementation of rumor detection framework so that the user information used for training the prediction model can be protected from unauthorized access. In our experiment, we have also found that besides SVM, Logistic Regression and Random Forest algorithms, Artificial Neural Network and k-Nearest Neighbor can be used for rumor detection purpose where Artificial Neural Network and Random Forest outperformed (more than 90%) among all these algorithms in terms of accuracy. Other three algorithms also performed well with 80% or more accuracy level. To establish the robustness and efficiency of our proposed rumor detection mechanism, Precision, Recall, F1 Score, 10-fold Cross Validation, MCC, Confusion Matrix performance measures are used.</p> 2020-07-01T16:39:16-04:00 Copyright (c) 2020 Md Rashed Ibn Nawab, Kazi Md. Shahiduzzaman, Titya Eng, Md. Noor Jamal Training of the Naïve Bayes Classifier for the Detection of the Power Quality Events (Voltage Dip, Voltage Swell and Voltage Interruption) 2020-07-15T15:26:45-04:00 Oluwaseun Elijah Adegbite M. O. Okelola <p>The effect of the Power Quality events can be devastating if not properly managed. To manage such PQ events effective detection and classification techniques must be developed. There are various mathematical models that can be used in the detection and classification of the events which could vary from Dip, Swell, Interruption, and Harmonic distortion. The paper is based on the classification of Voltage Dip, Voltage Swell and Voltage Interruption using the STFT as the method of the detection of the triggering point and using such synthetic signal to train the Naïve Bayes classifier to develop a classifier that is capable of classifying waveform signals that has such disturbances in them.</p> 2020-07-15T00:00:00-04:00 Copyright (c) 2020 Oluwaseun Elijah Adegbite, M. O. Okelola Modelling of Alpha and Beta for Rain Rate Prediction for Radio Propagation Systems 2020-07-17T05:03:07-04:00 Y. K. Sanusi O. Oyeleke A. O. J. Abiodun G. A. Alagbe <p>&nbsp;The effect of rain in the design of satellite and terrestrial microwave radio links is of interest to Engineers and Scientists. It is good to have a reliable design that guarantees high level of accuracy of the rain rate distribution from the lowest rain rate value to the highest. The present work proposes a model that expresses rain rate as a function of alpha and beta obtained at 0.01% of time. When tested, the results obtained with the measurement perform well for the stations considered at a rain rated between 5mm/h to 200mm/h. Thus, , the empirical models that were obtained through them could be a useful tool for the radio design engineers for high rain rate areas.</p> 2020-07-17T05:03:07-04:00 Copyright (c) 2020 Y. K. Sanusi, O. Oyeleke, A. O. J. Abiodun, G. A. Alagbe Comparisons Among Multiple Machine Learning Based Classifiers for Breast Cancer Risk Stratification Using Electrical Impedance Spectroscopy 2020-07-18T13:27:22-04:00 Md. Toukir Ahmed Md. Rayhanul Masud Abdullah Al Mamun <p>Nowadays, women worldwide are affected greatly by Breast cancer. The consequences of the disease and the number of affected are so alarming that it requires immediate attention. Prediction of the disease is the primary and most significant route to prevention of it. This study aims to have a comparison among multiple machine learning based classifiers for breast cancer risk stratification using resonance-frequency electrical impedance spectroscopy. Five machine learning based classifiers namely- Naïve Bayes, Multilayer perceptron, J48, Bagging and Random Forest were applied to the dataset and a comparison was made based on different performance metrics. The study demonstrated that Random Forest classifier performed slightly better than the others in both splitting and folding of the dataset.</p> 2020-07-18T13:27:22-04:00 Copyright (c) 2020 Md. Toukir Ahmed, Md. Rayhanul Masud, Abdullah Al Mamun Evaluation Transient Stability of Large Scale Power System with Multi-Terminal HVDC 2020-07-20T12:15:49-04:00 Prechanon Kumkratug <p>This paper presents the method of evaluating transient stability of large scale power system equipped with multi-terminal high voltage direct current (MTDC). The power system including synchronous machine, transmission network, and HVDC is based on the concepts of stability mode. In addition, various techniques to reduce the simulation time are systematically applied. The proposed method helps us to access the transient stability of the system with MTDC in the much simpler way. The verification of the methods is tested on 20 generators in an IEEE 118-bus system under various cases.</p> 2020-07-20T12:15:49-04:00 Copyright (c) 2020 Prechanon Kumkratug Toward Palmprint Recognition Methodology Based Machine Learning Techniques 2020-07-20T12:22:10-04:00 M. M. Ata K. M. Elgamily M. A. Mohamed <p>The presented paper proposes an algorithm for palmprint recognition using seven different machine learning algorithms. First of all, we have proposed a region of interest (ROI) extraction methodology which is a two key points technique. Secondly, we have performed some image enhancement techniques such as edge detection and morphological operations in order to make the ROI image more suitable for the Hough transform. In addition, we have applied the Hough transform in order to extract all the possible principle lines on the ROI images. We have extracted the most salient morphological features of those lines; slope and length. Furthermore, we have applied the invariant moments algorithm in order to produce 7 appropriate hues of interest. Finally, after performing a complete hybrid feature vectors, we have applied different machine learning algorithms in order to recognize palmprints effectively. Recognition accuracy have been tested by calculating precision, sensitivity, specificity, accuracy, dice, Jaccard coefficients, correlation coefficients, and training time. Seven different supervised machine learning algorithms have been implemented and utilized. The effect of forming the proposed hybrid feature vectors between Hough transform and Invariant moment have been utilized and tested. Experimental results show that the feed forward neural network with back propagation has achieved about 99.99% recognition accuracy among all tested machine learning techniques.</p> 2020-07-20T12:22:10-04:00 Copyright (c) 2020 M. M. Ata, K. M. Elgamily, M. A. Mohamed Towards the Ensemble: IPCBR Model in Investigating Financial Bubbles 2020-07-21T06:59:43-04:00 Francis Ekpenyong Georgios Samakovitis Stelios Kapetanakis Miltos Petridis <p>Asset value predictability remains a major research concern in financial market especially when considering the effect of unprecedented market fluctuations on the behaviour of market participants.</p> <p>This paper presents preliminary results toward the building a reliable forward problem on ensemble approach IPCBR model, that leverages the capabilities of Case based Reasoning(CBR) and Inverse Problem Techniques (IPTs) to describe and model abnormal stock market fluctuations (often associated with asset bubbles) using datasets from historical stock market prices. The framework uses a rich set of past observations and geometric pattern description and then applies a CBR to formulate the forward problem, Inverse Problem formulation is then applied to identify a set of parameters that can statistically be associated with the occurrence of the observed patterns.</p> <p>This research work presents a formative strategy aimed to determine the causes of behaviour, rather than predict future time series points which brings a novel perspective to the problem of asset bubbles predictability, and a deviation from the existing research trend. The results depict the stock dynamics and statistical fluctuating evidence associated with the envisaged bubble problem.</p> 2020-07-21T06:59:43-04:00 Copyright (c) 2020 Francis Ekpenyong, Georgios Samakovitis, Stelios Kapetanakis, Miltos Petridis Data Mining and Data Analytics for Analysing Customer Churn Rate 2020-07-30T03:33:24-04:00 Sharan Kumar Paratala Rajagopal <p>This research paper describes how to determine the various factors impacting the customers churn rate in telecom industry. And what factors impact customer to move from one telecom source to another. Using data analytics and data mining will analyze the factors for churn rate.</p> 2020-07-30T03:33:24-04:00 Copyright (c) 2020 Sharan Kumar Paratala Rajagopal ICT as a Tool to Foster Teaching and Learning in Nigeria 2020-07-31T04:18:13-04:00 GANIYU ABIODUN SALIHU NURA SIDI UMAR <p>Advancement in technology has brought about information technology. Information and communication technology (ICT) has changed the methods of carrying out activities in different areas of human endeavours. As a result of the world rapidly adopting digital media and information, the roles of ICT in assuring quality education is becoming important and the importance is expected to continue growing.&nbsp; In this paper, the effectiveness of adopting ICT as a tool for Teaching/Learning Processes and academic performance was investigated and issues militating against integration of ICT were reviewed. A total of 90 questionnaires were administered to respondents who were students selected randomly from three polytechnics in Nigeria. The selected students were classified into experimental group (learning using ICT) and control group (learning without ICT).&nbsp; Interviews were also employed for selected lecturers. The results show that the use of ICT as a tool for learning has improved the learning outcome of the selected students and the use of ICT for teaching has made teaching very interesting to students with consequential increase in performance of students. Integration of ICT into Teaching and Learning is considered to be a necessary issue for students, educators and education administrators to assure better understandings and effective teachings.</p> 2020-07-31T04:18:13-04:00 Copyright (c) 2020 GANIYU ABIODUN SALIHU, NURA SIDI UMAR Three-Phase Distribution System Load Flow Analysis Using Sequence Components 2020-08-04T03:42:07-04:00 Rudy Gianto <p>Electric power distribution system are usually unbalance. Therefore, a power flow method that can handle the three-phase configuration of the power system is needed so that the system planning and operation can properly be carried out. In the case of three-phase distribution system power flow analysis, for each system bus (except for substation bus), the voltage magnitude and angle of the three phases must be calculated. These calculations are carried out under certain loading conditions. After these voltages have been calculated, the electric power flows and losses in the distribution lines, and the substation power can also be determined. This paper proposes a new technique for three-phase distribution system power flow analysis using sequence components. The new formulation for the power flow problem in terms of sequence components is also proposed and developed in this paper. The application of sequence components has the advantage that the size of the problem can effectively be reduced, and solution to the power flow problem will be easier to find. Case study using a representative distribution test system confirms the validity of the proposed method where comparative studies between the proposed (i.e. sequence components based) method and the phase components based method are carried out.</p> 2020-08-04T03:42:07-04:00 Copyright (c) 2020 Rudy Gianto