Journal of Electrical Systems最新文献

{"title":"Quantum Convolutional Neural Networks for Line Orientation Classification in Pixelated Images","authors":"Haskar Marapelli, Hari Prasad Gandikota, K S Ranadheer Kumar, Sruthi Nath, Ch. Anil","doi":"10.52783/jes.3666","DOIUrl":"https://doi.org/10.52783/jes.3666","url":null,"abstract":"Quantum Convolutional Neural Networks (QCNNs) offer a promising avenue for image classification tasks due to their potential to leverage quantum properties for enhanced computational capabilities. In this paper, we explore the application of QCNNs for line orientation classification in pixelated images. Specifically, we investigate the differentiation between horizontal and vertical lines, a fundamental task in image processing and computer vision. We propose a QCNN architecture tailored to this task, leveraging quantum convolutional layers to extract features from pixelated images and classify line orientations. We demonstrate the effectiveness of our approach through experimental evaluation on benchmark datasets, comparing the performance of QCNNs with different optimizers. Our study integrated the QCNN operator and optimizer into Qiskit Machine Learning’s Neural Network Classifier, leveraging quantum computing techniques for classification tasks. Our QCNN model demonstrated a training accuracy of 71.43% and a test accuracy of 60.0%. Noteworthy observations include the failure of the SPSA optimizer to converge within the designated iterations, requiring twice the iterations compared to the COBYLA optimizer for convergence.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation and Operation of Various DC-DC Converter Topologies with Effective MPPT in a Photovoltaic System","authors":"Vishal G. Jotangiya","doi":"10.52783/jes.3651","DOIUrl":"https://doi.org/10.52783/jes.3651","url":null,"abstract":"This article describes the reliable and efficient DC-DC converter for Renewable Energy Sources. The system will function more accurately when the solar panel's irradiance is low. The Maximum Power Point Tracking (MPPT) control algorithm is used to operate the similar system in order to achieve greater efficiency. The characteristics curves for solar panel current v/s voltage (I–V) and power v/s voltage (P–V) are produced by MATLAB simulation. The curves derived from the experiment results are also compared to the simulation curves. A thorough analysis of solar-fed DC–DC converters (Boost, Push-Pull, and Coupled Inductor based converter) is also carried out. The proposed converters are simulated in MATLAB. Simulation results are presented and discussed. Results demonstrate the validity of the models.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Optimized Fraud Identification Framework Using DCNN For Wireless Communication","authors":"Dr D Nagaraju, Dr. Harsh Pratap, Singh, Dr. Lokendra SinghSongare, Maheswara Rao, Amit Gangopadhyay, Dr. M Sasikumar, Ziaul Haque, Choudhury, Dr.Balambigai Subramanian","doi":"10.52783/jes.3676","DOIUrl":"https://doi.org/10.52783/jes.3676","url":null,"abstract":"Convolution Neural Network (Cnn) Is The Powerful Framework To Solve The Lot Of Issues Of Link Detection In Unlabeled Wireless Communication. Last Few Decades Lot Of Fraud Detection Strategies Has Been Projected Bit That All Are Inefficient For Detecting The Frauds. Therefore, The Great Need For Effective And Fast Fraud Detection Scheme With Higher Detection Accuracy. In This Research, Spider Based Convolution Neural Network (Sbcnn) Model To Detect The Frauds In The Wireless Communication. Initially, Create The Wireless Channel To Transmit The Messages From Source To Destination.  Here, The Fraudulent Activities Are Detected Based On The Packet Delivery Time Of The Source To Destination Of The Wireless Medium. Moreover, The Proposed System Implementation Is Done In The Matlab Frame Work Additionally; The Obtained Results Are Validated With Prevailing Methods For Evaluating The Efficiency Of The Proposed Sbcnn Approach. \u0000Wireless communication fraud poses a significant threat as unauthorized use of services, compromising the security of cellular networks and infrastructure. With the surge in online services and users, the reliance on wireless communication for high-speed internet applications has grown. Despite the convenience brought by technologies like net banking, credit cards, and online services, financial frauds and unauthorized payments remain substantial risks. The intricate nature of wireless communication, illustrated in Fig. 1, where devices use signals between source and destination nodes, leads to challenges like network interference and loss rate, often exacerbated by fraudulent activities. Numerous techniques, including Artificial Intelligence (AI), hybrid ensemble models, oversampling, and machine learning, have been explored but haven't provided satisfactory solutions. In this study, an optimization-assisted intelligent framework is proposed to maximize communication performance, addressing the limitations of existing approaches. The subsequent sections analyse related research, identify issues with conventional methods, elaborate on the functioning of the proposed framework, discuss results, and conclude with research inferences","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Data Quality on Decision-Making. A Quasi Experimental Study","authors":"Afnan Alabduljabbar","doi":"10.52783/jes.3652","DOIUrl":"https://doi.org/10.52783/jes.3652","url":null,"abstract":"The current study aimed to investigate the relationship between data quality dimensions (completeness and timeliness) and decision-making efficiency. The researcher adopted the quasi-experimental approach to answer the research questions and hypotheses. The study participants consist of 60 subjects, distributed into 2 groups. The first group consisted of 20 sales executives from Saudi beverage manufacturing companies. The other group had 40 participants from Al-Imam university. The study experiment consisted of 4 scenarios, two for each dimension, that give the participants scenarios and ask them to make the best decision based on these data. The scenarios were applied through face-to-face meeting and time to take decisions was recorded by participants. For the first data quality dimension, completeness of data, both groups got scenarios where complete and incomplete data were offered, and they were asked to choose the best available option based on the offered data. For the second dimension, the groups were offered up-to-date data and obsolete data and were asked to choose the best decisions based on the scenarios. The results were analyzed for correlations to check If there is a correlation between the responses of the two groups. The study found strong evidence for a correlational relationship between data quality dimensions and decision-making efficiency at 0.05 and 0.01 significance level for the student and employee groups respectively. The study found that high-quality data leads to both better and faster decisions in both groups. There were no significant differences between occupation, or gender and time taken for making a decision. The current study highlights the importance of data quality dimensions. It urges organizations to use up-to-date data, and complete data sets to base their decisions.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Improved Feature Removal Approach for Classification of High Dimensional Feature Dataset","authors":"Hardikkumar Harishbhai Maheta","doi":"10.52783/jes.3653","DOIUrl":"https://doi.org/10.52783/jes.3653","url":null,"abstract":"Extracting and evaluating pertinent information in a high-dimensional feature set is extremely difficult when dealing with a high-dimensional feature space. Classification methods require additional training time to generate a classification model. Every feature is not equally relevant in a high-dimensional feature collection. As a result, feature selection is a productive method for identifying vital features and eliminating unnecessary ones. Feature selection serves as a method of pre-processing before classification. It decreases the dimension of the dataset to shorten the training period required to develop a classifier. This research study aims to propose a novel feature subset selection method that establishes the relative importance of each feature using several criteria. The proposed approach ranks available features from high to low using a variety of feature-ranking approaches. Different feature ranking algorithms perform differently on the same dataset. It is challenging to obtain robust performance with just one feature ranking algorithm. To overcome this problem, we have used the Schulze rank aggregation method. The Schulze method combines multiple feature ranking techniques to assign a rank to each feature inside the dataset. This study presents an optimization strategy for heuristic search based on the backward feature removal method. It eliminates features according to the rank determined by the Schulze rank aggregation technique. In this paper, we evaluated the performance of the proposed method against the current state-of-the-art feature ranking techniques for high-dimensional feature set classification.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anfis Based Energy Management System for Microgrids","authors":"Sobhana Obulareddy","doi":"10.52783/jes.3662","DOIUrl":"https://doi.org/10.52783/jes.3662","url":null,"abstract":"Microgrids are typical low or medium voltage distribution networks that operate on an adaptive system. Which, employing intelligent energy management techniques, govern the power exchange between the main grid, locally distributed generators (DGs), and associated loads. This paper describes and evaluates the intelligent ANFIS based energy management approach for grid integrated microgrid networks. The ANFIS based intelligent controller estimates the power that must be generated by (or) stored in batteries, taking into consideration of power demanded by loads and available battery power by accounting the battery state of charge. To evaluate the power allocation an artificial intelligent based technique i.e., Sugeno-based fuzzy EMS is implemented. The stated fuzzy logic control enhances power distribution within the micro-grid components while minimizing the requirement for power transfer to/from the main grid.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emotion Detection Through Electrocardiogram Signal Classification in an IOT Environment with Deep Neural Networks","authors":"Aloy Anuja Mary G","doi":"10.52783/jes.3657","DOIUrl":"https://doi.org/10.52783/jes.3657","url":null,"abstract":"An ECG detects the health and rhythm of the heart by measuring the electric activity of the heart. It has also been demonstrated that a person's emotions may influence the electrical activity of the heart. As a result, studying the electrical behaviour of the heart may simply determine a person's cardiac state and emotional wellness. IoT is a new technology that is quickly gaining acceptance throughout the world. Anybody, at any time, from anywhere, may connect to any network or service because to the extraordinary power and capacity of IoT. IoT-enabled devices have revolutionized the medical business by providing new capabilities such as remote patient monitoring and self-monitoring. This research proposed an IoT-based ECG monitoring system that employs a heart rate sensor to generate data and an intelligent hybrid classification algorithm to categorize the data. ECG monitoring has become a widely used method for detecting cardiac problems. The following are the primary contributions of this paper: To begin, this paper describes WISE (Wearable IoT-cloud-based health monitoring system), a one-of-a-kind system for real-time personal health monitoring. WISE makes use of the BASN (body area sensor network) technology to provide real-time health monitoring. WISE rapidly transfers data from the BASN to the cloud, and a lightweight wearable LCD may be included to enable quick access to real-time data. This model can address the issue of class imbalance in the ECG dataset, assisting in the development of an IoT-based smart and accurate healthcare system. Pre-processing, feature extraction, and classification are the three steps in any classification technique, whether it is emotion classification or heart health classification. Sensors are used to collect an ECG signal from a person's outside body. The provided ECG signal is first pre-processed using the Butterworth Filtering Method, which effectively reduces noise from the signal. Following pre-processing, the Adaptive Discrete Wavelet Transform technique is used to anticipate the signal's attributes. Lastly, a decision making classification approach based on relational weights is used to determine if the ECG signal is normal or abnormal.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improvement of Voltage profile by Integrating Renewable Generation Units at weak bus locations of the System","authors":"B.Harika","doi":"10.52783/jes.3667","DOIUrl":"https://doi.org/10.52783/jes.3667","url":null,"abstract":"The Grid consists of higher rating sources and transmission system that  supports local loads. The grid operates at voltages in the range of 66kV-132kV and transmits power in MW to smaller or longer distance locations. Due to higher rating power system the power quality issues are also more. For our consideration an IEEE 14 bus interconnected system is represented as grid operating at higher rated values. The weak bus of the interconnected system is determined by Fast voltage stability index (FVSI) and load flow analysis using Newton-Raphson method available in MATLAB software. The weak buses are integrated with renewable power generation units like PV plant and wind farm improving the bus characteristics. This paper presents a comparative analysis with and without the RGUs in the system. Improvisation of the parameters like power loss, reduced conventional power consumption, power factor and voltage magnitudes are validated through time domain simulations.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"End User Incentive-based Approach for Fast Charging Station","authors":"Lokendra Kumar","doi":"10.52783/jes.3612","DOIUrl":"https://doi.org/10.52783/jes.3612","url":null,"abstract":"The development of electric vehicles (EVs) is influenced by various factors such as cost, autonomy, charging speed, and infrastructure. The objective of this research paper is to model an EV fast-charging station that provides incentives to end users in terms of money. The charging station incorporates a renewable energy source (solar) and an energy storage system, taking into account the demand for EVs, state of charge (SOC), and vehicle arrival and departure times. This approach aims to increase the revenue of the station and reduce the high energy demand from the grid. To incentivize end users, the vehicle-to-grid (V2G) and battery swapping modes have been implemented. The Monte Carlo approach is used to model the demand for EVs and the production of renewable energy, considering hourly intervals. Subsequently, the installation and utilization of the EV fast-charging station (EVCS) are optimized using the Adaptive Harris Hawk Optimization (AHHO) algorithm. The system is analyzed with and without V2G and battery swapping modes. The comparison between the two modes reveals that the system with V2G and battery swapping provides both revenue and incentives to end users.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140986073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Analysis Project of OCR and DGR Protection Settings on Tristex Feeder of New Substation Using Digsilent Power Factory Software","authors":"Pawenary","doi":"10.52783/jes.3663","DOIUrl":"https://doi.org/10.52783/jes.3663","url":null,"abstract":"Increasing the reliability of the electricity system is very important in maintaining a stable and guaranteed electricity supply. One important factor in the electrical protection system is the setting of over current relay (OCR) and directional ground relay (DGR) settings. This study aims to analyze and evaluate the performance of the OCR and DGR protection settings on the New Pandaan Tristex Substation using DIgSILENT software. The method used in this      research is modeling and simulation using DIgSILENT software. Relevant data and electrical system parameters are obtained from reliable sources. OCR and DGR protection settings are evaluated by considering protection needs through simulation analysis of fault conditions and normal operation. Tristex feeder is one of the feeder in GI New Pandaan with a total length of 2.415 km. The calculation results for the OCR setting on the incoming 20 kV side obtained for the TMS value = 0.20 while for the OCR setting on the 20 kV feeder side obtained the TMS value = 0.15. Then for the DGR setting on the incoming 20 kV side, the TMS value = 0.26 is obtained, while for the DGR setting on the 20 kV feeder side, the TMS value = 0.10 is obtained.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}