International Journal of Electrical and Electronics Research最新文献

VSC-STATCOM Performance Under Different Fault Sensing using PSO Tuned Hybrid SMC 使用 PSO 调谐混合 SMC 的 VSC-STATCOM 在不同故障感应下的性能

International Journal of Electrical and Electronics Research Pub Date : 2024-05-05 DOI: 10.37391/ijeer.120220

S. Rajendran, A. Muthukumar, K. Vijayakumar, K. Rajesh

引用次数: 0

Application of Many-Objective Arithmetic Optimization Algorithm and TOPSIS for Optimal Planning of DGS in Distribution Systems 多目标算术优化算法和 TOPSIS 在配电系统 DGS 优化规划中的应用

International Journal of Electrical and Electronics Research Pub Date : 2024-05-05 DOI: 10.37391/ijeer.120219

Srikant Ganji, J. N. Manohar, G. Yesuratnam

{"title":"Application of Many-Objective Arithmetic Optimization Algorithm and TOPSIS for Optimal Planning of DGS in Distribution Systems","authors":"Srikant Ganji, J. N. Manohar, G. Yesuratnam","doi":"10.37391/ijeer.120219","DOIUrl":"https://doi.org/10.37391/ijeer.120219","url":null,"abstract":"The traditional planning of distribution networks is changing because of the accelerated expansion of distributed generation (DG) technologies in various capacities and forms. However, the improper integration of DGs in current distribution networks can give rise to several technical difficulties despite the advantages provided by distributed generation technologies. This paper presents the optimal DG planning in the distribution system using a Pareto-based many-objective arithmetic optimization algorithm (MOAOA) for optimal DG planning problems in the distribution system. This work focuses on improving four technical metrics related to distribution systems: mitigation of electrical energy not served (EENS), total voltage deviation (TVD) minimization, voltage stability index (VSI) maximization, and energy loss mitigation. Two scenarios are considered: the first scenario primarily focuses on optimal planning of DGs supporting active power only (e.g. Micro-Turbines DGs), and the second scenario focuses on optimal planning of DGs supporting both active and reactive power support (e.g. BIOMASS DGs). The optimal Pareto fronts between the competing objectives are generated using the Pareto-based MOAOA algorithm. The TOPSIS (a technique for order performance by similarity to ideal solution) multi-criteria decision-making technique is utilized for selecting the best trade-off solution from the optimal Pareto front. The posited method is examined on two standard IEEE-69 bus distribution systems. The efficacy of the MOAOA is compared with the outcomes of MOPSO, MOGWO and NSGA-II.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"261 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012960","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}

引用次数: 0

Risk Assessment of Radial Distribution Systems using Modified Jelly Fish Search Algorithm to analyse the Performance Indices 利用改良水母搜索算法分析性能指标，对径向配电系统进行风险评估

International Journal of Electrical and Electronics Research Pub Date : 2024-05-05 DOI: 10.37391/ijeer.120217

K.C. Archana, Y.V. Sivareddy, V. Sankar

{"title":"Risk Assessment of Radial Distribution Systems using Modified Jelly Fish Search Algorithm to analyse the Performance Indices","authors":"K.C. Archana, Y.V. Sivareddy, V. Sankar","doi":"10.37391/ijeer.120217","DOIUrl":"https://doi.org/10.37391/ijeer.120217","url":null,"abstract":"One of the essential techniques for figuring out Power Distribution System performance is reliability evaluation. With time, the range of methods for assessing reliability has grown, and the distribution system's evolution has also become more intricate. The likelihood of a network failing grows with time once it begins to function, especially if it is used for an extended period. Reliability indices have been evaluated using different algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and various modified versions of algorithms. The Jelly Fish Search Algorithm has been used in various power system applications such as to determine the most cost-effective way to dispatch generating units' loads, integrate Distributed Generation (DG) units, track the maximum power of photovoltaic systems, and determine optimal power flow solutions, among other uses. The performance indices for the Radial Distribution System (RDS) have not been evaluated using JFSA.Variation of performance indices with respect to unavailability has not been discussed in the literature. Here an attempt is made to analyse the variation of the indices with the unavailability. The proposed algorithm is evaluated first on 3 load point radial distribution system and the computations are performed on the popular IEEE-RBTS Bus2 test system. Based on the output it is observed that for the both the systems the behaviour of the indices with respect to the unavailability is in similar fashion. The equations are derived for the performance indices using the Minitab. With the equations obtained the Performance indices values can be predicted for the given unavailability value. It is the better appropriate method for the assessing the performance indices of Radia Distribution System.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141011902","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}

引用次数: 0

A Switched Z-Source and Switched Capacitor Multi-Level Inverter Integrated Low Voltage Renewable Source for Grid Connected Application 一种用于并网应用的集成低压可再生能源的开关式 Z 源和开关式电容器多电平逆变器

International Journal of Electrical and Electronics Research Pub Date : 2024-05-05 DOI: 10.37391/ijeer.120218

S. Sreenu, Dr. J. Upendar

{"title":"A Switched Z-Source and Switched Capacitor Multi-Level Inverter Integrated Low Voltage Renewable Source for Grid Connected Application","authors":"S. Sreenu, Dr. J. Upendar","doi":"10.37391/ijeer.120218","DOIUrl":"https://doi.org/10.37391/ijeer.120218","url":null,"abstract":"Most of the renewable sources generate power at lower voltage levels in the range of 20-50V which cannot be utilized by the loads. Therefore, stacking multiple modules in series increases the voltage level or using conventional boost converter or QZSis helpful. However, due to series stacking and boost converter or QZS there is a great power loss and also have reliability issues.The QZS inverter has very less boosting gain in the range of 2times. Theconventional boost converter or QZSis replaced with SZSC for voltage boosting and inverter operation. The SZSC boosts the voltage 4-5 times to the input voltage level. For further mitigation of harmonics, the conventional 6-switch inverter is replaced with switched capacitor MLI. Multiple renewable sources are at the input which include PV array, battery unit and PMSG wind module. The battery unit is a support to the renewable sources PV array and wind module. The DC link voltage stability is achieved by the battery unit placed in parallel to the renewable sources. The renewable sources share power to the grid through the SZSC and switched capacitor MLI. For DC voltage stability a CV control is integrated to SZSC. And for synchronized power sharing to the grid, a grid voltage feedback synchronization control is included for the control of MLI. A low rating renewable system is modelled and integrated to grid using Simulink MATLAB software. A comparative analysis is carried out operating the system with QZS and SZSC. The performances of the SZSC and MLI are evaluated by the graphs generated by the simulation of the modelled system.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"236 5‐8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012846","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}

引用次数: 0

An Optimized Fuzzy C-Means with Deep Neural Network for Image Copy-Move Forgery Detection 用于图像复制移动伪造检测的优化模糊 C-Means 与深度神经网络

International Journal of Electrical and Electronics Research Pub Date : 2024-03-28 DOI: 10.37391/ijeer.120142

Parameswaran Nampoothiri V, Dr. N. Sugitha

{"title":"An Optimized Fuzzy C-Means with Deep Neural Network for Image Copy-Move Forgery Detection","authors":"Parameswaran Nampoothiri V, Dr. N. Sugitha","doi":"10.37391/ijeer.120142","DOIUrl":"https://doi.org/10.37391/ijeer.120142","url":null,"abstract":"Copy Move Forgery Detection (CMFD) is one of the significant forgery attacks in which a region of the same image is copied and pasted to develop a forged image. Initially, the input digital images are preprocessed. Here the contrast of input image is enhanced. After preprocessing, Optimized Fuzzy C-means (OFCM) clustering is used to group the images into several clusters. Here the traditional FCM centroid selection is optimized by means of Salp Swarm Algorithm (SSA). The main inspiration of SSA is the swarming behavior of salps when navigating and foraging in oceans. Based on that algorithm, optimal centroid is selected for grouping images. Next, the unique features are extracted from each cluster. Due to the robust performance, the existing approach uses the SIFT-based framework for detecting CMFD. However, for some CMFD images, these approaches cannot produce satisfactory detection results. In order to solve this problem, the current method utilizes the stationary wavelet transform (SWT). After extracting the features, the CMFD detection is done by RB (Radial Basis) based neural network. Additionally, it is computed by means of diverse presentation metrics like sensitivity, specificity, accuracy; Positive Predictive Value (PPV), Negative Predictive Value (NPV), False Positive Rate (FPR), False Negative Rate (FNR) and False Discovery Rate (FDR). The proposed copy move forgery detection method is implemented in the working platform of MATLAB.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"52 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140373337","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}

引用次数: 0

A Novel Transfer Learning Approach to Improve Breast Cancer Diagnosing on Screening Mammography 改进乳腺癌筛查诊断的新型迁移学习方法

International Journal of Electrical and Electronics Research Pub Date : 2024-03-28 DOI: 10.37391/ijeer.120141

Dr. G N Keshava Murthy, Dr. Chaitra H V, Dr. Vidya E V, Dr. Manjula B M, Dr. Chetana Srinivas

{"title":"A Novel Transfer Learning Approach to Improve Breast Cancer Diagnosing on Screening Mammography","authors":"Dr. G N Keshava Murthy, Dr. Chaitra H V, Dr. Vidya E V, Dr. Manjula B M, Dr. Chetana Srinivas","doi":"10.37391/ijeer.120141","DOIUrl":"https://doi.org/10.37391/ijeer.120141","url":null,"abstract":"Segmentation is a technique for separating an image into discrete areas in order to separate objects of interest from their surroundings. In image analysis, segmentation—which encompasses detection, feature extraction, classification, and treatment—is crucial. In order to plan treatments, segmentation aids doctors in measuring the amount of tissue in the breast. Categorizing the input data into two groups that are mutually exclusive is the aim of a binary classification problem. In this case, the training data is labeled in a binary format based on the problem being solved. Identifying breast lumps accurately in mammography pictures is essential for the purpose of prenatal testing for breast cancer. The proposed TLA (Transfer Learning Approach) based CNN (Convolution Neural Network) –TLA based CNN aims to offer binary classification for rapid and precise breast cancer diagnosis (benign and malignant). In order to predict the sub-type of cancer, this exploration as used Deep Learning techniques on the Histogram of Oriented Gradient (HOG) - Feature extraction technique that creates a local histogram of the image to extract features from each place in the image with CNN classifier. This research work employs two well-known pre-trained models, ResNet-50 and VGG16, to extract characteristics from mammography images. The high-level features from the Mammogram dataset are extracted using a transfer learning model based on Visual Geometry Group (VGG) with 16-layer and Residual Neural Network with 50-layers deep model architecture (ResNet-50). The proposed model TLA based CNN has achieved 96.49% and 95.48% accuracy as compared to ResNet50 and VGG16 in the breast cancer classification and segmentation.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"28 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140372889","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}

引用次数: 0

Nutrient Deficiency of Paddy Leaf Classification using Hybrid Convolutional Neural Network 利用混合卷积神经网络对水稻叶片的营养缺乏症进行分类

International Journal of Electrical and Electronics Research Pub Date : 2024-03-28 DOI: 10.37391/ijeer.120139

Sherline Jesie R, Godwin Premi M S

{"title":"Nutrient Deficiency of Paddy Leaf Classification using Hybrid Convolutional Neural Network","authors":"Sherline Jesie R, Godwin Premi M S","doi":"10.37391/ijeer.120139","DOIUrl":"https://doi.org/10.37391/ijeer.120139","url":null,"abstract":"For billions of people worldwide, enhancing the quantity and quality of paddy production stands as an essential goal. Rice, being a primary grain consumed in Asia, demands efficient farming techniques to ensure both sufficient yields and high-quality crops. Detecting diseases in rice crops is crucial to prevent financial losses and maintain food quality. Traditional methods in the agricultural industry often fall short in accurately identifying and addressing these issues. However, leveraging artificial intelligence (AI) offers a promising avenue due to its superior accuracy and speed in evaluation. Nutrient deficiencies significantly impact paddy growth, causing issues like insufficient potassium, phosphorus, and nitrogen. Identifying these deficiencies in paddy leaves, especially during the mid-growth stage, poses a considerable challenge. In response to these obstacles, a novel approach is proposed in this study—a deep learning model. The methodology involves gathering input images from a Kaggle dataset, followed by image augmentation. Pre-processing the images involves using the Contrast Limited Adaptive Histogram Equalization (CLAHE) model, while the extraction of features utilizes the GLCM model. Subsequently, a hybrid convolutional neural network (HCNN) is employed to classify nutrient-deficient paddy leaves. The simulation is conducted on the MATLAB platform, and various statistical metrics are employed to assess overall performance. The results demonstrate the superiority of the proposed HCNN model, achieving an accuracy of 97.5%, sensitivity of 96%, and specificity of 98.2%. These outcomes surpass the efficacy of existing methods, showcasing the potential of this AI-driven approach in revolutionizing disease detection and nutrient deficiency identification in paddy farming.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"120 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140370163","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}

引用次数: 0

Speech Enhancement with Background Noise Suppression in Various Data Corpus Using Bi-LSTM Algorithm 使用 Bi-LSTM 算法增强各种数据语料库中的语音并抑制背景噪声

International Journal of Electrical and Electronics Research Pub Date : 2024-03-28 DOI: 10.37391/ijeer.120144

Vinothkumar G, Manoj Kumar D

{"title":"Speech Enhancement with Background Noise Suppression in Various Data Corpus Using Bi-LSTM Algorithm","authors":"Vinothkumar G, Manoj Kumar D","doi":"10.37391/ijeer.120144","DOIUrl":"https://doi.org/10.37391/ijeer.120144","url":null,"abstract":"Noise reduction is one of the crucial procedures in today’s teleconferencing scenarios. The signal-to-noise ratio (SNR) is a paramount factor considered for reducing the Bit error rate (BER). Minimizing the BER will result in the increase of SNR which improves the reliability and performance of the communication system. The microphone is the primary audio input device that captures the input signal, as the input signal is carried away it gets interfered with white noise and phase noise. Thus, the output signal is the combination of the input signal and reverberation noise. Our idea is to minimize the interfering noise thus improving the SNR. To achieve this, we develop a real-time speech-enhancing method that utilizes an enhanced recurrent neural network with Bidirectional Long Short Term Memory (Bi-LSTM). One LSTM in this sequence processing framework accepts the input in the forward direction, whereas the other LSTM takes it in the opposite direction, making up the Bi-LSTM. Considering Bi-LSTM, it takes fewer tensor operations which makes it quicker and more efficient. The Bi-LSTM is trained in real-time using various noise signals. The trained system is utilized to provide an unaltered signal by reducing the noise signal, thus making the proposed system comparable to other noise-suppressing systems. The STOI and PESQ metrics demonstrate a rise of approximately 0.5% to 14.8% and 1.77% to 29.8%, respectively, in contrast to the existing algorithms across various sound types and different input signal-to-noise ratio (SNR) levels.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"103 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140370787","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}

引用次数: 0

An Evaluation of the Proposed Security Access Control for BYOD Devices with Mobile Device Management (MDM) 利用移动设备管理 (MDM) 对 BYOD 设备的拟议安全访问控制进行评估

International Journal of Electrical and Electronics Research Pub Date : 2024-03-28 DOI: 10.37391/ijeer.120138

Jimshith. V.T, Mary Amala Bai V

{"title":"An Evaluation of the Proposed Security Access Control for BYOD Devices with Mobile Device Management (MDM)","authors":"Jimshith. V.T, Mary Amala Bai V","doi":"10.37391/ijeer.120138","DOIUrl":"https://doi.org/10.37391/ijeer.120138","url":null,"abstract":"Bring Your Own Device (BYOD) at Work is a growing practice that has significantly increased network security vulnerabilities. This development has tremendous implications for both businesses and individuals in every organization. As a result of the extensive spreading of viruses, spyware, and other problematic downloads onto personal devices, the government has been forced to examine its data protection legislation. Dangerous apps are downloaded into personal devices without the user's awareness. As a result, both people and governments may suffer disastrous repercussions. In this research, proposed BYODs are troublesome since they can change policies without consent and expose private information. This type of privacy violation has a domino effect, resulting in substantial legal and financial consequences as well as decreased productivity for enterprises and governments. Governments have a daunting problem since they must protect networks from these threats while simultaneously considering user rights and privacy legislation. The framework of this paper that decreases the number of system limits and access control methods that are established for BYODs and cloud environments has been presented by the researchers of the study. They also attempted to protect user privacy by implementing Mobile Device Management (MDM) technology. The study's preliminary findings were optimistic, implying that the framework might reduce access control difficulties.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"113 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140370769","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}

引用次数: 0

Design of Enhanced Wide Band Microstrip Patch Antenna Based on Defected Ground Structures (DGS) for Sub-6 GHz Applications 设计基于缺陷接地结构 (DGS) 的增强型宽带微带贴片天线，用于 6 GHz 以下频率应用

International Journal of Electrical and Electronics Research Pub Date : 2024-03-28 DOI: 10.37391/ijeer.120143

Mohamed Lemine El Issawi, Dominic Konditi, AD Usman

{"title":"Design of Enhanced Wide Band Microstrip Patch Antenna Based on Defected Ground Structures (DGS) for Sub-6 GHz Applications","authors":"Mohamed Lemine El Issawi, Dominic Konditi, AD Usman","doi":"10.37391/ijeer.120143","DOIUrl":"https://doi.org/10.37391/ijeer.120143","url":null,"abstract":"In this paper a comprehensive comparative study of three distinct microstrip patch antenna (MPA) designs, each optimized for the sub-6 GHz applications, is presented. The initial design phase utilized a Rogers RT 5880 substrate with a permittivity (εr1) of 2.2 and a thickness(H1) of 1.42 mm. The proposed model achieved a resonance band ranging from 4.8 to 7 GHz, with a bandwidth of 2.2 GHz and a return loss (S11) of -20 dB. Subsequent enhancements involved integrating a Barium Strontium Titanate (BST) thin film (εr2 = 250, thickness(H2) = 0.005 mm), effectively shifting the operational band to 3.5-5.3 GHz. The final design iteration, which incorporated both BST and a Defective Ground Structure (DGS), represented a substantial advancement, achieving wideband operation from 1.8 to 6 GHz, expanding the bandwidth to 4.2 GHz, and improving the S11 to -25 dB. This integration also resulted in a compact antenna size of 30 x 26.5 x 1.42 mm³. These findings underscore the synergistic impact of BST and DGS in enhancing MPA design, marking a significant progression in antenna technology, vital for a range of wireless communication.","PeriodicalId":158560,"journal":{"name":"International Journal of Electrical and Electronics Research","volume":"32 33","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140372653","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}

引用次数: 0