2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)最新文献_第4页

Power Spectral Density, Higuchi’s Fractal Dimension and Detrended Fluctuation Analysis of sEMG at Varying Weights 功率谱密度、Higuchi分形维数和表面肌电信号在不同权重下的去趋势波动分析

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085445

Sanjoy Kumar Das, Nilotpal Das, M. Chakraborty

{"title":"Power Spectral Density, Higuchi’s Fractal Dimension and Detrended Fluctuation Analysis of sEMG at Varying Weights","authors":"Sanjoy Kumar Das, Nilotpal Das, M. Chakraborty","doi":"10.1109/ICCECE51049.2023.10085445","DOIUrl":"https://doi.org/10.1109/ICCECE51049.2023.10085445","url":null,"abstract":"Our muscle cells produce rhythmical potentials that get totalized as millions of cells discharge simultaneously and represent as a waveform, the recording of this waveform is known as Electromyogram (EMG). The device is used this recording is called Electromyograph and process of this recording is known as Electromyography. The primary objective of this work is to see the changes in muscles dynamics when a person lifts various weights. This study used power spectral density (PSD) for linear analysis of surface EMG (sEMG) signal and total powers of the muscles were evaluated. This study used HFD (Higuchi’s Fractal Dimension) analysis to estimate fractal dimension of the sEMG signal during biceps and forearm muscles activities. Using Detrended Fluctuation Analysis (DFA) nonlinear analysis the change in the pattern of the sEMG signals was observed with varying weights. Surface electrodes with required signal collection circuitry were used for the experiments, and signal data was acquired using a laptop and processed using MATLAB 2013 platform. The signal was also subjected to frequency domain analysis to measure muscle power at varying weights conditions. The fractal dimension measured varies depending on the applied weights. The investigation of the nonlinear nature of the sEMG signal at various weight situations might yield substantial results as time-based quantitative monitoring of muscle durability and regeneration.","PeriodicalId":447131,"journal":{"name":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117286643","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

Network Throughput Improvement in Wi-Fi 6 over Wi-Fi 5: A Comparative Performance Analysis Wi-Fi 6相对于Wi-Fi 5的网络吞吐量改进:比较性能分析

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085684

Dwaipayan Bandyopadhyay, Sammilita De, Sinjini Hom Roy, Deepshikha Biswas, Madhura Bhose, Raja Karmakar

{"title":"Network Throughput Improvement in Wi-Fi 6 over Wi-Fi 5: A Comparative Performance Analysis","authors":"Dwaipayan Bandyopadhyay, Sammilita De, Sinjini Hom Roy, Deepshikha Biswas, Madhura Bhose, Raja Karmakar","doi":"10.1109/ICCECE51049.2023.10085684","DOIUrl":"https://doi.org/10.1109/ICCECE51049.2023.10085684","url":null,"abstract":"Novel Wi-Fi version 6 is the youngest generation of Wi-Fi standard, which supports better throughput than its successful predecessor Wi-Fi 5. Both of these standards have several physical (PHY) layer enhancements, such as higher channel bandwidths (40/80/160 MHz), also the improved Multi User-Multiple Input and Multiple Output (MU-MIMO). The novel IEEE 802.11ax protocol now supports MU-MIMO in case of both uplink transmission and downlink transmission, whereas Wi-Fi 5 can support only downlink MU-MIMO. In addition, Wi-Fi 6 practices Orthogonal Frequency-Division Multiple Access technology which is popularly known as OFDMA technology and a higher spectral efficiency, and as a result, Wi-Fi 6 can upsurge the average throughput/area in dense networks. Moreover, modulation and coding scheme (MCS) 10 and 11 are introduced in Wi-Fi 6, which further help improve the network throughput. To this end, in this research paper, we present a proportional network throughput analysis of Wi-Fi version 5 and Wi-Fi version 6, and also discuss the key features of these two WLAN standards. For the simulation, we use NS3, where it has been observed that Wi-Fi 6 can drastically improve the network throughput compared to Wi-Fi 5.","PeriodicalId":447131,"journal":{"name":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123548043","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

Investigation of Hybrid Power Performance with Solar Module & Wind Turbine in MATLAB 基于MATLAB的太阳能组件与风力发电机组混合动力性能研究

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085455

Md. Shajedul Islam, S. Rahman, Suman Chowdhury

引用次数: 0

Analysis of a Hysteresis Current Control DC–DC Buck Converter Suitable for Wide Range of Operating Conditions 适用于大范围工作条件的滞回电流控制DC-DC降压变换器分析

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085385

Roshan Ghosh, Koustav Dasgupta, S. Ghoshal

引用次数: 0

Early Screening of Valvular Heart Disease Prediction using CNN-based Mobile Network 基于cnn移动网络的瓣膜性心脏病早期筛查预测

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085513

Tanmay Sinha Roy, J. K. Roy, N. Mandal

{"title":"Early Screening of Valvular Heart Disease Prediction using CNN-based Mobile Network","authors":"Tanmay Sinha Roy, J. K. Roy, N. Mandal","doi":"10.1109/ICCECE51049.2023.10085513","DOIUrl":"https://doi.org/10.1109/ICCECE51049.2023.10085513","url":null,"abstract":"The rapid emergence of technology and big data science opened up a significant amount of work that has been carried out in the field of feature extraction and classification techniques of heart sound using various deep learning methods. Practically, medical practitioners use the same old scientific method and practice to seek out any cardiac disorders and predict any abnormality in the human heart. Heart sound normalization, denoising, segmentation, feature extraction, and classification techniques provide a suitable way of study of phonocardiography (PCG) signal analysis which eventually reduces the cost, makes the system compact, and simultaneously, can work with extensive training data. This paper mainly indulges in two parts feature extraction and classification. The proposed deep learning study for PCG signal used online available heart disease datasets, and time domain features like average energy, power, root mean square (RMS), total harmonic distortion, and zero Crossing rates are used. Statistical features used are kurtosis and skewness. The acoustic features used are Mel-frequency cepstrum coefficients (MFCCs), mel, chroma, contrast, and tonnetz. For the classification of heart sound, the proposed modified CNN-based mobile network is used. The modified CNN-based mobile network is very effective in heart sound analysis as it requires very less computation time and storage. The proposed CNN-based modified Mobile Network model attained an accuracy of 99.04 + 0.07% on the test dataset with a sensitivity of 96.8 + 0.03 % and specificity of 97.2 + 0.09%.","PeriodicalId":447131,"journal":{"name":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"441 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127727786","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: 2

Development of a Laboratory Prototype of a Three Phase Three Bus Transmission System Emulator 三相三总线传输系统仿真器实验室样机的研制

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085657

Jayanta Piri, G. Bandyopadhyay, M. Sengupta

引用次数: 0

Diabetic Retinopathy - An Ensemble Approach 糖尿病视网膜病变-综合方法

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085532

Aditi Rastogi, Timsal Zehra Rizvi, Dr Deeba Kanan

{"title":"Diabetic Retinopathy - An Ensemble Approach","authors":"Aditi Rastogi, Timsal Zehra Rizvi, Dr Deeba Kanan","doi":"10.1109/ICCECE51049.2023.10085532","DOIUrl":"https://doi.org/10.1109/ICCECE51049.2023.10085532","url":null,"abstract":"Diabetes is a lifestyle disease that affects many people all over the world, with India leading the count of diabetic patients. The most important organ in the human body is the eye. Any anomaly will impact the functioning of life in its operation. The main component of the eye's internal surface, the fundus, is checked to spot any anomalies. In this study, neural networks were used to classify retinal fundus images. Methods of transfer learning are used to put the image into a category based on how bad the diabetic retinopathy is. Diabetes mellitus often evolves into diabetic retinopathy (DR), leading to lesions in the retina that impair vision. Through this paper, we propose an ensemble approach to respectively diagnose diabetes and diabetic retinopathy from blood reports and digital fundus images and accurately classify its severity. In order to do so, we first determine whether the patient has diabetes or not. This has been made possible by using machine learning classification algorithm – K Nearest Neighbors. A high-end graphics processing unit (GPU) was used to train the ensembled network on the publicly accessible APTOS-19[16] dataset, and the results are outstanding, particularly for a high-level classification task. Our proposed method worked more than 95% of the time. It has also been tested against the custom Messidor and EyePACS datasets.","PeriodicalId":447131,"journal":{"name":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131591322","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

Flop Resistance Controlled Circulating Current Minimization of Parallel Quadratic Step-Up Converter in DCMicro grid Applications 并联二次型升压变换器在直流微电网中的应用

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085233

S. Hema, Y. Sukhi, R. Suguna

{"title":"Flop Resistance Controlled Circulating Current Minimization of Parallel Quadratic Step-Up Converter in DCMicro grid Applications","authors":"S. Hema, Y. Sukhi, R. Suguna","doi":"10.1109/ICCECE51049.2023.10085233","DOIUrl":"https://doi.org/10.1109/ICCECE51049.2023.10085233","url":null,"abstract":"In many situations high Current is required in high demand applications likeall automized industries, DC Microgridetc., Same converter modules connected in parallel combination results in generation of higher output current, but when connecting two converters in parallel creates the problem ofuneven distribution of current in each converter module due to Mismatch component Parameter tolerances, similarly in existing methods of all parallel converter used buck converter and boost converters to minimize the circulating current and percentage error. This study proposes two quadratic step-upconverters (QSC)in parallel connection called parallel Quadratic Step-up Converter (PQSC)with even distribution ofcurrent in both QSC by implementing passive flop resistance control method(FRC). By using this flop resistance control of QSC method adaptively adjust the reference voltage and also controls the converter duty ratio to achieve equal sharing of current in both Quadratic step-up converters.The adjustment of converter switch on time depends on output current, output voltage of each converter, overall output current, output voltage, Flop Resistance, Cable Resistance of both the converters. The MATLAB simulation model verify the usefulness of the proposed control technique. This effort of proposed control method achieve equal current sharing , reducescirculating current and percentage error of current sharing difference even though para-meters of two converter modules are different.","PeriodicalId":447131,"journal":{"name":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134404158","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

Analyzing and Addressing Data-driven Fairness Issues in Machine Learning Models used for Societal Problems 分析和解决用于社会问题的机器学习模型中数据驱动的公平问题

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085470

Vishnu S. Pendyala, Hyun-Gee Kim

{"title":"Analyzing and Addressing Data-driven Fairness Issues in Machine Learning Models used for Societal Problems","authors":"Vishnu S. Pendyala, Hyun-Gee Kim","doi":"10.1109/ICCECE51049.2023.10085470","DOIUrl":"https://doi.org/10.1109/ICCECE51049.2023.10085470","url":null,"abstract":"This work aims to systematically analyze and address fairness issues arising in machine learning models because of class imbalances present in data, specifically used for addressing societal problems and providing unique insights. Using a specific data set, spectral analysis is first performed to present evidence and characterize the fairness issues. Subsequently, a series of class imbalance correction techniques are applied before the data is used to generate various machine learning models. The models so generated are then evaluated using multiple metrics. The results are then analyzed to compare the various approaches to determine the relative merits of each. As the experiments described in this paper confirm, not all oversampling techniques help in correcting data-induced model biases. Based on the Kappa statistic, F-1 score, and accuracy measured by the area under the Receiver Operating Characteristic curve, among the approaches evaluated, the Majority Weighted Minority Oversampling Technique, MWMOTE oversampling technique addresses the fairness issues the best and also improves the performance of the models at least for the dataset in consideration. The experiments also demonstrate that some of the oversampling techniques can degrade the models both in terms of performance and fairness. The results are interpreted using the evaluation metrics.","PeriodicalId":447131,"journal":{"name":"2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133995990","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: 1

Design And Development of Cost-Effective Automatic Solar Panel Cleaning System 高性价比太阳能电池板自动清洗系统的设计与开发

2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE) Pub Date : 2023-01-20 DOI: 10.1109/ICCECE51049.2023.10085667

Abdullah Mohammed Zaki Khayyat, Abdulrahman Hamad Alharthi, Faisal Lafi Almohammadi, Ziyad Saad Almarwani, Tawfeeq Shawely, M. Dessouki, Y. Mobarak, N. Kannan

引用次数: 0