2020 International Conference on Computational Performance Evaluation (ComPE)最新文献_第6页

Selection of Appropriate Statistical Features of EEG Signals for Detection of Parkinson’s Disease 选取合适的脑电信号统计特征检测帕金森病

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200194

R. Haloi, Jupitara Hazarika, D. Chanda

{"title":"Selection of Appropriate Statistical Features of EEG Signals for Detection of Parkinson’s Disease","authors":"R. Haloi, Jupitara Hazarika, D. Chanda","doi":"10.1109/ComPE49325.2020.9200194","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200194","url":null,"abstract":"Analysis of signal transmission activities of human brain can give fruitful information about its functions. These information are of very importance in detection and diagnosis of different types of neurological disorders. Besides low spatial sensitivity, Electroencephalogram(EEG) signals are used for functional analysis of activities of brain because of the large temporal resolution of it. Identification of an appropriate feature of the EEG used to have a key role for its analysis. This work specifically describes feature extraction of EEG signals of persons with Parkinson’s Disease(PD) by using statistical methods. Mean, standard deviation, energy, kurtosis and skewness are the five statistical features selected for this work. In addition to the extraction of features, comparative analysis of these features are also provided considering the EEGs of both normal (Non PD) and the persons with PD symptoms by using T-test. With the use of T-test, without the application of any classification techniques, the features of any two classes can be well differentiated. In the proposed approach, the results show that the p-assessment of the T-experiment is less than 0.05 and hence it can be considered that the features of the two classes are having less than 5% similarity. This fulfils the objective of detecting PD most efficiently. Out of the five features considered, Mean and Energy are the features, which are capable of differentiating the two categories of the subjects most significantly.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"29 1","pages":"761-764"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83679901","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: 3

Comparative Gait Analysis of Healthy Young Male and Female Adults using Kinect-Labview Setup 使用Kinect-Labview程序对健康年轻男性和女性成人的步态进行比较分析

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200155

Jyotindra Narayan, Arjun Pardasani, S. K. Dwivedy

引用次数: 6

Predicting Joining Behavior of Freshmen Students using Machine Learning – A Case Study 使用机器学习预测大一新生的加入行为-一个案例研究

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200167

Pawan Kumar, Varun Kumar, R. Sobti

引用次数: 2

Comparative Analysis of Adaptive PI Controller for Current Harmonic Mitigation 自适应PI控制器对电流谐波抑制的比较分析

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200057

Anish Pratap Vishwakarma, Ksh. Milan Singh

引用次数: 5

Mechanisms for Improving the Productivity of the Existing Photovoltaic Panels: A Review 提高现有光伏板生产效率的机制:综述

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200005

Snehal A. Marathe, B. Patil

引用次数: 1

Effects of Injected Harmonics on Torque Pulsations of a Three Phase Induction Motor: Study on SPWM 注入谐波对三相异步电动机转矩脉动的影响:SPWM的研究

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200018

B. S. Venkat Raman, P. Tripathi, G. Gupta, R. Keshri

{"title":"Effects of Injected Harmonics on Torque Pulsations of a Three Phase Induction Motor: Study on SPWM","authors":"B. S. Venkat Raman, P. Tripathi, G. Gupta, R. Keshri","doi":"10.1109/ComPE49325.2020.9200018","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200018","url":null,"abstract":"This paper presents an analytical study of the effect of injected current harmonics on induction motor torque ripples. A three-phase induction motor (IM) when fed by an ideal three-phase sinusoidal voltage source produces a ripple-free torque output at the shaft. For better speed and torque control of induction motor, several methods have been proposed; such as V/F control, direct torque control, Field oriented control. All such control schemes involve pulse width modulation schemes with high frequency switching such as SPWM and SVPWM. These techniques provide excellent power optimization and control but induce harmonic currents at the stator winding, which in turn gives rise to torque ripples. In the present work, an analysis of the effects of injected harmonic currents on torque ripple is reported. Case study on SPWM by varying switching frequency and optimal switching frequency for least torque ripple are presented. It is reported that only higher frequency switching does not guarantee lower torque ripple. MATLAB Simulink Simscape toolbox is used for verifying the case study. Torque ripple corresponding to injected stator current ripple is presented for validation of the proposed analysis.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"74 1","pages":"637-642"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85960736","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

Conventional Neural Network approach for the Diagnosis of Lung Tumor 传统神经网络在肺肿瘤诊断中的应用

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200118

Vijay L. Agrawal, Dr. Sanjay Vasant Dudul

引用次数: 2

A User Scheduling in LTE Network having Environment with Mixed Traffic 混合流量环境下LTE网络的用户调度

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200105

Rahul, Manoj, J. K. Verma

引用次数: 0

Expert System to Manage Parkinson Disease by Identifying Risk Factors: TD-Rules-PD 通过识别危险因素管理帕金森病的专家系统:TD-Rules-PD

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200075

Arpita Nath Boruah, Saroj Kumar Biswas, Sivaji Bandyopadhyay, Sunita Sarkar

{"title":"Expert System to Manage Parkinson Disease by Identifying Risk Factors: TD-Rules-PD","authors":"Arpita Nath Boruah, Saroj Kumar Biswas, Sivaji Bandyopadhyay, Sunita Sarkar","doi":"10.1109/ComPE49325.2020.9200075","DOIUrl":"https://doi.org/10.1109/ComPE49325.2020.9200075","url":null,"abstract":"Advent of modern means of living and busy schedule, a person generally forget to look after the health and thereby prone to some of severe health disorders. From various researches it is clear that Parkinson Disease (PD) basically occur due to negligence of an individual. It is a disorderliness that affects a small part of the brain that manages the gesture and mental order. The syndrome vary from person. Generally PD is identified from a certain age level but recent studies shown that people of any age group can suffer from PD. Considering the extremity, if there is an system to identify the major factors of PD then it would be of great importance. Thus an expert system named Transparent Decision Rules for Parkinson Disease (TD-Rules-PD) is proposed in this paper which finds out the high risk factor of PD. TD-Rules-PD consist of four phases: Rule Production, Rule selection, Rule pruning and Merging and Identify High Risk Factor. Rule Production stage uses Decision tree to produce rules. Rule selection step choose the most efficient rules, from the so collected rules Rule Pruning and Merging step drops the confusing and insignificant rules and then combines the flittered rule set to a single rule and finally Identify High Risk Factor stage finds out the most prevailing factor of PD.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"41 1 1","pages":"001-006"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74694744","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

Generating Positive and Negative Sentiment Word Clouds from E-Commerce Product Reviews 从电子商务产品评论中生成正面和负面情绪词云

2020 International Conference on Computational Performance Evaluation (ComPE) Pub Date : 2020-07-01 DOI: 10.1109/ComPE49325.2020.9200056

Shaswat Dharaiya, Bhavin Soneji, D. Kakkad, N. Tada

引用次数: 3