2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)最新文献

Training a Neural Network for Lane Demarcation Detection in the Infrared Spectrum 红外光谱中车道划分检测的神经网络训练

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255732

Elizabeth Hofer, Taufiq Rahman, Ryan Myers, Ismail Hamieh

引用次数: 2

Implementation and Evaluation of LS-SVM Optimization Methods for Estimating DoAs 估计doa的LS-SVM优化方法的实现与评价

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255751

S. Komeylian

{"title":"Implementation and Evaluation of LS-SVM Optimization Methods for Estimating DoAs","authors":"S. Komeylian","doi":"10.1109/CCECE47787.2020.9255751","DOIUrl":"https://doi.org/10.1109/CCECE47787.2020.9255751","url":null,"abstract":"Important technological advancement in designing smart array antennas has been encouraged many researchers to concentrate their work on the two main concepts of the direction of arrival (DoA) and beamforming techniques. The preliminary objective of beamforming techniques includes, electronically, the mainbeam in the direction of interest at a certain time and measuring the output power. In this scenario, the main practical challenge resides in achieving maximum output power in which the direction of steered mainbeam coincides with the direction of arrivals. Since the involved problems in most DoA estimation optimizations consist of a lot of unknown parameters including direction of arrivals, SNRs, signal waveforms and samples of noises in the array output, it may become impossible to build a large enough training dataset for covering the distributions for all the aforementioned test data. An alternative way to overcome this constraint which we aim at stressing in this work involves employing support vector machine algorithms for separating unknown components of the actual input in the higher dimensional feature space. In this work, we have implemented the decision directed acyclic graph (DDAG) and Vapnik-Chervonenkis (VC) methods for the least squares support vector machine (LS-SVM) algorithms for estimating DoAs. We have rigorously verified that DoAs are very much affected the antenna array geometries. In addition, we have investigated the quality of the communication channel by the concept of bit error rate (BER).","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121268608","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

Assessment of Neuroplasticity Using EEG Signal in Rehabilitation of Brain Stem Stroke Patients 脑电图信号在脑干脑卒中患者康复中的神经可塑性评价

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255731

Maryam Butt, G. Naghdy, F. Naghdy, Geoffrey Murray, H. Du

{"title":"Assessment of Neuroplasticity Using EEG Signal in Rehabilitation of Brain Stem Stroke Patients","authors":"Maryam Butt, G. Naghdy, F. Naghdy, Geoffrey Murray, H. Du","doi":"10.1109/CCECE47787.2020.9255731","DOIUrl":"https://doi.org/10.1109/CCECE47787.2020.9255731","url":null,"abstract":"Robot-assisted motor training provides an efficient alternative to conventional rehabilitation methods used for poststroke patients. The re-learning of lost motor functions happens through neuroplasticity in the brain. Electroencephalogram (EEG) provides an effective method for assessing neuroplasticity. Movement-related cortical potential (MRCP), an EEG-derived time-domain pattern, indicates changes due to motor skills gained as a result of the training. This study aims to perform a two-stage robot-assisted rehabilitation program on brain stem stroke patients consisting of a total of 24 training sessions and to assess whether significant motor recovery and neuroplasticity induction are achieved after the first stage or after completing both stages of the designed rehabilitation program. Three brain stem stroke patients were recruited for hand motor training on AMADEO rehabilitation robot for 8 weeks consisting of two stages of 4 weeks each. Three assessments methods which include standard clinical tests, hand strength and range of movement measurements using AMADEO assessment tool, as well as EEG signal acquisition, were performed at the beginning of all the training sessions (week 0), after completion of the first stage of rehabilitation (week 4) and after completion of both stages of the training sessions (week 8). The experimental results demonstrate that all brain stem stroke patients show significant functional hand motor recovery, as indicated by clinical tests, hand strength, and range of movement measurements, after completing 8 weeks of the training. Moreover, MRCP signal negative peak showed a significant decrease in its amplitude when the patients completed two phases of rehabilitation training, indicating neuroplasticity induction.","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123418255","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: 4

Measuring Electric Fields Produced by MRI Gradient Coils Using a Patch Antenna Probe 利用贴片天线探头测量MRI梯度线圈产生的电场

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255698

Arjama Halder, A. Attaran, W. Handler, B. Chronik

引用次数: 1

Lighting Protection of VSC-HVDC Transmission Systems using ZnO Surge Arresters ZnO避雷器在直流输电系统中的防雷作用

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255785

Matheus Y. Ataka, Lucas L. Bacci, Thiago M. Lima, R. F. R. Pereira, E. Costa, L. Liboni

引用次数: 2

Performance Evaluation of Pre-Trained CNN Models for Visual Saliency Prediction 预训练CNN模型在视觉显著性预测中的性能评价

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255692

Bashir Ghariba, M. Shehata, Peter F. McGuire

引用次数: 1

DC and AC Voltage Investigation in Isolated and Grid-Connected Hybrid Microgrid 隔离型和并网型混合微电网的直流和交流电压研究

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255812

M. Thiam, Sengthavy Phommixay, Moustapha Diop, M. Doumbia, M. Wade

引用次数: 0

A DFFT and Coherence Analysis-Based Fault Diagnosis Approach for Induction Motors Fed by Variable Frequency Drives 基于DFFT和相干分析的变频异步电动机故障诊断方法

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255688

Md. Nasmus Sakib Khan Shabbir, Xiaodong Liang

{"title":"A DFFT and Coherence Analysis-Based Fault Diagnosis Approach for Induction Motors Fed by Variable Frequency Drives","authors":"Md. Nasmus Sakib Khan Shabbir, Xiaodong Liang","doi":"10.1109/CCECE47787.2020.9255688","DOIUrl":"https://doi.org/10.1109/CCECE47787.2020.9255688","url":null,"abstract":"For faults diagnosis in a Variable Frequency Drive (VFD)-fed induction motor, a Discrete Fast Fourier Transform (DFFT) and coherence analysis-based approach is proposed in this paper. To identify signature harmonics that maintain a strong correlation between a healthy and a faulty cases and are present under various conditions, a coherence analysis is conducted. After signature harmonics are identified, fault diagnosis can be carried out by comparing magnitudes of the fundamental and signature harmonics under various healthy and faulty conditions. Magnitudes of the fundamental voltage and the third harmonic voltage can serve as parameters to detect the five types of faults. The fifth harmonic current can effectively detect the occurrence of a fault although it cannot distinguish the fault types. The combination of the fundamental voltage and the third harmonic voltage from the stator voltage and the fifth harmonic current from the stator current can lead to effective fault diagnosis. The proposed approach is verified using two motor loading conditions.","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128209158","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

A Bedsheet for Baby Monitoring at Night: Measurement and Characterization Results 用于夜间婴儿监护的床单：测量和特性分析结果

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255671

Samal Munidasa, Parastoo Baghaei Ravari, Edward Shim, Olivia Lin, E. Ghafar-Zadeh

引用次数: 2

A Study on the Performance of PV Modules in Snowy Conditions Considering Orientation of Modules 考虑组件朝向的积雪条件下光伏组件性能研究

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI: 10.1109/CCECE47787.2020.9255738

E. Mohammadi, Javad Khodabakhsh, G. Moschopoulos, R. Fadaeinedjad

引用次数: 2