2021 IEEE 19th Student Conference on Research and Development (SCOReD)最新文献_第6页

Total Harmonic Distortion Comparison Analysis between High-Power Density Inverter and Multilevel Inverter 大功率密度逆变器与多电平逆变器总谐波失真比较分析

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652687

K. A. Khalid, M. I. Fahmi, H. F. Liew, M. Z. Aihsan, M. Saifizi

{"title":"Total Harmonic Distortion Comparison Analysis between High-Power Density Inverter and Multilevel Inverter","authors":"K. A. Khalid, M. I. Fahmi, H. F. Liew, M. Z. Aihsan, M. Saifizi","doi":"10.1109/SCOReD53546.2021.9652687","DOIUrl":"https://doi.org/10.1109/SCOReD53546.2021.9652687","url":null,"abstract":"The inverter is one of the most common things in converting electrical energy supply and it is a very important concept in the current modern electrical power system to utilize the maximum potential by generating the unit while considering the environment within the surrounding area and avoid pollution is the most ideal concept of energy management. The main purpose of this study is to consider which one of the inverters is more suitable for energy saving. There are two kinds of inverter that have been tested for this research which are the High-power density inverter (HPDI) and Multilevel inverter (MLI). In High-power density inverter (HPDI) it uses electrical components such as Insulated-gate Bipolar Transistor (IGBT) as the main component. As for the Multilevel inverter (MLI) it uses electrical components Metal- oxide-semiconductor field-effect-transistor (MOSFET) as the main component. Both inverters are being implemented and running by using MATLAB Simulink software. Besides that, the result is obtained by comparing the Total Harmonic Distortion (THD), the output of the waveform and energy efficiency for both inverters.","PeriodicalId":6762,"journal":{"name":"2021 IEEE 19th Student Conference on Research and Development (SCOReD)","volume":"os-41 1","pages":"228-232"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87227807","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

Malay Tweets: Discovering Mental Health Situation during COVID-19 Pandemic in Malaysia 马来语推文:在马来西亚COVID-19大流行期间发现心理健康状况

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652759

Ramadani Anwar Sabaruddin, Suhaila Saee

{"title":"Malay Tweets: Discovering Mental Health Situation during COVID-19 Pandemic in Malaysia","authors":"Ramadani Anwar Sabaruddin, Suhaila Saee","doi":"10.1109/SCOReD53546.2021.9652759","DOIUrl":"https://doi.org/10.1109/SCOReD53546.2021.9652759","url":null,"abstract":"During the unprecedented of COVID-19 pandemic, numbers of research had been conducted on mental health in social media worldwide. Past research has shown interest in Twitter sentiment analysis by using keywords, geographical area, and range of ages. Up to the authors’ analysis, there is no research conducted on mental health using keyword in the case of Malaysia. A Malay Tweet dataset was built for analysing mental health tweets during the first Movement Control Order period using unique keywords. Machine learning algorithms namely, Naïve Bayes classifier and Support Vector Machine were used to predict the sentiment of tweets. The classifiers were evaluated using 10-fold cross-validation, accuracy, precision, and F1-score. The data then visualized in charts and WordCloud. The results shows that Support Vector Machine performed better than Naïve Bayes classifier for both test set and 10-fold cross-validation in terms of performances in n-gram TF-IDF. The visualized data could provide insights to the authority pertaining the mental health issues, in which it relates to local news and situations during the periods.","PeriodicalId":6762,"journal":{"name":"2021 IEEE 19th Student Conference on Research and Development (SCOReD)","volume":"7 1","pages":"58-63"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87685237","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

Advanced Encryption Standard Mobile Application to Improve College Entrance Security in UNIMAS 先进加密标准移动应用提高UNIMAS高考安全

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652788

A. A. Julaihi, T. P. Ping, Fateen Afeefa Md Nor

引用次数: 0

Pre-processing Technique using Colour-based Feature Method to Detect Categories of Leaves Disease 基于颜色特征的叶片病害分类检测预处理技术

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652764

Siti Haslinda Bt Miasin, Phei-Chin Lim, Jacey-Lynn Minoi

{"title":"Pre-processing Technique using Colour-based Feature Method to Detect Categories of Leaves Disease","authors":"Siti Haslinda Bt Miasin, Phei-Chin Lim, Jacey-Lynn Minoi","doi":"10.1109/SCOReD53546.2021.9652764","DOIUrl":"https://doi.org/10.1109/SCOReD53546.2021.9652764","url":null,"abstract":"Oil palm leaves diseases is caused by various plant pathogens and micronutrient deficiency, and genetic disorders. This problem, if not identified and treated quickly could lead to losses in yield and profitability. The disease on leaves is currently being identified through the different colours, shapes, and forms. Other signs of an infected plant can be seen based on the discolouration on the leaves. In this paper, we present an approach to automatically identify the morphological features of leave diseases in category of healthy to non-healthy based on region of interest of discolouration on young oil palm leaves. Raw leaf images are captured using a built-in digital camera. Pre-processing was done on each of the non-uniform illumination condition raw data images. We tested the colour feature method using RGB (Red, Green Blue) colour filtering in the identification of the leaf region of interest. Next, further segmentation method using HSV (Hue, Saturation, Values) colour filtering approach is employed to remove shadows and to identify the different level of regions of discolouration. The results highlighted that the infected area on the leaves can be identified by 100% based on the discoloured in the region of interest. These regions can be categorised in three different groups – healthy leaves (20% of the discolouration region) to heavily infected (70% of the discolouration region) of the leaves – based on analysis of the pre-processing results. In top of that, the HSV colour feature method could also remove shadow and noise. The results of the detected discolouration will be used oil palm leaves datasets for further classification and recognition research work.","PeriodicalId":6762,"journal":{"name":"2021 IEEE 19th Student Conference on Research and Development (SCOReD)","volume":"29 1","pages":"119-124"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77542605","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

Bit Error Rate Comparison for Radio Frequency Interconnection Based on BPSK, PAM and QAM Modulation 基于BPSK、PAM和QAM调制的射频互连误码率比较

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652745

Ngu War Hlaing, A. Farzamnia

{"title":"Bit Error Rate Comparison for Radio Frequency Interconnection Based on BPSK, PAM and QAM Modulation","authors":"Ngu War Hlaing, A. Farzamnia","doi":"10.1109/SCOReD53546.2021.9652745","DOIUrl":"https://doi.org/10.1109/SCOReD53546.2021.9652745","url":null,"abstract":"The advancement of Ultra Large-Scale Integration (ULSI) technology has motivated the need to find an alternative solution such as wireless communication and on-chip Radio Frequency (RF), a popular method to substitute the hardwired metal interconnect that has reached its performance limit due to material limitations. Single-input-single-output schemes such as Binary Pulse Shift Keying (BPSK) modulation, Phase Amplitude Modulation (PAM), and Quadrature Amplitude Modulation (QAM) implemented with the RF interconnect has increased its advantages. However, the type of channel used is still unclear. Thus, this paper evaluated the Bit Error Rate (BER) of these three modulation types under Additive White Gaussian Noise (AWGN) and Rayleigh multipath fading channels. The findings indicate that BPSK delivers the highest BER performance on the AWGN channel, while 8-ary PAM and 64-ary QAM output attain the best BER on the Rayleigh channels, irrespective of its signal-to-noise proportion (SNR). Comparing AWGN and Rayleigh channels shows that AWGN offers the highest BER performance regardless of the modulation techniques and SNR. Thus, BPSK achieves better BER performance in the AWGN channel.","PeriodicalId":6762,"journal":{"name":"2021 IEEE 19th Student Conference on Research and Development (SCOReD)","volume":"20 1","pages":"445-449"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85520049","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

Signal Processing Application for Musical Notes Recognition 信号处理在音符识别中的应用

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652762

K. Othman, Any Arope Zainal Abidin

引用次数: 2

Estimation of Electric Vehicle Turning Radius Through Machine Learning for Roundabout Cornering 基于机器学习的电动汽车环形交叉口转弯半径估计

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652676

Ashaa Supramaniam, M. A. Zakaria, Baarath Kunjunni, M. H. Peeie, A. Nasir, M. I. Ishak

引用次数: 1

A Review of Surface EMG in Clinical Rehabilitation Care Systems Design 表面肌电信号在临床康复护理系统设计中的应用综述

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652736

B. Chan, I. Saad, N. Bolong, Kang Eng Siew

引用次数: 3

EcoWaste: A Smart Waste Platform Enabling Circular Economy 生态废物:实现循环经济的智能废物平台

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652721

Laura Ambrosio, Pedro Lucas Siqueira Paulino, João Antiquera, G. Aquino, Evandro César Vilas Boas

引用次数: 1

Wide-Coverage Suspended Metasurface Energy Harvester for ISM Band Applications 用于ISM波段应用的大覆盖悬挂超表面能量采集器

2021 IEEE 19th Student Conference on Research and Development (SCOReD) Pub Date : 2021-11-23 DOI: 10.1109/SCOReD53546.2021.9652779

Abdulrahman Ahmed Ghaleb Amer, S. Z. Sapuan, N. Nasimuddin

引用次数: 2