2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)最新文献_第2页

Design and Modeling of IoT IR Thermal Temperature Screening and UV Disinfection Sterilization System for Commercial Application using Blockchain Technology 区块链技术用于商业应用的物联网红外热温度筛选和紫外线消毒灭菌系统的设计和建模

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265363

S. Paramasivam, C. Shen, A. Zourmand, Amira Kamil Ibrahim Hassan, A. Alhassan, Abdelwhab Faroug Eltirifl

{"title":"Design and Modeling of IoT IR Thermal Temperature Screening and UV Disinfection Sterilization System for Commercial Application using Blockchain Technology","authors":"S. Paramasivam, C. Shen, A. Zourmand, Amira Kamil Ibrahim Hassan, A. Alhassan, Abdelwhab Faroug Eltirifl","doi":"10.1109/ICSET51301.2020.9265363","DOIUrl":"https://doi.org/10.1109/ICSET51301.2020.9265363","url":null,"abstract":"The increasing spread of the coronavirus across countries and with no sight of vaccine uncovered soon has prompted affected countries to impose strict containment measures. In view to ease the enormous strain on health systems; disinfection, decontamination, contact tracking, and isolation are a few health protocols that are to be observed by companies that resumed their activities to protect their employees from being infected. Hence, against a backdrop of heightened uncertainty, this project leverages on the advancement of technology to design and built a smart Infrared thermal scanning with a camera (Thermovis-Mi-FRAHT-800). An Ultraviolet-C spectrum disinfection system and integration of blockchain technology for data sharing, managing health records, and access control. SketchUp used as a 3D design platform for this project. This system designed with a precautionary measure which includes 3 conditions to be met for the automated barrier to be open which include temperature measurement, disinfection, and sanitization processes. Overall, a person spends less than a minute in the walkthrough path chamber as the process takes 20 to 25 seconds each. By this calculation, we assume that 2 people would be able to get disinfected within a minute which comes up to 120 people per hour. Thus, reducing the number of monitoring staffs in direct contact with the stakeholders with potential infection issues. It is envisaged that developing this conceptual design would be the cornerstone in adhering to control measure through appropriate infection control and modification using current and future technologies.","PeriodicalId":299530,"journal":{"name":"2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131754911","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: 6

Extending Multi-Object Detection Ability using Correlative Filter 利用相关滤波器扩展多目标检测能力

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265350

F. Kinasih, C. Machbub, L. Yulianti, A. Syaichu-Rohman

引用次数: 2

Classification of Chili Plant Growth using Deep Learning 辣椒植物生长的深度学习分类

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265351

A. Aldabbagh, C. Hairu, M. Hanafi

引用次数: 3

Highlight on Cryptocurrencies Mining with CPUs and GPUs and their Benefits Based on their Characteristics 重点介绍了cpu和gpu的加密货币挖掘及其基于其特点的优势

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265386

Mahdi Alkaeed, Zaid Alamro, M. Al-Ali, H. A. Al-Mohammed, K. Khan

{"title":"Highlight on Cryptocurrencies Mining with CPUs and GPUs and their Benefits Based on their Characteristics","authors":"Mahdi Alkaeed, Zaid Alamro, M. Al-Ali, H. A. Al-Mohammed, K. Khan","doi":"10.1109/ICSET51301.2020.9265386","DOIUrl":"https://doi.org/10.1109/ICSET51301.2020.9265386","url":null,"abstract":"Nowadays cryptography and their technologies have been with us for a long time. This field of science is developing day by day. Blockchain has come a long way since the birth of its first application. This application is Bitcoin which depends on Blockchain or DLT (Distributed Ledger Technology). Bitcoin is the most famous cryptocurrency intended for mass which appeared the first time in 2008. This innovation led to sparked in the digital revolution, which provides for many sectors and industries the security features, decentralization, and a reliable mechanism for transmission and storing data. This new technology led to the meteoric rise of Bitcoin and other such cryptocurrencies, so this has aroused the interest of governments and emerging companies to get an effective role in competition. We can apply blockchain in different sectors and different Internet of things (IoT). Cryptocurrency mining has become a major concern for computer professionals and also for those who earn more money from an additional source. Mining is a process for settle mathematical issues that depend on the strength and speed of the devices to solve those problems, which by resolving them leads to getting rewards in the form of a digital currency. In this paper, we will highlight the benefits of using both CPU (Central Processing Unit) and GPU (Graphical Processing Unit) and a practical comparison between them to find out the best and fastest based on previous studies and on the characteristics and architecture of each.","PeriodicalId":299530,"journal":{"name":"2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124785818","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

Iris Recognition using Convolutional Neural Network 基于卷积神经网络的虹膜识别

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265389

Yuan Zhuang, Joon Huang Chuah, C. Chow, M. Lim

{"title":"Iris Recognition using Convolutional Neural Network","authors":"Yuan Zhuang, Joon Huang Chuah, C. Chow, M. Lim","doi":"10.1109/ICSET51301.2020.9265389","DOIUrl":"https://doi.org/10.1109/ICSET51301.2020.9265389","url":null,"abstract":"The design of a pragmatic user authentication system is vital to provide accurate detection of personal identity. Iris recognition as a form of biometric identification technology has been actively researched for decades and is gaining wider popularity considering the increasing awareness of personal privacy. The rise of artificial intelligence provides a great opportunity to further elevate the penetration of iris recognition in safeguarding one's private data. Convolutional neural network is a practical algorithm that is highly suitable for image processing and pattern recognition, its effectiveness and flexibility have seen it being applied in many fields. This study focuses on the development of an iris recognition system based on convolutional neural network with high precision and efficiency. A total of iris samples from 20 individuals with both sides of the eyes included are used to train the deep recognition system. The model shows an early sign of underfitting and little convergence with inadequate number of training epoch. However, as the training epochs are increased, the trained model managed to achieve a testing accuracy of 99%.","PeriodicalId":299530,"journal":{"name":"2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122570904","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

StEPS: A Development of Students' Employability Prediction System using Logistic Regression Model Based on Principal Component Analysis 步骤:基于主成分分析的Logistic回归模型开发学生就业能力预测系统

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265371

Cherry D. Casuat, Julius C. Castro, Deanne Cameren P. Evangelista, Niño E. Merencilla, Christina P. Atal

{"title":"StEPS: A Development of Students' Employability Prediction System using Logistic Regression Model Based on Principal Component Analysis","authors":"Cherry D. Casuat, Julius C. Castro, Deanne Cameren P. Evangelista, Niño E. Merencilla, Christina P. Atal","doi":"10.1109/ICSET51301.2020.9265371","DOIUrl":"https://doi.org/10.1109/ICSET51301.2020.9265371","url":null,"abstract":"Predicting students' employability prior to graduation can be a great tool for every HEI's career center to intervene timely and to take steps on how to improve the weaknesses of the students to become more employable. At present, there is no tool that can be used to determine undergraduate students who are at risk of unemployment or becoming disadvantaged because vulnerabilities are not detected early. In this study the principal component analysis (PCA) and logistic regression were used to determine the most predictive features in the students' employability prediction system (STEPS). The Dataset used consist of 1000 information of engineering students who took their on-the Job training from School year 2017ߝ2018 to School year 2019. The features used were professionalism and branding, confidence, comprehension, communication skills, growth potential, student performance rating. Upon using PCA, the experiments resulted to communication skills growth potential and student performance rating obtained the most predictive attributes that affects the employability prediction.","PeriodicalId":299530,"journal":{"name":"2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132529410","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

Reconfigurable Systolic-based Pyramidal Neuron Block for CNN Acceleration on FPGA 基于FPGA的可重构收缩锥体神经元块CNN加速

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265388

Hossam O. Ahmed, M. Ghoneima, M. Dessouky

引用次数: 0

JuCo-IS: A Development of Web-Based Information System in Judicial Regional Trial Court 区域审判法院网络信息系统的开发

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265362

Aimee G. Acoba, Christopher Franco Cunanan, Niño E. Merencilla, Ryan R. Tejada, Michael Angelo D. Ligayo

引用次数: 0

Semi-Global Leader-Follower Consensus of Linear Multi-Agent System Via Time-varying Gain 时变增益下线性多智能体系统的半全局领导-随从一致性

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265359

Norfarhan Hidayah M. Pajar, N. Subha, R. A. Rahim, Fazilah Hassan, Norikhwan Hamzah

引用次数: 0

Near-Infrared Data Pre-Processing for Glucose Level Prediction in Blood 近红外数据预处理用于血糖水平预测

2020 IEEE 10th International Conference on System Engineering and Technology (ICSET) Pub Date : 2020-11-09 DOI: 10.1109/ICSET51301.2020.9265391

I. M. A. Rahim, H. A. Rahim, Rashidah Ghazali

{"title":"Near-Infrared Data Pre-Processing for Glucose Level Prediction in Blood","authors":"I. M. A. Rahim, H. A. Rahim, Rashidah Ghazali","doi":"10.1109/ICSET51301.2020.9265391","DOIUrl":"https://doi.org/10.1109/ICSET51301.2020.9265391","url":null,"abstract":"Estimated, 347 million people suffered from diabetes in 2004, and around 3.4 million patients died from consequences of high blood sugar. There are various techniques investigated by researchers in measuring the glucose level in human blood non-invasively, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. The implementation of near infrared (NIR) in predicting the glucose level in blood had been investigated in and the process of data pre-processing is presented in this paper. The selection of the wavelength region by previous researchers has been a debate as the suitable wavelength chose vary from one researcher to another. Despite the wavelength selection problem, the other fragment that needed a close attention is the process of enhancing the NIR data obtained from the experiment. The data pre-processing techniques used in this paper are the data filtering, data sampling, interval correction, wavelength selection and data distribution phases. The processed data then fed as an input to the linear and nonlinear prediction system implemented in this study.","PeriodicalId":299530,"journal":{"name":"2020 IEEE 10th International Conference on System Engineering and Technology (ICSET)","volume":"73 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132708968","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