J. of Electrical Engineering最新文献_第3页

The Design of Predictive Model for the Academic Performance of Students at University Based on Machine Learning 基于机器学习的大学生学业成绩预测模型设计

J. of Electrical Engineering Pub Date : 2018-07-08 DOI: 10.17265/2328-2223/2018.04.006

Barnabas Ndlovu Gatsheni, Olga Ngala Katambwa

{"title":"The Design of Predictive Model for the Academic Performance of Students at University Based on Machine Learning","authors":"Barnabas Ndlovu Gatsheni, Olga Ngala Katambwa","doi":"10.17265/2328-2223/2018.04.006","DOIUrl":"https://doi.org/10.17265/2328-2223/2018.04.006","url":null,"abstract":"Students in South African Universities come from different socio-cultural backgrounds, countries and high schools. This suggests that these students have different experiences which impacts on their levels of grasping information in class as they potentially use different lenses on tuition. The current practice in Universities in contributing to the academic performance of students include the use of tutors, the use of mobile devices for first year students, use of student assistants and the use of different feedback measures. What is problematic about the current practice is that students are quitting university in high numbers. In this study, knowledge has been drawn from data through the use of machine learning algorithms. Bayesian networks, support vector machines (SVM) and decision trees algorithms were used individually in this work to construct predictive models for the academic performance of students. The best model was constructed using SVM and it gave a prediction of 72.87% and a prediction cost of 139. The model does predict the performance of students in advance of the year-end examinations outcome. The results suggest that South African Universities must recognize the diversity in student population and thus provide students with better support and equip them with the necessary knowledge that will enable them to tap into their full potential and thus enhance their skills.","PeriodicalId":382952,"journal":{"name":"J. of Electrical Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115790506","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

Phase Modulation Characteristics of Spatial Light Modulator and the System for Its Calibration 空间光调制器的相位调制特性及其标定系统

J. of Electrical Engineering Pub Date : 2018-07-08 DOI: 10.17265/2328-2223/2018.04.001

Zhang Gongjian, Zhang Man, Zhao Yang

引用次数: 2

CCII-Based Inverse Active Filters with Grounded Passive Components 基于ccii的无源接地逆有源滤波器

J. of Electrical Engineering Pub Date : 2018-07-08 DOI: 10.17265/2328-2223/2018.04.003

Takao Tsukutani, Yasutomo Kunugasa, Noboru Yabuki

引用次数: 15

Development of PC Worker’s Management System in PC Training Room and Office by Using IoT Technology 利用物联网技术开发PC实训室、办公室PC工人管理系统

J. of Electrical Engineering Pub Date : 2018-07-08 DOI: 10.17265/2328-2223/2018.04.005

Keiichi Abe, Yuki Takabayashi, Masao Isshiki

{"title":"Development of PC Worker’s Management System in PC Training Room and Office by Using IoT Technology","authors":"Keiichi Abe, Yuki Takabayashi, Masao Isshiki","doi":"10.17265/2328-2223/2018.04.005","DOIUrl":"https://doi.org/10.17265/2328-2223/2018.04.005","url":null,"abstract":"At present time, there has been a demand for management systems that can survey and monitor a PC (personal computer) practice room, movement of people in an office, situation of utilization of facilities and so on in real time without causing psychological stress. For example, PC administrators in Japanese national educational institutions must report operation status of PC practice rooms once a year. But, there is currently no system for automatically recording PC operating situations. Therefore, the burden on the PC administrators is big. In this study, we aimed at systems for accurately managing the sitting and work time without psychologically stressing PC users. This time, we propose uniform management systems of sitting and work time using smart tap node and mat sensor node by IoT (Internet of Things) technology. The smart tap was connected to PCs to acquire the operating status of the PCs. In parallel with this smart tap, the mat sensor was used to acquire human presence state. By calculating binary data representing the PC operating status and human presence state from the two sensing data (smart tap and mat sensor) by the proposed technique, we can exactly calculate wasteful power consumption etc. The use of IoT technology makes it unnecessary to use large installation services when introducing our system. Therefore, this our proposal system can be easily installed even by unskilled workers.","PeriodicalId":382952,"journal":{"name":"J. of Electrical Engineering","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131354736","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