2020 15th International Conference on Computer Science & Education (ICCSE)最新文献_第6页

Research on Colorimetric Characterization of LCD Based on GA-Elman Neural Network 基于GA-Elman神经网络的LCD比色表征研究

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201675

Hongtai Guo, Tong Li, Zixuan Li, Qi Zheng

引用次数: 0

Fault Diagnosis of Uninterruptible Power System Based on Gaussian Mixed Model and XGBoost 基于高斯混合模型和XGBoost的不间断电力系统故障诊断

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201873

Hongyu Chen, Yanqing Peng, Qiuyu Yang, Lei Yan

{"title":"Fault Diagnosis of Uninterruptible Power System Based on Gaussian Mixed Model and XGBoost","authors":"Hongyu Chen, Yanqing Peng, Qiuyu Yang, Lei Yan","doi":"10.1109/ICCSE49874.2020.9201873","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201873","url":null,"abstract":"Uninterruptible power system (UPS) is an important equipment for guarantee data security. The previous research on UPS fault detection has established a mathematical model of the circuit system and combine with machine learning algorithm for fault diagnosis. Because the UPS circuit structure is complex and easy influence by environment temperature humidity, the research method of establishing mathematical model is suitable for the diagnosis of some internal circuits, but not for the whole UPS machine. Based on the analysis of UPS historical data, this paper has established a method that can catch and classify the UPS fault based on the Gaussian Mixed Model (GMM) and the eXtreme Gradient boost (XGBoost). This design is divided into two parts. The first part has used GMM to calculate the logarithmic summation probability of UPS data, and analyze the relationship between UPS logarithmic sum probability and fault working condition. Then set the threshold to capture the UPS fault according to the fault data recall rate. The second part was fault recognition by XGBoost model. The extremely unbalanced fault data makes it difficult to classify, so XGBoost algorithm has been used to do the classification. combine learning curve with grid search to optimize XGBoost parameters. Experimental results show that GMM can accurately detect equipment faults.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127024922","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

Project Based Instruction for Computer Aided Design and Mechatronics Courses 基于项目的计算机辅助设计与机电一体化课程教学

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201888

Yuelei Yang, H. Lang

引用次数: 1

Application of virtual reality and augmented reality technology in Teaching1 虚拟现实与增强现实技术在教学中的应用

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201763

Liping Li, Xiaosong Wu

引用次数: 0

Detection of Careless Mistakes during Programming Learning using a Simple Electroencephalograph 用简易脑电图检测编程学习过程中的粗心错误

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201772

K. Umezawa, M. Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, S. Hirasawa

引用次数: 0

Knowledge Description Frame of Learning Resources for Recommendation System: From the Perspectives of Learning Psychology 推荐系统学习资源的知识描述框架:基于学习心理学的视角

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201686

Wenlu Qiu, Jing Du, Fei Li

引用次数: 1

Experimental Teaching Reform to Embedded System Curriculum 嵌入式系统课程实验教学改革

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201757

Xing Liu, Yaobang Zhao, Jingling Yuan, Wenbi Rao, Liping Lu, Fei Huang

{"title":"Experimental Teaching Reform to Embedded System Curriculum","authors":"Xing Liu, Yaobang Zhao, Jingling Yuan, Wenbi Rao, Liping Lu, Fei Huang","doi":"10.1109/ICCSE49874.2020.9201757","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201757","url":null,"abstract":"With the rapid development of embedded technology, the traditional experiments of embedded system curriculum meet several challenges, such as the experiment design is lack of comprehensive perspective, the experimental program is insufficient to cultivate the students' independent development ability, and the teaching contents cannot keep up with the development trend of embedded technology. To address these challenges, an experimental teaching reform to the embedded system curriculum is implemented in this paper. To enable the students to build a comprehensive perspective to the embedded system architecture, five courses related to the embedded system are integrated to construct a complete embedded architecture ranging from the underlying hardware to the upper application. To strengthen the students' independent development ability, a real-time multithreaded embedded OS is required to be developed by the students. To keep the teaching contents up with the development trend of embedded technology, some emerging technologies such as multi-core embedded architecture, LoRa, NB-IoT, etc., are proposed and used as the experimental cases. The experimental teaching reform targets to enable the students to establish a comprehensive embedded system perspective, become proficient in the embedded software and hardware skills, cultivate the cross-layer software and hardware collaborative optimization thinking, and master the way to solve some difficulties in the embedded system. The teaching reform has been implemented in the Internet-of-Things speciality for four years, and the survey results proved it had achieved the expected teaching effects effectively.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132882316","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

Design of Video Cloud Networking Scheme in expressway 高速公路视频云网方案设计

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201708

Chunzhi Wang, Ruoxi Wang, Siwei Wei, Yong Zeng

引用次数: 0

Exploiting Crowd-based Learning Method in Software Engineering Course 在软件工程课程中运用群体学习方法

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201647

Xinjun Mao, Yao Lu, Yi Yang

{"title":"Exploiting Crowd-based Learning Method in Software Engineering Course","authors":"Xinjun Mao, Yao Lu, Yi Yang","doi":"10.1109/ICCSE49874.2020.9201647","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201647","url":null,"abstract":"Software engineering is one of main major course for computer science. The main objective of this course is to improve the engineering capabilities of students to develop complex software systems. However, current course practice methods are teacher-centered and thus highly depend on the limited talents, experiences and efforts of teachers. Such methods greatly restrict students’ scopes to gain necessary skills and artifacts, and to draw on successful experiences to address various personalized engineering issues and therefore enhance abilities to tackle engineering complexity. This paper presents a crowd-based learning method and introduces our exploration to use the method to reform the software engineering course practice. The essence of our exploration is to exploit the wisdoms and artifacts of crowds over Internet to support students to accomplish their course projects. The former is the engineering knowledges shared in question and answering (Q&A) platforms such as StackOverflow, and the latter is the open source software (OSS) hosted in OSS sites such as GitHub. We use the method in two separate course practices that aim to improve students’ abilities to develop original, high-quality and large-scale software systems. The results of three-year explorations are positive and impressive and show that the crowd-based learning method is effective.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131020288","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

Intelligent Pipeline Leak Detection and Analysis System 智能管道泄漏检测与分析系统

2020 15th International Conference on Computer Science & Education (ICCSE) Pub Date : 2020-08-01 DOI: 10.1109/ICCSE49874.2020.9201761

Huiwen Lin, Hezhi Lin, X. Fang, Mingkang Wang, Lianfeng Huang

{"title":"Intelligent Pipeline Leak Detection and Analysis System","authors":"Huiwen Lin, Hezhi Lin, X. Fang, Mingkang Wang, Lianfeng Huang","doi":"10.1109/ICCSE49874.2020.9201761","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201761","url":null,"abstract":"Urban water supply pipe network leakage accident is a joint problem that exists among the water supply industries all over the world. The leakage in the pipe network not only causes waste of water resources and energy, but also brings water supply security risks to the entire pipe network. Therefore, monitoring the leakage in the water supply system is an important component of water work nowadays. This paper presents an intelligent pipeline leak detection and analysis system. The proposed system collects pipe flow data with an ultrasonic flowmeter. This system uses NB-IoT for data transmission and One-Class-SVM’s outlier detection method for leakage judgment. It also gives a rough position of leakage. Compared with the traditional leakage detection method, the proposed system has many advantages such as simple equipment, convenient operation and access without breaking the original pipe section. Besides, the proposed system provides a friendly web interface and Android App interface, allowing users to observe real-time pipe flow data. It also has an alarm so that users will know whether there has leakage.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132114505","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: 10