Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590744
Cundong Tang, Zhiping Wang
Human beings can use artificial intelligence technology to model, predict and track moving targets. At present, visual target tracking is widely used in military and civil fields, such as visual navigation and positioning, radar target detection, air traffic control, robot visual navigation, video intelligent monitoring and automation, etc. Therefore, visual target tracking has not only theoretical research value, but also practical engineering value. The Kalman filter algorithm is improved to make the tracking effect of moving target better. Firstly, the time difference observation equation and signal arrival direction observation equation are used to locate the moving target, and its mathematical relationship is simplified to generate a pseudo linear model; Finally, the extended Kalman filter algorithm is applied to complete target tracking. Simulation results show that the extended Kalman filter algorithm has better tracking accuracy and stability than the traditional algorithm.
{"title":"Research and simulation of path estimation based on extended kalman filtering algorithm in video image","authors":"Cundong Tang, Zhiping Wang","doi":"10.1109/ICISCAE52414.2021.9590744","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590744","url":null,"abstract":"Human beings can use artificial intelligence technology to model, predict and track moving targets. At present, visual target tracking is widely used in military and civil fields, such as visual navigation and positioning, radar target detection, air traffic control, robot visual navigation, video intelligent monitoring and automation, etc. Therefore, visual target tracking has not only theoretical research value, but also practical engineering value. The Kalman filter algorithm is improved to make the tracking effect of moving target better. Firstly, the time difference observation equation and signal arrival direction observation equation are used to locate the moving target, and its mathematical relationship is simplified to generate a pseudo linear model; Finally, the extended Kalman filter algorithm is applied to complete target tracking. Simulation results show that the extended Kalman filter algorithm has better tracking accuracy and stability than the traditional algorithm.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116125638","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}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE55891.2022.9927572
Shiyan Pang, Anran Zhang, Shuhui Lai, Zhiqi Zuo
Recognition of teachers' nonverbal behavior is an important tool for assessing teachers' teaching behavior. Within the continuous progress of artificial intelligence technology, automatic recognition of nonverbal behavior has been more and more popular. Therefore, we take the teaching videos in the actual classroom as the data source, acquires and labels the teachers' nonverbal behavior dataset, extracts the teacher skeleton points information in the images using the target detection algorithm and the human pose estimation algorithm, and adopts a residual block model with dilated convolution for automatic recognition of teachers' nonverbal behavior. It is proved that the proposed method can effectively improve the accuracy of teachers' nonverbal behavior recognition. The research in this paper is to help solve the problem of automatic recognition of teachers' nonverbal behavior and assist teachers to optimize teaching strategies and improve teaching efficiency.
{"title":"Automatic Recognition of Teachers' Nonverbal Behavior Based on Dilated Convolution","authors":"Shiyan Pang, Anran Zhang, Shuhui Lai, Zhiqi Zuo","doi":"10.1109/ICISCAE55891.2022.9927572","DOIUrl":"https://doi.org/10.1109/ICISCAE55891.2022.9927572","url":null,"abstract":"Recognition of teachers' nonverbal behavior is an important tool for assessing teachers' teaching behavior. Within the continuous progress of artificial intelligence technology, automatic recognition of nonverbal behavior has been more and more popular. Therefore, we take the teaching videos in the actual classroom as the data source, acquires and labels the teachers' nonverbal behavior dataset, extracts the teacher skeleton points information in the images using the target detection algorithm and the human pose estimation algorithm, and adopts a residual block model with dilated convolution for automatic recognition of teachers' nonverbal behavior. It is proved that the proposed method can effectively improve the accuracy of teachers' nonverbal behavior recognition. The research in this paper is to help solve the problem of automatic recognition of teachers' nonverbal behavior and assist teachers to optimize teaching strategies and improve teaching efficiency.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123072321","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}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590806
Hui Pan
Information system integration project management has many functions that project management does not have, and its content is much richer than project management. Computer System (CIS) project management is a kind of systematic project management that analyzes and manages the cost, personnel, quality inspection, risks and progress, so that the project can carry out related activities according to the budgeted cost, progress and quality. With the continuous improvement of science and technology and productivity, quality management is also making continuous progress. Based on this, this paper puts forward a computer information system integration project management algorithm based on quality information integration, which combines the project management theory with the project practice of BMS company, thus shortening the project cycle, reducing the project cost, ensuring the project quality and creating maximum value and benefit for BMS company. In order to improve the comprehensive efficiency of project implementation, it is necessary to formulate a highly operable and reasonable work plan according to the specific characteristics of the project, and scientifically prepare and optimize various elements.
{"title":"Research on Project Management Algorithm of Computer Information System Integration Based on Quality Information Integration","authors":"Hui Pan","doi":"10.1109/ICISCAE52414.2021.9590806","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590806","url":null,"abstract":"Information system integration project management has many functions that project management does not have, and its content is much richer than project management. Computer System (CIS) project management is a kind of systematic project management that analyzes and manages the cost, personnel, quality inspection, risks and progress, so that the project can carry out related activities according to the budgeted cost, progress and quality. With the continuous improvement of science and technology and productivity, quality management is also making continuous progress. Based on this, this paper puts forward a computer information system integration project management algorithm based on quality information integration, which combines the project management theory with the project practice of BMS company, thus shortening the project cycle, reducing the project cost, ensuring the project quality and creating maximum value and benefit for BMS company. In order to improve the comprehensive efficiency of project implementation, it is necessary to formulate a highly operable and reasonable work plan according to the specific characteristics of the project, and scientifically prepare and optimize various elements.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124619857","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}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE52414.2021.9590791
Lili Ye
Compared with traditional 3G and 4G networks, 5G network, as a new network, can provide higher-speed mobile service coverage. In 5G networks, base stations need to achieve accurate time synchronization to ensure communication quality. In order to keep the accurate time of 5G network, a time synchronization system between satellite ground base station and software-defined optical network controller based on optical wireless network is proposed, which has the advantage of greatly improving the accuracy of time synchronization of ground base station. Based on random optimization, an air interface-based clustering synchronization algorithm for Small Cell is proposed. Network synchronization is divided into two synchronization processes, an intra-cluster synchronization process and an inter-cluster synchronization process. Simulation results show that this algorithm can ensure the synchronization accuracy of multiple nodes in the cluster, which is at least 6-10us higher than the traditional air interface synchronization process.
{"title":"High-precision time synchronization networking algorithm of 5G base station based on stochastic optimization","authors":"Lili Ye","doi":"10.1109/ICISCAE52414.2021.9590791","DOIUrl":"https://doi.org/10.1109/ICISCAE52414.2021.9590791","url":null,"abstract":"Compared with traditional 3G and 4G networks, 5G network, as a new network, can provide higher-speed mobile service coverage. In 5G networks, base stations need to achieve accurate time synchronization to ensure communication quality. In order to keep the accurate time of 5G network, a time synchronization system between satellite ground base station and software-defined optical network controller based on optical wireless network is proposed, which has the advantage of greatly improving the accuracy of time synchronization of ground base station. Based on random optimization, an air interface-based clustering synchronization algorithm for Small Cell is proposed. Network synchronization is divided into two synchronization processes, an intra-cluster synchronization process and an inter-cluster synchronization process. Simulation results show that this algorithm can ensure the synchronization accuracy of multiple nodes in the cluster, which is at least 6-10us higher than the traditional air interface synchronization process.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129013453","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}
Pub Date : 1900-01-01DOI: 10.1109/ICISCAE55891.2022.9927691
Xianwu Shan, Zhixing Song, Hongwei Pan, X. Ye
This paper focuses on the problems of low efficiency of abnormal control of line loss in XinJiang area, weak effect of loss reduction, and difficulty in abnormal monitoring. The computer eigenvector data method is used to integrate and optimize static and dynamic data. In this way, the in-depth mining of the data information of the XinJiang area is realized. Through the establishment of line damage and abnormal diagnosis and analysis models in the XinJiang area, scientific and standardized work management can be truly realized, the management lag problem can be effectively solved, and the management efficiency of the XinJiang area has been greatly improved.
{"title":"Research on the Algorithm Model of Smart Grid Line Loss Diagnosis Driven by Computer Eigenvector Method","authors":"Xianwu Shan, Zhixing Song, Hongwei Pan, X. Ye","doi":"10.1109/ICISCAE55891.2022.9927691","DOIUrl":"https://doi.org/10.1109/ICISCAE55891.2022.9927691","url":null,"abstract":"This paper focuses on the problems of low efficiency of abnormal control of line loss in XinJiang area, weak effect of loss reduction, and difficulty in abnormal monitoring. The computer eigenvector data method is used to integrate and optimize static and dynamic data. In this way, the in-depth mining of the data information of the XinJiang area is realized. Through the establishment of line damage and abnormal diagnosis and analysis models in the XinJiang area, scientific and standardized work management can be truly realized, the management lag problem can be effectively solved, and the management efficiency of the XinJiang area has been greatly improved.","PeriodicalId":115061,"journal":{"name":"International Conference on Information Systems and Computer Aided Education","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124463347","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}
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