Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as re...Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as reduction in the lifespan of equipment due to frequent switching and interruption,delay,and stoppage of services may occur.Therefore,applying a machine learning(ML)method,which is possible to automatically judge and classify network-related service anomaly,and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors,is required.In this paper,we propose an intelligent packet switching method based on the ML method of classification,which is one of the supervised learning methods,that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data.Furthermore,we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them.The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs.In the broadcasting gateway equipment to which the proposed method is applied,it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.展开更多
Standard examination is an effective approach to promote the teaching quality of modern education. On terms of the analysis of main target, function and constitution of special course examination system for remote edu...Standard examination is an effective approach to promote the teaching quality of modern education. On terms of the analysis of main target, function and constitution of special course examination system for remote education, the internet scheme of the examination system is given according to the students and teachers' requirements. The implementation method for the communication and dynamic production of tests on home page of the exam system are elaborated by using programming technology of Active Server Pages (ASP)3.0. The query of exam information and automatic marking of test questions can be easily realized by the developed exam system under World Wide Web enviromment according to users' requirements.展开更多
建立正常人标准脑是全球人类脑计划(HBP)的重要组成部分,建立适合中国人自己的标准脑结构模板更具有重要意义。本研究基于对所采集的3000例正常成人脑结构数据,以及对这些海量数据的有效管理这一关键问题,通过解析医学数字成像和通信标...建立正常人标准脑是全球人类脑计划(HBP)的重要组成部分,建立适合中国人自己的标准脑结构模板更具有重要意义。本研究基于对所采集的3000例正常成人脑结构数据,以及对这些海量数据的有效管理这一关键问题,通过解析医学数字成像和通信标准(DICOM)图像特殊的数据结构,引入了可扩展标记语言(XML),使用拥有自主知识产权的应用软件,设计和完成了NXD(Native XML Database)数据库,以对获取到的大量的脑结构数据进行管理和使用。系统以数据采集、序列分析、案例提取、案例编辑、案例管理为流程,有效减少了数据占有空间和数据冗余,提高了数据处理的速度和效率,使得数据库系统具有可扩充性、结构稳定性、功能独立性和存储效率高等特点。展开更多
基金This work was supported by a research grant from Seoul Women’s University(2023-0183).
文摘Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream.However,when the transmission environment is unstable,problems such as reduction in the lifespan of equipment due to frequent switching and interruption,delay,and stoppage of services may occur.Therefore,applying a machine learning(ML)method,which is possible to automatically judge and classify network-related service anomaly,and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as transmission errors,is required.In this paper,we propose an intelligent packet switching method based on the ML method of classification,which is one of the supervised learning methods,that presents the risk level of abnormal multi-stream occurring in broadcasting gateway equipment based on data.Furthermore,we subdivide the risk levels obtained from classification techniques into probabilities and then derive vectorized representative values for each attribute value of the collected input data and continuously update them.The obtained reference vector value is used for switching judgment through the cosine similarity value between input data obtained when a dangerous situation occurs.In the broadcasting gateway equipment to which the proposed method is applied,it is possible to perform more stable and smarter switching than before by solving problems of reliability and broadcasting accidents of the equipment and can maintain stable video streaming as well.
基金Sponsored by China Postdoctoral Science Foundation (No:200031)
文摘Standard examination is an effective approach to promote the teaching quality of modern education. On terms of the analysis of main target, function and constitution of special course examination system for remote education, the internet scheme of the examination system is given according to the students and teachers' requirements. The implementation method for the communication and dynamic production of tests on home page of the exam system are elaborated by using programming technology of Active Server Pages (ASP)3.0. The query of exam information and automatic marking of test questions can be easily realized by the developed exam system under World Wide Web enviromment according to users' requirements.
文摘建立正常人标准脑是全球人类脑计划(HBP)的重要组成部分,建立适合中国人自己的标准脑结构模板更具有重要意义。本研究基于对所采集的3000例正常成人脑结构数据,以及对这些海量数据的有效管理这一关键问题,通过解析医学数字成像和通信标准(DICOM)图像特殊的数据结构,引入了可扩展标记语言(XML),使用拥有自主知识产权的应用软件,设计和完成了NXD(Native XML Database)数据库,以对获取到的大量的脑结构数据进行管理和使用。系统以数据采集、序列分析、案例提取、案例编辑、案例管理为流程,有效减少了数据占有空间和数据冗余,提高了数据处理的速度和效率,使得数据库系统具有可扩充性、结构稳定性、功能独立性和存储效率高等特点。
