With the development of meteorological services, there are more and more types of real-time observation data, and the timeliness requirements are getting higher and higher. The monitoring methods of existing meteorolo...With the development of meteorological services, there are more and more types of real-time observation data, and the timeliness requirements are getting higher and higher. The monitoring methods of existing meteorological observation data transmission can no longer meet the needs. This paper proposes a new monitoring model, namely the “integrated monitoring model” for provincial meteorological observation data transmission. The model can complete the whole network monitoring of meteorological observation data transmission process. Based on this model, the integrated monitoring system for meteorological observation data transmission in Guangdong Province is developed. The system uses Java as the programming language, and integrates J2EE, Hibernate, Quartz, Snmp4j and Slf4j frameworks, and uses Oracle database as the data storage carrier, following the MVC specification and agile development concept. The system development uses four key technologies, including simple network management protocol, network connectivity detection technology, remote host management technology and thread pool technology. The integrated monitoring system has been put into business application. As a highlight of Guangdong’s meteorological modernization, it has played an active role in many major meteorological services.展开更多
A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat...A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat-form suitable for the Jining No.3 coal mine is presented. This network is an information superhighway intended to inte-grate all existing and new automation subsystems. Its standard interface can be used with future subsystems. The net-work,data structure and management decision-making all employ this uniform hardware and software. This effectively avoids the problems of system and information islands seen in traditional mine-automation systems. The construction of the network provides a stable foundation for digital communication in the Jining No.3 coal mine.展开更多
With the emergence of cloud technologies,the services of healthcare systems have grown.Simultaneously,machine learning systems have become important tools for developing matured and decision-making computer applicatio...With the emergence of cloud technologies,the services of healthcare systems have grown.Simultaneously,machine learning systems have become important tools for developing matured and decision-making computer applications.Both cloud computing and machine learning technologies have contributed significantly to the success of healthcare services.However,in some areas,these technologies are needed to provide and decide the next course of action for patients suffering from diabetic kidney disease(DKD)while ensuring privacy preservation of the medical data.To address the cloud data privacy problem,we proposed a DKD prediction module in a framework using cloud computing services and a data control scheme.This framework can provide improved and early treatment before end-stage renal failure.For prediction purposes,we implemented the following machine learning algorithms:support vector machine(SVM),random forest(RF),decision tree(DT),naïve Bayes(NB),deep learning(DL),and k nearest neighbor(KNN).These classification techniques combined with the cloud computing services significantly improved the decision making in the progress of DKD patients.We applied these classifiers to the UCI Machine Learning Repository for chronic kidney disease using various clinical features,which are categorized as single,combination of selected features,and all features.During single clinical feature experiments,machine learning classifiers SVM,RF,and KNN outperformed the remaining classification techniques,whereas in combined clinical feature experiments,the maximum accuracy was achieved for the combination of DL and RF.All the feature experiments presented increased accuracy and increased F-measure metrics from SVM,DL,and RF.展开更多
文摘With the development of meteorological services, there are more and more types of real-time observation data, and the timeliness requirements are getting higher and higher. The monitoring methods of existing meteorological observation data transmission can no longer meet the needs. This paper proposes a new monitoring model, namely the “integrated monitoring model” for provincial meteorological observation data transmission. The model can complete the whole network monitoring of meteorological observation data transmission process. Based on this model, the integrated monitoring system for meteorological observation data transmission in Guangdong Province is developed. The system uses Java as the programming language, and integrates J2EE, Hibernate, Quartz, Snmp4j and Slf4j frameworks, and uses Oracle database as the data storage carrier, following the MVC specification and agile development concept. The system development uses four key technologies, including simple network management protocol, network connectivity detection technology, remote host management technology and thread pool technology. The integrated monitoring system has been put into business application. As a highlight of Guangdong’s meteorological modernization, it has played an active role in many major meteorological services.
基金Project 50574094 supported by the National Natural Science Foundation of China
文摘A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat-form suitable for the Jining No.3 coal mine is presented. This network is an information superhighway intended to inte-grate all existing and new automation subsystems. Its standard interface can be used with future subsystems. The net-work,data structure and management decision-making all employ this uniform hardware and software. This effectively avoids the problems of system and information islands seen in traditional mine-automation systems. The construction of the network provides a stable foundation for digital communication in the Jining No.3 coal mine.
文摘With the emergence of cloud technologies,the services of healthcare systems have grown.Simultaneously,machine learning systems have become important tools for developing matured and decision-making computer applications.Both cloud computing and machine learning technologies have contributed significantly to the success of healthcare services.However,in some areas,these technologies are needed to provide and decide the next course of action for patients suffering from diabetic kidney disease(DKD)while ensuring privacy preservation of the medical data.To address the cloud data privacy problem,we proposed a DKD prediction module in a framework using cloud computing services and a data control scheme.This framework can provide improved and early treatment before end-stage renal failure.For prediction purposes,we implemented the following machine learning algorithms:support vector machine(SVM),random forest(RF),decision tree(DT),naïve Bayes(NB),deep learning(DL),and k nearest neighbor(KNN).These classification techniques combined with the cloud computing services significantly improved the decision making in the progress of DKD patients.We applied these classifiers to the UCI Machine Learning Repository for chronic kidney disease using various clinical features,which are categorized as single,combination of selected features,and all features.During single clinical feature experiments,machine learning classifiers SVM,RF,and KNN outperformed the remaining classification techniques,whereas in combined clinical feature experiments,the maximum accuracy was achieved for the combination of DL and RF.All the feature experiments presented increased accuracy and increased F-measure metrics from SVM,DL,and RF.
