介绍了电网管理信息系统(Management Information System,MIS)、数据仓库和联机分析处理(on-line analytical processing,OLAP)服务,分析了基于数据仓库的MIS系统中OLAP设计的系统架构。系统基于Web Service和SQL Server 2000,数据仓库...介绍了电网管理信息系统(Management Information System,MIS)、数据仓库和联机分析处理(on-line analytical processing,OLAP)服务,分析了基于数据仓库的MIS系统中OLAP设计的系统架构。系统基于Web Service和SQL Server 2000,数据仓库中的数据经过分析服务器处理后提供OLAP服务,客户端上的数据透视表服务通过HTTP连接分析服务器获得数据并存储到高速缓存中进行分析。展开更多
智能可穿戴领域是一个集多学科多门类的交叉研究领域,智能可穿戴数据手套在监测人体健康、信息传递、通信、虚拟交互等领域具有广阔的应用前景。运用Citespace软件以Wed of Science核心数据库为数据来源,对近5年的相关研究文献进行检索...智能可穿戴领域是一个集多学科多门类的交叉研究领域,智能可穿戴数据手套在监测人体健康、信息传递、通信、虚拟交互等领域具有广阔的应用前景。运用Citespace软件以Wed of Science核心数据库为数据来源,对近5年的相关研究文献进行检索,最终纳入126篇文献进行全文系统分析,从应用于数据手套基于不同工作原理的传感器类型、用于可穿戴传感显示转化的数据处理方法、多功能可穿戴传感手套集成的方法3个方面,对最新研究进行全面梳理总结。讨论了方法和技术的局限性,指出了存在的挑战和机遇。展开更多
To realize a hyperconnected smart society with high productivity,advances in flexible sensing technology are highly needed.Nowadays,flexible sensing technology has witnessed improvements in both the hardware performan...To realize a hyperconnected smart society with high productivity,advances in flexible sensing technology are highly needed.Nowadays,flexible sensing technology has witnessed improvements in both the hardware performances of sensor devices and the data processing capabilities of the device’s software.Significant research efforts have been devoted to improving materials,sensing mechanism,and configurations of flexible sensing systems in a quest to fulfill the requirements of future technology.Meanwhile,advanced data analysis methods are being developed to extract useful information from increasingly complicated data collected by a single sensor or network of sensors.Machine learning(ML)as an important branch of artificial intelligence can efficiently handle such complex data,which can be multi-dimensional and multi-faceted,thus providing a powerful tool for easy interpretation of sensing data.In this review,the fundamental working mechanisms and common types of flexible mechanical sensors are firstly presented.Then how ML-assisted data interpretation improves the applications of flexible mechanical sensors and other closely-related sensors in various areas is elaborated,which includes health monitoring,human-machine interfaces,object/surface recognition,pressure prediction,and human posture/motion identification.Finally,the advantages,challenges,and future perspectives associated with the fusion of flexible mechanical sensing technology and ML algorithms are discussed.These will give significant insights to enable the advancement of next-generation artificial flexible mechanical sensing.展开更多
文摘介绍了电网管理信息系统(Management Information System,MIS)、数据仓库和联机分析处理(on-line analytical processing,OLAP)服务,分析了基于数据仓库的MIS系统中OLAP设计的系统架构。系统基于Web Service和SQL Server 2000,数据仓库中的数据经过分析服务器处理后提供OLAP服务,客户端上的数据透视表服务通过HTTP连接分析服务器获得数据并存储到高速缓存中进行分析。
文摘智能可穿戴领域是一个集多学科多门类的交叉研究领域,智能可穿戴数据手套在监测人体健康、信息传递、通信、虚拟交互等领域具有广阔的应用前景。运用Citespace软件以Wed of Science核心数据库为数据来源,对近5年的相关研究文献进行检索,最终纳入126篇文献进行全文系统分析,从应用于数据手套基于不同工作原理的传感器类型、用于可穿戴传感显示转化的数据处理方法、多功能可穿戴传感手套集成的方法3个方面,对最新研究进行全面梳理总结。讨论了方法和技术的局限性,指出了存在的挑战和机遇。
基金support from National Natural Science Foundation of China(Nos.62274140,61904141,52173234)the State Key Laboratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeronautics and Astronautics)(Grant No.MCMS-E-0422G03)the Shenzhen-Hong Kong-Macao Technology Research Program(Type C,202011033000145,SGDX2020110309300301).
文摘To realize a hyperconnected smart society with high productivity,advances in flexible sensing technology are highly needed.Nowadays,flexible sensing technology has witnessed improvements in both the hardware performances of sensor devices and the data processing capabilities of the device’s software.Significant research efforts have been devoted to improving materials,sensing mechanism,and configurations of flexible sensing systems in a quest to fulfill the requirements of future technology.Meanwhile,advanced data analysis methods are being developed to extract useful information from increasingly complicated data collected by a single sensor or network of sensors.Machine learning(ML)as an important branch of artificial intelligence can efficiently handle such complex data,which can be multi-dimensional and multi-faceted,thus providing a powerful tool for easy interpretation of sensing data.In this review,the fundamental working mechanisms and common types of flexible mechanical sensors are firstly presented.Then how ML-assisted data interpretation improves the applications of flexible mechanical sensors and other closely-related sensors in various areas is elaborated,which includes health monitoring,human-machine interfaces,object/surface recognition,pressure prediction,and human posture/motion identification.Finally,the advantages,challenges,and future perspectives associated with the fusion of flexible mechanical sensing technology and ML algorithms are discussed.These will give significant insights to enable the advancement of next-generation artificial flexible mechanical sensing.
