Data Persistence on Physical Function Monitoring System for Athletes

2014 ◽  
Vol 602-605 ◽  
pp. 1622-1625
Author(s):  
Xue Ying Zhang ◽  
Kai Su

You can find out the law of matter and energy metabolism when you are active by means of monitoring the athletes’ physical function, and the law can provide a theoretical basis for the training to achieve scientific training ultimately. Monitoring system can achieve a comprehensive information management for monitorship; data persistence is an important work of building monitoring system, and the paper researches on the NHibernate technology that based on .Net. First, data structure design was conducted based on the SQL Server database management system; then, you can study NHibernate architecture through the graphics; finally, you can carry on persistence design on the "Physiological Indicators" Table according to the persistence steps of NHibernate. Result of this study can be applied to the field of athletic training and has important implications for improving athletic performance, promoting sports development and so on.

2014 ◽  
Vol 602-605 ◽  
pp. 1618-1621
Author(s):  
Xue Ying Zhang ◽  
Li Hua Chen

How to implement the system monitoring in the process of athletes training, diagnosis athletes body function scientific, technical characteristics and psychological state, effectively improve the training ability of athletes, prevent excessive fatigue or overtraining, is an urgent problem in the field of sports science. Database design of this paper is to develop function monitoring system on the basic work. Firstly, analyses the process and content of monitoring; Then, the conceptual structure design and physical structure design. Among them, the conceptual structure design using E-R diagram describes the entities and relations; logical structure design the table structure of the athletes category, athletes, physiological indicators, biochemical indicators, morphological function indicators, and other table structure. The content of this paper plays an important role in improving the information management of sport.


2014 ◽  
Vol 1039 ◽  
pp. 197-202
Author(s):  
Chuan Hong Zhou ◽  
Jin Jie Xiao ◽  
Wei Ren

Currently,some problems exist in the process of using standby generators, such as low efficiency,high cost and late service of artificial overhaul and maintenance.In order to overcome these problems, PC remote monitoring system is designed.This paper mainly introduces the structure composition,function,interface design and SQL Server database design of the system.In addition, the function of communication between the PC remote server and signal monitoring device was tested and the effect was desired


1990 ◽  
Vol 80 (6B) ◽  
pp. 1833-1851 ◽  
Author(s):  
Thomas C. Bache ◽  
Steven R. Bratt ◽  
James Wang ◽  
Robert M. Fung ◽  
Cris Kobryn ◽  
...  

Abstract The Intelligent Monitoring System (IMS) is a computer system for processing data from seismic arrays and simpler stations to detect, locate, and identify seismic events. The first operational version processes data from two high-frequency arrays (NORESS and ARCESS) in Norway. The IMS computers and functions are distributed between the NORSAR Data Analysis Center (NDAC) near Oslo and the Center for Seismic Studies (Center) in Arlington, Virginia. The IMS modules at NDAC automatically retrieve data from a disk buffer, detect signals, compute signal attributes (amplitude, slowness, azimuth, polarization, etc.), and store them in a commercial relational database management system (DBMS). IMS makes scheduled (e.g., hourly) transfers of the data to a separate DBMS at the Center. Arrival of new data automatically initiates a “knowledge-based system (KBS)” that interprets these data to locate and identify (earthquake, mine blast, etc.) seismic events. This KBS uses general and area-specific seismological knowledge represented in rules and procedures. For each event, unprocessed data segments (e.g., 7 min for regional events) are retrieved from NDAC for subsequent display and analyst review. The interactive analysis modules include integrated waveform and map display/manipulation tools for efficient analyst validation or correction of the solutions produced by the automated system. Another KBS compares the analyst and automatic solutions to mark overruled elements of the knowledge base. Performance analysis statistics guide subsequent changes to the knowledge base so it improves with experience. The IMS is implemented on networked Sun workstations, with a 56 kbps satellite link bridging the NDAC and Center computer networks. The software architecture is modular and distributed, with processes communicating by messages and sharing data via the DBMS. The IMS processing requirements are easily met with major processes (i.e., signal processing, KBS, and DBMS) on separate Sun 4/2xx workstations. This architecture facilitates expansion in functionality and number of stations. The first version was operated continuously for 8 weeks in late-1989. The Center functions were then transferred to NDAC for subsequent operation. Later versions will be distributed among NDAC, Scripps/IGPP (San Diego), and the Center to process data from many stations and arrays. The IMS design is ambitious in its integration of many new computer technologies, but the operational performance of the first version demonstrates its validity. Thus, IMS provides a new generation of automated seismic event monitoring capability.


2018 ◽  
Vol 232 ◽  
pp. 04024
Author(s):  
Yuchen Wang ◽  
Mantao Wang ◽  
Zhouyu Tan ◽  
Jie Zhang ◽  
Zhiyong Li ◽  
...  

With the growth of building monitoring network, increasing human resource and funds have been invested into building monitoring system. Computer vision technology has been widely used in image recognition recently, and this technology has also been gradually applied to action recognition. There are still many disadvantages of traditional monitoring system. In this paper, a human activity recognition system which based on the convolution neural network is proposed. Using the 3D convolution neural network and the transfer learning technology, the human activity recognition engine is constructed. The Spring MVC framework is used to build the server end, and the system page is designed in HBuilder. The system not only enhances efficiency and functionality of building monitoring system, but also improves the level of building safety.


2017 ◽  
Vol 140 ◽  
pp. 386-397 ◽  
Author(s):  
Elisa Sirombo ◽  
Marco Filippi ◽  
Antonio Catalano ◽  
Andrea Sica

2014 ◽  
Vol 535 ◽  
pp. 26-31
Author(s):  
Zhi Zhong Li ◽  
Shi Chun Yang ◽  
Zi Tao Liu

This paper analyzed the practical needs of remote monitoring of electric vehicle and illustrates the overall architecture of a remote monitoring system, and further developed a remote monitoring system of the Server and client application with the ASP.NET and Microsoft SQL Server database language, basically can meet the electric cars remote monitoring of the Server and client needs.


2013 ◽  
Vol 303-306 ◽  
pp. 2103-2106
Author(s):  
Cong Cheng

Popularization of the building monitoring system requires huge data storage, information management and computing services. However, the analog signal transmission cannot meet the requirements anymore, therefore cloud computing has to play its role. For this purpose, this article brings up an overall design idea and physical deployment of a cloud-based building monitoring system.


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