scholarly journals Physical Training Information System of College Sports Based on Big Data Mobile Terminal

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Xianfeng Dong
Keyword(s):  
Information System ◽  
Big Data ◽  
Embedded System ◽  
Physical Training ◽  
Skills Training ◽  
Mobile Terminal ◽  
College Sports ◽  
Sports Training ◽  
Sports Information ◽  
The University

The development of information technology is changing all walks of life. People’s health problem is more and more prominent; people begin to talk about the reform of college sports training. Sports no longer rely on individual games, but on the comprehensive strength of science and technology competition. The fierce competition for Olympic gold medal in modern competitive sports is largely due to the competition of scientific and technological strength of various countries. China has also conducted a lot of research on sports information and made some achievements. Through the investigation, we know that, at present, the provincial level sports teams have established the relevant sports training information management system, which is very effective. The latest scientific and technological achievements are combined with sports to establish the university sports information system. The purpose of this paper is to analyze the university sports physical training information system based on big data mobile terminal, study the big data embedded system, improve the effect of sports skills training, and meet the social demand for high skilled sports talents. This paper uses the literature method, experimental investigation method, and big data spectral clustering algorithm-related experiments to study the advantages of big data and uses the value of big data and embedded system model to study the university sports physical fitness training information system based on big data mobile terminal. The results show that 40.6% of college students spend more time in physical exercise, based on the application of big data embedded system in college sports training; it is of great significance to arrange sports training methods to improve students’ sports training performance.

MANAGEMENT OF THE SUCCESS OF STUDENT’S LEARNING BASED ON THE MARKOV MODEL

2018 ◽  
pp. 4-11
Author(s):  
M. V. Noskov ◽  
M. V. Somova ◽  
I. M. Fedotova
Keyword(s):  
Information System ◽  
Markov Process ◽  
Continuous Time ◽  
Information Technologies ◽  
Educational Process ◽  
Automated Information System ◽  
The Subject ◽  
The University ◽  
Independent Work ◽  
Near Future

The article proposes a model for forecasting the success of student’s learning. The model is a Markov process with continuous time, such as the process of “death and reproduction”. As the parameters of the process, the intensities of the processes of obtaining and assimilating information are offered, and the intensity of the process of assimilating information takes into account the attitude of the student to the subject being studied. As a result of applying the model, it is possible for each student to determine the probability of a given formation of ownership of the material being studied in the near future. Thus, in the presence of an automated information system of the university, the implementation of the model is an element of the decision support system by all participants in the educational process. The examples given in the article are the results of an experiment conducted at the Institute of Space and Information Technologies of Siberian Federal University under conditions of blended learning, that is, under conditions when classroom work is accompanied by independent work with electronic resources.

Big Data in the Field of Civil Security Research

2016 ◽  
Vol 7 (1) ◽  
pp. 54-64 ◽  
Author(s):  
Julia Gonschorek ◽  
Anja Langer ◽  
Benjamin Bernhardt ◽  
Caroline Räbiger
Keyword(s):  
Big Data ◽  
Temporal Distribution ◽  
Tactical Planning ◽  
Fire Departments ◽  
Prevention Measures ◽  
Scientific Contribution ◽  
Security Research ◽  
Geovisual Analytics ◽  
The University ◽  
Selection Of

This article gives insight in a running dissertation at the University in Potsdam. Point of discussion is the spatial and temporal distribution of emergencies of German fire brigades that have not sufficiently been scientifically examined. The challenge is seen in Big Data: enormous amounts of data that exist now (or can be collected in the future) and whose variables are linked to one another. These analyses and visualizations can form a basis for strategic, operational and tactical planning, as well as prevention measures. The user-centered (geo-) visualization of fire brigade data accessible to the general public is a scientific contribution to the research topic 'geovisual analytics and geographical profiling'. It may supplement antiquated methods such as the so-called pinmaps as well as the areas of engagement that are freehand constructions in GIS. Considering police work, there are already numerous scientific projects, publications, and software solutions designed to meet the specific requirements of Crime Analysis and Crime Mapping. By adapting and extending these methods and techniques, civil security research can be tailored to the needs of fire departments. In this paper, a selection of appropriate visualization methods will be presented and discussed.

scholarly journals Research on Enterprise Employee Information System Based On Big Data Analysis

2021 ◽  
Vol 1748 ◽  
pp. 032025
Author(s):  
Jicheng Wang ◽  
Donghai Li ◽  
Zhao Wang ◽  
Taifeng Wan
Keyword(s):  
Information System ◽  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Employee Information
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