scholarly journals Application of Data Mining in the Analysis of Martial Arts Athlete Competition Skills and Tactics

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Lingrong Tao
Keyword(s):  
Data Mining ◽  
Martial Arts ◽  
Statistical Data ◽  
Practical Significance ◽  
Data Mining Techniques ◽  
Develop Technology ◽  
Competitive Success ◽  
Daily Training ◽  
Using Data ◽  
The Relationship

In martial arts, data mining technologies are used to describe and analyze the moves of athletes and changes in the process and sequences. Martial arts is a process in which athletes use all kinds of strengths and actions to make offensive and defensive changes according to the tactics of opponents. One such martial arts is Wushu arts as it has a long history in reference to Chinese martial arts. During the Wushu competition, Wushu athletes show their adaptability and technical level in complex, random, and nonlinear competitive abilities, organized and systematic skills, tactics, and position movement. Using data mining techniques, in-depth mining a particular type of martial arts competition technology and tactics behind statistical data, and using the data to find the law of change to solve some problems, for martial arts athletes in daily training to develop technology and tactics and improve competition results, is the practical significance of data mining in martial arts athletes competition. This research explored the relationship between goal-oriented and mental intensity and their effect on competitive success outcomes.

IDENTIFICATION OF CRITICAL INFRASTRUCTURE USING DATA MINING TECHNIQUES

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Su-Ling Fan ◽  
Chang-Saar Chai ◽  
Kumar Vikram
Keyword(s):  
Data Mining ◽  
Continuous Flow ◽  
Critical Infrastructure ◽  
Economic Factors ◽  
Data Mining Techniques ◽  
The Social ◽  
Using Data ◽  
Disaster Protection ◽  
The Relationship

Critical Infrastructure (CI) is a term used to describe important national assets for producing or distributing a continuous flow of essential goods or services. They are marked by immense complexity, characterized predominantly by strong intra and interdependencies as well as hierarchies. These interconnections take many forms, including flows of information, shared security, physical flows of commodities, and others. Previous research has illustrated the relationship between the physical impacts of natural disasters and the social and economic factors on CI. Some research emphasized more the role of CI interdependencies and their importance and influence over the functioning of industries while others have looked the impacts due to disruption of CI after disasters. Nowadays comprehensive identification of all interdependency relationships of CI remains a challenge. As the complexity and interconnectedness of a country's CI evolve, threats and vulnerabilities increase. Thus, investigating how a set of CI interacts and identification of criticality of CI becomes an important topic. This research has made utilization of data mining techniques and proposes a method to identify the criticality of Critical Infrastructure so that to develop better disaster protection and prevention management.

Editor’s Pick: Regulatory and Ethical Issues in the New Era of Radiomics and Radiogenomics

EMJ Radiology ◽  
2020 ◽  
Author(s):  
Filippo Pesapane
Keyword(s):  
Ethical Issues ◽  
Medical Images ◽  
Practical Significance ◽  
Innovative Technology ◽  
New Era ◽  
Naked Eye ◽  
Disease Characteristics ◽  
The Future ◽  
Using Data ◽  
The Relationship

Radiomics is a science that investigates a large number of features from medical images using data-characterisation algorithms, with the aim to analyse disease characteristics that are indistinguishable to the naked eye. Radiogenomics attempts to establish and examine the relationship between tumour genomic characteristics and their radiologic appearance. Although there is certainly a lot to learn from these relationships, one could ask the question: what is the practical significance of radiogenomic discoveries? This increasing interest in such applications inevitably raises numerous legal and ethical questions. In an environment such as the technology field, which changes quickly and unpredictably, regulations need to be timely in order to be relevant.  In this paper, issues that must be solved to make the future applications of this innovative technology safe and useful are analysed.

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

Recognizing Job Apathy Patterns of Iraqi Higher Education Employees Using Data Mining Techniques

2019 ◽  
Vol 54 (4) ◽  
Author(s):  
Mustafa S. Abd ◽  
Suhad Faisal Behadili
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Psychiatric Patients ◽  
Human Life ◽  
A Priori ◽  
Psychological Research ◽  
Attribute Selection ◽  
Specific Class ◽  
Data Mining Techniques ◽  
Using Data

Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from a questionnaire, and the psychiatric researchers recommend these questions. Useless questions are pruned using the attribute selection method. Moreover, pieces of information gained through these questions are measured according to a specific class and ranked accordingly. Association and a priori algorithms are used to detect the most influential and interrelated questions in the questionnaire. Consequently, the decisive parameters that may lead to job apathy are determined.

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