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Computational Engineering Modeling for Runner Athletes
Author(s) -
Soheila Yavarmasroor,
Zahra Hojjati Zidashti,
A. K. Haghi,
Kaveh Hariri Asli
Publication year - 2013
Publication title -
journal of computational engineering
Language(s) - English
Resource type - Journals
eISSN - 2356-7260
pISSN - 2314-6443
DOI - 10.1155/2013/286426
Subject(s) - anthropometry , athletes , coaching , regression analysis , computer science , test (biology) , work (physics) , statistics , simulation , machine learning , mathematics , physical therapy , psychology , engineering , medicine , mechanical engineering , paleontology , psychotherapist , biology
The literature indicates that relatively little research is available to describe the relationship between functional running tasks and characteristics of individuals who perform these tasks. As a main purpose, the present work is to define the computational modeling for anthropometric characteristics of athletes. Thus the dynamic model presented by this 100-meter running test can play an important role in talent and coaching. The research question was formed by classification and comparison of statures of sportswomen with other anthropometric classes. On the other hand, the present work compares the anthropometric data for runner velocity (running time) against runner weight. The method of research is regression statistical analysis method. In this work, the regression method is based on the univariable ANOVA variance with repeated measures and t-test for independent samples. Data analysis was performed by using the software SPSS13. The results of the 100-meter running test of sportswomen showed good correlation between the parameters. As a dynamic modeling selection, the logarithmic function showed suitable correlation on scatter diagram. Consequently, the results of this work will help to reduce the risk of sportswomen activities. Therefore it can be recommended for medical professionals and athletic talent

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