This study aims to identify the most accurate prediction model for the possibility of victory from the annual average data of 25 seasons (1993-2017) of the Ladies Professional Golf Association (LPGA), and to determine the importance of the predicting factors. The four prediction models considered in this study were a decision tree, discriminant analysis, logistic regression, and artificial neural network analysis. The mean difference in the classification accuracy of these models was analyzed using SPSS 22.
View Article and Find Full Text PDFInt J Environ Res Public Health
May 2021
This study reveals the relationship between physical fitness factors and performance in modern pentathlon and identifies the contribution of each physical factor to overall performance. The physical fitness assessment data and the competition records collected by the Korean national team pentathletes for the years 2005 to 2019 were tracked. The correlation between the competition records and fitness factors was confirmed by correlation analysis.
View Article and Find Full Text PDFJ Strength Cond Res
August 2018
Chae, JS, Park, J, and So, W-Y. Ranking prediction model using the competition record of ladies professional golf association players. J Strength Cond Res 32(8): 2363-2374, 2018-The purpose of this study was to suggest a ranking prediction model using the competition record of the Ladies Professional Golf Association (LPGA) players.
View Article and Find Full Text PDFIn this paper, the development of compact transmission soft x-ray microscopy (XM) with sub-50 nm spatial resolution for biomedical applications is described. The compact transmission soft x-ray microscope operates at lambda = 2.88 nm (430 eV) and is based on a tabletop regenerative x-ray source in combination with a tandem ellipsoidal condenser mirror for sample illumination, an objective micro zone plate and a thinned back-illuminated charge coupled device to record an x-ray image.
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