• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.103-111
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• 2020

Performance indicators have often investigated and developed in order to identify foundational elements and factors for an enhancement of performance in sports. In order to identify the valid performance indicators it is important that the indicators used within a performance analysis system discriminate between the winning and losing performances within a match (Hughes and Bartlett, 2002). However, the performance indicators proposed in research studies on basketball performance have not been used for real-time analysis and feedback within a coaching context. Such real-time support for the coach and players has been described within research on other sports (Choi et al., 2004; O'Donoghue, 2001; Palmer et al., 1997). Within the process of real-time feedback, the identification of relevant performance indicators that distinguish winning and losing performances should be the first stage of the development of a real-time analysis system. Therefore, this study investigated the differences between winning and losing teams in terms of a set of performance indicators gathered during the analysis of 10 English National Basketball League matches. Winning and losing teams were compared using whole match data (N=10) as well as individual quarters (N=40). A series of Wilcoxon Signed Ranks tests was used to identify the relevant performance indicators that discriminate between winning and losing performers within whole matches and individual quarters. The tests found that 3 point shots made (p<0.05) and Assists (p<0.05) were significantly different between winning and losing teams within matches. However, 2 point shots made (p<0.05), 2 point shots attempted (P<0.05), percentages of 2 point shots scored (p<0.05), 3 point shots made (p<0.05), Defensive Rebounds (p<0.05) and Assists (p<0.05) were significantly different between winning and losing performance within quarters. The analysis task should be based on relevant performance indicators which explain the current performances to performance analysts and coaches. Within a real-time analysis and feedback scenario, this will have the additional benefit of supporting a decision based on immediate performance within the most recent quarter. Consequently, the real-time analysis system would use performance indicators which have the property of construct validity to support the decisions of the coach.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.104-108
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• 2016

African-American music heavily influences a variety of musical genres, including folk music, jazz, rhythm and blues, soul, and funk music. The music derived from traditional African music with its unique syncopated rhythm using a five-note pentatonic scale, and has developed through significant influences from gospel music. African-American music has also evolved through historical social movements, such as eliminating the racial discrimination, and has been influenced by the personalities of different cities in the United States. Modern music features fusion with elements of Western music. One of the most influential and respected artists of the 20th century was Stevie Wonder, who was known as "Father of African-American music." He was an accomplished artist, winning numerous awards despite being disabled. He has become one of the most famous and respected artists worldwide. This study of Stevie Wonder's life, music, and spiritual strength, aims to highlight his significant achievements and contributions to pop music. This is a study based on an analysis of the work of Stevie Wonder and describes how elements of African-American music influences current Korean pop music and musicians.

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.21-29
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• 2024

This study analyzed the difficulty of scoring in different match situations in relation to which competitor scored first. The study analyzed the data from the 2022 Guadalajara World Taekwondo Championships. The analysis was performed for two separate weight classes: lightweight and heavyweight. Four game content variables were used: whether the athlete scored first, attack type, attack area, and game situation. Descriptive statistics, the Rasch model, and discrimination function questions were applied for data processing. SPSS and Winsteps were used for the statistical analysis, and the statistical significance level was set at 0.05. Consequently, in the lightweight class, the scoring frequency of the first scorer was high for all the game variables. In the heavyweight class, the scoring frequency for the first scorer was high for the attack type and attack area. By contrast, those who did not score first were more frequently found to be in a loss situation. By analyzing the scoring difficulties in different match situations based on whether the competitor scored first, the athletes who scored first in attack type most easily scored first. In losing situations, the athletes who scored first in attack area scored most easily, whereas those who did not score first scored most easily in body and match situations. For the heavyweight class, those who scored first in terms of attack type, counter-attack, and attack area scored the most easily while winning in body and match situations.