• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.231-238
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• 2020

The main purpose of this current study was to identify the structural relationships between the variables of team attachment, location-based service, and future fan behaviors by utilizing Technology Acceptance Model (TAM). Among the 10 KBO franchises, SK Wyverns and KT Wiz were qualified to have their own smart applications programs and the relevant infrastructure at their home venues. Thus, a total of 500 surveys were collected from SK Wyverns and KT Wiz games during September of 2019 and a total of 448 were used for data analysis after deleting 52 surveys due to the missing data. According to the results of a structural equation modeling, 12 positive (+) causality out of 14 hypotheses were confirmed that there must be causal relationships among the variables of location-based service at the smart stadium, TAM, fan attachment, and future fan behavior. It is hoped that this study can be contributing to the foundational developments of marketing strategies by adopting the new technological advancement in the Korean sport industry in the future.

• Journal of Life Science
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• v.20 no.4
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• pp.549-554
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• 2010

Increased external rotation and decreased internal rotation have been noted to occur progressively in the throwing shoulders of baseball pitchers. The purpose of this study was to provide descriptive data for terminal range eccentric antagonist/concentric agonist shoulder muscle strength in collegiate baseball pitchers with humeral head retroversion diagnosed through MRI. The dominant and non-dominant shoulders of 9 asymptomatic baseball pitchers were tested through a range of 20 degrees of external rotation to 90 degrees of internal rotation using the Biodex system 3 isokinetic dynamometer at speeds of $90^{\circ}/s$ and $180^{\circ}/s$. Differences between the dominant and non-dominant shoulders were assessed using the paired samples t-test. Total range of motion, measured at $90^{\circ}$ of glenohumeral abduction, was $180.1^{\circ}$ for dominant shoulders and $183.7^{\circ}$ for non-dominant shoulders. Humeral head retroversion measured $47.6{\pm}6.1^{\circ}$ in dominant and $37.8{\pm}5.3^{\circ}$ in non-dominant extremities. The mean internal rotator concentric contraction (IR-Con) showed a significant difference compared to $31.5{\pm}5.1$ (Nm) in dominant and $38.7{\pm}5.2$ (Nm) in non-dominant shoulders at $180^{\circ}/s$ (p<0.05). The mean external rotator eccentric contraction (ER-Ecc) showed a significant difference compared to $20.3{\pm}4.7$ (Nm) in dominant and $25.1{\pm}3.7$ (Nm) in non-dominant shoulders at $90^{\circ}/s$ (p<0.05). There is a pattern of increased external rotation and decreased internal rotation in the dominant extremity that significantly correlates with an increase in humeral retroversion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.628-634
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• 2016

Many pitchers suffer from various types of injury (distortion, sprain and so on). The rate of injury is increased if there are differences in strength between the extensor and flexor muscles when a joint movement is performed with maximum speed. However, there has been insufficient research into the injury caused by strength differences between the extensor and flexor muscles. Thus, the purpose of the study was to examine the effects of elbow ulnar collateral ligament injury on the maximal isometric strength in young baseball pitchers. The data collection was conducted for 2 weeks. The subjects (n=36) who participated in this study were placed into either the injury group (n = 18, IG) or normal group (n = 18, NG). The maximal isometric strength for the pectoralis major (PM), infraspintus (I), biceps brachii (BB), triceps brachii (TB), flexor carpi radialis (ECR) and extensor carpi radialis (FCR) muscles were determined by an isometric strength machine (K-DFX) and then the differences in strength were calculated by muscle group. All of the data were analyzed by SPSS 18.0 with the independent t-test. In the results, the maximal isometric strengths in the IG for the I (p=0.035), BB (p=0.031) and TB (p=0.041) were significantly lower than those in the NG, while that for the ECR (p=0.047) was significantly greater. In addition, the differences of the maximal isometric strength between the PM and I (p = 0.008), BB and TB (p = 0.002), and FCR and ECR (p = 0.032) in the IG were significantly greater than those in the NG. In conclusion, the differences in muscle strengths of the subjects in the IG were greater than those in the NG, which suggests that they might have a higher injury rate in the future. However, they might be able to recover from their injury and achieve better performance if the differences in strength were reduced by training.

• Korean Journal of Applied Biomechanics
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• v.12 no.2
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• pp.109-130
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• 2002

The purpose of this paper was to make a comparative analysis for the difference of the various kinematic variation which is occurred in the each situation when pitchers throw a straight and a curve ball. Four pitchers, who are two national team players and two high level pitchers, were selected among the right over hand pitchers of D university in the Busan for this paper. The data were analyzed by using 3D equipment. The results of the analysis which was about the elapsed time of the pitching, the movement of the body center-point, the highest height of the left knee, stride length, knee joint angle, shoulder joint angle, elbow joint angle and wrist joint angle in the each section(ST, LKU, HBP, LCF, MCP, BRP) were as follows : 1. Pitching time in the each section and step in the pitching for straight and curve ball was similar. The total elapsed time of the straight and curve ball was 1.78${\pm}$0.07sec and 1.77${\pm}$0.11sec in the order. 2. The position change of the body center to the Z(above below) direction did not show significant difference in the each situation of the section and step between pitching for the straight and curve ball. 3. Height of the left knee did not show significant difference as 125.38${\pm}$11.85cm and 124.95${\pm}$11.63m in the each pitching motion for straight and curve ball. The rate(%H) between height and stride length showed 68.42${\pm}$5.53(%H), 68.40${\pm}$5.45(%H) in the each pitching motion. 4. Pitching for curve ball showed longer stride length than pitching for straight ball that as the stride length was 140.35${\pm}$4.96cm and 144.8${\pm}$1.69cm. The rate(%H) between height and stride length showed 76.9${\pm}$3.77(%H), 79.39${\pm}$2.23(%H) in the each pitching motion. 5. Left knee joint angle did not show significant difference in the ST, LKU and HBP section in the each pitching motion. However, it was shown that knee joint angle was flexed much more in the LFC, MCP and BRP section in the pitching for curve ball. 6. Right shoulder joint angle did not show significant difference in the ST, LKU and HSP section. However, when pitches threw a curve ball in the LKU section. In the LFC section, the right shoulder joint angle was extended much more in the pitching for curve ball, and the angle was extended much in the MCP and BRP section in the pitching for curve ball than straight ball. 7. Right elbow joint angle did not show significant difference in the ST, LKU and HRP section in the two pitching motion. The angle had more flexion in the LFC and MCP section in the pitching for curve ball than the pitching for straight ball. The angle in the each pitching motion for straight ball and curve ball were extended by a narrow margin in the BRP section. 8. Right wrist joint angle was extended much more in the LFC and MCP section in the pitching for curve ball. In the BRP section, the angle was extended much more in the pitching for straight ball than curve ball.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.