• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.31-36
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• 1998

250 winning products from 1985 to 1997 in the Korean market were examined in order to find that what kind of product attributes have been major determinants of commercial success in the market. The major determinants are different with product categories. For example, function has been the most important determinant in electric home appliances, while portability has been the most important in telecommunication products. The results will be a cue to the future direction of new product development.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.653-659
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• 2015

The Pythagorean formula for baseball postulated by James (1982) indicates the winning percentage as a function of runs scored and runs allowed. However sometimes, the Pythagorean formula gives a less accurate estimate of winning percentage. We use the records of team vs team historic win loss records of Korean professional baseball clubs season from 2005 and 2014. Using assumption that the difference between winning percentage and pythagorean expectation are affected by unusual distribution of runs scored and allowed, we suppose that difference depends on mean, standard deviation, and coefficient of variation of runs scored per game and runs allowed per game, respectively. In conclusion, the discrepancy is mainly related to the coefficient of variation and standard deviation for run allowed per game regardless of run scored per game.

• Review of Culture and Economy
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• v.20 no.2
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• pp.149-171
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• 2017

This paper presents empirical findings about the market inefficiency field in the korean horse track. We first use the place betting data instead of the win betting data inevitably depended on by past studies, and discuss the degree of the long shot anomaly and the bettor's risk attitude sequentially in the place betting market. The empirical result of betting simulations using the place winning function in this study reveals persistently higher returns than the expected payoff in korean racetrack betting market. The clear departures from perfect efficiency in horse-racing betting imply that much of the market information is insufficient and less accurate. This market asymmetry aggravates popular speculations exquisitely since people are attracted by the higher odds figures in the racetrack display although those are much uncertain in future. The findings suggest the more objective and credible information of winning possibilities such as the place winning function including the smart information of marginal odds needs to be available to the betting decision of the public, which contributes to reducing the speculative spirit in korean racetrack.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.237-250
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• 2017

A new field of e-sports gains the great popularity in Korea as well as abroad. AOS (aeon of strife) genre games are quickly gaining popularity with gamers from all over the world and the game companies hold game competitions. The e-sports broadcasting teams and webzines use a variety of statistical indicators. In this paper, as an AOS genre game, League of Legends game data is used for statistical analysis using the indicators to predict the outcome. We develop new indicators with the factor analysis to improve existing indicators. Also we consider discriminant function, neural network model, and SVM (support vector machine) for make winning forecasting models. As a result, the new position indicators reflect the nature of the role in the game and winning forecasting models show more than 95 percent accuracy.

• Journal of Korean Society for Quality Management
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• v.28 no.4
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• pp.119-139
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• 2000

In order to examine the determinants of new product success, 217 winning products in Korean market are analyzed with a focus on merchantability. For the purpose of the analysis, dimensions of products are classified into function, aesthetics, economy, safety, usability, reliability, brand image, assurance, distribution channel, advertisement, DFE(desing for the environment). The major dimensions of sinning products were identified for each category of the products. The results this study would be a cue to the future direction of new product development.

• Journal of IKEEE
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• v.23 no.4
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• pp.1187-1194
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• 2019

This paper proposes a CNN architecture as value function network of an artificial intelligence Othello game agent and its learning scheme using reinforcement learning algorithm. We propose an approach to construct the value function network by using CNN to learn the records of professional players' real game and an approach to enhance the network parameter by learning from self-play using reinforcement learning algorithm. The performance of value function network CNN was compared with existing ANN by letting two agents using each network to play games each other. As a result, the winning rate of the CNN agent was 69.7% and 72.1% as black and white, respectively. In addition, as a result of applying the reinforcement learning, the performance of the agent was improved by showing 100% and 78% winning rate, respectively, compared with the network-based agent without the reinforcement learning.

• Journal of Industrial Convergence
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• v.1 no.1
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• pp.115-126
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• 2003

In order to examine the determinants of new product success, winning products are analyzed with a focus on merchantability. The specific dimensions of product advantage have not been studied as yet. As results of the analysis, the determinants are classified into function, aesthetics, economy, safety, usability, reliability, brand image, assurance, distribution channel, advertisement, DEF(design for the environment). This study augmented the data set through questionnaire survey to marketing professor in University. The results of this study would be a cue to the future direction of new product development and to management of exist product.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.2
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• pp.1-16
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• 1996

The personality types developed by Gustav Jung are frequently used to identify peopl's decision-making style, especially to determine which functions are dominant ones in the perception and the processing of information. In this paper, the Jungian typology is utilized to investigate if there are any systematic relations between an individual's personality type and her/his attitude toward risk. For this purpose, an experiment was conducted where 99 subjects, mostly students, participated in a computer-simulated horse racing game. Each subject's risk-seeking propensity was measured by the winning chance of the selected horse and the amount of stakes. The results of the experiment show that a decision-maker who is extrovert (E) is attitude and intutive(N) in perception of information is more likely to be risk prone than the introvert(I) and sensing(S) type. Feeling(F) function in information processing seems to induce more risk seeking attitude than thinking (T) function, but the statistical significance could not be found from the data, for this statement.

• Journal of Korea Game Society
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• v.14 no.3
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• pp.47-54
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• 2014

The game of Go is one of the oldest games and originated at least more than 2,500 years ago. In game programming the most successful approach is to use game tree searches using evaluation functions. However it is really difficult to construct feasible evaluation function in computer Go. Monte-Carlo Tree Search(MCTS) has created strong computer Go programs such as MoGo and CrazyStone which defeated human Go professionals played on the $9{\times}9$ board. MCTS is based on the winning rate estimated by Monte-Carlo simulation. Prior to implementing MCTS into computer Go, we tried to measure each winning rate of three positions, center, corner and side, in Tic-Tac-Toe playing as the best first move. The experimental result revealed that the center is the best, a corner the next and a side the last as the best first move.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.17-24
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• 2019

In this paper, we propose a new model for predicting effective Win/Loss in professional baseball game in Korea using machine learning technique. we used basic baseball data and Sabermetrics data, which are highly correlated with score to predict and we used the deep learning technique to learn based on supervised learning. The Drop-Out algorithm and the ReLu activation function In the trained neural network, the expected odds was calculated using the predictions of the team's expected scores and expected loss. The team with the higher expected rate of victory was predicted as the winning team. In order to verify the effectiveness of the proposed model, we compared the actual percentage of win, pythagorean expectation, and win percentage of the proposed model.