• Smart Media Journal
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• v.4 no.1
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• pp.52-57
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• 2015

Currently the gamification as marketing technique has appeared in the field non-related with game, applied to game elements. The alternate reality game pulled down the boundary between the real and the virtual has come out. New trend game has shown beyond the range of the existing game. The possibility has import into online baseball simulation game. The objective of this research is the exploratory approach to build GOMS model through three subjects to the famous pro-baseball manager game. After game playing session, three subjects' utterance with game experience was recorded. We built the goal hierarchy of goal in GOMS to pro-baseball manager game to analyze the vocabulary in three subjects' utterance. We try to find the possibility of gamification in alternate reality game interacting between the real and the virtual, and demolishing them.

• Journal of Korea Game Society
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• v.20 no.4
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• pp.67-76
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• 2020

This study analyzes the lobby UI of the baseball manager game based on the mobile platform and proposes an optimized lobby UI. The UI layout-based detailed icons and button interactions in the four game lobbies are compared and analyzed by comparing and analyzing the common points and differences to finally calculate the optimized UI composition. Furthermore, based on the analysis, we intend to propose a lobby UI optimized for user-centered design.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.31-37
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• 2021

In this paper, we propose a method to effectively search by automatically classifying scenes in which specific images such as pitching or swing appear in baseball game images using a CNN(Convolution Neural Network) model. In addition, we propose a video scene search system that links the classification results of specific motions and game records. In order to test the efficiency of the proposed system, an experiment was conducted to classify the Korean professional baseball game videos from 2018 to 2019 by specific scenes. In an experiment to classify pitching scenes in baseball game images, the accuracy was about 90% for each game. And in the video scene search experiment linking the game record by extracting the scoreboard included in the game video, the accuracy was about 80% for each game. It is expected that the results of this study can be used effectively to establish strategies for improving performance by systematically analyzing past game images in Korean professional baseball games.

• Korean Journal of Artificial Intelligence
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• v.7 no.2
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• pp.13-17
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• 2019

Currently, the sports market continues to grow every year, and among them, professional baseball's entry income is larger than the rest of the professional league. In sports, strategies are used differently in different situations, and the analysis is based on data to decide which direction to implement. There is a part that a person misses in an analysis, and there is a possibility of a false analysis by subjective judgment. So, if this data analysis is done through artificial intelligence, the objective analysis is possible, and the strategy can be more rationalized, which helps to win the game. The most popular baseball to be applied to artificial intelligence to analyze athletes' strengths and weaknesses and then efficiently establish strategies to ease the competition. The data applied to the experiment were provided on the KBO official website, and the algorithms for forecasting applied linear regression. The results showed that the accuracy was 87%, and the standard error was ±5. Although the results of the experiment were not enough data, it would be possible to effectively use baseball strategies and predict the results of the game if the amount of data and regular data can be applied in the future.

• Journal of Korea Game Society
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• v.17 no.1
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• pp.109-118
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• 2017

The screen sports game is a motion-based game developed by combining the PC game and the sensor so that the user can directly participate in the game. Following screen golf, which was very popular in the 2000s, screen baseball has been on the rise since 2016. Most of the games released today employ the interface of traditional PC games. However, there is a need for a method that allows the user to manipulate the screen baseball in a more intuitive manner. In this study, we utilize a Kiosk independent of the game, which enables users to intervene naturally without disturbing the flow of the game. Such a Kiosk-based interface results in increased immersion in the game.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.66-72
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• 2018

In recent years, indoor simulated sports have become widely used, and screen baseball system has emerged that can play baseball in indoor space. In this paper, we propose a virtual pitching system that can improve the realism of screen baseball game. This virtual pitching system is characterized in that it uses a transmissive screen in the form of a pitching machine without a pitching hole and installed on the back of the screen. Therefore, unlike existing systems where pitching holes are formed on the screen, it enhances the immersion feeling of displayed images. Also, in this pitching system, the synchronization algorithm between the pitching machine and the virtual pitcher is used to form a sense of unity between the virtual pitcher and the ball according to various types of virtual pitchers, thereby enhancing the reality of baseball games.

• KIISE Transactions on Computing Practices
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• v.21 no.5
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• pp.343-350
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• 2015

While many games have been published that are used with input-devices such as a mouse and keyboard, the number of games that can recognize the behavior of a human utilizing devices such as Kinect and Wii has increased. In this paper, we present the development of a baseball game that utilizes a Leap Motion Controller. A Leap Motion Controller recognizes accurately the movement of a user's fingers. Our implemented game consists of characters, a background and animation. It is a moving animated game in which the users play a game in point of view of a third person. The major feature of our game is that the game players can enjoy the game using a Leap Motion Controller.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.539-549
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• 2008

Most important thing in professional baseball game among all kinds of sports is the winning. Both coaches and players collected and analyzed lots of game data to get a victory. In this paper, batting data are analyzed so as to represent informations of hitting direction visually. This method could be provided a lot of useful information about hitting direction of a specific batter or a team to not only coaches, players but also the audience.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.107-113
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• 2002

In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization. In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization.

• 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.