• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.785-794
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• 2009

We studied on a technic to improve and implement the virtual environment grid information in the war-game model. The virtual environment data are categorized into ground, sea, and air, and separatedly managed and operated. The data are implemented and managed in the geographical information and topography type information. The geographical information, including grid location coordinate and sea level, are managed in computer files as a grid type. We improved the representation of the sea level by mapping the sea level value of the grid information file into GCV and suggested the dynamic virtual environment implementation technic for the region with the large range of tide. In the experiments, we could know that it is possible to adopt the dynamic virtual environment to the war-game model.

• Journal of the military operations research society of Korea
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• v.3 no.1
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• pp.51-82
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• 1977

Decision making is a function of many variables, but among these, human burden (soft-ware) and machine burden (hard-ware) are critical. Decision Maker is rather concerned with the soft-ware and just wants to have machine calculate the quantitative arithmetic involved in the decision-making study, because he is responsible for that decision whether or not he knows details about the techniques used by his staffs. From the point of these considerations, computer-assisted war game model has its significance in military decision making. The major outcome of this model is time-phased FEBA movement. FEBA is moved mainly by the ratio of the Index of Combat Effectiveness (ICE). To calculate ICE, Ground Forces are concerning the Index of Firepower (IFP) of individual weapons and in the case of Air Force, sorties are allocated into each sector, and added to the Ground Force IFP. With the ratio of total ICE, FEBA is moved according to the War Game Tables and process is repeated after consideration of casualties. This model is used by IBM-370/135 in MND computer room and also tested by IBM-3741/3717 established at ROKA HQ.

• International Journal of Contents
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• v.14 no.1
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• pp.12-17
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• 2018

This study explored potential therapeutic mechanisms of playing preferred online games as predictors of therapeutic interventions for players' psychosocial factors (i.e., aggression, depression, and loneliness). Based on theories of catharsis, the generic model of psychotherapy, we took a therapeutic approach to integrate these perspectives. We created a path model describing how therapeutic catharsis-seeking, online game self-efficacy, and life self-efficacy were associated with psychosocial factors of aggression, depression, and loneliness, including generalized sub-constructs of each factor as multi-dimensional sources. We analyzed the path model using data of 1,227 online game players in Korea. Our results indicated that therapeutic catharsis-seeking could alleviate aggression via favorite game playing. Life self-efficacy was a primary predictor for alleviating depression and loneliness. However, online game self-efficacy was positively associated with depression and loneliness. Implications of these findings are discussed.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.145-155
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• 2018

This study aims to extract additional elements to the existing game value evaluation using Delphi technique to 23 game experts. As a result of reviewing the characteristics of the development model using the evaluation model of the existing game contents, it was found that the evaluation factor was selected when selecting the content. The Delphi analysis was conducted two times, the first was the expert FGI and the second was the Delphi questionnaire. More detailed elements were presented in the related items such as results, technology transfer and dissemination, and details for promoting commercialization. Through focus group interviews, we extracted additional factors and predicted market size, growth potential, regulatory and market appeal and risk through market analysis of content success in the game industry. This will allow the industry to understand market size, growth potential, regulation, market appeal and risk through a market analysis of its success targets. This study suggests that the proposed evaluation factors can be applied to the entire game and cultural contents industry and will also help to construct market factors such as market value evaluation of contents, goal and goal setting, selection of entry method, and strategic factors.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.102-103
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• 2018

최근 국내 게임 시장이 12조원을 육박하고 있는 시장 현황에서 게임 매출 부분에서 게임내 어떤 과금정책을 적용할 것인지가 가장 중요한 요소이다. 시중에 출시된 게임 중에서는 P2W 모델이 접하기 쉬운 모델이긴 하지만 최근에는 B2P 모델을 많이 적용하고 있는 과금정책이다. 본 논문에서는 온라인 게임 내 P2W의 과금 모델과 B2P의 과금 모델의 선호도를 조사한다. 그리고 본 논문에서 새롭게 명명한 T2H 모델의 선호도를 조사하여 어떠한 과금 모델이 게임시장에서 더 유리하고 선호도가 높은 모델인지를 제시한다.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.37-44
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• 2017

Games of the AOS genre are classified as an e-sport rather than a recreational computer game. The involved statistical analyses such as game playing patterns and the season's characters gain importance due to the expertise-requiring nature of sports. In this study, the strategic analysis of computer games was conducted by using data mining techniques on League of Legend, a representative AOS game. We designed and tested a winning forecast model using winning percentage prediction techniques such as logistic regression analysis, discriminant analysis, and artificial neural networks. The game data analysis results were represented by a probabilistic graph and used in the visualization tool for game play. Experimental results of the winning forecast model showed a high classification rate of 95% on average with potential for use in establishing various strategies for game play with the visualization tool.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1652-1660
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• 2009

The main objective of this research is to build a behavior prediction model of gameplay for MMO (Massively Multiplayer Online) game using the GOMS analysis method. GOMS analysis is an observational approach to HCI(Human Computer Interaction) to model and predict behaviors of a human operator in a highly interactive task. In this research, a pilot experiment was previously conducted with three skilled gamers. The gamers were provided with the goals and operators through the user's guide book, and they found methods and selection rules while being observed. Based on the results obtained from the pilot study, this research was expanded and the model was further tested with 30 subjects (game experts). The new outcomes revealed that the relevance of GOMS analysis for predicting selection rules is 96.25% according to the degree of abstraction and 77.35% based on the degree of complexity. This research will provide game designers with a new testing mechanism in the early development stages, in order to improve the quality of the game product.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.879-891
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• 2021

With improvements in living conditions, an increasing number of people are choosing to spend their time traveling. Comfortable tour routes are affected by the season, time, and other local factors. In this paper, the influencing factors and principles of scenic spots are analyzed, a model used to find the available routes is built, and a multi-route choice model based on a game theory utilizing a path recommendation weight is developed. A Monte Carlo analysis of a tourist route subjected to fixed access point conditions is applied to account for uncertainties such as the season, start time, end time, stay time, number of scenic spots, destination, and start point. We use the Dijkstra method to obtain multiple path plans and calculate the path evaluation score using the Monte Carlo method. Finally, according to the user preference in the input path, game theory generates path ordering for user choice. The proposed approach achieves a state-of-the-art performance at the pseudo-imperial palace. Compared with other methods, the proposed method can avoid congestion and reduce the time cost.

• Journal of the Korea Computer Industry Society
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• v.2 no.10
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• pp.1309-1316
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• 2001

In the majority of todays animation and computer games, the behaviours of characters are controlled by pre-defined game logic or pre-generated motion. As game developers strive for richer and more interactive games, they often encounter limitations with this approach. This paper attempts to construct a game model using Genetic Algorithms (GAs) in order to produce more intelligent and compelling computer games. Based on learning ability, the use of GAs will enable the characters to continually evolve, providing a changing and dynamic game environment. A real-time game was implemented to investigate the performance and limitations of the system.

• Asia pacific journal of information systems
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• v.11 no.3
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• pp.1-21
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• 2001

In recent years, the market for online computer games has become an important part in the entertainment industry. New online games have been introduced every month and the numbers of game players who are playing online games have grown rapidly. However, only a few online games have been successful in making a good profit among many online games. Why are most players playing only a few online games repeatedly? To answer the question, this research focuses on the customer loyalty and their optimal experience(flow) in playing specific online games. This research hypothesizes that customer loyalty for specific online game can be increased by customers' optimal experience(flow) in playing it, and they would feel optimal experience because of mechanic and social interaction in online games. In order to validate the hypothesis, this research analyzes online survey data of players of various online games. According to this survey results, players' optimal experience is affected by their mechanic interaction between a player and an online game system, and their social interaction with other players who participated in the online game. And their optimal experience during playing the online game affects the degree of customer loyalty to the game. This paper ends with conclusions of the survey results and study limits.