• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.71-72
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• 2019

올해 전세계게임 시장 매출 절반 이상을 모바일 게임이 차지했고 계속 성장해 가는 추세이다. 그중 항상 순위권 안에 들어가는 장르로 방치형 RPG 게임이 있다. 그러므로 게임 시장 추세에 맞혀 멀티 플랫폼이 지원되는 유니티 엔진을 이용하여 방치형 RPG 게임을 개발한다. 본 논문에서는 Unity 엔진의 기능을 사용하여 방치형 RPG 게임을 개발하는 법에 관해 설명한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.75-78
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• 2019

본 논문에서는 최근 모바일 RPG 시장의 판도에 영향을 끼치는 매크로(이하 오토 시스템)의 성공 요인과 그 환경적 배경을 연구하여 새로운 게임 경향을 파악하고 그 종류를 크게 3가지로 분류하여 게임의 수익적 관점에서 분석하고자 한다. 또한 그에 따른 유저들의 인식 현황과 플레이 형태를 연구하고 올바른 오토 시스템의 적용 모델과 나아가 바람직한 게임 개발에 대한 방향을 제시한다.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.4
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• pp.111-126
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• 2015

Currently, many enterprises are trying to allocate the investment costs and risks through collaboration, and strengthen their competitiveness by sharing their resources and gains. Intercorporate sharing economy, a type of intercorporate collaboration, refers to the economic activity to share the idle resources of enterprises and enhance their efficiency. For a successful intercorporate economy with the participation of various stakeholders, there is a need to establish the clear allocation method of gains. Accordingly, this study suggested three methods-the MST method that can apply transaction cost incurred when forming a coalition for sharing economy; the average of transaction cost incurred by each participant, and the Shapley Value application method for the transaction cost incurred between the participants. In addition, this study also suggested gain allocation methods such as the "Equal distribution of gain" method, a gain allocation method based on the Cooperative Game Theory, the the "Proportional distribution of gain" method, and the Shapley Value method that takes in consideration the transaction costs.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.15-27
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• 2020

This study starts with the idea that the process of creating a Gantt Chart for schedule planning is similar to Tetris game with only a straight line. In Tetris games, the X axis is M machines and the Y axis is time. It is assumed that all types of orders can be worked without separation in all machines, but if the types of orders are different, setup cost will be incurred without delay. In this study, the game described above was named Gantris and the game environment was implemented. The AI-scheduling table through in-depth reinforcement learning compares the real-time scheduling table with the human-made game schedule. In the comparative study, the learning environment was studied in single order list learning environment and random order list learning environment. The two systems to be compared in this study are four machines (Machine)-two types of system (4M2T) and ten machines-six types of system (10M6T). As a performance indicator of the generated schedule, a weighted sum of setup cost, makespan and idle time in processing 100 orders were scheduled. As a result of the comparative study, in 4M2T system, regardless of the learning environment, the learned system generated schedule plan with better performance index than the experimenter. In the case of 10M6T system, the AI system generated a schedule of better performance indicators than the experimenter in a single learning environment, but showed a bad performance index than the experimenter in random learning environment. However, in comparing the number of job changes, the learning system showed better results than those of the 4M2T and 10M6T, showing excellent scheduling performance.

• Journal of Korea Game Society
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• v.6 no.4
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• pp.55-61
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• 2006

Graphics rendering pipeline (application, geometry, and rasterizer) is the core of real-time graphics which is the most important functionality for computer games. Usually this rendering process is completed by both the CPU and the GPU, and a bottleneck can be located either in the CPU or the GPU. This paper focuses on reducing the bottleneck between the CPU and the GPU. We are proposing a method for improving the performance of parallel processing for real-time graphics rendering by separating the CPU operations (usually performed using a thread) into two parts: pure CPU operations and operations related to the GPU, and let them operate in parallel. This allows for maximizing the parallelism in processing the communication between the CPU and the GPU. Some experiments lead us to confirm that our method proposed in this paper can allow for faster graphics rendering. In addition to our method of using a dedicated thread for GPU related operations, we are also proposing an algorithm for balancing the graphics pipeline using the idle time due to the bottleneck. We have implemented the two methods proposed in this paper in our networked 3D game engine and verified that our methods are effective in real systems.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.31-57
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• 1991

Korean firms of all sizes, from virtually every industry, have used and are using the term "excessive competition" to describe the state of their industry and to call for government interventions. Moreover, the Korean government has frequently responded to such calls in various ways favorable to the firms, such as controlling entry, curbing capacity investments, or allowing collusion. Despite such interventions' impact on the overall efficiency on the Korean economy as well as on the wealth distribution among diverse groups of economic agents, the term "excessive competition", the basis for the interventions, has so far escaped rigorous scrutiny. The objective of this paper is to clarify the notion of "excessive competition" and "over-investment" which usually accompanies "excessive competition", and to examine the circumstances under which they might occur. We first survey the cases where the terms are most widely used and proceed to examine those cases to determine if competition is indeed excessive, and if so, what causes "excessive competition". Our main concern deals with the case in which the firms must make investment decisions that involve large sunk costs while facing uncertain demand. In order to analyze this case, we developed a two period model of capacity precommitment and the ensuing competition. In the first period, oligopolistic firms make capacity investments that are irreversible. Demand is uncertain in period 1 and only the distribution is known. Thus, firms must make investment decisions under uncertainty. In the second period, demand is realized, and the firms compete with quantity under realized demand and capacity constraints. In the above setting, we find that there is "no over-investment," en ante, and there is "no excessive competition," ex post. As measured by the information available in period 1, expected return from investment of a firm is non-negative, overall industry capacity does not exceed the socially optimal level, and competition in the second period yields an outcome that gives each operating firm a non-negative second period profit. Thus, neither "excessive competition" nor "over-investment" is possible. This result will generally hold true if there is no externality and if the industry is not a natural monopoly. We also extend this result by examining a model in which the government is an active participant in the game with a well defined preference. Analysis of this model shows that over-investment arises if the government cannot credibly precommit itself to non-intervention when ex post idle capacity occurs, due to socio-political reasons. Firms invest in capacities that exceed socially optimal levels in this case because they correctly expect that the government will find it optimal for itself to intervene once over-investment and ensuing financial problems for the firms occur. Such planned over-investment and ensuing government intervention are the generic problems under the current system. These problems are expected to be repeated in many industries in years to come, causing a significant loss of welfare in the long run. As a remedy to this problem, we recommend a non-intervention policy by the government which creates and utilizes uncertainty. Based upon an argument which is essentially the same as that of Kreps and Wilson in the context of a chain-store game, we show that maintaining a consistent non-intervention policy will deter a planned over-investment by firms in the long run. We believe that the results obtained in this paper has a direct bearing on the public policies relating to many industries including the petrochemical industry that is currently in the center of heated debates.