• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1794-1806
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• 2023

This study presents a method for capturing photographs of users as input and converting them into 2D character animation sprites using a generative adversarial network-based artificial intelligence network. Traditionally, 2D character animations have been created by manually creating an entire sequence of sprite images, which incurs high development costs. To address this issue, this study proposes a technique that combines motion videos and sample 2D images. In the 2D sprite generation process that uses the proposed technique, a sequence of images is extracted from real-life images captured by the user, and these are combined with character images from within the game. Our research aims to leverage cutting-edge deep learning-based image manipulation techniques, such as the GAN-based motion transfer network (impersonator) and background noise removal (U² -Net), to generate a sequence of animation sprites from a single image. The proposed technique enables the creation of diverse animations and motions just one image. By utilizing these advancements, we focus on enhancing productivity in the game and animation industry through improved efficiency and streamlined production processes. By employing state-of-the-art techniques, our research enables the generation of 2D sprite images with various motions, offering significant potential for boosting productivity and creativity in the industry.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.759-774
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• 2001

This research has the theoretical faces of education with the internet games are based on the Networking and interactive features be caused by network focused on cooperative education, and presentation about educational game model. It includes educational features about various internet games(adventure game, simulation game). Educational game model is a definite model can realize the learning with internet game according to each stages of educational games are based on the networking.

• Journal of Korea Game Society
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• v.19 no.3
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• pp.65-74
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• 2019

This study presented specific alternatives for the use of digital storytelling elements as college education and provided basic data for future Serious games to be more popularized and used as reference materials in various academic circles by considering the criteria for the quality evaluation of game contents, which had been pointed out as limitations of functional games. In particular, the factors to be considered were mainly in developing functional games to learn the clinical reasoning process.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.59-64
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• Journal of Korea Game Society
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• v.1 no.1
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• pp.61-67
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• 2001

This paper describes a program which learns good strategies for two-poison, deterministic, zero-sum board games of perfect information. The program learns by simply playing the game against either a human or computer opponent. The results of the program's teaming of a lot of games are reported. The program consists of search kernel and a move generator module. Only the move generator is modified to reflect the rules of the game to be played. The kernel uses a temporal difference procedure combined with a backpropagation neural network to team good evaluation functions for the game being played. Central to the performance of the program is the search procedure. This is a the capture tree search used in most successful janggi playing programs. It is based on the idea of using search to correct errors in evaluations of positions. This procedure is described, analyzed, tested, and implemented in the game-teaming program. Both the test results and the performance of the program confirm the results of the analysis which indicate that search improves game playing performance for sufficiently accurate evaluation functions.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.39-46
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• 2020

Recently, for designing virtual characters in the battle game field effectively, some methods are very needed to predicate the win rates of the battle of them efficiently. In this paper, we propose a method to solve this problem by combining simulation and machine learning. Firstly, a simulation is used to analyze the win rates of the battle of virtual characters in the battle game. In addition, we apply a regression model based machine learning scheme to predict win rates of the battle of virtual characters according to their abilities. Our experimental results using suggested method show that it is almost no difference between the win rates of the simulation and the prediction results using the machine learning scheme. And also, we can obtain good performance in the experiment using only simple regression based machine learning model.

• Cartoon and Animation Studies
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• s.29
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• pp.129-149
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• 2012

The purpose of this study was to investigate the clustering and Big Five Personality domains in discriminating groups by level of school-related adjustment, as experienced by Social Sims game users. Social Games are based on web that has simple rules to play in fictional time and space background. This paper is to analyze the relationships between social networks and user behaviors through the social games . In general, characteristics of social games are simple, fun and easy to play, popular to the public, and based on personal connections in reality. These features of social games make themselves different from video games with one player or MMORPG with many unspecific players. Especially Social Game show a noticeable characteristic related to social learning. The object of this research is to provide a possibility that game that its social perspective can be strengthened in social game environment and analyze whether it actually influences on problem solving of real life problems, therefore suggesting its direction of alternative play means and positive simulation game. Data was collected by administering 4 questionnaires (the short version of BFI, Satisfaction with life, Career Decision-.Making Self-.Efficacy, Depression) to the participants who were 20 people in Seoul and Daejeon. For the purposes of the data analysis, both Stepwise Discriminant analysis and Cluster analysis was employed. Neuroticism, Openness, Conscientiousness within the Big Five Personality domains were seen to be significant variables when it came to discriminating the groups. These findings indicated that the short version of the BFI may be useful in understanding for game user behaviors When it comes to cultural research, digital game takes up a significant role. We can see that from the fact that game, which has only been considered as a leisure activity or commercial means, is being actively research for its methodological, social role and function. Among digital game's several meanings, one of the most noticeable ones is the research on its critical, social participating function. According to Jame Paul gee, the most important merit of game is 'projected identity'. This means that experiences from various perspectives is possible.[1] In his recent autobiography , he described gamer as an active problem solver. In addition, Gonzalo Francesca also suggested an alternative game developing method through 'game that conveys critical messages by strengthening critical reasons'. [2] They all provided evidences showing game can be a strong academic tool. Not only does a genre called social game exist in the field of media and Social Network Game, but there are also some efforts to positively evaluate its value Through these kinds of researches, we can study how game can give positive influence along with the change in its general perception, which would eventually lead to spreading healthy game culture and enabling fresh life experience. This would better bring out the educative side of the game and become a social communicative tool. The object of this game is to provide a possibility that the social aspect can be strengthened within the game environment and analyze whether it actually influences the problem solving of real life problems. Therefore suggesting it's direction of alternative play means positive game simulation.

• Journal of Korea Game Society
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• v.11 no.4
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• pp.27-35
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• 2011

Concentration is one of the most important factor in learning ability. It is important to improve concentration for learning ability. Most digital kids have been accustomed to addictive media like games since childhood, so traditional methods of teaching and learning has been difficult to give interests for them. Therefore introducing a new teaching methods was inevitable for students with low concentration. This is an experiment to prove the hypothesis that the concentration training by certain serious game would be helpful for improving students' concentration. Not only some serious games but also meditation by music was effective to improve concentration in the experiment. Average people is hard to immerge in meditation. but some serious games involve fun factors like curiosity, challenges, competitions and rewards. Games are not more negative to young people, will be helpful to society in various forms.

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.99-107
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• 2008

Over online education based on wired Internet technologies, due to recent development of various mobile technologies, education based on mobile environment becomes popular. In the meanwhile, the young students are more interested in game-based education that provides more interaction and instant feedback than one-way cramming education. The purpose of this thesis is to develop a new motivation model for mobile environment and apply the model to the elementary school students. The proposed model, based on Keller's motivation model, is designed to increase study effects through motivating students with various game strategies. The proposed motivation model has the following characteristics. First of all, the best game genre can be provided for each study theme in early planning stage. Second, the model can allow students to have more interests in their study activity by providing various edutainment elements. Third, a stage of producing game synopsis and concrete scenario is included in motivation model. The stage enables more complete combination of game and mobile motivation strategies. Finally, the proposed model allows contents developed to be appled in teaching plan without any refinement. That is, the model allows a teaching plan to be extracted from study contents instantly.

• Journal of Korea Game Society
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• v.17 no.2
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• pp.145-154
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• 2017

In the age of low fertility and aging society, youth suicide is not the problem of a certain class but it should be recognized as an urgent and important social problem to be solved by our society. We aim to support the training of youth gatekeeper who can acquire the right attitude and understanding of suicide for adolescents, detect premature suicide signs of peer friends and link them to specialized institutions. In this paper, we propose a scenario based learning program that is linked to the concrete situation that the young people can sympathize with and a serious educational game of visual novel type that encourages participation of youth. We expect that the proposed serious game will improve the accessibility of educational facilities and youths through smart devices.