• Journal of Korea Game Society
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• v.9 no.1
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• pp.105-114
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• 2009

In the game of Go, the life-and-death problem is a fundamental problem to be definitely overcome when implementing a computer Go program. To solve local Go problems such as life-and-death problems, an important consideration is how to tackle the game tree's huge branching factor and its depth. The basic idea of the experiment conducted in this article is that we modelled the human behavior to get the recognized first moves to kill the surrounded group. In the game of Go, similar life-and-death problems(patterns) often have similar solutions. To categorize similar patterns, we implemented Kohonen Neural Network(KNN) based clustering and found that the experimental result is promising and thus can compete with a pattern matching method, that uses supervised learning with a neural network, for solving life-and-death problems.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.7
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• pp.167-176
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• 2019

Recently, as the types of services that can be enjoyed in mobile telecommunication networks such as social networks and video streaming are increasing, mobile users(MUs) can access mobile contents easily by consuming mobile data. However, under a mobile telecommunication environment, MUs have to pay a high data fee to a network service provider(SP) in order to enjoy contents. The 'data sponsor' technique, introduced as a way to solve this problem, has attracted attention as a breakthrough method for enhancing contents accessibility of MUs. In this paper, we propose an algorithm that determines the optimal discount rate through the Stackelberg game in the data sponsor environment. We also propose an algorithm to design edge caching, which caches highly popular content for MUs on edge server, through many-to-many matching game. Simulation results clearly indicate that the profit for CP's content consumption is improved by about 6~11%, and the profit of CP according to the ratio of edge caching is improved by about 12% than the other existing schemes under data sponsor environment.

• Journal of Korea Game Society
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• v.21 no.1
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• pp.139-148
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• 2021

In a game, the visual environment element is a means of expressing the intention of the developer, and is mediums that enable the player to gain to play experience of interaction. In this paper, the player's reaction to the visual environmental elements of the adventure game was patterned with a collection and analysis process by empirical experiments. The data collected through the experiment were about 10,000, and as a result of the analysis, 24 types of player reaction patterns were found in total. This can be used as a guideline for game space design by matching the properties of visual environment elements and the reactions against players occurring in the game play process to examine the play experience.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.785-793
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• 2009

This paper proposes a signature using dominant singular values for video sequence matching. By considering the input image as matrix A, a partition procedure is first performed to separate the matrix into non-overlapping sub-images of a fixed size. The SVD(Singular Value Decomposition) process decomposes matrix A into a singular value-singular vector factorization. As a result, singular values are obtained for each sub-image, then k dominant singular values which are sufficient to discriminate between different images and are robust to image size variation, are chosen and normalized as the signature for each block in an image frame for matching between the reference video clip and the query one. Experimental results show that the proposed video signature has a better performance than ordinal signature in ROC curve.

• Journal of Korea Game Society
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• v.20 no.2
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• pp.75-90
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• 2020

The purpose of this study is to identify the functional role of music, which is one of the main elements that make up PC games. To this end, theme music by genre of PC game was divided through analysis and then the relationship between variables was analyzed by visually positioning the distance between 'music type', 'structural element of music' and 'image' using multiple correspondence matching analysis. As a result, it was confirmed that there was a difference in location between the types of music by game genre, the structural elements of music, and the characteristics of the image.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.203-210
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• 2016

Korean is free of omission of sentence elements and modifying scope, so managing it on morphological analyzer is better than parser. In this paper, we propose functional expansion methods of the morphological analyzer to ease the burden of parsing. This method is a longest phrase matching method. When the series of several morpheme have one syntax category by processing of Unknown-words, Compound verbs, Compound nouns, Numbers and Symbols, our method combines them into a syntactic unit. And then, it is to treat by giving them a semantic features as syntax unit. The proposed morphological analysis method removes unnecessary morphological ambiguities and deceases results of morphological analysis, so improves accuracy of tagger and parser. By empirical results, we found that our method deceases 73.4% of Parsing tree and 52.4% of parsing time on average.

• Journal of Korea Game Society
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• v.15 no.2
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• pp.95-104
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• 2015

Many games for English vocabulary learning, such as hangman, cross puzzle, matching, etc, have been developed which are of board-type or computer game-type. Most of these computer games are adapting strategy-style game plays so that there is a limit on giving the fun, a nature of games, to learners who do not like games of this style. In this paper, a system for memorizing new English words is proposed which is based on a single-player car racing game targeting youths and adults. In the game, the core of our system, a learner drives a car and obtains game points by colliding with English word texts like game items appearing on the track. The learner keeps on viewing English words being exposed on the track while driving, resulting in memorizing those words according to a learning principle stating viewing is memorization. To our experiment, the effect of memorizing English words by our car racing game is good, and the degree of satisfaction with our system as a English vocabulary learning tool is reasonably high. Also, previous word games are suitable for the memory enforcement of English words but our game can be used for the memorization of new words.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.97-108
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• 2016

Multi-client online games usually employ multi-serve architectures. For group play, if the user response time deviation between the clients in a group is large, the fairness and attractions of the game will be degraded. In this paper, given new clients, we propose a method for assigning the clients to servers to minimize the deviation of client-server distance which plays a major role in the user response time. This method also supports client matching for group play and server load balancing. We formulate the client-server assignment problem as an IP one, and present a GA(Genetic Algorithm)-based algorithm to solve it. We experimented our method under various settings and analyzed its features. To our survey, little research has been previously performed on client-server assignment under consideration of client matching, distance deviation minimization and server load balancing.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.49-56
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• 2014

Console game has high market occupancy in the world game market and has popular favor for many players. Especially, the experience console game in which body movement is used to control the game has made its own market. However, previous experience console games can easily make players to be boring and require additional payments to update the game. In this paper, we present an experience dance game using Kinet, which has high interest and can be continuously updated. Differently from previous console games, the presented game makes the player to see how they are playing and to know what the next action is. Also, the accuracy of the player motion is compared 20 times in each second to get high interests of players. Through these functions, the presented game can achieve high satisfaction rates based on the qualitative evaluation of users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1426-1447
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• 2021

The payoff game between task publishers and users in the mobile crowdsensing environment is a hot topic of research. A optimal payoff selection model based on stochastic evolutionary game is proposed. Firstly, the process of payoff optimization selection is modeled as a task publisher-user stochastic evolutionary game model. Secondly, the low-quality data is identified by the data quality evaluation algorithm, which improves the fitness of perceptual task matching target users, so that task publishers and users can obtain the optimal payoff at the current moment. Finally, by solving the stability strategy and analyzing the stability of the model, the optimal payoff strategy is obtained under different intensity of random interference and different initial state. The simulation results show that, in the aspect of data quality evaluation, compared with BP detection method and SVM detection method, the accuracy of anomaly data detection of the proposed model is improved by 8.1% and 0.5% respectively, and the accuracy of data classification is improved by 59.2% and 32.2% respectively. In the aspect of the optimal payoff strategy selection, it is verified that the proposed model can reasonably select the payoff strategy.