• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4043-4060
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• 2017

Network Intrusion Detection (NID), an important topic in the field of information security, can be viewed as a pattern recognition problem. The existing pattern recognition methods can achieve a good performance when the number of training samples is large enough. However, modern network attacks are diverse and constantly updated, and the training samples have much smaller size. Furthermore, to improve the learning ability of SVM, the research of kernel functions mainly focus on the selection, construction and improvement of kernel functions. Nonetheless, in practice, there are no theories to solve the problem of the construction of kernel functions perfectly. In this paper, we effectively integrate the advantages of the radial basis function kernel and the polynomial kernel on the notion of the game theory and propose a novel kernel SVM algorithm with game theory for NID, called GTNID-SVM. The basic idea is to exploit the game theory in NID to get a SVM classifier with better learning ability and generalization performance. To the best of our knowledge, GTNID-SVM is the first algorithm that studies ensemble kernel function with game theory in NID. We conduct empirical studies on the DARPA dataset, and the results demonstrate that the proposed approach is feasible and more effective.

• Journal of Korean Home Economics Education Association
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• v.6 no.2
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• pp.147-160
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• 1994

The purpose of this study was to review the literatures on designing and developing the CAI program and to develop the middle school students’CAI program for tutorial and instructional game. For these purposes, the learning and instructional theories and the developing phases and strategies for the program were reviewed to design the CAI program. And then the developing unit was selected and the CAI types and the developing direction were set according to the analysis of the CAI programs and related literatures on home economics teaching, The four phases-analysis, design, development, and formative evaluation-were carried out in this study. The results of this study are as following: 1. The CAI porgram was developed on health and food life units. The program contains 12 classes on health and food life in two floppy diskettes. It consisted of total 9,000 lines and 76 frame and takes two hours to study this program. This program could be used in educational computers an could be utilized for unit learing tutorial. It was composed of three parts-unit learning, finding maze, and finding food. In the unit learning part, the learning contents in health and food life units were structured and presented. In finding maze and food part, the basic and the applied problems were presented with game. The characteristics of this program were as followings: (1)This program was able to bring learners’motivation due to the strategies of tutorial and instructional game and they can interestingly learn the program for themselves. (2) The learner could practive the learning contents repeatedly and unit learning while playing the gaming, (3) The learner himself can review and supplement the learning contents without teacher’s help. (4) This program was developed to unit learning on health and food life, on the other hand so far many CAI programs for home economics teaching were developed for studying separate learning units. 2. To effectively utilize this program, the guide book for the student and the teacher was developed. It contained method of using the program, introduction of the program, review of the program, the program objectives, the learning contents, and the keys to progress the program.

• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.927-937
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• 2006

Auto-playing programs are often used in behalf of human players in MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character's level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and the Decision Tree learning is applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPG show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.397-402
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• 2013

The development case presented is about the development of smart education contents for development of creativity, and suggests the development contents and approach to design of software of teaching materials based on G-Learning which allow learner to interact depending on their dispositions. Above all, focusing on design approach in order to maximize interaction which is the characteristic of game, the education contents that enable learner to be immersed by education level as per learner's disposition have been developed, and it allows to compose the level of difficulty based contents according to level design plan. Also, it is the case that the contents allow for effective education by setting visual environment which enables learner to be immersed depending on learner's disposition with the realization of object which appears in respect of vision and visual Customizing of character.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5820-5834
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• 2017

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

• Journal of Korea Game Society
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• v.19 no.3
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• pp.5-14
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• 2019

The gaming server is based on a distributed server. In order to distribute workloads of gaming servers, distributed gaming servers apply some algorithms which divide each of gaming server's workload into balanced workload among the gaming servers and as a result, efficiently manage response time and fusibility of server requested by the clients. In this paper, we propose a load balancing agent using PPO(Proximal Policy Optimization) which is one of the methods from a greedy algorithm and Policy Gradient which is from Reinforcement Learning. The proposed load balancing agent is compared with the previous researches based on the simulation.

• Journal of Korea Multimedia Society
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• v.25 no.5
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• pp.703-720
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• 2022

Based on the love styles theory used in psychology, this paper classifies users(Passionate Love, Game-playing Love, Friendship Love, Practical Love, Possessive Love, Altruistic Love) and investigates satisfaction with the motivation for using TikTok love videos(Entertainment, Social Relationship, Love skills-learning, Self-verification, Problem-solving) according to the theory of use and satisfaction. First, 414 users were selected to conduct TikTok surveys to collect data. Then, through the analysis of the research results, among the six love types, game-playing type and possessive type have a positive (+) impact on entertainment motivation and love skill-learning motivation. Game-playing type also have a positive (+) impact on social relationship motivation and self-verification motivation. In addition, altruistic type and possessive type are also factors to strengthen the motivation of self-verification. The altruistic type, possessive type and practical type will improve the problem-solving motivation. Finally, through hierarchial multiple regression analysis, it is confirmed that game-playing love type, entertainment motivation, love skill-learning motivation and self-verification motivation can improve user satisfaction. The above results enrich the research of user classification as well as providing inspiration for improving the quality and communication efficiency of TikTok's video and enhancing user experience.

• Journal of Korea Game Society
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• v.22 no.1
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• pp.33-42
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• 2022

In online games, interactions with other players may threaten player satisfaction. Therefore, matching players of similar skill levels is important for players' experience. However, with the current evaluation method which is only based on the final result of the game, newbies and returning players are difficult to be matched properly. In this study, we propose a method to improve matchmaking quality. We build machine learning models to predict the MMR of players and derive the basis of the prediction. The error of the best model was 40.4% of the average MMR range, confirming that the proposed method can immediately place players in a league close to their current skill level. In addition, the basis of predictions may help players to accept the result.

• Proceedings of the Korea Society of Design Studies Conference
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• 2003.11a
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• pp.70-71
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• 2003

• Journal of Korea Game Society
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• v.13 no.3
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• pp.141-152
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• 2013

This research aims at suggesting a case of designing theme-based integrated learning for usage smart media. New approach and direction for developing a gaming instructional design was suggested which can encourage learners to participate in. Quest-based learning, the learning environment design where learners conduct various learner-centered activities, plays an important role of reinforcing the motivation, promoting experiential and cooperative learning based on social interaction. The design using QR codes has been proved to be able to offer the learner-centered learning environment which includes social interaction strategy required for learners expanding their cognitive structure, motivation enhancing strategy encouraging their consistent participation in learning, complex problematic situation and scaffolding strategy emphasized by constructivism. And it is expected to contribute to promoting the design of theme-based integrated learning which is being demanded in the educational environment recently by combining systematic design process and strategies.