• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.724-733
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• 2017

Conventional methods of automatically recording Go game positions do not properly consider obstacles (hand or object) on a Go board during the Go game. If the Go board is blocked by obstacles, the position of a Go stone may not be correctly recognized, or the sequences of moves may be stored differently from the actual one. In the proposed algorithm, only the complete Go board image without obstacles is stored as a background image and the obstacle is recognized by comparing the background image with the current input image. To eliminate the phenomenon that the shadow is mistaken as obstacles, this paper proposes the new obstacle detection method based on the gradient image instead of the simple differential image. When there is no obstacle on the Go board, the background image is updated. Finally, the successive background images are compared to recognize the position and type of the Go stone. Experimental results show that the proposed algorithm has more than 95% recognition rate in general illumination environment.

• Journal of Korea Game Society
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• v.16 no.5
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• pp.89-98
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• 2016

The purpose of this paper is to analyze corporate image of Korean game companies. The questionnaires such as corporate image, gaming playing period, dispute with parents included The lowest score was 2.75 on Han Game which is servicing web board games. Kakao which is a game platform got the highest score. Result through the tests showed that 5 companies were categorized into 3 groups, lower group(Han Game and NEXON), middle (NCSoft and Netmarble), higher (Kakao). Correlation with gender factor showed that only NEXON is significant. NEXON Score by female is higher than that of male. In addition, longer playing period on NEXON games has negative corporate image. Correlation between conflict with parents and negative corporate image of NEXON is also significant.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.89-94
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• 2010

This paper proposes an educational robot game framework for novice students in k-12 to learn concepts of programming through interesting experiences. It is designed to be able to enjoy robot games without technical knowledge of robotics and programming. For this, in the proposed robot game framework, educational robots based on line-tracer are used and the programming APls that can be used for various educational programming languages are offered. And the proposed robot game framework also offers a game board to create several games with easy operations. Additionally, through experiments, it shows that novice students are able to create different games that have several game solutions for various programming using this robot game framework.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.163-173
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• 2011

In this paper, we propose a new paradigm of augmented reality board game environment and a portable game assistant(PGA) which can help gamers with strategy information. Previous AR board games consist of a private and public space. The public space provides rules of the game and shows the scene of game. And the gamers control game pieces in the public space. The previous games use the RFIDs for recognizing positions of the pieces, and the VR/AR environment for providing the scene of the game. However the RFIDs are expansive, and the VR/AR environment is inconvenient because it uses additional devices: the DataGlove, the digital pen, and the HMD. The proposed system recognizes positions of real pieces using the computer vision technique, and uses a monitor to provide dynamic effects. In the private space, previous systems provide entire screen of game and position of specific pieces, but cannot be controled the pieces by gamers. Therefore, in this system, we provide PGA that helps the user to plan of the strategy individually using universally mobile. The PGA helps to plan the strategy in the individual area, and to play easily in the side of the user's convenience.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.1
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• pp.117-131
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• 2022

The purpose of this study is to develop a board game design activity for environmental education and to investigate how it affects high school students' environmental knowledge, environmental literacy, and creative engineering problem solving propensity. Twenty-five freshman and sophomore students belonging to the environmental club participated in this study. The board game activity was designed as 10 class hours lessons based on the engineering design process. The main data source of this study was pre-post students' conceptual maps of the environmental topics (global warming or ecosystem destruction) to measure the background knowledge on the topic. In addition, the environmental literacy measurement questionnaire and the creative engineering problem solving propensity questionnaire were collected before and after the activity. The result shows that the number of environment-related words described by the students on the post-concept map increased compared to the pre-concept map. In addition, the environmental literacy score and the creative engineering problem-solving propensity score increased significantly after performing the board game design activity. The results show that environmental lessons using board game design activities can help student develop various competencies in a good way. As above, research that combines board games and secondary education must be activated, and a new educational method and systemic support for in-service teachers who want to apply it to science classroom is required.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2294-2300
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• 2013

As smartphones have become widely used, topics of smartphone become a hot research subject in IT technologies. Many applications have been developed for the smartphone and the application market has become more and more increasing. However here are few studies or application developments on Korea's traditional games. In this paper we developed Korea's traditional board game Gonu. People who are young or old can play the game. We expect that many applications which related with Korean culture are developed on the smartphone environment.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.531-539
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• 2011

A board-game is the genre which is the oldest among various game genres. Reflecting the issues, aspects & trend of the era, It contains social & cultural sources. For family activity, socializing & human networking, It is regarded such a good alternative leisure replacing on-line video game causing negative infection. In this research, for city marketing usage, we develop a specifically designed board-game with the source of historical people, must-see sights & local products. Also educational & commercial purposes are seriously considered.

• Journal of Korea Game Society
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• v.10 no.1
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• pp.105-113
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• 2010

It takes quite amount of time to study a board game because there are many game characters and different stages are exist for board games. Also, the opponent is not just a single character that means it is not one on one game, but group vs. group. That is why strategy is needed, and therefore applying optimum learning is a must. If there were equal result that both are considered to be best ones during the course of learning stage, Heuristic which utilizes learning of problem area of Jul-Gonu was used to improve the speed of learning. To compare a normal character to an improved one, a jul-gonu game was created, and then they fought against each other. Improved character considered distance and attacked other one. As a result, improved character's ability was improved on learning speed.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.1
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• pp.83-90
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• 2002

This paper proposed the strategy learning method by means of the fusion of Back-Propagation neural network and Q learning algorithm for two-person, deterministic janggi board game. The learning process is accomplished simply through the playing each other. The system consists of two parts of move generator and search kernel. The one consists of move generator generating the moves on the board, the other consists of back-propagation and Q learning plus $\alpha$$\beta$ search algorithm in an attempt to learn the evaluation function. while temporal difference learns the discrepancy between the adjacent rewards, Q learning acquires the optimal policies even when there is no prior knowledge of effects of its moves on the environment through the learning of the evaluation function for the augmented rewards. Depended on the evaluation function through lots of games through the learning procedure it proved that the percentage won is linearly proportional to the portion of learning in general.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.187-192
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• 2017

Autonomous driving vehicle research demands complex road and lane understanding such as lane departure warning, adaptive cruise control, lane keeping and centering, lane change and turn assist, and driving under complex road conditions. A fast and robust road lane detection subsystem is a basic but important building block for this type of research. In this paper, we propose a method that performs road lane detection from black box input. The proposed system applies Random Sample Consensus to find the best model of road lanes passing through divided regions of the input image under HSV color model. HSV color model is chosen since it explicitly separates chromaticity and luminosity and the narrower hue distribution greatly assists in later segmentation of the frames by limiting color saturation. The implemented method was successful in lane detection on real world on-board testing, exhibiting 86.21% accuracy with 4.3% standard deviation in real time.