• Child Studies in Asia-Pacific Contexts
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• v.5 no.2
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• pp.63-81
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• 2015

The present study examined electrical brain activations in participants playing three different video games. Forty-five adolescents between the ages of 13-17 (M=14.3 years, SD=1.5) were randomly assigned to play either a violent game, non-violent game, or brain training game. Electroencephalography (EEG) was recorded during video game play. Following game play, participants completed a questionnaire measuring prosocial personality. Results show an association between prosocial personality factors and differential patterns of brain activation in game groups. Adolescents with higher empathy playing the brain training game were positively correlated with frontal asymmetry scores, while empathy scores for those in non-violent and violent game groups were negatively linked to frontal asymmetric activation scores. Those with higher scores in helpfulness in the non-violent game group showed a positive association to left hemisphere activation. Implications behind these findings are discussed in the manuscript.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.3
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• pp.545-557
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• 1997

This paper deals with dynamic optimal pricing for new products by a firm which maximizes the discounted profit stream of it's own in a duopoly. The problem is constructed as differential games and dynamic optimization theory. Cost is assumed to decline as time goes on. A modified customer's choice model is formulated as a diffusion model and we solve a dynamic optimization problem by adopting the diffusion model. Since this paper focus on deriving real prices not showing a time trend, we formulate recursive form equations of costate variables(shadow price) and a simultaneous equation of price. Hence we derive a dynamic optimal pricing model for using in real market. In particular, we construct a dynamic optimal pricing model in the case that there are benefits from not only new subscribers but also previous subscribers. We analyze instant camera market in U.S.A(1976-1985) by utilizing the above model.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.2
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• pp.110-117
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• 2010

We propose guidance laws based on a pursuit-evasion game. The game solutions are obtained from a pursuit-evasion game solver developed by the authors. We introduce a direct method to solve planar pursuit-evasion games with control variable constraints in which the game solution is sought by iteration of the update and correction steps. The initial value of the game solution is used for guidance of the evader and the pursuer, and then the pursuit-evasion game is solved again at the next time step. In this respect, the proposed guidance laws are similar to the approach of model predictive control. The proposed guidance method is compared to proportional navigation guidance for a pursuit-evasion scenario in which the evader always tries to maximize the capture time. The capture sets of the two guidance methods are demonstrated.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.293-303
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• 2016

Analysis of bargaining games utilizing evolutionary computation in recent years has dealt with important issues in the field of game theory. In this paper, we investigated interaction and coevolution process among heterogeneous artificial agents using evolutionary computation in the bargaining game. We present three kinds of evolving-strategic agents participating in the bargaining games; genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE). The co-evolutionary processes among three kinds of artificial agents which are GA-agent, PSO-agent, and DE-agent are tested to observe which EC-agent shows the best performance in the bargaining game. The simulation results show that a PSO-agent is better than a GA-agent and a DE-agent, and that a GA-agent is better than a DE-agent with respect to co-evolution in bargaining game. In order to understand why a PSO-agent is the best among three kinds of artificial agents in the bargaining game, we observed the strategies of artificial agents after completion of game. The results indicated that the PSO-agent evolves in direction of the strategy to gain as much as possible at the risk of gaining no property upon failure of the transaction, while the GA-agent and the DE-agent evolve in direction of the strategy to accomplish the transaction regardless of the quantity.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.380-385
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• 2018

Recently, interest in baseball has been increasing as the level of international baseball games, the popularity of domestic leagues, and the number of players entering the MLB has increased. In this paper, we propose a pitching system that can be applied to both professional and amateur baseball. The pitching system consists of a control module using MSB764T PLC, a pitching mechanism including AC motors and a ball feed rail, an HMI using the CHA-070WR model, inverter, etc. To pitch the breaking balls, the two AC motors each use an inverter to independently control the speed. The implemented pitching system was experimented on, investigating ball speed and ball movement according to RPM using the BUSHNELL Velocity Speed Gun. Experimental results on ball speed are similar to the theoretical data and the measured data. From the experimental data, it is confirmed that the damping coefficient value for the pitching ball is about 0.98. In the case of the breaking ball, the larger the difference between the speeds on the sides of the ball and the faster the ball speed, the larger the bending degree.

• 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.

• Korean Institute of Interior Design Journal
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• v.25 no.3
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• pp.121-128
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• 2016

Focusing on the cases applied to korean brand-name apartments In 1960s, economical growth and introduction of western-type cultures led to a boom of apartment construction. After internationalization'in 1980s through Olympic games in 1988, korean culture has attracted attention and individual life quality has been improved. Since 1990s, changes in personal life style has affected the housing culture and the construction companies started moving from quantitative supply to developing their own differential characteristics. Differentiation scheme triggered by construction companies since mid-1990s mainly focused on various ideas for space deployment. Space plans include such things as a private ground, a kitchen in the south, etc. while interior plans include to provide selection of the korean traditional style, natural or casual one. 'korean traditional style' apartment is one of such theme of the brand-named apartment. Interests on 'Tradition' can be broken down into a social trend and media trend. Firstly, the former includes the designation of Bukchon as a reserving area, one of the governmental 'Hanok Survival Program', and traditional building promotion scheme on the basis of construction policy plans. Secondly, the latter covers the interests which attract through the media showing oriental cosmetics, korean culture export via Hallyu, popularity of korean dramas, etc. Thus, it seems worth studying on the apartments with traditional factors. And also, this study aims to setup the concept and trends of korean traditional style apartments through the interior expression on the korean-factor space developed by brand-name apartments so that it could correct such false knowledge out of misunderstood concept of traditional space which results from simple decoration or structure type not accompanying Korean emotion or spirit rendered by some misleading media.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.