• Journal of Korea Game Society
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• v.7 no.1
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• pp.31-42
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• 2007

In the natural world, most materials such as skin, marble and cloth are translucent. Their appearance is smooth and soft compared with metals or mirrors. In this paper, we propose a new GPU based hierarchical rendering technique for translucent materials, based on the dipole diffusion approximation, at interactive rates. Information of incident light, position, normal, and irradiance, on the surfaces are stored into 2D textures by rendering from a primary light view. Huge numbers of pixel photons are clustered into quad-tree image pyramids. Each pixel, we select clusters (sets of photons), and then we approximate multiple subsurface scattering term with the clusters. We also introduce a novel hierarchical screen-space interpolation technique by exploiting spatial coherence with early-z culling on the GPU. We also build image pyramids of the screen using mipmap and pixel shader. Each pixel of the pyramids is stores position, normal and spatial similarity of children pixels. If a pixel's the similarity is high, we render the pixel and interpolate the pixel to multiple pixels. Result images show that our method can interactively render deformable translucent objects by approximating hundreds of thousand photons with only hundreds clusters without any preprocessing. We use an image-space approach for entire process on the GPU, thus our method is less dependent to scene complexity.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.77-87
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• 2011

The advent of new platforms each year along with the advancement of technology provides a new opportunity for digital media designers to develop creative and innovative contents. This phenomenon affect the same way the students that major in the digital media, and the use of the platforms that is based on the new technology in the development of contents gives a newer and useful opportunity for learning to the students who recently study the digital media area. As the main technology of the recent digital media that attract many students' attention, we are presenting virtual reality display, movement cognition, physical engine and the gesture interface, and developed the consolidated platform based on these four technologies, and designed them in a way that can be more easily implemented in a simpler way. In order to study the efficiency of the platform with the objective of the development of digital media contents, we have developed four different prototype contents, and have measured based on the user's preference, efficiency and satisfaction. In the results of usability evaluation, functionality, effectiveness, efficiency, satisfaction were rated as 'high'. This results shows that the suggested 3D platform environment provides students to develop a rapid prototype fast and easy, and this may have a positive influence on students major in the digital media to conduct creative development research.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.197-203
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• 2018

As people's interest in Virtual Reality has recently increased, peripherals have also made many progress. There is a lot of research being done from VR environment to VR configuration through scanning at room level with various interface devices that can interact with objects in the environment. According to current VR research Home VR uses multiple haptic interfaces to interact with objects configured in the VR environment, the method uses room scanning to some extent is beyond the spatial constraints and may use tracking equipment to interact with real objects. And advances in 3D printers have enabled the distribution of commercial 3D printers and home 3D printers, and made it easy for 3D printers to create models of their choice at home or at home. Considering the above two factors, We think it is necessary to study the difference between a model's object that people feel when interacting directly with an easy-to-create model in a VR environment. Therefore, in this paper, we are going to implement objects produced by 3D printers in VR space and study the differences between using real objects and other general interaction equipment through user testing with those that are actually implemented.

• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.49-66
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• 2018

This research explores a value chain structure of VR-AR media including user's perception, uses, and evaluation. The purpose of this research focused on factor analysis and the relationship among user's VR-AR adoption motivations and utilities. This research explores correlation between personal value and using motivation. This study was to identify the value structure of respondent on VR-AR usages based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. This study is based on the analysis of the value chain structure factors that affect VR and AR use behavior (attributes, functional benefits, psychological benefits, use value), 'Hierarchical Value Map' between users' The purpose of the model is to construct a model. For this, 'means-end chain theory' was applied to measure the causal relationship between personal value and VR related use behavior. In order to solve this research problem, 135 people were analyzed through the structured questionnaire using the AR and VR content fitness measure and the second APT laddering, and the use of VR-AR : 1) Functional benefits; 2) Psychological benefits; 3) Means to reach value, 4) Objective value chain structure was identified. The results show that VR users tried to smooth the social life through the new virtual reality audiovisual element, the newness of experience, fun, and pleasure through the departure of reality, vividness of experience, and leading fashion. The AR fitness was a game and a new program, and the value of interacting with other people and the value of 'periwinkle' played an important role through the vividness and peripheral interaction of AR, It was an important choice. The important basic values of users' VR and AR selection were correlated with psychological attributes of interaction with others, achievement, happiness and favorable values.

• Journal of KIISE:Software and Applications
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• v.35 no.3
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• pp.179-188
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• 2008

An important issue in multiagent reinforcement learning is how an agent should team its optimal policy through trial-and-error interactions in a dynamic environment where there exist other agents able to influence its own performance. Most previous works for multiagent reinforcement teaming tend to apply single-agent reinforcement learning techniques without any extensions or are based upon some unrealistic assumptions even though they build and use explicit models of other agents. In this paper, basic concepts that constitute the common foundation of multiagent reinforcement learning techniques are first formulated, and then, based on these concepts, previous works are compared in terms of characteristics and limitations. After that, a policy model of the opponent agent and a new multiagent reinforcement learning method using this model are introduced. Unlike previous works, the proposed multiagent reinforcement learning method utilize a policy model instead of the Q function model of the opponent agent. Moreover, this learning method can improve learning efficiency by using a simpler one than other richer but time-consuming policy models such as Finite State Machines(FSM) and Markov chains. In this paper. the Cat and Mouse game is introduced as an adversarial multiagent environment. And effectiveness of the proposed multiagent reinforcement learning method is analyzed through experiments using this game as testbed.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.561-568
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• 2022

The purpose of this study is to explore the narrative of VR disaster and safety Education introduced by disaster film narrative. VR(Virtual Reality) is be suitable technology for disaster and safety Education due to media characteristics as 'immersion', 'presence', 'interactivity', 'pleasure'. Disaster film narrative is able to be worth VR disaster and safety education as a variety of stories and educational effect. For this study, examine a theoretical study and a visiting research of 'Busan 119 Safety & Experience Center'. This study concludes that Firstly need to introduce catharsis effect, Secondly, build 'interactive narratives' that ensure active participation of users, Thirdly, introduce an 'adventure game' narrative element, Fourthly, introduce a hero-shaped narrative in which the user becomes a one-man hero, And lastly, need education as use user's multiple access and group experience learning. Therefore, This thesis is of academic value in that it suggest a desirable new direction of narrative in VR disaster and safety education.

• Informatization Policy
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• v.25 no.4
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• pp.65-83
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• 2018

This study examined the effects of smartphone usage types and excessive expectation for smartphone on adolescents' smartphone overdependence. It utilized the data of 3,454 adolescents (1,758 males and 1,696 females), aged between 13 and 19 from a smartphone overdependence survey of the National Information Society Agency. As a result of the hierarchical multiple regression analysis, age and household income had a negative effect on smartphone overdependence. Weekly smartphone usage time positively affected the serious consequences (sub-factor of smartphone overdependence). Among the different types of smartphone usage, information seeking, SNS, gaming, and the excessive expectation for smartphones had positive impact on smartphone overdependence. Smartphone usage for leisure seeking did not affect smartphone overdependence, but it negatively influenced serious consequences. Messenger use did not affect smartphone overdependence, but the use had a positive effect on salience, and a negative effect on serious consequences. The results of this study suggest that it is necessary to identify the types of smartphone use as well as the usage time to understand the smartphone dependence of adolescents. In addition, it seems necessary to recognize and correct the irrational excessive expectation for smartphone in order to prevent dependence and implement effective interventions.

• Journal of Fashion Business
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• v.20 no.3
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• pp.43-53
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• 2016

As the quality of life has improved with development of science and technology, desire for better quality of life of disable people has also increased. Currently, prejudiced views of disabled people in South Korea are changing, but sports for all disabled people is not revitalized and social support is also inadequate. In developed countries, administration and systems for sports among people with disabilities are provided at the consumer level, and many companies willingly provide support to disabled athletes. However, in South Korea, low awareness of sports for disabled people is companied by minimal support companies. In order for South Korea to advance, support for the disable sports players is needed, especially sports-wear that fits their body conditions and differences game playing from ordinary sports players. This study specifically focused on the ice sledge hockey players, taking into account the complaints on their jersey and their special conditions through motion analysis while sleds. For the easy use of the hockey, armhole depth and sleeve breadth was reduced and sleeve hem was designed for flexibility of sleeve such that it does not slide down. Also, because only the front of the Jersey is tucked in the pants, the side vent was designed to be deep such that the back hem is prevented from being pulled. Sportswear pattern making for the players with disabilities required to account for distinct body characteristics, as compared to the ordinary players. Thus, studies that develops sports-wear design for those with disabilities contributes to the qualitative development of sports for people with disabilities.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

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 choose 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-output 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 these algorithms 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 space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.