• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.59-64
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• 2001

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 chose 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 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 it 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 effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• 한국지능시스템학회논문지
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• 제26권1호
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• pp.64-69
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• 2016

본 논문에서는 휴머노이드 로봇의 마라톤 경기를 소개하고, 전략을 제시하고자 한다. 인간을 모방하는 휴머노이드 로봇이 인간에게 협조할 수 있는 능력을 가지기 위해서는 운용시간, 안전성 및 주변 환경인식 기술들이 요구된다. 이에 대한 적합한 연구 모델로 인간의 마라톤 경기를 꼽을 수 있다. 본 논문에서는 인간의 마라톤 경기를 이해하고 그와 유사한 휴머노이드 로봇의 마라톤 경기에 대해 연구한다. 휴머노이드 로봇 관련 대회 중 HuroCup의 마라톤 경기는 인간의 마라톤과 가장 유사한 경기이다. 충분한 운용시간을 갖도록 설계 및 개발한 휴머노이드 로봇으로 마라톤 경기를 수행하고자 한다. 컴퓨터 비전을 통해 마라톤 트랙을 인식하여 보행하기 위한 전략을 세우고 휴머노이드 로봇에 적용한다. 실험 결과를 분석하여 휴머노이드 로봇의 마라톤 경기가 가능하도록 적용한 실제 경기 사례를 소개하고자 한다.

• 전자공학회논문지CI
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• 제37권5호
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• pp.54-63
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• 2000

본 논문에서는 음성인식, 음성합성, Motion Tracking, 3D Animation이 가능한 가상캐릭터를 구현하였다. 음성인식으로는 K-means 128 Level VQ와 MFCC의 특징패턴을 바탕으로 Discrete-HMM 알고리즘을 이용하였다. 음성합성에는 반음절 단위의 TD-PSOLA를 이용하였으며, Motion Tracking에서는 계산량을 줄이기 위해 Fast Optical Flow Like Method를 제안하고, 3D Animation 시스템은 Vertex Interpolation방법으로 Animation을 하고 Direct3D를 이용하여 Rendering을 하였다. 최종적으로 위에 나열된 시스템들을 통합하여 사용자를 계속적으로 주시하면서 사용자와 함께 구구단 게임을 할 수 있는 가상캐릭터를 구현하였다.

• 한국전자통신학회논문지
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• 제12권5호
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• pp.977-982
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• 2017

최근에 ICT(information communication technology)의 발달과 더불어 스포츠를 ICT와 융합하고자 하는 노력이 지속되고 있다. 이러한 대표적인 것이 게임을 들 수 있다. 또한 스크린 골프, 스크린 볼링과 같은 스포츠와 디지털을 혼합한 형태의 디지털 스포츠가 발달하고 있다. 일반 스포츠에도 중독 문제가 있듯이 디지털 스포츠에도 중독 문제가 존재한다. 본 논문에서는 디지털 스포츠에서의 중독 모델을 분수차수(fractional-order)로 제시하고 이 모델로부터 비선형 거동을 시계열과 위상 공간으로 나타내고, 이들 사이의 차이점을 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.570-595
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• 2017

Robust and perceptually-adaptive image watermarking algorithms have mainly targeted gray-scale images either at the modeling or embedding levels despite the widespread availability of color images. Only few of the existing algorithms are specifically designed for color images where color correlation and perception are constructively exploited. In this paper, a new perceptual and high-capacity color image watermarking solution is proposed based on the extension of Tsui et al. algorithm. The $CIEL^*a^*b^*$ space and the spatio-chromatic Fourier transform (SCFT) are combined along with a perceptual model to hide watermarks in color images where the embedding process reconciles between the conflicting requirements of digital watermarking. The perceptual model, based on an emerging color image model, exploits the non-uniform just-noticeable color difference (NUJNCD) thresholds of the $CIEL^*a^*b^*$ space. Also, spread-spectrum techniques and semi-random low-density parity check codes (SR-LDPC) are used to boost the watermark robustness and capacity. Unlike, existing color-based models, the data hiding capacity of our scheme relies on a game-theoretic model where upper bounds for watermark embedding are derived. Finally, the proposed watermarking solution outperforms existing color-based watermarking schemes in terms of robustness to standard image/color attacks, hiding capacity and imperceptibility.

• Nuclear Engineering and Technology
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• 제49권3호
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• pp.517-524
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• 2017

Cyber security is an important issue in the field of nuclear engineering because nuclear facilities use digital equipment and digital systems that can lead to serious hazards in the event of an accident. Regulatory agencies worldwide have announced guidelines for cyber security related to nuclear issues, including U.S. NRC Regulatory Guide 5.71. It is important to evaluate cyber security risk in accordance with these regulatory guides. In this study, we propose a cyber security risk evaluation model for nuclear instrumentation and control systems using a Bayesian network and event trees. As it is difficult to perform penetration tests on the systems, the evaluation model can inform research on cyber threats to cyber security systems for nuclear facilities through the use of prior and posterior information and backpropagation calculations. Furthermore, we suggest a methodology for the application of analytical results from the Bayesian network model to an event tree model, which is a probabilistic safety assessment method. The proposed method will provide insight into safety and cyber security risks.

• 한국멀티미디어학회논문지
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• 제10권10호
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• pp.1310-1318
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• 2007

최근 매스컴이나 공영방송에서 예쁜 여자, 멋있는 남자들만이 대우를 받는다는 것이 사회 문제로 대두되어 TV프로의 주제로 다루어진 적이 있습니다. 분명 이러한 편향된 사고방식이 올바르지는 않지만 상대적으로 현대 사회를 살아가는 많은 사람들이 외적 이미지 즉, 1차 적인 시각적 이미지와 효과를 중시하고 있다는 것을 알 수 있습니다. 컴퓨터 영상 게임 역시 유행과 소비자 기호가 빠르게 변화하고 있으며 캐릭터 디자인 역시 빠른 변화를 거듭하고 있습니다. 이러한 급변하는 환경 속에서 디자이너가 창조적이고 효율적인 게임 캐릭터 디자인 개발을 하기 위해서는 이를 뒷받침해줄 수 있는 새로운 프로세스의 개발이 필요합니다. 또한 유저(User)에게 최초의 구매 욕구를 자극하는 첫 번째 수단은 바로 영상 그래픽디자인의 질입니다. 바로 강력한 시각적 효과로써 그래픽의 화면이 더욱 부드럽게, 보다 더 화려한 리얼리티의 실현을 유저(User)들은 바라고 있으며 또한 컴퓨터게임 그래픽 역시 이러한 방향으로 발전해 가고 있습니다. 본 연구에서는 이러한 과정을 3d와 2d의 게임그래픽을 적절히 배합하고 효율적으로 사용하여 디자이너가 3D 캐릭터를 개발하는데 있어서 능력의 한계를 극복하고 최대의 효과를 낼 수 있도록 하는데 그 목적을 두었습니다.

• 산업경영시스템학회지
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• 제39권3호
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• pp.192-203
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• 2016

Uganda is a country blessed with the biggest number of mountain Gorillas in the whole world. These animals contribute at least 12% in revenue generation to the Tourism sector through tracking by both local and foreign tourists who pay for the tracking permits. However, Gorilla tracking is also a big challenge even in the presence of highly skilled and well-trained game rangers. Development and implementation of a secure Computer and Mobile based Gorilla Tracking (GT) system that uses GIS and GPS technologies would be the most ideal technology to use. Therefore, this study aimed to find out the critical factors that would affect the Behavioral Intention of the would-be users to successfully decide to use such GIS/GPS-GT system. We used the existing UTAUT model to integrate six factors such as Performance Expectancy, Effort Expectancy, Employee Peer Influence, Facilitating Conditions, Behavioral Intention and System Use. However, Infrastructure Availability and Non-Technical Facilitating Conditions were added to reflect Ugandan ICT context. This amended UTAUT model was used to carry out the survey. The questionnaire was emailed to 220 government employees in the fields of ICT, Tour and Travel, Environmental Groups officials and Farmers who garden near the game reserves. A total of 133 were obtained fully completed, whereas 127 were deemed usable thus yielding a response rate of 58%. The analysis results show that except for non-technical facilitating conditions, effort expectancy, peer influence, performance expectancy and infrastructure availability positively affects behavioral Intention to use GIS/GPS-GT. This indicates that people in Uganda don't bother about regulations and rules in regard to using information system. As long as the system does what they want it to, anything else does not matter. As an employee in an organization is told to use a system by their supervisor, they have no objection to otherwise they risk losing their job. This implies that, supervisors have a great responsibility in the process of developing, implementing and using the system in Uganda.

• 동력기계공학회지
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• 제13권2호
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• pp.71-82
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• 2009

This paper presents a real-time haptic rendering method for a realistic force feedback in a remote environment with varying communication time-delay. The remote environment is assumed as a virtual environment based on a computer graphics, for example, on-line shopping mall, internet game and cyber-education. The properties of a virtual object such as stiffness and viscosity are assumed to be unknown because they are changed according to the contact position and/or a penetrated depth into the object. The DARMAX model based output estimator is proposed to trace the correct impedance of the virtual object in real-time. The output estimator is developed on the input-output relationship. It can trace the varying impedance in real-time by virtue of P-matrix resetting algorithm. And the estimator can trace the correct impedance by using a white noise that prevents the biased input-output information. Realistic output forces are generated in real-time, by using the inputs and the estimated impedance, even though the communication time delay and the impedance of the virtual object are unknown and changed. The generated forces trace the analytical forces computed from the virtual model of the remote environment. Performance is demonstrated by experiments with a 1-dof haptic device and a spring-damper-based virtual model.

• 한국멀티미디어학회논문지
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• 제21권7호
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• pp.779-786
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• 2018

In this paper, we are applied a nerve network to allow for the reflection of data learning methods in their overall forms by using cluster data rather than data learning by the stages and then selected a nerve network model and analyzed its variables through learning by the cluster. The CkLR algorithm was proposed to analyze the reaction variables of clustering outcomes through an approach to the initialization of K-means clustering and build a model to assess the prediction rate of clustering and the accuracy rate of prediction in case of new data inputs. The performance evaluation results show that the accuracy rate of test data by the class was over 92%, which was the mean accuracy rate of the entire test data, thus confirming the advantages of a specialized structure found in the proposed learning nerve network by the class.