• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.460-469
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• 2006

Recently, a demand of adaptive multimedia service, which supports multimedia service migration according to user's location and characteristics of user device, is increased. In this paper, we propose a service migration system, which becomes aware of user device using intelligent agent. And we design and implement the ontology-based intelligent agent, which is aware of the context in its environment. Moreover, we implement a context reasoning system using location information.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.4
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• pp.3-12
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• 2009

In recent years, the development of ubiquitous computing environment, according to the time, place, regardless of the environment changes dynamically based on providing a service. In particular, ubiquitous computing environment, education support services in the fields of education according to the principal of each member is required to provide personalized information. Therefore, this paper describes the education support system which provide adaptive information to member of education. The structure of the proposed system consists of mobile agents multi-agent system platform, JADE (Java Agent DEvelopment framework) is based. Also, we describes the design of agents for application services and the interaction model. In this paper, the performance of proposed system to verify availability, classroom teachers, students and parents and administrators as a service application based on the user's role to provide appropriate information system was implemented. Finally, we shows the result of user interface GUIs according to adaptive education services.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.91-93
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• 2009

In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.473-474
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• 2010

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.35-50
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• 2000

Diverse requirements of users on web-based model management force a system agent to develop user-adaptive building a model in reality and providing an adequate solution method of the model. The relationship between models is important knowledge for the agent to effectively build a new model to adaptively adjust an existing model under a problem and to efficiently connect the new model into an adequate solution method. Since the generating process of the inter-model relationship is more difficult than the building a new model however the process mostly depends on the knowledge of operation research experts. Without the adequate scheme of the inter-model relationship the burden of the management for the agent increases rapidly and the quality of the services may worsen. This study shows that meta-knowledge generated from relationship between models is important for the user to build a model in reality and to acquire the solver appropriate to the model. The relationship that consists of common and exclusive objects between models can be represented by frames. The system under development to implement the idea includes user-adaptive ability which identifies a model through forward chaining method and searches the solver appropriate to the model by using the meta knowledge. We illustrate the meta knowledge with an applied delivery system in supply chain management.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1062-1072
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• 2006

Recently, new intelligent service frameworks, such as ubiquitous computing are proposed. So, the necessity of adaptive agent system has been increased. In this paper, we propose an intelligent service agent to help that ubiquitous computing system offer user suitable service in ubiquitous computing environment. In order to offer user suitable uT-service, an intelligent service agent mediates the gap between the context information in uT-service system, and user preference is reflected in it. Therefore, we focus on following three components; the first is suitable multi agent framework-agent communication analysis and applicable method of inference engine, the second is uT-ontologies to describe various context information-context information sharing between agents and context information understanding between agents, the third is learning method of user profile to apply in uT-service system. This approach enables us to build adaptive uT-service system to offer suitable service according to user preference.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.94-96
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• 2009

In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8B
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• pp.716-729
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• 2003

As the public Internet and private internet have grown from small networks into large infrastructures, the need to more systematically manage the large number of network components within these networks has grown more important as well. The rapid growth of network size has brought into question the salability of the existing centralized model, such as SNMP(Simple Network Management Protocol) and CMIP(Common Management Information Protocol). Thus, for efficient network management, researches about mobile agent have also been performed recently. This paper presents analytical models of centralized approach based on SNMP protocol, distributed approach based on mobile agent, and mixed mode to make up for shortcomings of SNMP and mobile agent. We compare the performance of these analytical models based on network management response time. Experiment results show that performance of mobile agent and the nixed mode is less sensitive to the delay in WAN network environment. However, SNMP is more efficient for the simple network environment like LAN. We also propose an adaptive network management algorithm in consideration of network t environment. delay, task, and the number of nodes based on the results of analytical models. The results show that the adaptive network management algorithm can reduce the network management response time by 10% compared with either mobile agent or mixed mode network management algorithm.

• Environmental Mutagens and Carcinogens
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• v.21 no.2
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• pp.142-148
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• 2001

We studied adaptive response in CHL cells by benzidine dihydrochloride, a derivative of benzidine, which was a major mutagenic agent in dye industry. Chromosome aberration analysis was used for the identification of adaptive response to this mutagen. Adaptive and reactive doses were confirmed by cell proliferation rate curve. Cell proliferation rate curve was obtained from the mitotic indices of cells treated with various concentrations of benzidine dihydrochloride for 24 hours. Marked adaptive responses to benzidine dihydrochloride in the induction of chromosome aberration were observed in CHL cells by pre-treatment with low concentrations of benzidine dihydrochloride (0.0047 mg/$m\ell$ or 0.0094 mg/$m\ell$) for 24 hours following post-treatment with high concentrations (0.0187, 0.0375, 0.075, 0.15 mg/$m\ell$) for 24 hours. These adaptive responses were found mostly in the type of chromatid breaks and chromatid exchanges. There is no difference in these results between two adaptive doses, 0.0047 mg/$m\ell$ and 0.0094 mg/$m\ell$. The amount of adaptive response, however, was dependent on post-treatment doses.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.263-268
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• 1999

지능형 교육 시스템에서 학습자 모델은 학습자의 반응을 토대로 교수모듈과 전문가 모듈을 연계하여 새로운 학습자 모델을 제시하는 역할을 수행하고 있으며, 이는 성공적인 지능형 교육 시스템의 구현에 있어서 핵심적인 부분이다. 따라서 많은 대학교 및 연구소에서 그동안 학습자 모형에 관한 많은 연구가 이루어져오고 있다. 그러나 대부분의 연구는 단일 학습자 모형을 기반으로 두고 있으며, 이러한 단일 학습자 모형을 이용한 시스템들은 학습자의 지식 또는 학습자의 성향을 정확히 파악하기는 어려움을 갖고 있을 뿐만 아니라 다른 모듈과의 인터페이스 부분에서 중복된 많은 정보를 가지고 있다. 따라서 본 논문에서는 학습자의 지식을 정확하게 진단하고 각 모듈간의 중복된 정보를 보완할 수 있는 다중 학습자 모형을 개발하여 구현하였다. 또한 이러한 다중 학습자 모형을 최적으로 수행할 수 있도록 하기위하여 agent기법을 적용하였다. Agent를 이용한 다중 학습자 모형을 적용하여 구현한 시스템은 첫째, 단계적인 접근 방법으로 보다 정확한 학습자의 지식 진단이 가능하다. 둘째, 학습과정중 학습자의 심리 상태 및 학습자의 선호도 등 파악이 용이하다. 셋째, 교수모듈과 전문가 모듈과의 연계에 있어서 정보의 중복됨의 최소화 등의 장점을 제공한다.