• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.18-20
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• 2000

에이전트를 다른 소프트웨어와 구별 시켜주는 요인들은 여러 가지가 있지만 그 중에서도 가장 큰 특징은 에이전트의 자율성, 적응성, 그리고 지능을 들 수 있다. 이러한 것을 가능하게 만들기 위해서는 행동 선택을 유발하는 모티브의 생성이 자동적으로 이루어져야 한다. 이러한 행동 선택에 있어서 자동적인 모티브를 제공해 주는 것이 감정이다. 감정은 그것을 가지고 있는 자율 시스템이 그 동안 겪어온 외부 환경과 내부 상태에 대한 글로벌 상태를 함축하고 있다. 그러므로, 접근 가능한 정보와 자원이 제한되어 있는 자율 시스템이 다중의 목표, 환경에서의 모호성과 다른 에이전트와의 조정 등을 하는데 있어서 감정 모델은 유용한 해결책을 제시해 줄 수 있다. 본 논문에서는 에이전트가 환경과 적응하면서 변화하는 에이전트의 내부 상태의 변화와 외부 사건에 대한 에이전트의 인식과 평가를 계속 반영하여 에이전트가 시스템 환경을 경험하면서 가질 수 있는 에이전트만의 시스템에 대한 광범위한 시야를 갖도록 감정 모델을 구축하는 것을 목적으로 한다. 또한 이렇게 생성된 감정 델을 통해서 에이전트에 특정 사건이 발생하였을 때 에이전트가 감정 모델에 기초하여 적절히 행동에 반응할 수 있는 적응적 에이전트 모델을 제시한다.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.82.1-82.1
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• 2003

The protective adaptive response to electrophiles and reactive oxygen species is mediated by enhanced expression of phase II detoxifying genes including glutathione S-transferases. ${\alpha}$-Lipoic acid, which exerts prooxidant or antioxidant activities, has been shown to activate the insulin signaling pathway and thus to induce insulin-like actions via PI3-kinase and Akt. Our previous studies have shown that PI3-kinase plays an essential role in Nrf2-or C/EBP${\beta}$-mediated glutathione S-transferase A2 (GSTA2) induction. (omitted)

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.442-445
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• 2023

최근 딥러닝 및 로봇기술의 발전으로 인해 대량의 데이터를 빠르게 수집하고 처리하는 연구 분야들로 확대되었다. 이와 관련된 한 가지 분야로써 다중 로봇을 이용한 분산학습 연구가 있으며, 이는 단일 에이전트를 이용할 때보다 대량의 데이터를 빠르게 수집 및 처리하는데 용이하다. 본 연구에서는 기존 Distributed Neural Network Optimization (DiNNO) 알고리즘에서 제안한 정적 분산 학습방법과 달리 단계적 분산학습 방법을 새롭게 제안하였으며, 모델 성능을 향상시키기 위해 원시 변수를 근사하는 단계수를 상수로 고정하는 기존의 방식에서 통신회차가 늘어남에 따라 점진적으로 근사 횟수를 높이는 방법을 고안하여 새로운 알고리즘을 제안하였다. 기존 알고리즘과 제안된 알고리즘의 정성 및 정량적 성능 평가를 수행하기 MNIST 분류와 2 차원 평면도 지도화 실험을 수행하였으며, 그 결과 제안된 알고리즘이 기존 DiNNO 알고리즘보다 동일한 통신회차에서 높은 정확도를 보임과 함께 전역 최적점으로 빠르게 수렴하는 것을 입증하였다.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.192-201
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• 2005

For the past ten years, the goal of ubiquitous computing research has been the establishment of a new technology system with the aim 'Anytime, Anywhere, and Any form'. The needs for agent technology innovations such as ontology-based structure, ontology-based agent communication language, and multi-agents frameworks have been identified. This paper proposes a noble multi-agents architecture for ubiquitous systems. We suggest four major steps in the interaction between human and agents which enable ubiquitous agents to process by themselves to provide adaptive service to meet human's needs. First, we propose a semantic web technology to represent the association between information resources more explicitly Second, we construct a semantic ontology so that agents can recognize web contents.'Third, we propose a method to communicate between agents using OWL ontologies. Finally, we suggest a multi-agents structure based on the JADE of FIPA to analyze messages and get information. The semantic multi-agents framework proposed in this paper infers semantic situations using semantic web technology based on ontologies. A service provided is inferred differently according to user state because the multi-agents communicate by using OWL ontology language. Therefore, our system better infers context information than other without ontologies.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.180-191
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• 2005

The rapid growth of mobile communication technology has provided the expansion of mobile internet services, particularly mobile commerce takes much weight among them. Even though current mobile commerce service has serious problems which check its development, such as limited contents, expensive charge system and hardware restriction of mobile device, it is strongly expected as one of the next generation Internet services. In this paper, we summarize the problems like above and provide some total solution to meet them as follows: a function for automatic gathering of product information on online Internet and automatic translation it to data for mobile commerce, a middlelet application which provides functions for product search and order on the mobile device through off-line processing, and a function of user adaptive recommendation. We have actually designed and implemented the proposed system and verified the functions and effectiveness of the system.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.351-368
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• 2005

The manual construction of the knowledge-base takes much time and effort, and it is hard to adjust intelligence systems to dynamic and flexible environment. Thus mental development in those systems has been investigated in recent years. Autonomous mental development is a new paradigm for developing autonomous machines, which are adaptive and flexible to the environment. Learning conversation, a kind of mental development, is an important aspect of conversational agents. In this paper, we propose a learning conversation method for conversational agents which uses several promising techniques; speech-act templates and genetic programming. Knowledge acquisition of conversational agents is implemented by finite state machines and templates, and dynamic sentence generation is implemented by genetic programming Several illustrations and usability tests how the usefulness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.465-470
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• 2012

This paper proposes a distributed autonomous control method of swarm robot behavior strategy based on artificial immune system and an optimization strategy for artificial immune system. The behavior strategies of swarm robot in the system are depend on the task distribution in environment and we have to consider the dynamics of the system environment. In this paper, the behavior strategies divided into dispersion and aggregation. For applying to artificial immune system, an individual of swarm is regarded as a B-cell, each task distribution in environment as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows: When the environmental condition changes, the agent selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other agent using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. In order to decide more accurately select the behavior strategy, the optimized parameter learning procedure that is represented by stimulus function of antigen to antibody in artificial immune system is required. In this paper, particle swarm optimization algorithm is applied to this learning procedure. The proposed method shows more adaptive and robustness results than the existing system at the viewpoint that the swarm robots learning and adaptation degree associated with the changing of tasks.

• Journal of the Economic Geographical Society of Korea
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• v.13 no.3
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• pp.416-441
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• 2010

This paper attempts to develop a framework articulating a suite of indicators of cluster development, based upon existing work on the economic geography of clusters, cluster frameworks and indicators and cluster policies. Unlike other work the framework adopted here emphasizes adaptive and proactive roles played by agents, whether individual or collective, within the cluster when understanding it as a learning environment to capture an implication made from adopting the cluster perspective. Some possible indicators are operationalized and suggested even if they are not definitive and exhaustive. The conceptual framework and the specific indicators suggested can provide policy-makers and key stakeholders in clusters with a proper set of tools for measuring the level of cluster development, maneuvering a broader strategic planning exercise for successful cluster development.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.77-79
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• 2012

MSN 라우팅 프로토콜 설계에서 노드의 이동성 정도를 반영하는 것은 중요한 문제이며 다른 네트워크 인자의 특성들과 통합적으로 고려되어야 한다. 하지만, 기존 라우팅 기법들은 이동성의 고려가 미미하거나 다른 환경 인자들과 통합적인 고려가 되지 않았다. 본 논문에서는 모바일 센서 네트워크(MSN)에서 신뢰성 있고 에너지 효율적인 라우팅 기법을 제안한다. 먼저 동적인 네트워크 환경에서 이동성과 패킷발생율에 따른 에너지 소모 패턴 분석을 하였다. 분석된 결과를 바탕으로 제안 기법은 다양한 환경 인자에 따라 에이전트들이 싱크를 중심으로 자율적으로 구성하고 통신한다. 이러한 에이전트 기반의 라우팅 기법은 신뢰성 있고, 에너지 효율적인 통신을 가능하게 한다. 시뮬레이션 결과 제안 기법은 기존 기법에 비해 노드의 이동성의 변화가 심한 환경에서 에너지 효율적임을 보인다.

• The Korean Journal of Physiology and Pharmacology
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• v.24 no.1
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• pp.47-52
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• 2020

We previously demonstrated that Bordetella bronchiseptica (B. bronchiseptica) antigen (Ag) enhances the Mycoplasma hyopneumoniae Ag-specific immune response. The focus of this study was whether acellular bacterin of B. bronchiseptica could be used as an adjuvant to increase antigen-presenting capability of dendritic cells (DCs) by increasing the level of activation. The metabolic activity of DCs was increased by B. bronchiseptica, similar to lipopolysaccharide (LPS). Flow cytometry analysis revealed that B. bronchiseptica increases the expression of major histocompatibility complex class-2, cluster of differentiation (CD)40, CD54, and CD86 which are closely related to DC-mediated immune responses. B. bronchiseptica enhanced the production of cytokines related to adaptive immune responses. Furthermore, the survival rate of B. bronchiseptica-injected groups was 100% at 15 and 20 mg/kg doses, whereas that of LPS-injected groups was only 20%, 0% at 15 and 20 mg/kg doses respectively, and so B. bronchiseptica is likely to be safer than LPS. Taken together, these results indicate that B. bronchiseptica can be used as an adjuvant to enhance the antigen-presenting capability of DCs. B. bronchiseptica is a candidate for producing vaccines, especially in case of DC-mediating efficacy and safety demands. This study provides researchers and clinicians with valuable information regarding the usage of B. bronchiseptica as a safe bacteria-derived immunostimulating agent for developing efficient vaccines.