• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.339-349
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• 2017

In this paper, we present a finite-time sliding mode control (FSMC) with an integral finite-time sliding surface for applying the concept of graph theory to a distributed wheeled mobile robot (WMR) system. The kinematic and dynamic property of the WMR system are considered simultaneously to design a finite-time sliding mode controller. Next, consensus and formation control laws for distributed WMR systems are derived by using the graph theory. The kinematic and dynamic controllers are applied simultaneously to compensate the dynamic effect of the WMR system. Compared to the conventional sliding mode control (SMC), fast convergence is assured and the finite-time performance index is derived using extended Lyapunov function with adaptive law to describe the uncertainty. Numerical simulation results of formation control for WMR systems shows the efficacy of the proposed controller.

• Journal of Information Technology Applications and Management
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• v.21 no.3
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• pp.65-77
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• 2014

Ubiquitous learning has aroused great interest and is becoming a new way for foreign language education in today's society. However, how to increase the learners' initiative and their community cohesion is still an issue that deserves more profound research and studies. Emotional intelligence can help to detect the learner's emotional reactions online, and therefore stimulate his interest and the willingness to participate by adjusting teaching skills and creating fun experiences in learning. This is, actually the new concept of smart education. Based on the previous research, this paper concluded a neural mechanism model for analyzing the learners' emotional characteristics in ubiquitous environment, and discussed the intelligent monitoring and automatic recognition of emotions from the learners' speech signals as well as their behavior data by multi-agent system. Finally, a framework of emotional intelligence system was proposed concerning the smart foreign language education in ubiquitous learning.

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.226-248
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• 2022

The existing model for sentiment analysis of product reviews learned from past data and new data was labeled based on training. But new data was never used by the existing system for making a decision. The proposed Aspect-based multi-agent Deep Reinforcement learning Sentiment Analysis (ADRSA) model learned from its very first data without the help of any training dataset and labeled a sentence with aspect category and sentiment polarity. It keeps on learning from the new data and updates its knowledge for improving its intelligence. The decision of the proposed system changed over time based on the new data. So, the accuracy of the sentiment analysis using deep reinforcement learning was improved over supervised learning and unsupervised learning methods. Hence, the sentiments of premium customers on a particular site can be explored to other customers effectively. A dynamic environment with a strong knowledge base can help the system to remember the sentences and usage State Action Reward State Action (SARSA) algorithm with Bidirectional Encoder Representations from Transformers (BERT) model improved the performance of the proposed system in terms of accuracy when compared to the state of art methods.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.205-210
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• 2022

Drones, which have rapidly grown along with the 4th industrial revolution, spread over industries and also widely used for military purposes. In recent wars in Europe, drones are being evaluated as a game changer on the battlefield, and their importance for military use is being highlighted. The Republic of Korea Army also planned drone-bot systems including various drones suitable for echelons and missions of the military as future defense forces. The keyword of these drone-bot systems is autonomy by artificial intelligence. In addition, common use of operating platforms is required for the rapid development of various types of drones. In this paper, we propose software framework that applies diverse artificial intelligence technologies such as multi-agent system, cognitive architecture and knowledge-based context reasoning for mission autonomy and common use of military drones.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.167-186
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• 1999

인터넷 유통업은 기본적으로 대량 트랜잭션 발생을 목표로 한다. 본 논문에서는 인터넷 유통업의 대표적인 형태인 인터넷 쇼핑몰 운영을 위한 내부 프로세스 에이전트를 정의하고 이들의 참조 구축 프레임웍을 제시하고 있다. 인터넷 쇼핑몰의 후방 프로세스를 분석해 보았으며 이를 토대로 다양한 운영층 프로세스 에이전트 유형과 특성을 정의하였다. 또한, 다수의 에이전트로 구성된 프로세스 에이전트팀 조직과 활동 원칙도 제시하였다. 에이전트의 구현을 위해 멀티쓰레딩 기법을 사용하였다. 단순한 데이터 처리를 담당하는 운영층 프로세스 에이전트에 대한 연구는 향후 보다 복잡한 지능을 가진 전략층 프로세스 에이전트에 대한 연구로 발전할 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1847-1854
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• 2005

This paper proposes a approach to configure efficient video-on-demand system by introducing Multicast and Cache Video-on-Demand (MCVoD) system. As a key element or the MCVoD system, interchange agent provides this system with multicasting and switching functions. With the multicasting, the MCVoD system is able to reduce the load on the network as well as VoD servers by transmitting only one video request instead of sending multiple requests on a same video stream. The switching enables clients to receive the lust stream of requested video streams instantly without waiting time and also allows avoiding undesirable duplication of video streams in the system. With various experiment results through simulation about waiting tine and cache hit ratio, we show that the MCVoD system employing the interchange agent provides better performance than current uni-proxy based system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.213-220
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• 1999

최근 인터넷의 급속한 확산에 따른 전자상거래의 활성화는 조직과 규모 면에서 열세인 중소기업들의 판로 확장 및 홍보를 위한 새로운 대안으로 인식되고 있다. 그러나, 전자상거래 환경은 비약적으로 성장하고 있지만, 여전히 국내 중소기업들은 인력 및 자금의 상대적인 열세로 이러한 환경변화에 효과적으로 대응치못하고 있다. 본 논문은 이러한 문제를 해결하기위한 노력의 일환으로, 인터넷 상의 판매 에이전트를 지원할 수 있는 가상생산 에이전트(Virtual Manufacturing Agent)의 개발에 관한 내용을 담고 있다. 지금까지의 가상생산 시스템(Virtual Manufacturing Systme)에 관한 연구는 주로 설계, 공정, 제어 최적화에 그 초점을 두고 있으며, 가상생산 에이전트에 관한 연구는 이러한 문제를 지능형 에이전트 구조로 해결하고자 하였다. 본 논문에서는 이러한 기존의 연구와 달리 전자상거래 환경하에서 중소제조업체의 판매활동을 돕기 위한 판매에이전트를 실제 생산시스템과 연계하는 관점에서 가상생산 에이전트를 설계, 구현하였다.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.118-120
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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.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.591-593
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• 2000

Mobile Agent System은 최근 각광받기 시작한 새로운 컴퓨팅 기법으로서 서버의 과부하를 줄이고, 네트워크 이벤트의 발생을 줄이면서 필요한 서비스를 사용자에게 지원하기 위한 해결책으로 연구되고 있다. 이동에이전트시스템은 해결해야할 많은 과제들이 있으나 그 중에서 주요한 문제로 인식되고 있는 것이 보안 문제이다. 본 논문은 이동에이전트시스템의 보안 고려사항을 분석하고, 공개키 기반의 암호시스템과 일반향함수를 사용하는 디지털 다중서명 기법을 적용하여 이동에이전트 시스템의 보안구조를 제안한다.

• Journal of Internet Computing and Services
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• v.2 no.4
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• pp.41-53
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• 2001

Multi-distributed web cluster model built for high availability E-Business model exposes internal system nodes on its structural characteristics and has a potential that normal job performance is impossible due to the intentional prevention and attack by an illegal third party. Therefore, the security system which protects the structured system nodes and can correspond to the outflow of information from illegal users and unfair service requirements effectively is needed. Therefore the suggested distributed invasion detection system is the technology which detects the illegal requirement or resource access of system node distributed on open network through organic control between SC-Agents based on the shared memory of SC-Server. Distributed invasion detection system performs the examination of job requirement packet using Detection Agent primarily for detecting illegal invasion, observes the job process through monitoring agent when job is progressed and then judges the invasion through close cooperative works with other system nodes when there is access or demand of resource not permitted.