• Proceedings of the Korea Society for Simulation Conference
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• 2000.04a
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• pp.84-90
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• 2000

인터넷을 발전에 따라 데이터의 전송량이 음성 전송량을 능가하고 있으나 현재의 네트워크로는 빠르고 신뢰성 있는 데이터의 전송을 보장할 수 없다. 데이터와 음성 모두의 빠르고 신뢰성 있는 전송과 관리를 위하여 개발된 패킷 중심 네트워크를 NGN이라 한다. NGN에서는 효율적인 전송과 관리를 위하여 기존(PSTN)의 교환기의 콜 에이전트를 소프트웨어로 구성하여 범용컴퓨터에서 운용될 수 있도록 하였다. 본 논문에서는 콜 에이전트를 소프트웨어로 설계하기 위하여 H/W 개발을 위하여 설계된 기본호처리모델인 BCSM을 객체지향방법론의 표준인 UML을 이용하여 설계를 하였다. 그리고 설계된 모델의 검증을 위하여 LSL(LarchShared Language)를 이용하여 정형명세를 하였다.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.100-103
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• 2004

Experiments and simulation were done to study the impact of contrast agent when CT scan was used to attenuation correction for PET images in PET/CT system. Whole body phantom was imaged with various concentration of iodine-based contrast agent using CT. Mathematical emission and transmission density map with liver were made to simulate for whole body FDG imaging. Various transmission density maps was generated with non-uniform enhancement of contrast agent, hypo-attenuating of contrast agent for tumor, different concentration of contrast agent, and so on. Attenuation correction was done with all transmission maps. In the experiments, we confirmed that attenuation coefficient was changed by concentration of contrast agent. From the simulation data, image quality of attenuation corrected images was affected by contrast agent and artifact was produced by contrast agent. These results indicated that the contrast agent should be used with a full understanding of its potential problem in PET/CT system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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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.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.11-26
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• 2004

Software for analyzing documents on the net to detect specific categories of occurrences is in great demand. In the current world where detecting terrorist threats is critical there is a great need for such systems. One of the critical application areas of such software is the automatic detection of a national infrastructure emergency. In this research an agent-based generic architecture for emergency warning systems is proposed and implemented. This system, called the National Infrastructure Emergency Warning System (NIEWS), is designed to analyze given documents, to detect threats, and to report possible threats with the necessary information to the appropriate users autonomously. In addition, a systematic analysis framework to detect emergencies on the subject of defensive information warfare is designated and implemented through a knowledge base. The developed system along with the knowledge base is implemented and successfully deployed to Strategic Crisis Exercise (SCE) at the United State Army War College (USAWC), saving a good amount of money by replacing human SMEs (subject matter experts) in the SCE.

• Journal of Power Electronics
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• v.15 no.2
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• pp.455-468
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• 2015

A microgrid (MG) with integrated renewable energy resources can benefit both utility companies and customers. As a result, they are attracting a great deal of attention. The control of a MG is very important for the stable operation of a MG. The droop-control method is popular since it avoids circulating currents among the converters without using any critical communication between them. Traditional droop control methods have the drawback of an inherent trade-off between power sharing and voltage and frequency regulation. An adaptive droop control method is proposed, which can operate in both the island mode and the grid-connected mode. It can also ensure smooth switching between these two modes. Furthermore, the voltage and frequency of a MG can be restored by using the proposed droop controller. Meanwhile, the active power can be dispatched appropriately in both operating modes based on the capacity or running cost of the Distributed Generators (DGs). The global information (such as the average voltage and output active power of the MG and so on) required by the proposed droop control method to restore the voltage and frequency deviations can be acquired distributedly based on the Multi Agent System (MAS). Simulation studies in PSCAD demonstrate the effectiveness of the proposed control method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.83-104
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• 2011

Mobile grid is a combination of grid computing and mobile computing to build grid systems in a wireless mobile environment. The development of network technology is assisting in realizing mobile grid. Mobile grid based on established grid infrastructures needs effective resource management and reliable job scheduling because mobile grid utilizes not only static grid resources but also dynamic grid resources with mobility. However, mobile devices are considered as unavailable resources in traditional grids. Mobile resources should be integrated into existing grid sites. Therefore, this paper presents a mobile grid middleware interconnecting existing grid infrastructures with mobile resources and a mobile service agent installed on the mobile resources. This paper also proposes a mobile resource reliability-based job scheduling model in order to overcome the unreliability of wireless mobile devices and guarantee stable and reliable job processing. In the proposed job scheduling model, the mobile service agent calculates the mobile resource reliability of each resource by using diverse reliability metrics and predicts it. The mobile grid middleware allocated jobs to mobile resources by predicted mobile resource reliability. We implemented a simulation model that simplifies various functions of the proposed job scheduling model by using the DEVS (Discrete Event System Specification) which is the formalism for modeling and analyzing a general system. We also conducted diverse experiments for performance evaluation. Experimental results demonstrate that the proposed model can assist in improving the performance of mobile grid in comparison with existing job scheduling models.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1090-1101
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• 2017

This study analyzes spatial density and integration of Space Syntax and Discrete Event Simulation (DEVS) of complex system theory and analyzes spatial structure by property, type and depth. The aim of this study is to secure the validity of the theoretical application. The study evaluated the correlation between spatial density and integration by setting up eight types of analysis models. In addition, analyzed the correlation of structural characteristics and approached the application of discrete event simulation of spatial syntax theory. It is confirmed that the concept of integration of spatial syntax theory and analysis using discrete event simulation are valid as new spatial analysis methodology. Also expect that realistic and concrete predictions will be possible if discrete event simulation evolves into research for space allocation and space efficiency optimization.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.526-532
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• 2014

In this paper, we present and analyze a LQ (Linear Quadratic) inverse optimal state-consensus protocol for continuous-time multi-agent systems with undirected graph topology. By Lyapunov analysis of the state-consensus error dynamics, we show the sufficient conditions on the algebraic connectivity of the graph to guarantee LQ inverse optimality and closed-loop stability. A more relaxed stability condition is also provided in terms of the algebraic connectivity. Finally, a formation control protocol for multiple mobile robots is proposed based on the target LQ inverse optimal consensus protocol, and the simulation results are provided to verify the performance of the proposed LQ inverse formation control method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.984-990
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• 2005

The aim of this paper is to investigate a control framework for mobile robots, operating in shared environment with humans. The Intelligent Space (iSpace) can sense the whole space and evaluate the situations in the space by distributing sensors. The mobile agents serve the inhabitants in the space utilizes the evaluated information by iSpace. The iSpace evaluates the situations in the space and learns the walking behavior of the inhabitants. The human intelligence manifests in the space as a behavior, as a response to the situation in the space. The iSpace learns the behavior and applies to mobile agent motion planning and control. This paper introduces the application of fuzzy-neural network to describe the obstacle avoidance behavior teamed from humans. Simulation results are introduced to demonstrate the efficiency of this method.