• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.548-551
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• 1997

Performance of force tracking impedance control of robot manipulators is degraded by the uncertainties in the robot and environment dynamic model. The purpose of this paper is to improve the controller robustness by applying neural network. Neural networks are designed to learn the uncertainties in robot and environment model for compensating the uncertainties. The proposed scheme is verified through the simulation of 20DOF robot manipulator.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.126-137
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• 1994

Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Importance of perfomance management is growing as many functions of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to determine the magnitude and direction of parameter adjustment. This paper is the first part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of performance evaluation which utilizes the principle of perturbation analysis of discrete event dynamic systems. The developed algorithm can estimate the network performance under a perturbed protocol parameter setting from observations of the network operations under a nominal parameter setting.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.249-254
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• 2001

Abstract In this paper, we propose a method of cooperative control based on artifical intelligent system in distributed autonomous robotic system. In general, multi-agent behavior algorithm is simple and effective for small number of robots. And multi-robot behavior control is a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. However when the number of robot goes on increasing, this becomes difficult to be realized because multi-robot behavior algorithm provide on multiple constraints and goals in mobile robot navigation problems. As the solution of above problem, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for obstacle avoidance. Here, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for their direction to avoid obstacle. Our focus is on system of cooperative autonomous robots in environment with obstacle. For simulation, we divide experiment into two method. One method is motor schema-based formation control in previous and the other method is proposed by this paper. Simulation results are given in an obstacle environment and in an dynamic environment.

• Journal of KIISE
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• v.43 no.7
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• pp.801-811
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• 2016

Self-adaptive systems (SASs) can change their goals and behaviors to achieve its ultimate goal in a dynamic execution environment. Existing approaches have designed, at the design time, utility functions to evaluate and predict the goal satisfaction, and set policies that are crucial to achieve each goal. The systems can be adapted to various runtime environments by utilizing the pre-defined utility functions and policies. These approaches, however, may or may not guarantee the proper adaptability, because system designers cannot assume and predict all system environment perfectly at the design time. To cope with this problem, this paper proposes a new method of dynamic decision making, which takes the following steps: firstly we design a Dynamic Decision Network (DDN) with environmental data and goal model that reflect system contexts; secondly, the goal satisfaction is evaluated and predicted with the designed DDN and real-time environmental information. We furthermore propose a dynamic reflection method that changes the model by using newly generated data in real-time. The proposed method was actually applied to ROBOCODE, and verified its effectiveness by comparing to conventional static decision making.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.367-372
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• 2001

This paper proposes a hierachically structured navigation algorithm for multiple mobile robots under unknown dynamic environment. The proposed algorithm consists of three basic parts as follows. The first part based on the fuzzy rule generates the turning angle and moving distance of the robot for goal approach without obstacles. In the second part, using both fuzzy and neural network, the angle and distance of the robot to avoid collision with dynamic and static obstacles are obtained. The final adjustment of the weighting factor based on fuzzy rule for moving and avoiding distance of the robots is provided in the third stage. Some simulation results show the effectiveness of the proposed algorithm.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.938-947
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• 2016

A mobile ad hoc network (MANET) is a collection of mobile nodes communicating in an infrastructure-less environment without the aid of a central administrating authority. Such networks entail greater dependency on synergy amongst the nodes to execute fundamental network operations. The scarcity of resources makes it economically logical for nodes to misbehave to preserve their resources which makes secure routing difficult to achieve. To ensure secure routing a mechanism is required to discourage misbehavior and maintain the synergy in the network. The proposed scheme employs a partially distributed dynamic model at each node for enhancing the security of the network. Supplementary information regarding misbehavior in the network is partially distributed among the nodes during route establishment which is used as a cautionary measure to ensure secure routing. The proposed scheme contemplates the real world scenario where a node may exhibit different kinds of misbehavior at different times. Thus, it provides a dynamic decision making procedure to deal with nodes exhibiting varying misbehaviors in accordance to their severity. Simulations conducted to evaluate the performance of the model demonstrate its effectiveness in dealing with misbehaving nodes.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.32-35
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• 2002

In order to characterize the migration of DNAPL in rock fractures, the dynamic macromodified invasion percolation (DMMIP) model, that is able to reflect the viscous force of groundwater in a fracture network, is suggested. DMMIP simulations are verified against the laboratory expenments, which shows a good qualitative and quantitative agreement.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.59-72
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• 2006

The rapid growth of technology for network and terminal devices is able to service multimedia contents in mobile environments. But as the environment of networks and the performance of devices is varied, the same quality service is very difficult to be provided for user in internet and mobile environment. Therefore, multimedia streaming system must provide an adaptive service in considering network and device environment. Video transcoding techniques are the good solution that can provide video streaming service in various network environments adaptively. This paper proposes a dynamic frame-skipping transcoding scheme to provide adaptive streaming service in various network environments. This scheme uses the prediction period for transcoding. A proposed transcoding scheme can reduce time complexity through combination of prediction period and skipping period to control frame-skipping rate in encoder. In simulation results, the performance of proposed scheme is similar to the performance of a traditional dynamic frame-skipping scheme in PSNR value. But the performance of proposed scheme outperforms the performance of traditional scheme in time complexity.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.115.5-115
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• 2001

This paper suggests that the immune algorithm can effectively be used in tuning of a multivariable system. Then artificial immune network always has a new paraller decentralized processing mechanism for various situations, since antibodies communication to each other among different species of antibodies/B-cells through the simulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach ...

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.69-72
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• 2003

This paper presents a traffic control agent that can perform the dynamic resource allocation by controlling traffic flows on a DiffServ network. In addition, this paper presents a router that can support DiffServ on Linux to support selective QoS in IP network environment. To implement a method for selective traffic transmission based on priority on a DiffServ router, this paper changes the queuing discipline in Linux, and presents the traffic control agent so that it can efficiently control routers, efficiently allocates network resources according to service requests, and relocate resources in response to state changes of the network.