• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.243-246
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• 1998

A predictive controller is designed based upon stochastic methods for compensation of network time delay which caused by the spatial separation between controllers and actuators. Current commands are generated by using time varying probability functions which can be defined according to the values of previous control inputs and actual outputs. To demonstrate the effect of this control methodology, simulation experiments are performed. The results show that even an unstabilized system by a long time delay can be stabilized with this predictive controller.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.144-148
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• 1989

We solve the inverse kinematics problems in robotics by employing a neural network. In the practical situation. it is not easy to obtain the exact inverse kinematics solution, since there are many unforeseen errors such as the shift of a robot base the link's bending, et c. Hence difficulties follow in the trajectory planning. With the neural network, it is possible to train the robot motion so that the robot follows the desired trajectory without errors even under the situation where the unexpected errors are involved. In this work, Back-Propagation rule is used as a learning method.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.303-310
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• 2006

The sorting algorithms have been developed to take advantage of distributed computers. But the speedup of parallel sorting algorithms decrease rapidly with increased number of processors due to parallel processing overhead such as context switching time and inter-processor communication cost. In this paper, we propose a parallel sorting method which provides linear speedup of an optimal serial algorithm for a system with a large number of processors. This algorithm may even provide superlinear speedup for a practical system. The algorithm takes advantage of an interconnection network properties and its protocol.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.659-662
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• 2007

알고리즘의 설계에 있어서 주어진 연결망을 다른 연결망으로 임베딩하는 것은 알고리즘을 활용하는 중용한 방법중의 하나이다. 본 논문에서는 하이퍼큐브보다 망비용이 개선된 이븐 연결망과 오드 연결망 사이의 임베딩을 분석하고, 이븐 연결망이 이분할 연결망임을 보인다. 이븐 연결망을 오드 연결망에 연장율 2, 밀집율 1에 임베딩 가능함을 보이고, 오드 연결망을 이븐 연결망에 연장율 2, 밀집율 1에 임베딩 가능함을 보인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.667-670
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• 2007

알고리즘의 설계에 있어서 주어진 연결망을 다른 연결망으로 임베딩하는 것은 알고리즘을 활용하는 중용한 방법중의 하나이다. 본 논문에서는 하이퍼큐브보다 망비용이 개선된 이븐 연결망과 오드 연결망 사이의 임베딩을 분석하고, 이븐 연결망이 이분할 연결망임을 보인다. 이븐 연결망을 오드 연결망에 연장율 2, 밀집율 1에 임베딩 가능함을 보이고, 오드 연결망을 이븐 연결망에 연장율 2, 밀집율 1에 임베딩 가능함을 보인다.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.5-23
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• 2007

According to the system dynamics model of this study, if there is a significant network effect on vehicle operating costs, it is difficult to achieve the shift to AFV even in the long term without a policy intervention because the car market is locked in to the current structure. Network effect can be caused by an increasing return to scale in fuel supply sector as well as in maintenance service sector. It is also related to the fact that the reliability and awareness of consumers on new products increases with the growth of the market share of the new products. There are several possible policy options to break the 'locked in' structure of car market, such as subsidy on vehicle price (capital cost), subsidy on fuel (operating cost) and niche management policy. Combined policy options would be more effective than relying on a single policy option to increase the market share of AFV.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.103-111
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• 2004

In this survey paper, we attempt to introduce the subjects of fuzzy logic and neural network technology for flight control systems based on completed and ongoing research programs other developed countries. Also, it is prepared with intention of providing the reader with an overview of related topics and a basic concepts of fuzzy logic and neural network control. The focus is on relatively practical control schemes realistically applicable in the area of flight control system design that could find its usage in the near future in our country. It is hoped that this paper will serve as a useful reference and even concepts provide solutions far current problems and future designs.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.111-114
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• 1996

This paper proposes a robust control method using Universal Learning Network(U.L.N.) and second order derivatives of U.L.N.. Robust control considered here is defined as follows. Even if external input (equal to reference input in this paper) to the system at control stage changes awfully from that at learning stage, the system can be controlled so as to maintain a good performance. In order to realize such a robust control, a new term concerning the perturbation is added to a usual criterion function. And parameter variables are adjusted so as to minimize the above mentioned criterion function using the second order derivative of the criterion function with respect to the parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2101-2105
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• 2003

Recently the number of Internet users has very sharply increased, and the number of intrusions has also increased very much. Consequently, security products are being developed and adapted to prevent systems and networks from being hacked and intruded. Even if security products are adapted, however, hackers can still attack a system and get a special authorization because the security products cannot prevent a system and network from every instance of hacking and intrusion. Therefore, the researchers have focused on an active hacking prevention method, and they have tried to develop a traceback system that can find the real location of an attacker. At present, however, because of the characteristics of Internet - diversity, anonymity - the real-time traceback is very difficult. To over-come this problem the Network-based Real-Time Connection Traceback System (NRCTS) was proposed. But there is a security problem that the victim system can be hacked during the traceback. So, in this paper, we propose modified NRCTS with connection redirection technique. We call this traceback system as Connection Redirected Network-based Real-Time Connection Traceback System (CR-NRCTS).

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.432-435
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• 1990

Neural networks are a class of systems that have many simple processors (neurons) which are highly interconnected. The function of each neuron is simple, and the behavior is determined predominately by the set of interconnections. Thus, a neural network is a special form of parallel computer. Although major impetus for using neural networks is that they may be able to "learn" the solution to the problem that they are to solve, we argue that another, perhaps even stronger, impetus is that they provide a framework for designing massively parallel machines. The highly interconnected architecture of switching networks suggests similarities to neural networks. Here, we present switching applications in which neural networks can solve the problems efficiently. We also show that a computational advantage can be gained by using nonuniform time delays in the network.