• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.419-426
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• 1999

A novel motion analysis system is presented in this paper. The proposed system is inspired by processing functions observed in the fly visual system, which detects changes in input light intensities, determines motion on both the local and the wide-field levels. The system has several differences from conventional motion analysis system. First, conventional systems usually focused on matching similar feature or optical flow, but neural network is applied in this system. Back propagation is used by learning method, and Tine Delay Neural Network (TDNN) is also used as analysis method. Second, while conventional systems usually limited on only two frames of sequence, the proposed system accept multiple frames of sequence. The experimental results showed a 94.7% correct rate with a speed of 71.47 milli seconds for real and synthetic images.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.165-166
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• 2006

Recently, after Wide Area Outage of the North-Eastern United States occurred, many countries started to be concerned about WAMS (Wide Area Monitoring System), and Korean power system also experienced Wide Area outage according to typhoon Mae-Mi, and Haenam-Jeju HVDC line fault. Since it is too difficult to detect a symptom based on SCADA or EMS, a defense system of electric power infrastructure has required. In this research, the designed and developed system processes the time synchronized real time power system information based on GPS and shows the 2D/3D monitoring viewer using the phasor data and the results of three algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.898-906
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• 1999

A control structure is introduced for the purpose of rejecting periodic (or repetitive) disturbances on a tracking system. The objective of the proposed structure is to drive the output of the system to the reference input that will result in perfect following without any changing the inner configuration of the system. The structure includes an adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances, on the output of the system to be reduced. Since the control structure acquires the dynamics of the disturbance by on-line adaptation, it is possible to generate control signals that reject any slowly varying time-periodic disturbance provided that its amplitude is bounded. The artificial neural network is adopted as the adaptation block. The adaptation is done at an on-line process. For this , the real-time recurrent learning (RTRL) algoritnm is applied to the training of the artificial neural network.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.241-249
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• 2001

The objective of this paper is to develop the optimal path algorithm for dynamic route guidance system in advanced traveler information system (ATIS). The travel time is forecasted in each path between network nodes. Floyd-Warshall algorithm is used to find the optimal route based on this forecasted travel time in dynamic traffic network. This algorithm is modified to apply the real traffic network that has left-turn restriction, U-turn, and P-turn. A big value is assigned to one of arcs in turn restriction and a virtual node is used to consider U-turn and P-turn for Floyd-Warshall algorithm.

• Journal of the military operations research society of Korea
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• v.24 no.1
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• pp.18-40
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• 1998

This paper is aimed to design an intelligent military decision aiding system in a network computing environment, especially focusing on designing an intelligent analytic system that has data mining tools and inference engine. Through this study, we concluded that the intelligent analytic system can aid military decision making processes. Highlights of the proposed system are as follows : 1) Decision making time can be reduced by the On-line and Real-time analysis ; 2) Intelligent analysis on military decision problems in network computing environments in enabled; 3) The WWW-based implementation models, which provide a standard user interface with seamless information sharing and integration capability and knowledge repository.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.168-171
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• 2002

A neural network model for predicting the quality or soundness of the injected plastic aspherical lens based on process parameters has been developed. The approach uses a Real Time Recurrent Neural Network 4-5-2 (RTRN) trained based on input/output data that were taken from FE analysis worts carried out through a CAE software. The system has been developed to search an optimum set of process parameters and reduce the time required for planning the conditions of plastic injection molding at the design stage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.334-343
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• 2008

In this work we propose a universal pricing machine, which incorporates a universal pricing framework for the future IEEE802.16 WiMAX service with multiple classes of service. A multimedia service is provided by a QoS provisioning scheme in the WiMAX network and universal pricing means that it can compute the price for any type of service in a unified framework. In the proposed pricing framework we incorporate multiple types of services such as the real time and nonreal time services that are supposed to be provided in the WiMAX network. To that purpose, let us first carry out an analysis on the current pricing scheme of Korean WiMAX service which incorporates only the data size. From that analysis we propose a new pricing scheme for the future WiMAX service that provides different service classes in the network. Via numerical experiment, we verify the implication of the work.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.914-921
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• 1992

In this paper, we introduce a Walsh network and an LMS algorithm, and show how these can be realized as an adaptive equalizer. The Walsh network is built from a set of Walsh and Block pulse functions. In the LMS algorithm, the convergence factor is an important design parameter because it governs stability and convergence speed, which depend on the proper choice of the convergence facotr. The conventional adaptation techniques use a fixed time constant convergence factor by the method of trial and error. In this paper, we propose an optimal method in the choice of the convergence factor. The proposed algorithm depends on the received signal and the output of the Walsh network in real time.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.43-49
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• 2018

In this paper, we propose a displacement measurement method based on deep learning using image data obtained from tensile tests of a material specimen. We focus on the fact that the sequential images during the tension are generated and the displacement of the specimen is represented in the image data. So, we designed sample generation model which makes sequential images of specimen. The behavior of generated images are similar to the real specimen images under tensile force. Using generated images, we trained and validated our model. In the deep neural network, sequential images are assigned to a multi-channel input to train the network. The multi-channel images are composed of sequential images obtained along the time domain. As a result, the neural network learns the temporal information as the images express the correlation with each other along the time domain. In order to verify the proposed method, we conducted experiments by comparing the deformation measuring performance of the neural network changing the displacement range of images.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.95-101
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• 2018

In this paper, we propose an efficient friendly forces location data sharing algorithm in a troops using a low bandwidth radio. The future battlefield is a 'Network Centric Warfare' with a concept of identifying the position and power of the enemy and friendly forces and leading the battlefield to victory through proper links at the time of our need. One of the basic elements in the 'Network Centric Warfare' is to share friendly forces location data. The bandwidth and transmission rates of radio used in battalion are low. Nevertheless, we should share our locations data almost in real time for effective fighting in a war situation. This paper describes the efficient method of friendly forces location data sharing based on low bandwidth radio. In particular, the concept of 'network-centered warfare' is reflected in the troop below the battalion to present an integrated and efficient way to shared location data of friendly forces.