• 한국통신학회논문지
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• 제17권4호
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• pp.398-414
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• 1992

Netted 레이다의 추적정보를 수집하기 위한 레이다 정보 통신망의 설계를 위하여 본 연구에서는 multi-static 레이다의 정보 전송용 근거리망을 공간적 계증구조로 분류하고 최하의 공간 계층인 group 계층의 통신 모델을 소프트웨어 모듈로 설계하여 이를 모듈간의 조합에 의한 기본적인 레이다 정보망 단위를 구성하므로써 여러가지 통신 link 형태에 대한 전송상태를 분석하였다. 각 통신 node에서의 데이터 전송에 관련된 프로세서들은 통계적 모델에 의한 알고리즘을 사용하였으며, 데이터 link를 통하여 이러한 부분적인 하위층 통신모델들을 하나의 지역망으로 구성한 후 내부 node의 전송성능 변화를 분석하였고 이에 따라 망구성전체에 대한 각 통신 link들의 전송특성 분석도 가능하였다.

• 대한전기학회논문지
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• 제38권8호
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• pp.585-592
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• 1989

This paper presents an efficient algorithm for the reactive planning of transmission network under normal operating conditions. The optimal operation of a power system is a prerequisite to obtain the optimal investment planning. The operation problem is decomposed into a P-optimization module and a Q-optimization module, but both modules use the same objective function of generation cost. In the investment problem, a new variable decomposition technique is adopted which can operate the operation and the investment variables. The optimization problem is solved by using the gradient projection method (GPM).

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 A
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• pp.393-395
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• 1998

This paper presents a modeling of railway facilities based on object-oriented software development technique for train operation simulation program. Railway network is decomposed by Line Structure Model and Signal System Model which can be composed to make the train routes and train performance calculation. A brief explanation of class design about these model is provided.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.831-842
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• 1999

We propose a wavelet decomposition feature extraction method for the hand-written character recognition. Comparing the recognition rates of which methods with original image features and with selected features by the wavelet decomposition we study the characteristics of the proposed method. LDA(Linear Discriminant Analysis) QDA(Quadratic Discriminant Analysis) RDA(Regularized Discriminant Analysis) and NN(Neural network) are used for the calculation of recognition rates. 6000 hand-written numerals from CENPARMI at Concordia University are used for the experiment. We found that the set of significantly selected wavelet decomposed features generates higher recognition rate than the original image features.

• 한국구조물진단유지관리공학회 논문집
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• 제10권6호
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• pp.213-223
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• 2006

본 연구에서는 화강풍화토 지반에 시공된 PHC 매입말뚝의 지지력의 평가를 위해 인공신경망을 적용하였다. 오류역전파 인공신경망의 적용성을 증명하기 위해 168개의 PHC 매입말뚝의 현장시험 데이터가 사용되었다. 연구결과 오류역전파 인공신경망의 말뚝지지력 평가가 동재하시험결과와 잘 일치함을 보여주었으며, 이러한 결과는 인공신경망을 이용한 PHC 매입말뚝의 지지력 평가가 신뢰성이 있음을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1036-1041
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• 2003

Non-destruction examinations are required in medical sciences and various engineering now. We wish to emulate the examinations in very simplified experiments. It is an educational program. We show a neural network analysis to predict the locations of a sound-source or a body irradiated by sound-waves in audio-region. The sound is an interest flux, and it enables to clear local-structures in a non-transparent space. However, the sound-propagation equations are not solved easily, therefore, we consider to adopt multi-layer neural-networks instead of the direct solutions. We used detected intensities and coordinates for input data and teaching data. A neural network learned them. The neural-network analysis decomposed the distance of 50cm. The resolution is rather rough; however, it is caused by the limitation of our equipments. Since there is no problem in the neural network processing, if we could revise experiments, then, progress of the resolution would be got. Thus, the proposed method functioned as an educational and simplified non-destruction examination.

• 경영과학
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• 제27권3호
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• pp.15-31
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• 2010

We consider a reverse logistics network design problem for recycling. The problem consists of three stages of transportation. In the first stage products are transported from retrieval centers to disassembly centers. In the second stage disassembled modules are transported from disassembly centers to processing centers. Finally, in the third stage modules are transported from either processing centers or a supplier to a manufacturer, a recycling site, or a disposal site. The objective is to design a network which minimizes the total transportation cost. We design a cooperative coevolutionary algorithm to solve the problem. First, the problem is decomposed into three subproblems each of which corresponds to a stage of transportation. For subproblems 1 and 2, a population of chromosomes is constructed. Each chromosome in the population is coded as a permutation of integers and an algorithm which decodes a chromosome is suggested. For subproblem 3, an heuristic algorithm is utilized. Then, a performance evaluation procedure is suggested which combines the chromosomes from each of two populations and the heuristic algorithm for subproblem 3. An experiment was carried out using test problems. The experiments showed that the cooperative coevolutionary algorithm generally tends to show better performances than the previous genetic algorithm as the problem size gets larger.

• 한국경영과학회지
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• 제22권3호
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• pp.145-162
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• 1997

This paper an analytical model for estimating packet waiting times at stations in the DQDB network, where the most upstream station is saturated. This model is useful in comparing the extreme unfairness which downstream stations experience due to their geographical locations in accessing the medium. Each station is modeled as an M/G/1, where the service time is defined to be the time a packet spends in the transmission buffer. The service time is decomposed into five components, and in turn, the first and second moment of each component are derived in three different modes of operation. Simulation experiments are presented for model validation and results are discussed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.178-186
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• 2003

Recently, many researchers have been interested in biometric systems such as fingerprint, handwriting, key-stroke patterns and human iris. From the viewpoint of reliability and robustness, iris recognition is the most attractive biometric system. Moreover, the iris recognition system is a comfortable biometric system, since the video image of an eye can be taken at a distance. In this paper, we discuss human iris recognition, which is based on accurate iris localization, robust feature extraction, and Neural Network classification. The iris region is accurately localized in the eye image using a multiresolution active snake model. For the feature representation, the localized iris image is decomposed using wavelet transform based on dyadic Haar wavelet. Experimental results show the usefulness of wavelet transform in comparison to conventional Gabor transform. In addition, we present a new method for setting initial weight vectors in competitive learning. The proposed initialization method yields better accuracy than the conventional method.

• 한국경영과학회지
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• 제19권1호
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• pp.69-83
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• 1994

This paper deals with a capacitated ring-star network design problem (CRSNDP) with node capacity constraints. The CRSNDP is formulated as a mixed 0-1 integer problem, and a 2-phase heuristic solution procedure, ADD & VAM and RING, is developed, in which the CRSNDP is decomposed into two subproblems : the capacitated facility location problem (CFLP) and the traveling sales man problem (TSP). To solve the CFLP in phase I the ADD & VAM procedure selects hub nodes and their appropriate capacity from a candidate set and then assigns them user nodes under node capacity constraints. In phase II the RING procedure solves the TSP to interconnect the selected hubs to form a ring. Finally a solution of the CRSNDP can be achieved through combining two solution of phase I & II, thus a final design of the capacitated ring-star network is determined. The analysis of computational results on various random problems has shown that the 2-phase heuristic procedure produces a solution very fast even with large-scale problems.