• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.6
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• pp.325-332
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• 2003

The loss minimization is one of the most important problems to save the operational cost in distribution systems. This paper presents an efficient method for optimal feeder reconfiguration of distribution systems. Chaos search algorithm (CSA) is used to reconfigure distribution systems so that active power losses are globally minimized with turning on/off sectionalizing switches. In optimization problem, the CSA searches the global optimal solution on the basis of regularity in chaotic motions and easily escapes from local or near optimal solution. The CSA is tested on 15 buses and 32 buses distribution systems, and the results indicate that it is able to determine appropriate switching options for global optimum reconfiguration.

• MALSORI
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• no.45
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• pp.47-61
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• 2003

In this paper, we consider the implementation of connected digit recognition system and the several approaches to improve its performance. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with one pass dynamic programming search algorithm that is used for general speech recognition system for fast search. To find the efficient modeling of digit recognition system, we perform some experiments along the various conditions to affect the performance and summarize the results.

• IE interfaces
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• v.19 no.2
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• pp.168-173
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• 2006

In the Reporting Cell Location Management (RCLM) system, a subset of cells in the network is designated as the reporting cells. Each mobile terminal performs location update only when it enters one of these reporting cells. When a call arrives, the paging is confined to the reporting cell the user last reported and the neighboring bounded non-reporting cells. Frequent location update may result in degradation of quality of service due to interference. Miss on the location of a mobile terminal will necessitate a search operation on the network when a call comes in. We must decide the number of reporting cells and which cell should be reporting cell to balance the registration (location update) and search (paging) operations to minimize the cost of RCLM system. This paper proposes a ranking ant colony system (RACS) for optimization of RCLM system.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.594-607
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• 2000

The goal of this research is to develop a Remote Medical Examination System on Oriental Medicine on the very high sped information communication network. We developed a remote medical examination system based on the sample examination data of 10 patients and develop the information of search database based on contents. We analyzed the sample data and the requirements of patients, doctors, and nurses. By the analyzed result, we designed and constructed a prototype are as follow: the multimedia ORDBMS server system, network interface technology, internal/external database schema design, oriental medicine expert knowledge base design, inter-data search algorithm design and thesaurus.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2158-2160
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• 2002

In this paper, we designed the adaptive fuzzy controller(AFLC) using neural network and tabu search. We tuned the weights of neural network changing adaptively input/output gain of fuzzy logic controller and the gain of fuzzy logic controller using tabu search. To evaluate the proposed method's effectiveness, we apply the proposed AFLC to the speed control of an actual AC servomotor system. The experimental results show that AFLC has the better control performance than PI controller in terms of settling time, rising time and overshoot.

• Journal of Industrial Technology
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• v.27 no.B
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• pp.53-58
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• 2007

In this paper, we propose a design of the implementation for a search and rescue system for mountain climbers and evaluate the performance of the system. Search and rescues of people in emergency situations in mountain areas have been difficult due to lack of information about their location. In the proposed design, several small and commonly-available RF-based sensors, some amount of storage and processing devices are used. Infestations offer geographically intermittent coverage at high speeds. The proposed mountain climber tracking system use the directed diffusion scheme combined with infostation system. We also analyze the performance of the proposed system with NS-2 simulation package. From the performance analysis results, we expect that the proposed system will be very useful to early detect climbers' locations in emergency situations in Korea mountain areas.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.28-33
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• 1997

This paper presents an application of genetic algorithms for optimal configuration of distribution network. Optimal nehvork is defined to satisfy the condition of load balancing. Three problems are suggested to show the performance of genetic algorithms. To resolve the problems, we propose two different mutation operators, in stead of crossover and mutation operators, which are utilized in both global and local search operations. In addition, arc pattern list is also proposed for an efficient search.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.114-119
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• 2002

Realtime assignment of railways is an important component in the railway control systems. To solve this problem, we must exactly represent the track topology. Graph is a proper data structure for representing general network topologies, but not Proper for track topologies. In this paper, we define a new data structure, railway graph, which can exactly represent topologies of railway networks. And we describe a path search algorithm in the defined railway graph, and a top-down approach for designing railway network by the Proposed graph.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.88.5-88
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• 2001

We propose a neural network solver for an inverse problem. The problem is that input data with complete teaching include defects and predict the defect value. The solver is constructed of a three layer neural network whose learning method is combined from BP and reconstruction learning. The input data for the defects are unknown; therefore, the circulation of an arithmetic progression replaces them; rightly, the learning procedure is not converged for the circulation data vut for the normal data. The learning is quitted after such a learning status id kept. Then, we search a minimum of the differences between teaching data and output of the circulation. Then, we search a minimum of the ...

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.685-687
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• 2023

최근에 이르러 인공신경망의 발전은 CNN(Convolutional Neural Network) 알고리즘을 활용한 이미지 분석 및 검색 시스템에 비약적인 기여를 하고 있다. 이는 이미지를 입력으로 받아 유사한 이미지를 찾아내는 기능을 향상시키는 연구를 촉진시켰다. 이와 같은 기술의 실용화는 다양한 분야를 포괄하며, 대표적으로 쇼핑몰의 상품검색, 검색 엔진 등에 응용되어 사용자의 편의를 제고하고 있다. 이에 따라 상품명에 대한 정보가 없는 상황에서도 단순한 이미지 정보를 통해 원하는 상품을 검색하는 것이 가능해졌다. 그러나, 실제 세계의 이미지에는 다양한 객체들이 복잡하게 혼재하고 있어 CNN 알고리즘 단독으로는 이미지 내부의 객체를 정확히 분석하고, 그 객체가 포함된 다른 이미지들을 효과적으로 검색하는데 한계가 있음이 인지되고 있다. 본 연구는 이러한 문제점을 개선하기 위해 객체 탐지 알고리즘을 적용하는 방안을 모색하였다. 본 논문에서는 객체 탐지 알고리즘을 통해 이미지 내부의 객체를 분석하고, 그에 따른 유사 객체를 포함하는 이미지를 찾아내는 전략을 제시한다. 이를 통해 이미지 분석 및 검색의 정확성을 더욱 향상시킬 수 있는 가능성을 제안한다.