• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.670_671
• /
• 2009

This paper presents a optimum design process for static torque characteristics of the Claw-Poles PM Stepping Motor(CPSM). Since the shape of CPSM changes along with axial direction, CPSM should only be analyzed by 3D-FEM. But 3D-FEM needs too much computation time and computer resources. Therefore, it is essential to reduce the number of 3D-FEM analysis models. In this paper, two design factors which affect the static torque characteristics of CPSM were selected. Optimum design process was able to make progress by using Pattern Search Algorithm and 3D-FEM. Finally, optimized model was compared with a conventional model.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 2007.11a
• /
• pp.349-357
• /
• 2007

Named entities (NEs) are important in many Natural Language Processing (NLP) applications, and discovering NE-related relations in texts may be beneficial for these applications. This paper proposes a method to extract the ISA relation between a "named entity" and its category, and an IS-RELATED-TO relation between the category and its related object. Based on the pattern extraction algorithm "Person Category Extraction" (PCE), we extend it for solving our problem. Our experiments on Wall Street Journal (WSJ) corpus show promising results. We also demonstrate a possible application of these relations by utilizing them for semantic search.

• Journal of the Korean Society for Railway
• /
• v.9 no.1 s.32
• /
• pp.76-80
• /
• 2006

The Optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model have been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme are utilized, respectively. As a result, two meta-models for trip time and energy consumption were constructed. The optimization to search an economical running pattern was achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

• Proceedings of the KIEE Conference
• /
• 2005.10c
• /
• pp.238-240
• /
• 2005

The Optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model have been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme are utilized, respectively. As a result, two meta-models for trip time and energy consumption were constructed. The optimization to search an economical running pattern was achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

• Journal of Korea Multimedia Society
• /
• v.18 no.1
• /
• pp.52-64
• /
• 2015

Recently, as the quality of life has been improving, search items in the area of entertainment represent an increasing share of the total usage of Internet portal sites. Information retrieval in the entertainment area is mainly depending on keywords that users are inputting, and the results of information retrieval are the contents that contain those keywords. In this paper, we propose a search method that takes natural language inputs and retrieves the database pertaining to entertainment. The main components of our study are the simple Korean morphological analyzer using case particle information, predicate-oriented token generation, standardized pattern generation coherent to tokens, and automatic generation of the corresponding SQL queries. We also propose an efficient retrieval system that searches the most relevant results from the database in terms of natural language querying, especially in the restricted domain of music, and shows the effectiveness of our system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.5
• /
• pp.594-600
• /
• 2006

The optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model has been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme ate utilized, respectively. As a result, two meta-models for trip time and energy consumption are constructed. The optimization to search an economical running pattern is achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.50 no.7
• /
• pp.323-330
• /
• 2001

Niching method enables the genetic algorithm(GA) to be applied to the problems that require the location of multiple solutions in the search space, but these methods have fatal disadvantages. The main disadvantage is that the method requires too much calculation of object function. In this paper, a niching method using restricted competition selection(RCS) combined with a pattern search method(PSM) is proposed to identify multiple niches more efficiently and fast in a multimodal domain. The validity of the proposed method is verified by the simulation of test functions and the optimal design of an torque motor.

• The KIPS Transactions:PartB
• /
• v.13B no.6 s.109
• /
• pp.585-590
• /
• 2006

Although motion estimation Plays an important role in digital video compression, complex search procedure is required to find an optimal motion vector. To reduce the search time, the search start point should be set up properly md efficient search pattern is needed. If the overall motion of the torrent block can be predicted, motion estimation can be performed efficiently. In this paper. block types are classified using candidate vectors and the motion activity of the block is predicted which leads to the search start point close to the optimal motion vector. The proposed method proves to be about 1.5$\sim$7 times faster than existing methods with about 0.02$\sim$0.2(dB) improvement of picture quality in images with large movements.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.6
• /
• pp.57-65
• /
• 2019

In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.6
• /
• pp.38-47
• /
• 2000

In pattern classification, the Bhattacharyya distance has been used as a class separability measure. Furthemore, it is recently reported that the Bhattacharyya distance can be used to estimate error of Gaussian ML classifier within 1-2% margin. In this paper, we propose a feature extraction method utilizing the Bhattacharyya distance. In the proposed method, we first predict the classification error with the error estimation equation based on the Bhauacharyya distance. Then we find the feature vector that minimizes the classification error using two search algorithms: sequential search and global search. Experimental reslts show that the proposed method compares favorably with conventional feature extraction methods. In addition, it is possible to determine how man, feature vectors arc needed for achieving the same classification accuracy as in the original space.