• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.2
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• pp.114-120
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• 2013

An EP(Electrolytic Polishing)-MAP(Magnetic Abrasive Polishing) hybrid process was applied to remove burr on the micro pattern. Micro pattern fabrication processes are combined with micro milling and EP-MAP hybrid process for deburring. Depending on the micro milling conditions which are applied, micro burrs are formed around the side and top of the pattern. The EP-MAP deburring is used to remove these burrs effectively. To optimize removal rate and form error in the EP-MAP hybrid process, a design of experiment was performed. The effect of deburring process and form error of micro pattern are evaluated via SEM images and the results of AFM.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.51-56
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• 2019

In this paper, we propose an algorithm that can quickly generate and synthesize city maps in racing games. Racing games are characterized by moving a wide map rather than a fixed map, but designing and developing a wide map requires a lot of production time. This problem can be mitigated by creating a large map in the preprocessing step, but a fixed map makes the game tedious. It is also inefficient to process all the various maps in the preprocessing step. In order to solve this problem, we propose a technique to create a terrain pattern in the preprocessing process, to generate a map in real time, and to synthesize various maps randomly. In addition, we reduced unnecessary rendering computations by integrating view-dependent techniques into the proposed framework. This study was developed in Unity3D and can be used for various contents as well as racing game.

• The KIPS Transactions:PartD
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• v.18D no.2
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• pp.81-88
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• 2011

Sequential pattern mining that determines frequent patterns appearing in a given set of sequences is an important data mining problem with broad applications. For example, sequential pattern mining can find the web access patterns, customer's purchase patterns and DNA sequences related with specific disease. In this paper, we develop the sequential pattern mining algorithms using MapReduce framework. Our algorithms distribute input data to several machines and find frequent sequential patterns in parallel. With synthetic data sets, we did a comprehensive performance study with varying various parameters. Our experimental results show that linear speed up can be achieved through our algorithms with increasing the number of used machines.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.277-282
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• 2003

In this paper we propose Using Higher Order Neuron on the Supervised Learning Machine of the Kohonen Feature Map. The architecture of proposed model adopts the higher order neuron in the input layer of Kohonen Feature Map as a Supervised Learning Machine. It is able to estimate boundary on input pattern space because or the higher order neuron. However, it suffers from a problem that the number of neuron weight increases because of the higher order neuron in the input layer. In this time, we solved this problem by placing the second order neuron among the higher order neuron. The feature of the higher order neuron can be mapped similar inputs on the Kohonen Feature Map. It also is the network with topological mapping. We have simulated the proposed model in respect of the recognition rate by XOR problem, discrimination of 20 alphabet patterns, Mirror Symmetry problem, and numerical letters Pattern Problem.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.3
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• pp.34-39
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• 2006

This paper introduces a network security situation awareness tool using a traffic pattern map which facilitates recognizing a current network status by extracting and analyzing predetermined traffic features and displaying an abnormal or harmful traffic which deteriorates network performance. The traffic pattern-map consists of $26{\times}26$ intersections, on which the occupancy rate of the port having maximum occupancy is displayed as a bar graph. In general, in case of the Internet worm, the source address section on the traffic pattern map is activated. In case of DDoS the destination address section is activated.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.2
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• pp.65-70
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• 2003

In this study, researchers developed the estimative algorithm for artificial defect in semiconductor packages and performed it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Backpropagation Neural Network. Self-organizing Map and Backpropagation Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages : Crack, Delamination and Normal. According to the results, we were confirmed that estimative algerian was provided the recognition rates of 75.7% (for Crack) and 83.4% (for Delamination) and 87.2 % (for Normal).

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.824-828
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• 2000

Prior to the downloading of the NC codes to a machining center, the NC tool-path can be verified in a computer. The Z-map is one of the tools for the verification of NC tool-path. The Z-map is a two dimensional array in which the height values of the Z-axis direction vectors are stored. The Z-axis direction vectors are arranged in a rectangular grid pattern on the XY plane. The accuracy of the simulation comes from the grid interval. In the rectangular Z-map, the distances between the grid points are different. The distance in diagonal direction is larger than those in X or Y axis directions. For the rendering of the Z-map, a rectangular grid is divided into two triangular facets. Depending on the selection of a diagonal, there are two different cases. In this paper, triangular Z-map, in which the Z-axis direction vectors are arranged in a triangular grid pattern on XY plane, is proposed. In the triangular Z-map, the distances between grid points are equal. There is no ambiguity to make triangular facets for the rendering.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.62-68
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.10
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• pp.515-522
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• 2004

In this study, we tried to investigate that the advantages of SOM(Self Organizing Map) algorithm such as data accumulation ability and the degradation trend trace ability would be adaptable to the analysis of partial discharge pattern recognition. For the purpose, we analyzed partial discharge data obtained from the typical artificial defects in GIS and XLPE power cable system through SOM algorithm. As a result, partial discharge pattern recognition could be well carried out with an acceptable error by use of Kohonen map in SOM algorithm. Also, it was clarified that the additional data could be accumulated during the operation of the algorithm. Especially, we found out that the data accumulation ability of Kohonen map could make it possible to suggest new patterns, which is impossible through the conventional BP(Back Propagation) algorithm. In addition, it is confirmed that the degradation trend could be easily traced in accordance with the degradation process. Therefore, it is expected to improve on-site applicability and to trace real-time degradation trends using SOM algorithm in the partial discharge pattern recognition

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.8
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• pp.1033-1041
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• 2003

Two-phase flow pattern data during horizontal in-tube flow boiling are presented for pure and mixed refrigerants of R134a and Rl23, The flow pattern is observed through tubular sight glasses located at inlet and outlet of the test section, which is made of a stainless steel tube, 2m long with 10mm I.D., 1.5mm wall thickness. The obtained results are compared with the available various correlations for flow pattern. The flow pattern map of Hashizume was in good agreement with the present data except the region of low mass velocity. Weisman flow pattern map was also known to satisfactorily predict data for refrigerants in the region of annular flow. In this study, the flow pattern are simply classified into two groups; stratified(including intermittent, stratified and stratified-wavy) flow and annular flow. The transition quality from stratified to annular flow was obtained by modifying the liquid Froude number.