• 한국CDE학회논문집
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• 제4권1호
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• pp.19-31
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• 1999

One of the non-photorealistic rendering method, a drawing technique which uses only fine curves and dashed line, is widely employed in an knots and post stamps printing. Engraving of the curves and lines are traditionally performed by human engravers which leads to low productivity in printing preparation. As an effort to improve productivity and quality, a drawing automation method which can easily produce a portrait composed of vector data for laser or chemical engraving is proposed. The method shows that it is possible to draw a portrait by controling the width and length of predefined fine lines according to the gray scales a the end points of each fine lines. A gradually controled weighting factor method is proposed in addition to the author previous works to prevent undesirable boundaries in an identical texture region. User interface functions of a commercial CAD system are heavily employed to exploit the presented method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집B
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• pp.410-416
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• 2001

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity field of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. In this study, stereo photogrammetty was applied for the 3-D matching of tracer particles. Epipolar line was used to decect the stereo pair. 3-D CFD data was used to estimate algorithm. 3-D position data of the first frame and the second frame was used to find velocity vector. Continuity equation was applied to extract error vector. The algorithm result involved error vecotor of about 0.13 %. In Pentium III 450MHz processor, the calculation time of cross-correlation for 1500 particles needed about 1 minute.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.595-601
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• 2003

In this paper we propose an on line training method for classification based on least squares support vector machine. Proposed method enables the computation cost to be reduced and the training to be peformed incrementally, With the incremental formulation of an inverse matrix in optimization problem, current information and new input data can be used for building the new inverse matrix for the estimation of the optimal bias and Lagrange multipliers, so the large scale matrix inversion operation can be avoided. Numerical examples are included which indicate the performance of proposed algorithm.

• 한국정보통신학회논문지
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• 제16권6호
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• pp.1279-1284
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• 2012

본 연구는 ASTER영상을 이용한 해안선 변화에 관한 연구이다. ASTER영상은 1999년 12월에 일본에서 발사된 지구탐사위성에 탑재된 센서이다. ASTER 영상은 15m, 30m, 90m의 해상도와 VNIR, TIR, WIR의 3개의 센서를 가지고 있으나 비교적 영상이 저렴하다. 특히 다양한 파장대를 분포하고 있어 기존의 위성영상보다 지구상의 많은 정보의 획득이 가능하다. 해안선은 국지성이 강하므로 지형 형상에 따라서 변화하게 된다. 그리고 해양지리정보구축에서 가장 중요한 요소 중의 하나다. 따라서 본 연구에서는 ASTER 위성영상으로부터 해안선을 Vector Line으로 자동추출 후 변화량을 분석하였다. 연구결과는 향후 해안선 변화를 분석하는데 중요한 기초자료로 활용될 것이다.

• Journal of information and communication convergence engineering
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• 제7권1호
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• pp.41-45
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• 2009

In mobile GIS environments, a client needs to receive the isogram data with a topographical map from a server, if the mobile client wants to display map with elevation information. Because the elevation data size is normally quite large, the client will suffer some problems to receive the elevation data from server. The main reason is a resource limitation of the mobile devices. To overcome these problems, this paper proposes new data structures and algorithms. They are designed for efficient transmission of contour data to a client. Because of the contour data are generated as a vector style from elevation information stored at a server, the proposed algorithms are focused to minimize the transmission data volume and time.

• Industrial Engineering and Management Systems
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• 제14권4호
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• pp.392-400
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• 2015

Monitoring of plasma etch processes for fault detection is one of the hallmark procedures in semiconductor manufacturing. Optical emission spectroscopy (OES) has been considered as a gold standard for modeling plasma etching processes for on-line diagnosis and monitoring. However, statistical quantitative methods for processing the OES data are still lacking. There is an urgent need for a statistical quantitative method to deal with high-dimensional OES data for improving the quality of etched wafers. Therefore, we propose a robust relevance vector machine (RRVM) for regression with statistical quantitative features for modeling etch rate and uniformity in plasma etch processes by using OES data. For effectively dealing with the OES data complexity, we identify seven statistical features for extraction from raw OES data by reducing the data dimensionality. The experimental results demonstrate that the proposed approach is more suitable for high-accuracy monitoring of plasma etch responses obtained from OES.

• 한국멀티미디어학회논문지
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• 제16권4호
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• pp.418-429
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• 2013

본 논문은 혼합형 폴리라인 단순화와 공간 에너지 집중을 이용한 GIS 벡터맵 데이터 압축을 제안한다. 제안한 방법에서는 GIS 벡터맵에서 폴리라인 속성을 가지는 레이어들에 대해, 최소 면적 오차 기반의 혼합형 폴리라인 단순화 및 공간 에너지 집중에 의하여 선택된 레이어 내의 폴리라인 데이터들을 압축한다. 제안한 단순화 및 공간 에너지 집중는 폴리라인의 형상을 유지하면서 데이터 압축 효과를 향상시킨다. 가시적 화질과 압축률을 통한 평가 결과로부터 제안한 방법이 기존 방법보다 우수한 화질과 높은 압축률을 보임을 확인하였다.

• 대한원격탐사학회지
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• 제26권6호
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• pp.731-740
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• 2010

A region merging technique is suggested in this paper for the segmentation of high-spatial resolution imagery. It employs a region growing scheme based on the region adjacency graph (RAG). The proposed algorithm uses directional neighbor-line average feature vectors to improve the quality of segmentation. The feature vector consists of 9 components which includes an observation and 8 directional averages. Each directional average is the average of the pixel values along the neighbor line for a given neighbor line length at each direction. The merging coefficients of the segmentation process use a part of the feature components according to a given merging coefficient order. This study performed the extensive experiments using simulation data and a real high-spatial resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for the object-based analysis of high-spatial resolution images.

• Journal of Information Processing Systems
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• 제1권1호
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• pp.9-13
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• 2005

Computer security has become a critical issue with the rapid development of business and other transaction systems over the Internet. The application of artificial intelligence, machine learning and data mining techniques to intrusion detection systems has been increasing recently. But most research is focused on improving the classification performance of a classifier. Selecting important features from input data leads to simplification of the problem, and faster and more accurate detection rates. Thus selecting important features is an important issue in intrusion detection. Another issue in intrusion detection is that most of the intrusion detection systems are performed by off-line and it is not a suitable method for a real-time intrusion detection system. In this paper, we develop the real-time intrusion detection system, which combines an on-line feature extraction method with the Least Squares Support Vector Machine classifier. Applying the proposed system to KDD CUP 99 data, experimental results show that it has a remarkable feature extraction and classification performance compared to existing off-line intrusion detection systems.

• Journal of Electrical Engineering and Technology
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• 제11권1호
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• pp.192-199
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• 2016

With changes in insulated defects, the environment, and so on, new partial discharge (PD) data are highly different from the original samples. It leads to a decrease in on-line recognition rate. The UHF signal and pulse current signal of four kinds of typical artificial defect models in gas insulated switchgear (GIS) are obtained simultaneously by experiment. The relationship map of ultra-high frequency (UHF) cumulative energy and its corresponding apparent discharge of four kinds of typical artificial defect models are plotted. UHF cumulative energy and its corresponding apparent discharge are used as inputs. The support vector machine (SVM) incremental method is constructed. Examples show that the PD SVM incremental method based on simulated annealing (SA) effectively speeds up the data update rate and improves the adaptability of the classifier compared with the original method, in that the total sample is constituted by the old and new data. The PD SVM incremental method is a better pattern recognition technology for PD on-line monitoring.