• 지구물리
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• 제9권1호
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• pp.7-19
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• 2006

Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

• 한국철도학회논문집
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• 제2권1호
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• pp.38-46
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• 1999

This study proposes the analysis and evaluation method of time series ultrasonic signal using the attractor analysis. Features extracted from time series signal analyze quantitatively characteristics of weld defects. For this purpose, analysis objective in this study is fractal dimension and attractor quadrant feature. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics resulting from distance shifts such as parts of head and flange even though the types of defects are identified. These differences in characteristics of weld defects enables the evaluation of unique characteristics of defects in the weld zone. In quantitative fractal feature extraction, feature values of 3.848 in the case of part of head(crack) and 4.102 in the case of part of web(side hole) and 3.711 in the case of part of flange(crack) were proposed on the basis of fractal dimensions. Proposed attractor feature extraction in this study can enhance the precision rate of ultrasonic evaluation for defect signals of rail weld zone such as side hole and crack.

• 한국철도학회:학술대회논문집
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• 한국철도학회 1998년도 추계학술대회 논문집
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• pp.87-95
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• 1998

This study proposes the analysis and evaluation method of time series ultrasonic signal using the attractor analysis. Features extracted from time series signal analyze quantitatively characteristics of welding defects. For this purpose, analysis objective in this study is fractal dimension and attractor Quadrant feature. Trajectory changes in the attractor indicated that even the same type of defects carried substantial difference in fractal characteristics resulting from distance shifts such as parts of head and flange. Such differences in characteristics of weld defects enables the evaluation of unique features of defects in the weld zone. In quantitative fractal feature extraction, feature values of 3.848 in the case of part of head(crack) and 4.102 in the case of part of web(side hale) and 3.711 in the case of part of flange(crack) were proposed on the basis of fractal dimensions. Proposed attractor feature extraction in this study can enhance the precision rate of ultrasonic evalaution for defect signals of rail weld zone such as side hole and crack.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.278-278
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• 2000

In this paper, we introduce a new genetic reordering operator based on the concept of schema to solve optimization problems such as the Traveling Salesman Problem(TSP) and maximizing or minimizing functions. In particular, because TSP is a well-known combinational optimization problem andbelongs to a NP-complete problem, there is huge solution space to be searched. For robustness to local minima, the operator separates selected strings into two parts to reduce the destructive probability of good building blocks. And it applies inversion to the schema part to prevent the premature convergence. At the same time, it searches new spaces of solutions. Additionally, the non-schema part is applied to inversion for robustness to local minima. By doing so, we can preserve diversity of the distributions in population and make GA be adaptive to the dynamic environment.

• Bulletin of the Korean Chemical Society
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• 제24권1호
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• pp.99-105
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• 2003

A liquid-liquid extraction followed by evaporative concentration method was used to determine the concentration of normal, or straight chain, saturated hydrocarbons (NSH) $(C_{10}\;to\;C_{24})$ and polycyclic aromatic hydrocarbons (PAH) here defined as: fluorene, anthracene, pyrene, chrysene and perylene, in the Buriganga River water of Bangladesh. Samples were collected from 5 and 25 cm depth of water at the southern, middle and northern parts of the river at Postogolla, Sadarghat and Sowarighat stations. Hydrocarbons were extracted from 450 mL of water into 75 mL n-hexane and then concentrated into 1 or 2 mL solution by evaporation. These solutions were analyzed by gas chromatography. The highest and lowest concentrations were determined as $257\;{\mu}gL^{-1}\;for\;C_{13}\;and \;0.24\;{\mu}g\;L^{-1}\;for\;C_{22}$ at 5 ㎝ depth of water, at the northern part of the Sowarighat and southern part of the Postogolla, respectively. This method could allow the analysis of water for $C_{22}$ as low as $0.24\;{\mu}g\;L^{-1}$.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.891-894
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• 1998

This paper introduces an automatic face region extraction method. This method consists of two part: face recognition and extraction of facial organs which are eye, eyebrow, nose and mouth. In first stage, we use genetic algorithms(GAs) to get face region in complex background. In second stage, we use Geometrical Face Model to textract eye, eyebrow, nose and mouth. In both stage, stochastic component is used to deal with the problems caused by had lighting condition. According to this value, blurring number is determined. Average Computation time is less than 1 sec, and using this method we can extract facial feature efficiently from several images which has different lightning condition.

• East Asian mathematical journal
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• 제33권1호
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• pp.1-9
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• 2017

In [8] they introduced a new finite element method for accurate numerical solutions of Poisson equations with corner singularities, which is useful for the problem with known stress intensity factor. They consider the Poisson equations with homogeneous Dirichlet boundary condition, compute the finite element solution using standard FEM and use the extraction formula to compute the stress intensity factor, then they pose a PDE with a regular solution by imposing the nonhomogeneous boundary condition using the computed stress intensity factor, which converges with optimal speed. From the solution they could get accurate solution just by adding the singular part. This approach works for the case when we have the reasonably accurate stress intensity factor. In this paper we consider Poisson equations defined on a domain with a concave corner with Neumann boundary conditions. First we compute the stress intensity factor using the extraction formular, then find the regular part of the solution and the solution.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1349-1355
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• 1999

A power distribution facility map is drawn on cadastral map. Besides, grid lines are added on the map for sectionalization. For automatic recognition of the map, we first extract recognizing regions. In this paper, we propose an extraction method of recognizing regions by partially extending thinned image. The proposed method is consist of three phases, binarization phase, thinning phase and partial extending phase. The first phase generate a binary image using threshold value which is obtained by histogram analysis. The binary image contains many part of recognizing regions, but not all. The second phase generate thinned image which is generated by appling thinning operator to the binary image. And the third phase extends thinned image from terminal point until satisfying termination condition. The proposed method is tested on several power distribution facility maps, and the results are presented.

• 전자공학회논문지CI
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• 제39권3호
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• pp.32-43
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• 2002

본 논문에서는 신경망에 기반한 디지털 신호를 위한 패턴분류 시스템을 제안한다. 제안하는 시스템은 두 가지 신경망 모델로 구성된다. 첫 번째 부분은 특징 추출의 역할을 하는 웨이블릿 신경망이다. 이 부분을 위해 기존의 웨이블릿 신경망 모델들을 비교한 후, 특징 추출을 위한 새로운 웨이블릿 신경망 모델을 제안한다. 다른 부분은 패턴 분류를 위한 웨이블릿 신경망이다. 패턴 분류에 적용하기 위해 기존의 웨이블릿 신경망 구조를 수정하고 학습 방법을 제안한다. 패턴 분류 웨이블릿 신경망의 입력은 특징 추출 신경망의 은닉노드의 연결강도, 확장 및 이동 파라미터로 구성되었다. 또 출력은 특징 추출 신경망의 입력 신호가 속한 부류를 나타낸다. 제안한 시스템을 EEG 신호를 주파수에 따라서 분류하는 문제에 적용하였다.

• 대한전자공학회논문지SP
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• 제40권3호
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• pp.203-216
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• 2003

In this paper a new feature extraction and target classification method is proposed for the recognition part of FLIR(Forwar Looking Infrared)-image-based ATR system. Proposed feature extraction method is "cluster(=set of classes)-based"version of previous fisherfaces method that is known by its robustness to illumination changes in face recognition. Expecially introduced class clustering and cluster-based projection method maximizes the performance of fisherfaces method. Proposed target image classification method is based on the mixture of experts model which consists of RBF-type experts and MLP-type gating networks. Mixture of experts model is well-suited with ATR system because it should recognizee various targets in complexed feature space by variously mixed conditions. In proposed classification method, one expert takes charge of one cluster and the separated structure with experts reduces the complexity of feature space and achieves more accurate local discrimination between classes. Proposed feature extraction and classification method showed distinguished performances in recognition test with customized. FLIR-vehicle-image database. Expecially robustness to pixelwise sensor noise and un-wanted intensity variations was verified by simulation.