• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집B
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• pp.144-147
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• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• 한국정밀공학회지
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• 제16권6호
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• pp.133-140
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• 1999

In this study, a monitoring method to detect chip disposal state in drilling system based on neural network was proposed and its performance was evaluated. If chip flow is bad during drilling, not only the static component but also the fluctuation of dynamic component of drilling. Drilling torque is indirectly measured by sensing spindle motor power through a AC spindle motor drive system. Spindle motor power being measured drilling, four quantities such as variance/mean, mean absolute deviation, gradient, event count were calculated as feature vectors and then presented to the neural network to make a decision on chip disposal state. The selected features are sensitive to the change of chip disposal state but comparatively insensitive to the change of drilling condition. The 3 layerd neural network with error back propagation algorithm has been used. Experimental results show that the proposed monitoring system can successfully recognize the chip disposal state over a wide range of drilling condition even though it is trained under a certain drilling condition.

• 한국통신학회논문지
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• 제41권3호
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• pp.328-330
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• 2016

본 논문에서는 단일 차선표시선 검출 기반 차선 이탈 경보 시스템을 제안한다. 제안하는 방법은 어두운 조명이나 마모로 인하여 좌 우 차선표시선의 동시 검출이 불가능한 경우에도 단일 차선표시선의 검출 및 추적을 통해 강건한 차선이탈 감지를 목표로 한다. 실험을 통해 제안 방법이 한쪽 차선표시선만 검출된 경우에도 차선이탈을 감지하는 것을 확인하였다.

• Journal of Magnetics
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• 제16권2호
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• pp.114-119
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• 2011

This paper presents a magnetization modeling method combined with material sensitivity information to identify the unknown magnetization distribution of a hull and improve the accuracy of the predicted fields. First, based on the magnetization modeling, the hull surface was divided into three-dimensional sheet elements, where the individual remanent magnetization was assumed to be constant. For a fast search of the optimum magnetization distribution on the hull, a material sensitivity formula containing the first-order gradient information of an objective function was combined with the magnetization modeling method. The feature of the proposed method is that it can provide a stable and accurate field solution, even in the vicinity of the hull. Finally, the validity of the method was tested using a scale model ship.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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• pp.635-640
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• 2004

절리, 단층, 습곡, 암맥, 파쇄대 및 암상의 경계에 의해 나타나는 지질학적 선구조는 지하의 물성이나 지질구조를 반영한다. 따라서 지구조 운동 분석을 위한 기초 자료로 이용가능하기 때문에 그동안 전문가의 육안 판독이외에 영상에서 선구조를 추출하기 위한 많은 연구가 이루어져왔다. 최근에 이용 가능한 위성영상자료가 증가하고 영상을 지구과학 응용분야에 적용하는 사례가 많아짐에 따라 영상으로부터 선구조를 빠르고 정확하게 추출해야 할 필요성이 높아졌다. 본 연구에서는 위성영상으로부터 선구조를 자동으로 추출하기 위해 구배 방향 프로파일 분석(Gradient Direction Profile Analysis. GDPA) 알고리즘과 Hough 변환 알고리즘을 이용한 프로그램을 개발하였고, 각 알고리즘에 필요한 모든 변수들을 사용자가 직접 입력할 수 있도록 설계하였다. 이 프로그램을 옥천 습곡대의 북동부에 위치한 강원도 정선지역의 Landsat TM 에 적용하여 가능성을 검토에 보았고, 오차 검증 방법을 이용하여 각 알고리즘을 정량적으로 평가하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.117-118
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• 2007

A robot needs a human detection algorithm for interaction with a human. This paper proposes a method that finds people using a SVM (support vector machine) classifier and a stereo camera. Feature vectors of SVM are extracted by HoG (histogram of gradient) within images. After training extracted vectors from the clustered images, the SVM algorithm creates a classifier for human detection. Each candidate for a human in the image is generated by clustering of depth information from a stereo camera and the candidate is evaluated by the classifier. When compared with the existing method of creating candidates for a human, clustering reduces computational time. The experimental results demonstrate that the proposed approach can be executed in real time.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2558-2561
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• 2008

In the present study, a parallel Taylor-Galerkin/level set based two-phase flow code was developed using finite element discretization and domain decomposition method based on MPI (Message Passing Interface). The proposed method can be utilized for the analysis of a large scale free surface problem in a complex geometry due to the feature of FEM and domain decomposition method. Four-step fractional step method was used for the solution of the incompressible Navier-Stokes equations and Taylor-Galerkin method was adopted for the discretization of hyperbolic type redistancing and advection equations. A Parallel ILU(0) type preconditioner was chosen to accelerate the convergence of a conjugate gradient type iterative solvers. From the present parallel numerical experiments, it has been shown that the proposed method is applicable to the simulation of large scale free surface flows.

• 음성과학
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• 제7권4호
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• pp.11-26
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• 2000

In this paper, we propose the HMM with the MIN module. Because initial and re-estimated variance vectors are important elements for performance in HMM recognition systems, we propose a method which compensates for the mismatched statistical feature of training and test data. The MIN module function is a differentiable function similar to the sigmoid function. Unlike a continuous density function, it does not include variance vectors of the data set. The proposed hybrid HMM/MIN module is a unified network in which the observation probability in the HMM is replaced by the MIN module neural network. The parameters in the unified network are re-estimated by the gradient descent method for the Maximum Likelihood (ML) criterion. In estimating parameters, the variance vector is not estimated because there is no variance element in the MIN module function. The experiment was performed to compare the performance of the proposed HMM and the conventional HMM. The experiment measured an isolated number for speaker independent recognition.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(C)
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• pp.406-407
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• 2012

Texture transfer is a NPR technique for expressing various styles according to source (reference) image. By late 2000s, there are many texture transfer researches. But video base researchers are not active. Moreover, they didn't use important feature like directional information which need to express detail characteristics of target. So, we propose a new method to generate texture transfer animation (using video) with directional effect for maintaining temporal coherence and controlling coherence direction of texture. For maintaining temporal coherence, we use optical flow and confidence map to adapt for occlusion/disocclusion boundaries. And we control direction of texture for taking structure of input. For expressing various texture effects according to different regions, we calculate gradient based on directional weight. With these techniques, our algorithm can make animation result that maintain temporal coherence and express directional texture effect. It is reflect the characteristics of source and target image well. And our result can express various texture directions automatically.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2008년도 춘계학술발표논문집
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• pp.286-289
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• 2008

홍채인식은 홍채의 무늬 패턴 정보를 이용하여 동일인 여부를 판별하는 생체인식 기술이다. 최근 들어 홍채정보를 이용하여 출입통제, 정보보안등의 분야에 많이 활용되고 있다. 이러한 홍채 인식 시스템에 있어 조명의 영향이나 동공의 크기, 홍채의 회전 등 홍채 취득시 다양한 환경 조건으로 인해 발생될 수 있는 홍채 무늬 패턴의 변화에 강인한 특징을 추출하는 것은 홍채인식에 있어 매우 중요한 과제이다. 본 논문에서는 국부적 방향 히스토그램을 이용한 새로운 홍채 특징 추출 방법을 제안하였다. 제안된 방법은 성능면에서 기존의 방법들과 비교하여 대등한 성능을 보여주는 것을 실험을 통해 확인하였다.