• 한국게임학회 논문지
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• 제20권3호
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• pp.65-74
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• 2020

섀도우 매핑 알고리즘에서 섀도우 맵이 확대되면 계단형 섀도우 실루엣이 나타난다. 본 논문에서는 재구성된 실루엣을 이용하여 소프트 섀도우를 생성한다. 먼저 섀도우 실루엣은 선형 또는 2차 곡선 모델을 기반으로 한 서브 텍셀 엣지 검출 방법을 통해 확보한다. 그리고 적분을 이용하여 정확한 섀도우 밝기의 평균을 얻기 위해 적분 기반 섀도우 필터링 알고리즘을 사용한다. 본 논문은 상기 과정을 통해 앨리어싱 현상이 두드러지는 실루엣을 효과적으로 제거하며 소프트 섀도우를 효율적으로 생성하는 방법을 제시한다.

• 한국분말재료학회지
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• 제30권1호
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• pp.29-34
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• 2023

A fixed-point iteration is proposed to integrate the stress and state variables in the incremental analysis of plastic deformation. The Conventional Newton-Raphson method requires a second-order derivative of the yield function to generate a complicated code, and the convergence cannot be guaranteed beforehand. The proposed fixed-point iteration does not require a second-order derivative of the yield function, and convergence is ensured for a given strain increment. The fixed-point iteration is easier to implement, and the computational time is shortened compared with the Newton-Raphson method. The plane-stress condition is considered for the biaxial loading conditions to confirm the convergence of the fixed-point iteration. 3-dimensional tensile specimen is considered to compare the computational times in the ABAQUS/explicit finite element analysis.

• 제어로봇시스템학회논문지
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• 제8권2호
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• pp.126-135
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• 2002

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• 한국전산구조공학회논문집
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• 제14권4호
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• pp.435-444
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• 2001

대변형 탄소성 프레임의 해석은 운동학적, 재질적, 수치해법상으로 매우 복잡하여 정확하고 효율적인 요소나 알고리즘이 부족하다. 본 논문에서는 3차원 보요소에 대하여 봉이론으로부터 유한요소를 만들고 소성을 적용하기 위하여 Cauchy응력과 공학적변형률을 구성방정식에 적용하는 방법으로 객관화된 증분해법에 의한 보요소를 제안하였다. 특히 항복조건의 만족을 위하여 정확하고도 효율적인 소성방정식의 적분법을 개발하고 적용하였으며 연속법과 일차원 탐색 등을 고려하여 광역수렴성과 2차 수렴속도를 갖는 수치해법을 개발하고 예제를 통하여 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2762-2764
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• 2001

In this study, we introduce and investigate a class of dynamic perceptron architectures, discuss a comprehensive design methodology and carry out a series of numeric experiments. The proposed dynamic perceptron architectures are called as Polynomial Neural Networks(PNN). PNN is a flexible neural architecture whose topology is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated on the fly. In this sense, PNN is a self-organizing network. PNN has two kinds of networks, Polynomial Neuron(FPN)-based and Fuzzy Polynomial Neuron(FPN)-based networks, according to a polynomial structure. The essence of the design procedure of PN-based Self-organizing Polynomial Neural Networks(SOPNN) dwells on the Group Method of Data Handling (GMDH) [1]. Each node of the SOPNN exhibits a high level of flexibility and realizes a polynomial type of mapping (linear, quadratic, and cubic) between input and output variables. FPN-based SOPNN dwells on the ideas of fuzzy rule-based computing and neural networks. Simulations involve a series of synthetic as well as experimental data used across various neurofuzzy systems. A detailed comparative analysis is included as well.

• Steel and Composite Structures
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• 제34권2호
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• pp.227-239
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• 2020

The aim of this study is to obtain the nonlinear and post-buckling responses of relatively thick functionally graded plates with oblique elliptical cutouts using a new semi-analytical approach. To model the oblique elliptical hole in a FGM plate, six plate-elements are used and the connection between these elements is provided by the well-known Penalty method. Therefore, the semi-analytical technique used in this paper is known as the plate assembly technique. In order to take into account for functionality of the material in a perforated plate, the volume fraction of the material constituents follows a simple power law distribution. Since the FGM perforated plates are relatively thick in this research, the structural model is assumed to be the first order shear deformation theory and Von-Karman's assumptions are used to incorporate geometric nonlinearity. The equilibrium equations for FGM plates containing elliptical holes are obtained by the principle of minimum of total potential energy. The obtained nonlinear equilibrium equations are solved numerically using the quadratic extrapolation technique. Various sets of boundary conditions for FGM plates and different cutout sizes and orientations are assumed here and their effects on nonlinear response of plates under compressive loads are examined.

• 정보처리학회논문지B
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• 제10B권4호
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• pp.373-380
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• 2003

대부분의 저가형 디지털 카메라에 사용되는 광학계의 경우 상대적으로 심한 렌즈 왜곡을 보이고 있다. 본 연구의 목적은 렌즈의 기하학적 왜곡에 의한 영상 품질의 저하를 보정하려는 것으로 Tsai의 카메라 캘리브레이션 방법을 단순화한 렌즈 왜곡 변수 계산 방법 및 계산된 렌즈 왜곡 변수를 이용하여 왜곡된 원영상을 이미지 워핑을 통해 보정하는 방법을 제안한다. 렌즈 왜곡 변수 계산 단계에서는 카메라 캘리브레이션 과정의 단순화를 위해 scale factor ratio 및 이미지 센터를 처리하는 실질적인 방식에 대해 보고하며 정량적인 이미지 품질 척도를 이용하여 왜곡보정 효과를 측정함으로써 제안된 방법의 타당성을 보인다. 한편, 렌즈 왜곡 변수 계산 단계에서의 결과를 바탕으로 이미지 워핑을 적용하기 위해 역공간 매핑 방식을 적용하는 경우 본 연구에서 적용된 방사상 렌즈 왜곡 모델의 정확한 해를 구하기 위해서는 3차 방정식의 해를 구하여야 한다. 본 논문에서는 정보기기로의 내장형 구현에 필수적인 실시간 처리를 목적으로 2차 방정식으로의 근사화 방법을 제안한다. 실험을 통하여 제안된 근사화 방법의 실시간 구현 가능성을 보이며 아울러 3차 방정식의 해를 이용한 이미지 워핑의 경우와 성능이 동등함을 보인다.