• 한국전산구조공학회논문집
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• 제26권1호
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• pp.39-48
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• 2013

본 논문은 기존의 1차원 Stefan 문제를 해석할 수 있는 이동최소제곱 차분법을 확장하여 복잡한 계면경계 형상을 갖는 2차원 문제에 적용할 수 있는 수치기법을 개발한다. 1차원 경우와 달리 2차원 영역에서 임의로 움직이는 이동경계의 위상변화를 효과적으로 모델링할 수 있는 기법을 제안했으며, 이동경계 모사시 절점만 사용하는 이동최소제곱 차분법의 강점을 그대로 살리면서 이동경계의 불연속 특이성과 kinetics 조건을 정확하게 만족시키는 이동최소제곱 미분근사식을 제시했다. 평형방정식은 implicit(음해)법으로 차분하여 수치 안정성을 확보했으며, 이동경계는 explicit(양해)법으로 update하여 계산효율성의 극대화했다. 몇 가지 수치예제를 통해 개발된 이동최소제곱 차분법이 다양한 계면경계 형상을 갖는 2차원 Stefan 문제를 정확하고 효율적으로 풀 수 있음을 검증했다.

• 한국항공우주학회지
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• 제36권5호
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• pp.438-447
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• 2008

본 논문에서는 이동최소자승법을 이용한 근사모델을 사용하여 신뢰성 최적설계를 수행하였다. 신뢰성 최적설계의 수행을 위한 반응표면 생성에는 RSM 과 Kriging이 사용될 수 있다. RSM은 계산시간은 빠르나 비선형성이 강한 문제에 약하며 Kriging은 비선형성이 강한 문제에 적용할 수 있으나 계산시간이 오래 걸리는 단점이 있다. 이 두 방법을 보완한 방법인 이동최소자승법(MLSM)을 이용하여 신뢰성 최적설계를 위한 반응표면을 생성하였다. 이동최소자승법을 이용한 신뢰성 최적설계기법은 Rosenbrock function 과 six-hump carmel back function으로 검증하였고 다른 기법과 비교하였다. 이동최소자승법을 이용하여 무인항공기 배기 덕트의 신뢰성 최적설계를 수행하였고 이는 항공우주구조물의 최적설계에 유용할 것으로 보여 진다.

• Archives of Pharmacal Research
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• 제10권1호
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• pp.1-8
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• 1987

One of the problems of derivatie spectrophotometry, the decrease of signal-to-noise ratio by derivative operations, was solved by three concepts of digital filtering, ensemble averaging, least squares polynomial smoothing and Fourier smoothing. The suthors made several compouter programs written in APPLE SOFT BASIC language for the actual applications of the concepts of these digital filters on UV spectrophotometer system. As a result, ensemble averaging could not be used as a routine operation for the spectrophotometer used. The maximum S/N ratio enhancement factors achieved by least squares polynomial smoothing were 6.17 and 7.47 for the spectra of Gaussian and Lorentzian distribution models, and by Fourier smoothing 16.42 and 11.78 for the spectra of two models, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2045-2050
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• 2004

An optimal combination of arbitrary number correlated estimates is derived. In particular, for two estimates this combination represents the well-known Millman and Bar-Shalom-Campo formulae for uncorrelated and correlated estimation errors, respectively. This new result is applied to the various estimation problems as least-squares estimation, Kalman filtering, and adaptive filtering. The new approximate adaptive filter with a parallel structure is proposed. It is shown that this filter is very effective for multisensor systems containing different types of sensors. Examples demonstrating the accuracy of the proposed filter are given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권1호
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• pp.45-61
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• 2010

In the communication channel, the received signal is affected by many factors that can cause errors. These effects mean that received signal strength (RSS) based methods incur more errors in measuring distance and consequently result in low precision in the location detection process. As one of the approaches to overcome these problems, we propose using direction calibration to improve the performance of the RSS-based method for distance measurement, and sequentially a weighted least squares (WLS) method using reliability factors in conjunction with a conventional RSS weighting matrix is proposed to solve an over-determined localization process. The proposed scheme focuses on the features of the RSS method to improve the performance, and these effects are proved by the simulation results.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.373-379
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• 2001

There is a big issue to generate 3D hexahedral finite element (FE) model, since a process to divide the whole domain into several simple-shaped sub-domains is required before generating a continuous mesh with mapped mesh generators. In general, it is nearly impossible to set up proper division numbers interactively to keep mesh connectivity between sub-domains on a complicated arbitrary-shaped domain. If mesh continuity between sub-domains is not required in an analysis, this complicated process can be omitted. Element-free Galerkin method (EFGM) can accept discontinuous meshes, which only requires nodal information. However it is difficult to choose a reasonable influenced domain in moving least squares scheme with non-uniformly distributed nodes in discontinuous FE models. A new FE scheme fur discontinuous mesh is proposed in this paper by applying improved EFGM with some modification to derive FE approximated function in discontinuous parts. Its validity is evaluated on linear elastic problems.

• IEIE Transactions on Smart Processing and Computing
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• 제5권5호
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• pp.319-322
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• 2016

We propose a parametric blind deconvolution method for bi-level images with unknown intensity levels that estimates unknown parameters for point spread functions and images by minimizing a penalized nonlinear least squares objective function based on normalized correlation coefficients and two regularization functions. Unlike conventional methods, the proposed method does not require knowledge about true intensity values. Moreover, the objective function of the proposed method can be effectively minimized, since it has the special structure of nonlinear least squares. We demonstrate the effectiveness of the proposed method through simulations and experiments.

• Industrial Engineering and Management Systems
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• 제14권3호
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• pp.312-317
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• 2015

The dynamic system approach in time series has been used in many real problems. Based on Taken's embedding theorem, we can build the predictive function where input is the time delay coordinates vector which consists of the lagged values of the observed series and output is the future values of the observed series. Although the time delay coordinates vector from multivariate time series brings more information than the one from univariate time series, it can exhibit statistical redundancy which disturbs the performance of the prediction function. We apply dimension reduction techniques to solve this problem and analyze the effect of this approach for prediction. Our experiment uses delayed Lorenz series; least squares support vector regression approximates the predictive function. The result shows that linearly preserving projection improves the prediction performance.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.393-396
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• 2011

In this paper, we propose a constrained alternating least squares nonnegative matrix factorization algorithm (cALSNMF) to detect active brain regions from single subject's task-related fMRI data. In cALSNMF, we define a new cost function which considers the uncorrelation and noisy problems of fMRI data by adding decorrelation and smoothing constraints in original Euclidean distance cost function. We also generate a novel training procedure by modifying the update rules and combining with optimal brain surgeon (OBS) algorithm. The experimental results on visuomotor task fMRI data show that our cALSNMF fits fMRI data better than original ALSNMF in detecting task-related brain activation from single subject's fMRI data.

• Structural Engineering and Mechanics
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• 제35권4호
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• pp.511-533
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• 2010

As a truly meshfree method, meshless equilibrium on line method (MELM), for 2D elasticity problems is presented. In MELM, the problem domain is represented by a set of distributed nodes, and equilibrium is satisfied on lines for any node within this domain. In contrary to conventional meshfree methods, test domains are lines in this method, and all integrals can be easily evaluated over straight lines along x and y directions. Proposed weak formulation has the same concept as the equilibrium on line method which was previously used by the authors for enforcement of the Neumann boundary conditions in the strong-form meshless methods. In this paper, the idea of the equilibrium on line method is developed to use as the weak forms of the governing equations at inner nodes of the problem domain. The moving least squares (MLS) approximation is used to interpolate solution variables in this paper. Numerical studies have shown that this method is simple to implement, while leading to accurate results.