• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.1
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• pp.39-48
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• 2013

This paper develops a 2-D moving least squares(MLS) difference method for Stefan problem by extending the 1-D version of the conventional method. Unlike to 1-D interfacial modeling, the complex topology change in 2-D domain due to arbitrarily moving boundary is successfully modelled. The MLS derivative approximation that drives the kinetics of moving boundary is derived while the strong merit of MLS Difference Method that utilizes only nodal computation is effectively conserved. The governing equations are differentiated by an implicit scheme for achieving numerical stability and the moving boundary is updated by an explicit scheme for maximizing numerical efficiency. Numerical experiments prove that the MLS Difference Method shows very good accuracy and efficiency in solving complex 2-D Stefan problems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.457-465
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• 2009

This study presents a moving least squares (MLS) finite difference method for solving elastic crack problems with stress singularity at the crack tip. Near-tip functions are intrinsically employed in the MLS approximation to model near-tip field inducing singularity in stress field. employment of the functions does not lose the merit of the MLS Taylor polynomial approximation which approximates the derivatives of a function without actual differentiating process. In the formulation of crack problem, computational efficiency is considerably improved by taking the strong formulation instead of weak formulation involving time consuming numerical quadrature Difference equations are constructed on the nodes distributed in computational domain. Numerical experiments for crack problems show that the intrinsically enriched MLS finite difference method can sharply capture the singular behavior of near-tip stress and accurately evaluate stress intensity factors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.88-95
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• 2015

This paper presents the study of the efficient localization algorithm for non-linear least square estimation. Although non-linear least square(NLS) estimation algorithms are more accurate algorithms than linear least square(LLS) estimation, NLS algorithms have more computation loads because of iterations. This study proposed the efficient algorithm which reduced complexity for small accuracy loss in NLS estimation. Simulation results show the accuracy and complexity of the localization system compared to the proposed algorithm and conventional schemes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.97-105
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• 2015

Multiresponse optimization (MRO) seeks to find the setting of input variables, which optimizes the multiple responses simultaneously. The approach of weighted mean squared error (WMSE) minimization for MRO imposes a different weight on the squared bias and variance, which are the two components of the mean squared error (MSE). To date, a weighted sum-based method has been proposed for WMSE minimization. On the other hand, this method has a limitation in that it cannot find the most preferred solution located in a nonconvex region in objective function space. This paper proposes a Tchebycheff metric-based method to overcome the limitations of the weighted sum-based method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.577-580
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• 2023

물리 기반 시뮬레이션과 같이 연속적인 움직임을 표현하기 위해서 고차 보간(High-order interpolation)을 설계하는 것을 중요한 문제이다. 본 논문에서는 제약적인 벡터와 밀도 형태를 몬테카를로법을 사용하여 이동최소제곱(MLS, Moving least squares)을 제곱하여 이를 통해 속도 필드를 표현할 수 있는 방법을 제안한다. 결과적으로 밀도의 형태를 고려하여 MLS의 가중치가 적용된 결과를 보여주며, 그 결과가 벡터 보간에 얼마나 큰 영향을 끼치는지를 다양한 실험을 통해 보여준다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.921-929
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• 2011

In Information age, the academic liberal art Computer education course set up goals for promoting computer literacy and for developing the ability to cope actively with in Information Society and for improving productivity and competition among nations. In this paper, we analyze on discovering of decisive property and satisfaction index to have a influence on computer education on university students. As a preprocessing method, the proposed method select optimum property using correlation feature selection of machine learning tool based on Java and then we use multiclass least square support vector machine based on statistical learning theory. After applying that compare with multiclass support vector machine and multiclass least square support vector machine, we can see the fact that the proposed method have a excellent result like multiclass support vector machine in analysis of the academic liberal art computer education satisfaction index data.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.227-239
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• 1997

PLSR is a powerful multivariate statistical tool that has been successfully applied to the quantitative analyses of data in spectroscopy, chemistry, and industrial process control. Data in spectorscopy is represented by spectrum matrix measured in many wavelengths. Problems of many kinds of noise in data and itercorrelation between wavelengths are quite common in such data. PLSR utilizes whole data set measured in many wavelengths to the analysis, and handles such problems through data compression method. We investigated the PLSR theory, and applied this method to the data for spectroscopic diagnosis of Total Hemoglobin in whole blood.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.271-279
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• 2006

Acoustic Emission (AE) technology is an effective nondestructive testing for continuous monitoring of defect formation and failures in structural materials. This paper presents a source location model using Acoustic Emission (AE) sensors in a Pre-Stressed Concrete (PSC) beam and the evaluation of the model was performed through lab experiments. 54 AE events were made on the surface of the 5m-PSC beam using a Schmidt Hammer and arrival times were measured with 7AE sensors. The source location f3r each event was estimated using least squares. The results were compared with actual positions and the RMSE (Root Mean Square Errors) was about 2cm.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.150-158
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• 2013

In this paper we present approximated constrained least squares filter for real-time directionally adaptive image restoration. The proposed method makes a hardware implementation easier for real-time image restoration because of reducing the filter size. Furthermore, for directional adaptive image restoration, this paper estimates the local orientation by analyzing the covariance matrix and applies to approximated constrained least squares filter. Experimental results show that the proposed method is sharper and less artifacts than existing methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.2
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• pp.177-184
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• 1988

The method of least squares has been applied to the static data, but it was not applications for the processing of observed values accompaning real-time variation. In this paper, having been considered all observations to be the function of time, leveling nets were analized dynamically by introducing the concept of time to conventional method of least squares. As a results, the method of dynamic least squares was well applicable to the adjustment of leveling nets.