• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.5
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• pp.411-420
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• 2009

This study presents an extended finite difference method based on moving least squares(MLS) method for solving potential problems with interfacial boundary. The approximation constructed from the MLS Taylor polynomial is modified by inserting of wedge functions for the interface modeling. Governing equations are node-wisely discretized without involving element or grid; immersion of interfacial condition into the approximation circumvents numerical difficulties owing to geometrical modeling of interface. Interface modeling introduces no additional unknowns in the system of equations but makes the system overdetermined. So, the numbers of unknowns and equations are equalized by the symmetrization of the stiffness matrix. Increase in computational effort is the trade-off for ease of interface modeling. Numerical results clearly show that the developed numerical scheme sharply describes the wedge behavior as well as jumps and efficiently and accurately solves potential problems with interface.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.4
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• pp.501-507
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• 2007

In the first part of this study, the moving least squares finite difference method for solving solid mechanics problems was formulated. This second part verified the accuracy, robustness and effectiveness of the developed method through several numerical examples. It was shown that the method gives excellent convergence rate for elasticity problem. The solution process of elastic crack problems showed the easiness in discontinuity modeling and demonstrates the accuracy and efficiency in finding singular stress solution based on adaptive node distribution. The applicability to the engineering problem with abrupt change in displacement and stresses gradient fields is verified through a localization band problem. The developed method is expected to be extended to the various special engineering problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.957-963
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• 2007

In this paper, Nonlinear Autoregressive (NAR) method based on Least Square-Support Vector Regression (LS-SVR) is introduced and tested for nonlinear sustained vowel modeling. In the database of total 43 sustained vowel of Benign Vocal Fold Lesions having aperiodic waveform, this nonlinear synthesizer near perfectly reproduced chaotic sustained vowels, and also conserved the naturalness of sound such as jitter, compared to Linear Predictive Coding does not keep these naturalness. However, the results of some phonation are quite different from the original sounds. These results are assumed that single-band model can not afford to control and decompose the high frequency components. Therefore multi-band model with wavelet filterbank is adopted for substituting single band model. As a results, multi-band model results in improved stability. Finally, nonlinear sustained vowel modeling using NAR based on LS-SVR can successfully reconstruct synthesized sounds nearly similar to original voiced sounds.

• Journal of the Korea Computer Industry Society
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• v.8 no.4
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• pp.263-268
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• 2007

It applied the linear tapped delay line structure to the least mean square algorithm and the recursive least square algorithm it investigated the mean square error characteristics of compensation algorithm. The purpose of this paper is to propose multi-tap update algorithm, which is superior to compensation capacity of data, and then compare and analyze it from the perspective of convergence characteristics at time invariant transmission channel and frequency selective fading channel.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.739-748
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• 2012

In this paper we propose a mixed effects least squares support vector machine (LS-SVM) for the censored data which are observed from different groups. We use weights by which the randomly right censoring is taken into account in the nonlinear regression. The weights are formed with Kaplan-Meier estimates of censoring distribution. In the proposed model a random effects term representing inter-group variation is included. Furthermore generalized cross validation function is proposed for the selection of the optimal values of hyper-parameters. Experimental results are then presented which indicate the performance of the proposed LS-SVM by comparing with a standard LS-SVM for the censored data.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.255-264
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• 2008

It is common in practice to use mean squared error(MSE) for prediction. Recently, Park and Shin (2005) and Jones et al. (2007) studied prediction based on mean squared relative error(MSRE). We proposed a new nonparametric way of prediction based on MSRE substituting Jones et al. (2007) and provided a small simulation study which highly supports the proposed method.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.217-223
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• 1998

공통의 자유도를 갖는 $textsc{k}$개의 비중심 카이제곱분포들의 동질성을 검정하기 위하여 우선 적당한 형태의 검정방법을 제시하였다. 통상적인 방법대로, 제시된 검정방법이 주어진 유의수준을 만족시키도록 하기 위해서는, 귀무가설하에서 제 1종의 오류의 확률을 최대화하는 모수의 최소 우호적 위치(Least favorable configuration)가 유도되었으며, 이에 따라서 주어진 유의수준을 충족하는 기각치를 도표화하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.293-301
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• 2007

We present a new global-local analysis with the aid of MLS(Moving Least Square) variable-node finite elements which can possess an arbitrary number of nodes on element master domain. It enables us to connect one finite element with a few finite elements without complex remeshing. Compared to other type global-local analysis, it does not require any superimposed mesh or need not solve the equilibrium equation twice. To demonstrate the performance of the proposed scheme, we will show several examples in relation to capturing highly local stress field using global-local analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.89-96
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• 2012

The Falling Weight Deflectormeter has been widely used in evaluating the structural adequacy of pavement structures. The deflections measured from the FWD are capable of estimating the stiffness of pavement layers and measuring the pavement responses in the pavement structure. The objective of paper is to develop the pavement response model using a partial least square regression technique based on the FWD deflection data. The partial least square regression method enables to solve the multicollinearity problem occurred in multiple regression model. It is also found that the pavement response model can be developed using the raw data when a partial least square regression was used.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.119-134
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• 2004

Generally to estimate the priority vector in AHP, an eigen-vector method or a log-arithmic least square method is applied to pairwise comparison matrix itself. In this paper an estimating method is suggested, which is applied to pairwise comparison matrix adjusted by using the eigen-decomposition of skew-symmetric matrix. We also show theoretical background, meanings, and several advantages of this method by example. This method may be useful in case that pairwise comparison matrix is quite inconsistent.