• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.16-26
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• 1989

The terminal layout problem is fundamental in may centralized computer networks, which is generated formulated as the capaciated minimum spanning tree problem (CMSTP). We present an implementation of the dual-based procedure to solve the CMSTP. Dual ascent procedure generates a good feasible solutions to the dual of the linear programming relaxation of CMSTP. A feasible primal solution to CMSTP can then be constructed based on this dual solution. This procedure can be used either as a stand-alone heuristic or, else, it can be incorporated into a branch and bound algorithm. A numerical result is given with quite favorable results.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.931-939
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• 2014

In this paper we propose the iteratively reweighted least squares procedure to solve the quadratic programming problem of support vector expectile regression with an asymmetrically weighted squares loss function. The proposed procedure enables us to select the appropriate hyperparameters easily by using the generalized cross validation function. Through numerical studies on the artificial and the real data sets we show the effectiveness of the proposed method on the estimation performances.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1286-1290
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• 2003

This paper presents a newly implemented parallel finite element procedure for contact-impact problems. Three sub-algorithms are includes in the proposed parallel contact-impact procedure, such as a parallel Belytschko-Lin-Tsay (BLT) shell element generation, a parallel explicit time integration scheme, and a parallel contact search algorithm based on the master slave slide-line algorithm. The underlying focus of the algorithms is on its effectiveness and efficiency for inclusion in future finite element systems on parallel computers. Throughout this research, a prototype code, named GT-PARADYN, is developed on the IBM SP2, a distributed-memory computer. Some numerical examples are provided to demonstrate the timing results of the procedure, discussing the accuracy and efficiency of the code.

• Journal of Korea Foundry Society
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• v.34 no.4
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• pp.136-142
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• 2014

Numerical solution of thermal stress by CAE analysis could be an effective method in product development stage of castings to predict and treat the problem of solidification cracking of castings. Quantitative stress-strain data are necessary, in this case. Tension type apparatus of a solidification crack test which can measure stress-strain relationship quantitatively was developed and the test procedure was established by this research. Solidification crack strength obtained from the following test procedure could be utilized to evaluate it in terms of effect factors on thermo-plastic characteristic of solidifying alloy such as grain size of solid, grain morphology, distribution of solid grain, etc. Proposed test procedure is as follow: Prediction of temperature at the failure site of solidification cracked specimen by computer simulation of solidification, Calculation of solid fraction of the failure site from thermodynamic solution of solidification under Scheil condition.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.167-182
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• 1999

This article is concerned with the selection of subsets of predictor variables to be included in building the binary response probit regression model. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the probit regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. The appropriate posterior probability of each subset of predictor variables is obtained through the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as the one with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.143-160
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• 1998

This article is concerned with the selection of subsets of predictor variables to be included in bulding the binary response logistic regression model. It is based on a Bayesian aproach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the logistic regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. It is done by use of the fact that cdf of logistic distribution is a, pp.oximately equivalent to that of $t_{(8)}$/.634 distribution. The a, pp.opriate posterior probability of each subset of predictor variables is obtained by the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as that with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.03a
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• pp.407-414
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• 1999

A simple seismic design procedure for pile foundation using PAR and LPILE$\^$plus/ was proposed. A case of pile foundation under a simple bridge was selected and analyzed. The calculated horizontal movements, shear forces and moments were compared with those evaluated by the numerical exact solutions, and the farmers had similar trends with the tatters.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.647-655
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• 2006

In this paper, we consider multiple comparisons for the ratio of the failure rates in two components system that the lifetimes of the components have independent exponential distributions. Also we suggest Bayesian multiple comparisons procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Finally, we give numerical examples to illustrate our procedure.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.467-474
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• 2006

In this paper we present a weighted support vector machine(SVM) and a weighted least squares support vector machine(LS-SVM) for the prediction in the heteroscedastic regression model. By adding weights to standard SVM and LS-SVM the better fitting ability can be achieved when errors are heteroscedastic. In the numerical studies, we illustrate the prediction performance of the proposed procedure by comparing with the procedure which combines standard SVM and LS-SVM and wild bootstrap for the prediction.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.224-227
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• 1997

The objective of this study is to propose a new procedure to synthesize the multi-experts priorities in AHP. To aggregate the multi-experts priorities, in this paper, we suggest a way which Decision Maker can exclude outlier matrix from group using the concept of the compatability and we introduce Delphi method to use compatability in AHP. Some numerical example are shown to illustrate the procedure.