• Journal of the Korean Mathematical Society
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• v.43 no.5
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• pp.1099-1114
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• 2006

Relations between closure-type properties of hyperspaces over a $\v{C}ech$ closure space (X, u) and covering properties of (X, u) are investigated.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1996.06a
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• pp.111-131
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• 1996

In order to analyze stamping processes and to select optimum material properties of sheet steels for customer lines, 3-dimensional finite element analysis software were used. Commercial explicit finite element code, PAM-STAMP, was able to simulate 3-dimensional press formed parts with good accuracy and gave some useful results by orthogonal array experiments. Deformation of draw-bead were predicted by ABAQUS accurately, so that material selection for those parts by simulation were possible.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.149-161
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• 2019

In this article, we suggest the following approaches to simultaneous variable selection and outlier detection. First, we determine possible candidates for outliers using properties of an intercept estimator in a difference-based regression model, and the information of outliers is reflected in the multiple regression model adding mean shift parameters. Second, we select the best model from the model including the outlier candidates as predictors using stochastic search variable selection. Finally, we evaluate our method using simulations and real data analysis to yield promising results. In addition, we need to develop our method to make robust estimates. We will also to the nonparametric regression model for simultaneous outlier detection and variable selection.

• Advances in concrete construction
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• v.14 no.1
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• pp.15-34
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• 2022

The use of waste rubber in concrete can reduce natural aggregate consumption and improve some technical properties of concrete. Although there are several equations for estimating the mechanical properties of concrete containing waste rubber, limited numbers of machine learning-based models have been proposed to predict the mechanical properties of rubbercrete. In this study, an extensive database of the mechanical properties of rubbercrete was gathered from a comprehensive survey of the literature. To model the mechanical properties of rubbercrete, M5P tree and linear gene expression programming (LGEP) methods as two machine learning techniques were employed to achieve reliable mathematical equations. Two procedures of input variable selection were considered in this study. The crucial component ratios of rubbercrete and concrete age were assumed as the input variables in the first procedure. In contrast, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber were considered the second procedure of the input variables. The results show that the models obtained by LGEP are more accurate than those achieved by the M5P model tree and existing traditional equations. Besides, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber are better predictors of the mechanical properties of rubbercrete compared to the first procedure of input variable selection.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.147-157
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• 2015

We consider a sparse high-dimensional linear regression model. Penalized methods using LASSO or non-convex penalties have been widely used for variable selection and estimation in high-dimensional regression models. In penalized regression, the selection and prediction performances depend on which penalty function is used. For example, it is known that LASSO has a good prediction performance but tends to select more variables than necessary. In this paper, we propose an additive sparse penalty for variable selection using a combination of LASSO and minimax concave penalties (MCP). The proposed penalty is designed for good properties of both LASSO and MCP.We develop an efficient algorithm to compute the proposed estimator by combining a concave convex procedure and coordinate descent algorithm. Numerical studies show that the proposed method has better selection and prediction performances compared to other penalized methods.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.109-117
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• 2008

This research analyzed which average comparisons and differences between groups' view motive and selection for information sources, product properties with theater animation spectator. Based on view frequency, each of groups' organization were classified to heavy, occasional, and thinly viewers. As average comparison analysis result, firstly, view motive appeared in order to "want to see animation", "to spend time and leisure activity", "to enjoy fun activity", and "because of others canvassing or recommendation", etc. Secondly, view selection for information source appeared in order to "rumor circumstance or reputation", "theater or TV previews", "internet evaluation and grade", etc. At last, view selection for practical property appeared in order to "story", "character", "special effects", "background music", "background art", "director/directing", "manufacturer/nation", and "dubbing of artist". As difference between group result, view motive and selection for product properties appeared significant differences between each of group. To the contrary, view selection for information sources did not appeared significant differences between each of group.

• Journal of the Korean Mathematical Society
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• v.43 no.3
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• pp.677-690
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• 2006

We show that a group of three closure properties including the selectively Pytkeev property coincide on $C_k$(X) for a locally compact X. We also introduce a new game characterization of these properties for such spaces.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1653-1660
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• 2016

Smoothly clipped absolute deviation (SCAD) penalty is known to satisfy the desirable properties for penalty functions like as unbiasedness, sparsity and continuity. In this paper, we deal with the regression function estimation and variable selection based on SCAD penalized censored regression model. We use the local linear approximation and the iteratively reweighted least squares algorithm to solve SCAD penalized log likelihood function. The proposed method provides an efficient method for variable selection and regression function estimation. The generalized cross validation function is presented for the model selection. Applications of the proposed method are illustrated through the simulated and a real example.

• Culinary science and hospitality research
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• v.21 no.4
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• pp.55-71
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• 2015

The purpose of current study is to identify moderator effects of a number of use in terms of the influences of selection properties as perceived by college foodservice. This study was collected 297 survey from college students in Busan and Gyeongnam using the statistics program SPSS (18.0). Result shown that the selection properties of the institutional food service were analyzed with four elements: physical environments, service of worker, diversity of menu, and quality of food. All of the selection properties were found to have significant effects on satisfaction. Although there was no significant effect on the second stage, partial moderating effects were found in the third stage only when the interaction term of physical environments ${\times}$ the number of use is applied. Considering these results, it can be considered that a number of use of foodservice facilities are moderated by physical environments. Therefore, it implies that institutional foodservice operators should improve physical environments including interior, tableware, and cleanliness. In addition, satisfaction and preference were found to be closely related each other, which indicates that preference is improved as satisfaction increases.

• Journal of Korean Dental Science
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• v.15 no.2
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• pp.112-120
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• 2022

In this article, the contemporary root canal treatment procedure using nickel-titanium (NiTi) instruments was reviewed to understand the correlations between the properties of files and safety of the clinical usage. Literatures were reviewed according to the process of clinical procedure of the root canal preparation, mainly for shaping during orifice flaring, glide-path preparation, and main canal instrumentation. Considering the reasons for NiTi file fracture, clinically implacable issues and ideas were discussed to reduce the fracture risk and increase clinical efficiency of the NiTi file systems. Various kinds of NiTi file systems have their own characteristics and properties given from their geometries and heat treatments and so on. Proper selection and careful usage of the NiTi file systems may reduce the risk of file fracture and increase the efficiency of NiTi file systems. Understanding of the clinical implications from the mechanical properties and characteristics of the engine driven NiTi instruments may decrease the risk of NiTi file fractures and increase the success rate in root canal treatment.