• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.3
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• pp.245-256
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• 2014

This work is focused on the boundary layer and heat transfer characteristics of hydromagnetic flow over a stretching sheet with variable thickness. Steady, two dimensional, nonlinear, laminar flow of an incompressible, viscous and electrically conducting fluid over a stretching sheet with variable thickness and power law velocity in the presence of variable magnetic field and variable temperature is considered. Governing equations of the problem are converted into ordinary differential equations utilizing similarity transformations. The resulting non-linear differential equations are solved numerically by utilizing Nachtsheim-Swigert shooting iterative scheme for satisfaction of asymptotic boundary conditions along with fourth order Runge-Kutta integration method. Numerical computations are carried out for various values of the physical parameters and the effects over the velocity and temperature are analyzed. Numerical values of dimensionless skin friction coefficient and non-dimensional rate of heat transfer are also obtained.

• Structural Engineering and Mechanics
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• v.11 no.4
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• pp.443-460
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• 2001

This paper presents an effective application of a variable-node axisymmetric solid element designated as AQV (Axisymmetric Quadrilateral Variable-node element). The variable-node element with physical midside nodes helps to overcome some problems in connecting the different layer patterns on a quadrilateral mesh in the adaptive h-refinement. This element alleviates the necessity of imposing displacement constraints on irregular (hanging) nodes in order to enforce the inter-element compatibility. Therefore, the elements with variable mid-side nodes can be used effectively in the local mesh refinement for the axisymmetric structures which have stress concentrations. A modified Gaussian quadrature should be adopted to evaluate the stiffness matrices of the variable-node elements mainly because of the slope discontinuity of assumed displacement within the elements. Some numerical examples show the usefulness of variable-node axisymmetric elements in the practical application.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.303-306
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• 1995

In this study we present the inverse correlation method to select the exploratory variables, while Sugeno used RC method in his paper[6] We assume linear model with measurement error variables as in Fuller's Book[9]. we provide possibilistic linear model and predict the fuzzy response variable in case of fuzzy exploratory variables. By plotting data we can divide them for piecewise plane and provide the piecwise possibilistic linear model. If the exploratory variable is fuzzy trapezoidal variable or interval variable, then we estimate fuzzy trapezoidal variable or interval variable, then we estimate fuzzy trapezoidal response variable respondent to it. We will illustrate using Nonlinear System data in Sugeno's paper

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.69-74
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• 2021

This paper accumulates the product structure data such as bond obligation ratio and investment ratio for variable insurance using crawling from the insurance company's API, also accumulates variable insurance income and project expenses for variable insurance using crawling from the API of life insurance association. From these accumulated data, the correlation coefficient between fund product and customer preference is calculated with an investment algorithm, and variable insurance funds by customer investment preference and product structure are recommended according to market conditions. From the simulation results, it is shown that the proposed variable insurance management system properly recommends and manages variable insurance according to customer preferences.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.

• 한국노년학
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• v.37 no.3
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• pp.637-653
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• 2017

Meta-analysis was conducted on 56 studies published in Korea until April 2017 to systematically integrate factors of ego integrity of the elderly. The variables related to ego integrity were divided into 6 groups of variable, and the effect sizes were computed for each variable of their groups. The analysis results are as follows. First, the total effect size showed the middle effect size, and the effect size according to the variable group showed the largest effect size for the positive psychological variable group, followed by the negative psychological variable, the physical variable, the familial variable, the social variable and the demographic variable. Second, the largest effect size of the sub-variables on the each individual variable group showed positive psychological variable was life quality, negative psychological variable was depression, physical variable was health behavior, familial variable was children relationship, social variable was social support and demographic variable was economic status. As described above, suggesting that these variables may have a strong influence on ego integrity among the variables related to ego integrity because the quality of life, life satisfaction and depression were shown as the largest effective variables related to ego integrity.

• KIEAE Journal
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• v.15 no.4
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• pp.37-43
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• 2015

Purpose : The study applied control strategy to reduce through optimal control and operation of pump by applying control on variable speed to the circulation pump of HVAC system in the office building. The study has the purpose to review validity of control on variable speed as ESMs(Energy Saving Measures) and establish the control technology on variable speed pump. The study performed reduction analysis of building energy and economic evaluation of pump through energy effectiveness control strategy of HVAC system. Method: The study sought possible reduction through energy control strategy which can provide proper flow fitting to building load by applying control on variable speed pump. The study applied control strategy to reduce through pressure differential set-point control and operation of pump by applying control on variable speed to the circulation pump of HVAC system in the office building. Result : The results showed that about 16-35% of pump energy could be saved by using these optimal control strategies. In the result of analysis on 10 years life cycle cost of analysis on payback period of initial investment pump, variable speed pump control showed 5.1 years.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.459-473
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• 2004

It has well known that an exhaustive search algorithm suggested by Breiman et. a1.(1984) has a trend to select the variable having relatively many possible splits as an splitting rule. We propose an algorithm to overcome this variable selection bias problem and then construct unbiased regression trees based on the algorithm. The proposed algorithm runs two steps of selecting a split variable and determining a split rule for binary split based on the split variable. Simulation studies were performed to compare the proposed algorithm with Breiman et a1.(1984)'s CART(Classification and Regression Tree) in terms of degree of variable selection bias, variable selection power, and MSE(Mean Squared Error). Also, we illustrate the proposed algorithm with real data sets.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.271-281
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• 2013

This paper considers a problem of classification of variable stars based on functional data analysis. For a better understanding of galaxy structure and stellar evolution, various approaches for classification of variable stars have been studied. Several features that explain the characteristics of variable stars (such as color index, amplitude, period, and Fourier coefficients) were usually used to classify variable stars. Excluding other factors but focusing only on the curve shapes of variable stars, Deb and Singh (2009) proposed a classification procedure using multivariate principal component analysis. However, this approach is limited to accommodate some features of the light curve data that are unequally spaced in the phase domain and have some functional properties. In this paper, we propose a light curve estimation method that is suitable for functional data analysis, and provide a classification procedure for variable stars that combined the features of a light curve with existing functional data analysis methods. To evaluate its practical applicability, we apply the proposed classification procedure to the data sets of variable stars from the project STellar Astrophysics and Research on Exoplanets (STARE).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.341-348
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• 2021

The aim of this study is to fill gaps in emerging empirical evidence and negative electronic word of mouth (NeWOM) in repurchase intention (RI) moderated by the roles of social network sites (SNS) and company mitigation response (CMR). This type of research is descriptive. The sample used in this study is online consumers who buy energy drinks, based on the questionnaire obtained by 145 respondents. Based on the results of testing the estimation of the structural equation model, it was found that the negative variable brand experience sharing had no significant effect on NeWOM; the negative variable electronic reviews had a significant effect on the electronic word of mouth variable, the negative variable electronic reviews had a significant effect on the negative electronic variable word of mouth, the variable intensity of the use of social networking sites can strengthen the direction of the causal influence between the negative variables sharing brand experiences on negative electronic words of mouth. The variable social networking sites usage intensity can strengthen the direction of the effect of causality between negative electronic review variables on negative electronic word of mouth, the negative brand experience sharing variable does not have a significant effect on the repurchase intention variable.