• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.555-566
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• 2017

For multivariate datasets with large number of variables, classical dimensional reduction methods such as principal component analysis may not be effective for data visualization. The underlying reason is that the dimensionality of the space of variables is often larger than two or three, while the visualization to the human eye is most effective with two or three dimensions. This paper proposes a working procedure which first partitions the variables into several "latent" clusters, explores individual data subsets, and finally integrates findings. We use R pakacage "ClustOfVar" for partitioning variables around latent dimensions and the principal component biplot method to visualize within-cluster patterns. Additionally, we use the technique for embedding supplementary variables to figure out the relationships between within-cluster variables and outside variables.

• Korean Journal of Child Studies
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• v.22 no.1
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• pp.35-49
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• 2001

The purpose of this study was to identify how characteristics of children, parents, and the family context relate to parental disciplinary practices and to examine the effects of cumulative positive variables on effective parental disciplinary practices. Subjects were 220 each mothers and fathers of 6-year-old children. Data were analyzed with correlation, multiple regression, and chi-square. Both Maternal and paternal disciplinary practices were correlated with child birth order, child emotionality, attention span and persistence, perceived social support and quality of life, and retrospective punitive parenting. Perceived quality of life and social support were predictive of maternal disciplinary practices and child emotionality was predictive of paternal disciplinary practices. Both mothers and fathers exposed to several positive variables were much more likely to exhibit effective disciplinary practices than parents exposed to no positive variables. Findings were generally consistent with Belsky's(1984) process model of parenting.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.47-52
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• 1997

This study was carried out to investigate effects of fabric properties and the changes of microclimates on comfort sensations and to identify effective varuables on clothing wear comfort sensations. A wied range of nontreated and functionally treated woven fabrics, knits, and nonwoven fabrics and test garments made of them were used as specimens. Linear structural equation was used to analyze causal relation among the variables on a path diagram. The results were as follows: 1. Almost of causal relations among variables were significant excdpt the effects of fabric properties including air permeability and water-vapor permebility on the changes of microclimate temperature. 2. Fabric properties were most effective variables on clothing wear comfort sensations including thermal sensation, subjeceive wettedness, and overall comfort and therefore comfort sensations and fabric properties were identified for improving clothing comfort.

• Journal of the Korean Applied Science and Technology
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• v.37 no.5
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• pp.1190-1199
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• 2020

The purpose of this study is to analyze the variables affecting the effective stroke in the swing performed through 12 weeks of training for golf beginners, and to provide basic data on the effective stroke factors for the golf beginners to settle on the fairway. Twenty subjects were participate in the study (age: 21.35±1.69 yrs, height: 176.75±7.99 cm, weight: 70.70±9.76 kg). All subjects were subjected to a 12-week golf training, and trackman 4 was used in the 12th week to calculate variables affecting the effective stroke during a golf swing. Trackman data was divided into club-variables and ball-variables, and a binary logistic regression analysis was performed to find out the variables affecting effective strokes. In club-variables, high dynamic loft and low face angles were found in effective stroke, and in ball-variables, fast ball speed, large smash factor, high launch angle, and many spin rates were also found in effective stroke. As a result of the binary logistic regression analysis of club-variables, the probability of an effective stroke increased as the club speed and dynamic loft increased, and the probability of an effective stroke decreased as the face angle increased. The influence of effective stroke in the club-variables was in the order of dynamic loft, face angle, and club speed. In the ball-variable, the probability of an effective stroke increased when the lunch angle increased, and the probability of an effective stroke decreased as the lunch direction increased. As a condition to increase the probability of effective stroke based on the results, it is necessary to increase the club speed through high dynamic loft and low face angle during swing through continuous practice. Through this, the probability of effective stroke through increasing the launch angle and decreasing the launch direction will increase.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.161-168
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• 2014

In mixture experiments with process variables, we consider the case that some of process variables are either uncontrollable or hard to control, which are called noise variables. Given the such mixture experimental data with process variables, first we study how to search for candidate models. Good candidate models are screened by the sequential variables selection method and checking the residual plots for the validity of the model assumption. Two methods, which use numerical optimization methods proposed by Derringer and Suich (1980) and minimization of the weighted expected loss, are proposed to find a cost-effective robust optimal condition in which the performance of the mean as well as the variance of the response for each of the candidate models is well-behaved under the cost restriction of the mixture. The proposed methods are illustrated with the well known fish patties texture example described by Cornell (2002).

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.180-183
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• 2003

In this research, on-line model for prediction of effective strain distribution hi strip on finishing mill process is prescribed. It has been developed using several selected non-dimensional parameters and previously made average effective strain model via series of finite element process simulations, $\Delta$$\varepsilon$ was introduced to describe the effective strain distribution in strip. To confirm adequate non-dimensional variables uniqueness test was done. And to decide the order of polynomial in on-line model equation tendency test for each variables was done. The prediction accuracy of the proposed model is examined through comparison with finite element calculation results.

• Korean Journal of Child Studies
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• v.32 no.3
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• pp.19-41
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• 2011

This paper was an examination of gender-specific behaviors in children and the types of bullying behavior among 1,181 fifth and sixth grade elementary schools student identified were then classified. Differences were identified in individual variables, family variables, and school variables. The data thus collected were subjected to descriptive and comparative statistical analysis using the SPSS software program. Our results showed that multiple discriminant analysis yielded a function of individual, family and school variables that proved effective in classifying bully, reinforcer, assistant, victim, outsider and defender types in boys. In girls, multiple discriminant analysis yielded a function of individual variables that was effective in classifying bully, reinforcer, assistant, victim, outsider and defender types.

• Journal of Engineering Education Research
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• v.16 no.3
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• pp.10-19
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• 2013

Recently, Korean universities have increased the number of English Medium Instruction (EMI) lectures in order to allow students to gain both specialized knowledge and enhanced English ability. Previous researches on effective EMI lectures have focused on exploring the effects of learners' cognitive and affective characteristics on learning outcomes. Whereas the input variables of learning have been investigated as predicting variables of effects in EMI lectures, there has been a few research for investigating process variables to yield learning outcomes. The purpose of this study is to analyze the structural relationships among variables affecting on learner satisfaction and effects. The participants are 209 engineering students from various majors. Independent variables are defined as English motivation, English competency, and English confidence, a mediated variable is Cognitive engagement, and dependent variables are Learning satisfaction and Educational effect perception. The results show that the relationships are statistically significant: learners' English competency & English confidence ${\rightarrow}$ Cognitive engagement ${\rightarrow}$ Learning satisfaction ${\rightarrow}$ Educational effect perception. Especially, the structural model confirms that the effect of learners' English confidence on Learning satisfaction and Educational effect perception is mediated by the level of learners' Cognitive engagement. Further, the implication for effective EMI lectures is discussed based on the observed research results.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.831-844
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• 2008

Since cooperatives consist of many distinct members in the management environment and characteristics, it is necessary to make similar cooperatives into a few groups for the effective risk management of cooperatives' mutuality bank. This paper is a priori research for suggesting a guidance for effective risk management of cooperatives with different management strategy. For such purpose, we propose a way to group the members of cooperative's mutuality bank. The 30 continuous variables which is relative to cooperatives' management status are considered and six factors are extracted from those variables through factor analysis with empirical consideration to avoid wrong grouping and to enhance the practical interpretation. Based on extracted six factors and additional 3 categorical variables, six representative groups are derived by the two step clustering analysis. These findings are useful to execute a discriminatory risk management and other management strategy for a mutuality bank and others.

• Korean Management Science Review
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• v.11 no.1
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• pp.165-186
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• 1994

The increasing importance of end-user computing(EUC) is reflected in the proliferation of academic and practitioner literature on the subject. However, much of this literature assumes widely differing dimensions of EUC, which tends to make many researchers suggest different success factors for managing EUC. Moreover, the variables regarding EUC management have been considerably restricted in previous research. In order to overcome these problems, this study focuses on identifying EUC dimensions theoretically and deriving generic variables representing the mode of EUC management by factor analysis first. Then, based on these EUC dimensions and generic variables for EUC management, effective ways of managing EUC are hypothesized and tested empirically through a mail survey of end-users in 83 Korean business organizations. The results suggest that effective management of EUC should be different depending upon which dimension more importance is attached to in implementing EUC.