• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1204-1209
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• 1990

This paper offers the theory and method for regression analysis of the regression model with operational parameter variables based on the fundamentals of mathematical statistics. Regression coefficients are usually constants related to the problem of regression analysis. This paper considers that regression coefficients are not constants but the functions of some operational parameter variables. This is a kind of method of two-step fitting regression model. The second part of this paper considers the experimental step numbers as recursive variables, the recursive identification with unknown operational parameter variables, which includes two recursive variables, is deduced. Then the optimization and the recursive identification are combined to obtain the sequential experiment optimum design with operational parameter variables. This paper also offers a fast recursive algorithm for a large number of sequential experiments.

• Journal of the Korean Home Economics Association
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• v.41 no.12
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• pp.207-228
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• 2003

The purpose of this study is to investigate what antecedents and how much these antecedents have an effect on mother's parenting behaviors. The subjects of this study are 251 mothers who have child 3 to 6 year old in Daegu and Kyugbook province. The data are analysed through frequency, percentile, mean, standard deviation, Cronbach's α, Pearson's correlation coefficient, multiple regression analysis, and hierarchical regression analysis. The major findings of this study are as follows：First, child's sex, temperament, and behavior problem, mother's parenting self-efficacy, and marital satisfaction and satisfaction of social support affect maternal affectionate parenting behavior. Second, child's temperament, mother's personality and parenting self-efficacy, and satisfaction of social support affect maternal control parenting behavior Third, mother's variables, especially parenting self-efficacy, have great effect on maternal affectionate parenting behavior than any other variables have. Forth, mother's variables, especially personality and efficacy of parenting, have great effect on maternal control parenting behavior than any other variables have.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.198-200
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• 1987

This paper presents the choice of appropriate sets of input variables for large-scale linear multivariable systems. It is shown that the selection of a good set of input variables for control may become important when both strong and weak input variables are available. The transmission of information from the inputs to the outputs is investigated and appropriate scaling procedures to derive a scaled input matrix are proposed. Singular value decomposition methods facilitate the quantification of the systems excitation stemming from the various input variables, and thus the selection of an appropriately strong and orthogonal set of input variables. The need for and the implementation and benefits of reducing the number of input variables are illustrated by a large-scale steam generator model of a real process.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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• pp.43-51
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• 2009

This study was designed to analyze the relationship of process quality, result quality and management performance in Korean insurance industry. For this study the linkage scheme of service quality concept is used on PZB model and BSC(Balances Score Card) system. In the linkage model, the 5 service qualitry factors used in PZB model are used as the result quality variables, and internal process factor, learning/growth factor in BSC are used the process quality variables affecting the result quality variables. And also customer satisfation factor and financial performance index are used as the management performance variables. In the ivsurance industry, the process quality variables were verified to meaningfully affect the result quality variables, and the result service quality variables were verified to affect the management performance indices. As the result, the process quality and the service quality must be emhanced for the competitiveness of Korean insurance industry.

• Journal of Navigation and Port Research
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• v.43 no.2
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• pp.134-141
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• 2019

The objective of this study was to establish whether global macroeconomic indicators affect the profitability of Korean shipping companies by using panel regression analysis. OROA (operating return on assets) and ROA (ratio of net profit to assets) were selected as proxy variables for profitability. OROA and ROA were used as dependent variables. The world GDP growth rate, interest rate, exchange rate, stock index, bunker price, freight, demand and supply of the world shipping market were set as independent variables. The size of the firm was added to the control variable. For small-sized firms, OROA was not affect by macroeconomic indicators. However, ROA was affected by variables such as interest rates, bunker prices, and size of firms. For medium-sized firms, OROA was affected by demand, supply, GDP, freight, and asset variables. However, macroeconomic indicators did not affect ROA. For large-sized firms, freight, GDP, and stock index (SCI; Shanghai Composite Index) have an effect on OROA. ROA was analyzed to be influenced by bunker price and SCI.

• Communications of the Korean Mathematical Society
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• v.20 no.3
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• pp.547-562
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• 2005

The distribution of products of random variables is of interest in many areas of the sciences, engineering and medicine. This has increased the need to have available the widest possible range of statistical results on products of random variables. In this note, the distribution of the product | XY | is derived when X and Y are Student's t and Bessel function random variables distributed independently of each other.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.124-137
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• 2001

In general, it is very efficient and effective to use screening variables that are correlated with the performance variable in case that measuring the performance variable is impossible (destructive) or expensive. The general methodology for searching surrogate variables is regression analysis. This paper considers the inspection problem in CRT (Cathode Ray Tube) production line, in which the performance variable (dependent variable) is binary type and screening variables are continuous. The general regression with dummy variable, discriminant analysis and binary logistic regression are considered. The cost model is also formulated to determine economically inspection procedure with screening variables.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.394-397
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• 2004

In this paper, we consider interval number-valued random variables and fuzzy number-valued random variables and discuss Choquet integrals of them. Using these properties, we define the Choquet expected value of fuzzy number-valued random variables which is a natural generalization of the Lebesgue expected value of Lebesgue expected value of fuzzy random variables. Furthermore, we discuss some application of them.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1231-1239
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• 2012

An estimating procedure is introduced for kernel Poisson regression when the input variables consist of numerical and categorical variables, which is based on the penalized negative log-likelihood and the component-wise product of two different types of kernel functions. The proposed procedure provides the estimates of the mean function of the response variables, where the canonical parameter is linearly and/or nonlinearly related to the input variables. Experimental results are then presented which indicate the performance of the proposed kernel Poisson regression.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.27-30
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• 1996

Determination of input variables for artificial neural network (ANN) depends entirely on the judgement of a modeller. As the number of input variables increases, the training time for the resulting ANN increases exponentially. Moreover, larger number of input variables does not guarantee better performance. In this research, we employ Genetic Algorithm for selecting proper input variables that yield the best performance in training the resulting ANN.