• Journal of Korean Academy of Nursing
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• v.50 no.2
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• pp.210-227
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• 2020

Purpose: This study aimed to develop a scale to measure variables related to alcohol drinking prevention behavior in early elementary school, based on the theory of planned behavior. Methods: A scale was developed to measure variables related to alcohol drinking prevention behavior. Initial items for direct evaluation were constructed through a literature review, and those for belief-based indirect measure were generated through interviews with 30 second- and third-grade elementary school students. The collected data from 286 third-grade elementary school students were then subjected to item analysis, exploratory and confirmative factor analysis, criterion-related validity testing, and internal consistency assessment. Results: The final scale consisted of 35 items. Intention, attitudes, subjective norms, and perceived behavioral control explained 82.7% of the variance; behavioral beliefs, normative beliefs, and control beliefs explained 65.6% of the variance; and evaluation of outcome, motivation to comply, and power of control beliefs explained 72.8% of the variance. The confirmatory factor analysis indicated that the theoretical models had a satisfactory goodness of fit. Criterion-related validity was confirmed between the direct evaluation variables and the indirect measure variables (attitudes r=.64, p<.001; subjective norms r=.39, p<.001; perceived behavioral control r=.62, p<.001). Cronbach's α was .89 for the direct evaluation variables and .93 for the indirect measure variables. Conclusion: The scale developed in this study is valid and reliable. It could be used to measure and explain variables related to alcohol drinking prevention behavior in early elementary school.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.211-221
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• 1998

It is very important to have a satisfactory measurement system, since it is useless to try to improve the manufacturing process without an adequate measurement system. Therefore, evaluation of the measurement system is the first step for the quality improvement of the manufacturing process. To estimate the measurement error we must conduct a controlled gage repeatability and reproducibility(gage R&R) study. Many manufacturers use a gage or instrument to measure multiple dimensions for the overall quality of the manufactured parts. In this case, it is necessary to estimate the gage R&R for multiple dimensions. When a gage measures a large number of dimensions of a part, it is very time-consuming and costly to measure all the dimensions. In this paper we propose the use of the principal component analysis method to identify a few principal components out of the original multivariate measurement capability to explain most of the measurement system variation pattern.

• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.813-820
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• 2009

In this paper, we review the utility-based generalization of the Shannon entropy and Kullback-Leibler information measure as the U-entropy and the U-relative entropy that was introduced by Friedman et al. (2007). Then, we derive some relations between the U-relative entropy and other information measures based on a parametric family of utility functions.

• Progress in Superconductivity and Cryogenics
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• v.10 no.3
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• pp.1-4
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• 2008

For the effective evaluation of superconducting properties of a coated conductor, with a long length, a non destructive characterization technique including a reel-to-reel (R2R) Hall measuring system have been developed. A non-contact R2R Hall sensor array system was particularly designed to measure the superconducting property of coated conductors. The superconducting properties of long length coated conductors were measured by using this device. It was demonstrated that this system was convenient to measure the intensity and distribution of the magnet field applied perpendicular to the surfaces of the coated conductors. Using this device, the defect and low critical current density(Jc) area of coated conductors could be detected in real-time measurement.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.605-618
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• 2018

Risk management has been a crucial part of the daily operations of the financial industry over the past two decades. Value at Risk (VaR), a quantitative measure introduced by JP Morgan in 1995, is the most popular and simplest quantitative measure of risk. VaR has been widely applied to the risk evaluation over all types of financial activities, including portfolio management and asset allocation. This paper uses the implementations of multivariate GARCH models and copula methods to illustrate the performance of a one-day-ahead VaR prediction modeling process for high-dimensional portfolios. Many factors, such as the interaction among included assets, are included in the modeling process. Additionally, empirical data analyses and backtesting results are demonstrated through a rolling analysis, which help capture the instability of parameter estimates. We find that our way of modeling is relatively robust and flexible.

• Journal of the Korean Mathematical Society
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• v.39 no.4
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• pp.495-507
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• 2002

In this paper, the characterization results related to Chernoff-type inequalities are applied for exponential-type (continuous and discrete) families. Upper variance bound is obtained here with a slightly different technique used in Alharbi and Shanbhag [1] and Mohtashami Borzadaran and Shanbhag [8]. Some results are shown with assuming measures such as non-atomic measure, atomic measure, Lebesgue measure and counting measure as special cases of Lebesgue-Stieltjes measure. Characterization results on power series distributions via Chernoff-type inequalities are corollaries to our results.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.57-64
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• 2018

In this paper, a method to measure similarity between two graphs is proposed, which is based on centralities of the graphs. The similarity between two graphs $G_1$ and $G_2$ is defined by the difference of distance($G_1$, $G_{R_1}$) and distance($G_2$, $G_{R_2}$), where $G_{R_1}$ and $G_{R_2}$ are set of random graphs that have the same number of nodes and edges as $G_1$ and $G_2$, respectively. Each distance ($G_*$, $G_{R_*}$) is obtained by comparing centralities of $G_*$ and $G_{R_*}$. Through the computational experiments, we show that it is possible to compare graphs regardless of the number of vertices or edges of the graphs. Also, it is possible to identify and classify the properties of the graphs by measuring and comparing similarities between two graphs.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.417-427
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• 2015

Measures in response rate used to measure the representativeness of the sample (the more high response rate) better explain the representativeness of the sample. However, we cannot often explain the representativeness of the sample because there is nonresponse even in the high response rate. Therefore, Schouten et al. (2009) presented a new R-indicator measure that can be described as a representative of the sample. We research the new estimator of the R-indicator in this paper because there are parameters that require estimations. We describe the meanings as representative of the R-indicator; consequently, the bias and efficiency of the proposed estimator for R-indicator are compared to the existing estimator under various simulations. The representativeness of the sample is also explained by applying the proposed estimators in the actual data.

• Communications of the Korean Mathematical Society
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• v.17 no.1
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• pp.71-80
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• 2002

We give a formulation of the large deviation property for rescalings of random measures on the d-dimensional Euclidean space R$^{d}$ . The approach is global in the sense that the objects are Radon measures on R$^{d}$ and the dual objects are the continuous functions with compact support. This is applied to the cluster random measures with Poisson centers, a large class of random measures that includes the Poisson processes.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.3
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• pp.579-586
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• 2009

Let $\varphi$ be a complete probability measure on $\mathbb{R}$, let $m_{\varphi}$ be the analogue of Wiener measure over paths on [0, T] and let f(t) be continuously differentiable on [0, T]. In this note, we give the analogue of Wiener measure $m_{\varphi}$ of {x in C[0, T]$\mid$x(0) < f(0) and $x(s_0){\geq}f(s_{0})$ for some $s_{0}$ in [0, T]} by use of integral equation techniques. This result is a generalization of Park and Paranjape's 1974 result[1].