• Child Health Nursing Research
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• v.16 no.4
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• pp.297-303
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• 2010

Purpose: The purpose of this study was to identify the relationship of self-differentiation, family function and mental health among adolescents. Methods: The data were collected from 967 adolescents and analyzed using descriptive statistics, t-test, ANOVA, Scheffe's test, Pearson correlation coefficient and Stepwise multiple regression with the SPSS program. Results: Mental health differed according to grades, sibling position, father's education and mother's education. Self-differentiation and family function had a significant negative correlation with mental health. Multiple regression analysis showed recognition.emotional function, emotional cutoff and family projection as influencing self-differentiation. Grades, affective responsiveness in family function, and sibling position explained 20.8% of the total variance in mental health. Conclusion: The findings show that self-differentiation and family function influence mental health, indicating a need to develop nursing intervention programs to enhance adolescents' mental health and prevent negative outcomes. For these programs, the family must be included.

• International Journal of Costume and Fashion
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• v.10 no.2
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• pp.51-59
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• 2010

This study regarded fashion selection criteria as clothing consumption value and desired fashion images, and examined selection differences according to regional subculture groups. Clothing consumption value is a direct value that people seek with clothing products and a perceived value which is divided into emotional, social, price, quality values. Fashion image which is a feeling communicated to others by wearing a certain fashion style is the most superficial value. Multivariate Analysis of Variance (MANOVA) was performed to test the differences between regional subculture groups in clothing consumption values and desired fashion images. We found some differences in clothing consumption value specifically in emotional value and social value. The group differences were remarkably significant in fashion image comparison. 'Kang-nam' group pursued 'lively', 'sophisticated', 'charming', feminine', 'gorgeous' image more than 'Kang-buk' group. While 'Kang-buk' group produced lower scores in ideal fashion images, the group had significant higher seeking in 'sportive' image compared to 'Kangnam' group.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2438-2450
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• 2000

The Design Axioms provide a general framework for design methodologies. The axiomatic design framework has been successfully applied to various design tasks. However, the axiomatic design has been rarely utilized in the detailed design process of structures where the optimization technology is generally carried out. The relationship between the axiomatic design and the optimization is investigated and Logical Decomposition method is developed for a systematic structural optimization. The entire optimization process is decomposed to satisfy the Independence Axiom. In the decomposition process, design variables are grouped according to sensitivities. The sensitivities are evaluated by the Analysis of Variance(ANOVA) to avoid considering only local values. The developed method is verified through examples such as the twenty -five members transmission tower and the two -bay-six-story frame.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.57-76
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• 2007

Kriging is a nonparametric regression method used in geostatistics for estimating curves and surfaces for spatial data. It may come as a surprise that the Kriging estimator, normally derived as the best linear unbiased estimator, is also the solution of a particular variational problem. Thus, Kriging estimators can also be interpreted as generalized smoothing splines where the roughness penalty is determined by the covariance function of a spatial process. We build off the early work by Silverman (1982, 1984) and the analysis by Cox (1983, 1984), Messer (1991), Messer and Goldstein (1993) and others and develop an equivalent kernel interpretation of geostatistical estimators. Given this connection we show how a given covariance function influences the bias and variance of the Kriging estimate as well as the mean squared prediction error. Some specific asymptotic results are given in one dimension for Matern covariances that have as their limit cubic smoothing splines.

• The Journal of Korean Academic Society of Nursing Education
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• v.22 no.2
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• pp.182-190
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• 2016

Purpose: This study explored factors that influence happiness in nursing students. Methods: The participants were 182 nursing students at a university in B city. Data were collected with a structured questionnaire. Data were analyzed using descriptive analysis, t-test, ANOVA, Pearson correlation coefficients, and multiple regression with the SPSS Win 22.0. Results: Happiness in nursing students correlated significantly with resilience (r=.79, p<.001) and self-differentiation (r=.38, p<.001). Resilience, subjective health status, and selection motivation to study nursing explained 69.1% of the variance in happiness. Conclusion: The study shows resilience, subjective health status, and selection motivation to study nursing are important factors for happiness in nursing students. These findings can be utilized to develop strategies for increasing nursing students' happiness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.305-312
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• 2005

Three classification algorithms are tested using musical instruments. Several classification algorithms are introduced and among them, Bayes rule, NN and k-NN performances evaluated. ZCR, mean, variance and average peak level feature vectors are extracted from instruments sample file and used as data set to classification system. Used musical instruments are Violin, baroque violin and baroque cello. Results of experiment show that the performance of NN algorithm excels other algorithms in musical instruments classification.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.68-75
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• 1991

The purpose of this thesis is to develop the new technique for the analysis of seasonal time series by extending the vector sample auto-correlation function(VSACF), which was developed for ARMA modelling procedure. After the problems of VSACF for modelling seasonal time series are investigated, the adjacent variance is defined and used for decomposing the seasonal factor from the seasonal time series. The seasonal indices are calculated and the VSACF is applied to the transformed series. The automatic procedure for modelling seasonal time series is suggested and applied to the real data, the international airline passenger travel.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.258-263
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• 2001

This paper complements the shortcomings of the original edge following algorithm. We propose a new edge following method which exploits the uncertainty residing in fingerprint analysis. Based on fuzzy set theory, the proposed algorithm computes the current local quality of a fingerplinL image by considering two Jocal properties: a relative cardinality of fuzzy set and a local variance. According to the calculated local quality infonnation, we dynamically adopt the appropriate different methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.59-66
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• 2005

In this paper, a robust stationary Kalman filter is designed by minimizing selected performance indices so that it is less sensitive to uncertainties. The uncertainties include not only stochastic factors such as process noise and measurement noise, but also deterministic factors such as unknown initial estimation error, modeling error and sensing bias. To reduce the effect on the uncertainties, three performance indices that should be minimized are selected based on the quantitative error analysis to both the deterministic and the stochastic uncertainties. The selected indices are the size of the observer gain, the condition number of the observer matrix, and the estimation error variance. The observer gain is obtained by optimally solving the multi-objectives optimization problem that minimizes the indices. The robustness of the proposed filter is demonstrated through the comparison with the standard Kalman filter.

• Journal of Fashion Business
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• v.9 no.5
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• pp.114-121
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• 2005

The purpose of this study was to examine which factors had affected on Internet shopping addiction significantly related to fashion products. 235 female college students were surveyed for this study. For data analysis, descriptive statistics, $X^2$-test, ANOVA and Duncan test were used. As the results, generally Internet shopping addiction was correlated to Internet addiction, impulse, self-esteem, age, the usage time of Internet, and Internet skills. Also, heavy Internet shopping addictive group had higher Internet addictive tendency, impulsive tendency than light Internet shopping addictive group, while heavy Internet shopping addictive group had lower self-esteem than light Internet shopping addictive group. Also, multiple regression results revealed that Internet addictive tendency, self-esteem, impulsive tendency, age accounted for 38.1% of the explained variance in Internet shopping addiction. Based on these results, fashion marketing strategies would be suggested.