• Journal of the Korean Society of School Health
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• v.34 no.1
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• pp.53-61
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• 2021

Purpose: The purpose of this study was to investigate the affect of eating behaviors on subjective health of multi-cultural adolescents in South Korea. Methods: This study is designed as cross-sectional. Using the statistics from the 15th (2019) Korea Youth Risk Behavior Web-based Survey, multiple logistic regression analysis was conducted. Overall, 711 multi-cultural adolescents were included in the analysis. Results: When analyzing the factors affecting the subjective health status of multi-cultural adolescents, normal body mass index (OR: 0.56, 95% CI: 0.35~0.89) and milk consumption (OR: 0.54, 95% CI: 0.35~0.83) showed a lower risk of being unhealthy, while skipping breakfast for 5 days (OR: 1.97, 95% CI: 1.33~2.93) and convenience store food consumption (OR: 1.59, 95% CI: 1.05~2.40) showed a higher risk of being unhealthy. Conclusion: It is necessary to form positive eating habits that influence the subjective health perception of multi-cultural adolescents. Therefore, appropriate dietary education and systematic support should be provided for multi-cultural families.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.851-865
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• 2017

Ransomware such as WannaCry is a global issue and methods to defend against malware attacks are important. We have to be able to classify the malware types efficiently in order to minimize the damage from malwares. This study makes models to classify malware properly with various statistical techniques. Several classification techniques such as logistic regression, random forest, gradient boosting, and support vector machine are used to construct models. This study also helps us understand key variables to classify the type of malicious software.

• Journal of Korean Academy of Nursing
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• v.48 no.2
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• pp.143-153
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• 2018

Purpose: The purpose of this study was to identify factors predicting behavioral and psychological symptoms of dementia (BPSD) in persons with dementia. Factors including the patient, caregiver, and environment based on the multi-dimensional behavioral model were tested. Methods: The subjects of the study were 139 pairs of persons with dementia and their caregivers selected from four geriatric long-term care facilities located in S city, G province, Korea. Data analysis included descriptive statistics, inverse normal transformations, Pearson correlation coefficients, Spearman's correlation coefficients and hierarchical multiple regression with the SPSS Statistics 22.0 for Windows program. Results: Mean score for BPSD was 40.16. Depression (${\beta}=.42$, p<.001), exposure to noise in the evening noise (${\beta}=-.20$, p=.014), and gender (${\beta}=.17$, p=.042) were factors predicting BPSD in long-term care facilities, which explained 25.2% of the variance in the model. Conclusion: To decrease BPSD in persons with dementia, integrated nursing interventions should consider factors of the patient, caregiver, and environment.

• Journal of the Korean Home Economics Association
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• v.47 no.9
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• pp.27-36
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• 2009

The purpose of this study to gather information on demographic statistics, children’s attachment to their mothers, and daily stress variants in order to assess their effects on child’s self-concept and depression within multi-ethnic familiy settings. A questionnaire survey was used to targeted 3rd, 4th, 5th and 6th graders in elementary schools in Jeonnam. A total of 158 children were surveyed. SPSS for Windows 12.0 was used to carry out descriptive, and comparative statistical analysis such as Cronbach's $\alpha$, correlations analysis, and a hierarchical regression analysis. Result showed that the most significant variant affecting self-concept among children from multi-ethnic families was attachment to their mothers. Other related individual variants were in order of importance, communication skills, feelings of alienation, and mothers’ nationalities. The variant most responsible for having an affect on depression among children from multi-entnic families was the attachment to their mothers. Other related individual variants were in order of importance, feelings of alienation, stress from peer relationships, mothers’ nationalities, and stress from economic and physical environments.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.232-236
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• 2000

Multi-regression statistical analyses were applied for the water quality data of shallow alluvial ground water (n = 47) collected from the Youngdeok area, in order to quantitatively generalize the natural (non-anthropogenic) causes of regional water quality variation. Seven samples having the high contamination index ( $C_{a}$ > 3) reflect the striong effects by anthropogenic activity. Most of the alluvial groundwaters have acquired their quality primarily due to the dissolution of carbonate minerals. The results of multi-regression analysis show that chlorine is mainly derived from seawater effect. Sulfur isotopic compositions of dissolved sulfur and the S $O_4$/Cl ratio also enable us to discriminate the samples (n = 18) which are affected by atmospheric input of marine aerosol (sea-spray) and also by mixing between freshwater and seawater. Hydrogen and oxygen isotope data of the samples collected lie close to the local meteoric water line obtained from nearby Pohang city but has lower slope (5.45) on the $\delta$D-$^{18}$ O plot, indicating that alluvial groundwater was recharged from infiltrated meteoric water which has undergone some degree of kinetic evaporation. The estimated initial isotopic composition of the recharged water ($\delta$D = -74.8$^{0}$ /$_{00}$, $\delta$$^{18}$ O = -10.8$^{[-1000]}$ /$_{[-1000]}$ ) suggests that the alluvial ground water recharge largely occurs during summer storm events.s.s.

• Atmosphere
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• v.25 no.4
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• pp.669-683
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• 2015

In this study, we investigated the prediction skills of four multiple linear regression methods for monthly air temperature over South Korea. We used simulation results from four regional climate models (RegCM4, SNURCM, WRF, and YSURSM) driven by two boundary conditions (NCEP/DOE Reanalysis 2 and ERA-Interim). We selected 15 years (1989~2003) as the training period and the last 5 years (2004~2008) as validation period. The four regression methods used in this study are as follows: 1) Homogeneous Multiple linear Regression (HMR), 2) Homogeneous Multiple linear Regression constraining the regression coefficients to be nonnegative (HMR+), 3) non-homogeneous multiple linear regression (EMOS; Ensemble Model Output Statistics), 4) EMOS with positive coefficients (EMOS+). It is same method as the third method except for constraining the coefficients to be nonnegative. The four regression methods showed similar prediction skills for the monthly air temperature over South Korea. However, the prediction skills of regression methods which don't constrain regression coefficients to be nonnegative are clearly impacted by the existence of outliers. Among the four multiple linear regression methods, HMR+ and EMOS+ methods showed the best skill during the validation period. HMR+ and EMOS+ methods showed a very similar performance in terms of the MAE and RMSE. Therefore, we recommend the HMR+ as the best method because of ease of development and applications.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.19-33
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• 2022

With the explosive growth of social media, its abundant text-based data generated by web users has become an important source for data analysis. For example, we often witness online movie reviews from the 'Naver Movie' affecting the general public to decide whether they should watch the movie or not. This study has conducted analysis on the Naver Movie's text-based review data to predict the actual ratings. After examining the distribution of movie ratings, we performed semantics analysis using Korean Natural Language Processing. This research sought to find the best review rating prediction model by comparing machine learning and deep learning models. We also compared various regression and classification models in 2-class and multi-class cases. Lastly we explained the causes of review misclassification related to movie review data characteristics.

• Steel and Composite Structures
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• v.21 no.1
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• pp.93-107
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• 2016

Seismic fragility analysis is a probabilistic decision-making framework which is widely implemented for evaluating vulnerability of a building under earthquake loading. It requires ingredient named probabilistic model and commonly developed using statistics requiring collecting data in large quantities. Preparation of such a data-base is often costly and time-consuming. Therefore, in this paper, by developing generic seismic drift demand model for regular-multi-story steel moment resisting frames is tried to present a novel application of the probabilistic decision-making analysis to practical purposes. To this end, a demand model which is a linear function of intensity measure in logarithmic space is developed to predict overall maximum inter-story drift. Next, the model is coupled with a set of regression-based equations which are capable of directly estimating unknown statistical characteristics of the model parameters.To explicitly address uncertainties arise from randomness and lack of knowledge, the Bayesian regression inference is employed, when these relations are developed. The developed demand model is then employed in a Seismic Fragility Analysis (SFA) for two designed building. The accuracy of the results is also assessed by comparison with the results directly obtained from Incremental Dynamic analysis.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.2
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• pp.138-145
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• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• The Journal of Korean Society for School & Community Health Education
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• v.14 no.1
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• pp.37-47
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• 2013

Objectives: A descriptive correlational study was designed to examine the relationship of anger to psychosomatic symptoms. In addition, this study investigated the mediating effect of parental attachment in relation to anger and other variable. Methods: Data were collected from 112 subjects in grade 4 or 6, and descriptive statistics, Pearson correlation coefficient, and hierachical multiple regression were used with SPSS/PC 18.0 program to analyze the data. Results: There was a significantly positive effects between state-trait anger and psychosomatic symptoms. Father attachment negatively correlated state-trait anger and psychosomatic symptoms. Also, mother attachment negatively correlated state anger and psychosomatic symptoms. However, maternal attachment was not significantly associated with trait anger. Parental attachment had a significant mediating effect in relation to state-trait anger and psychosomatic symptoms. Conclusions: For the effective management of multi-cultural children's psychosomatic symptoms, programs including parental attachment increasing strategies should be established. These programs can increase parental attachment security which is mediator role between anger and psychosomatic symptoms.