• Journal of dental hygiene science
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• v.10 no.6
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• pp.417-424
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• 2010

The aim of this study was to assess the relevancy to oral health behaviors and socioeconomic characteristic among Korean adolescents. From '2007 Youth Behavior Risk Factor Surveillance 73,836 subjects database' which provided from 'Korean Centers for Disease Control and Prevention'. We conducted statistically analyzed binary logistic regression to determine the relation between dental health behavior and socioeconomic characteristic. Compared to adolescents in high-economic group, adolescents in medium or low-economic group had more likely poor dental health behaviors(p<0.05, p<0.01, p<0.001). In particular, there were significantly difference in toothbrushing the frequency of visiting a dental clinic and had received dental health education experiences. Conclusions, Because of the strong relation with demographic socioeconomic characteristic, must consider it when we improve of oral health by behavioral change. These results the need for the further development spread of oral health programs.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.994-1004
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• 2021

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients' needs for intensive care (yes/no) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79-0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77-0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85-0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66-0.88). Conclusion: Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.3
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• pp.123-143
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• 2007

The world has become the most globalize in the new millenium since the beginning of the human being history. In proportion to female economic activity has increased, we have seen many women CEO. Top class sociologists have already started to study female Cooperation. Gradually, they are using highly advanced statistical methods and scientific tools to demonstrate their theory. As survey, this study of relations between CEO characteristics and performance of Woman's Enterprise, we are looking forward to provide a implication about between strengthen the competitiveness and improvement in outcome theoretically and practically. This study executed to woman establishment enterprise among national woman enterprise and to collect achieved data. Analysis result, Woman founder's characteristic and enterprise have been shown to influence school ability among demographic characteristic. Also, management ability, entrepreneurship, technological ability have been shown to influence sales, market share, profitability. According to research, it IS important for business women to know management, improving of technology ability and entrepreneurship.

• Korean Journal of Health Education and Promotion
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• v.19 no.2
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• pp.73-98
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• 2002

This study was carried out to investigate the relationship between social support, social network and health behaviors as surveyed by cross-sectional study in 744 rural people aged above 30 of a community dwelling sample of one county for 6 days of July in 2000. Objectives of this study was in order to establish an effective health promotion. The sample was accrued by face to face interview of direct visiting from clustered sampling method. Interview was conducted by trained medical students with the questionnaire consisted of socio-demographic data, health behavior, social support and social network based on previous literature. The summarized results were as follows: 1. There were significant difference in the level of social support and social network by general characteristic variables except occupation and residency type(p〈0.05). 2. There were significant difference in knowledge about hypertension, smoking status, status of physical exercise, diet patterns by social support and social network in spite of variation of social support and social network subconcept(p〈0.05). And there were significant difference in alcohol drinking status, body weight control and diet pattern according to level of social network(p〈0.05). But smoking status by social support and network results opposite direction(p〈0.05). 3. There were no regular or consistent result in the relationship between social support, social network and health behavior. 4. Major predictors for health behavior on the multiple logistic regression that included general characteristic, social support and social network were age, instrumental social support and worry about health. Significant variables of multiple logistic regression for health behavior that included social support(instrumental and emotional) and social network were instrumental social support and social network. These results suggest that only a instrumental element and social network may be associated with health behavior. Inconsistent with prior research in these some item, a positive consistent relationship was not found between social support, social network and health behavior. So the study should be replicated to determined the reliability of our findings.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.96-101
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• 2021

This paper presents a machine learning model that predicts stroke risks in atrial fibrillation patients using public big data. As the training data, 68 independent variables including demographic, medical history, health examination were collected from the Korean National Health Insurance Service. To predict stroke incidence in patients with atrial fibrillation, we applied deep neural network. We firstly verify the performance of conventional statistical models (CHADS2, CHA2DS2-VASc). Then we compared proposed model with the statistical models for various hyperparameters. Accuracy and area under the receiver operating characteristic (AUROC) were mainly used as indicators for performance evaluation. As a result, the model using batch normalization showed the highest performance, which recorded better performance than the statistical model.

• Journal of the Korea Fashion and Costume Design Association
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• v.13 no.2
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• pp.35-46
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• 2011

The purpose of this study was to investigate the effect of mass media on women's clothing image, make-up image, and hair image. The subjects of the study were 306 women who lived in Gyeongnam area. Data were collected during June in 2009. Statistical analysis used in this study were frequency, F-test, t-test, Duncan test, factor analysis, Cronbach's ${\alpha}$, correlation coefficient, and multiple regression. The results of this study were as follows. The mass media according to the demographic characteristic of women showed significant difference. Three factors of clothing image were titled as elegance, youth, and visibility. Three factors of make-up image were titled as modern, romanticism, and mediocrity. Four factors of hair image were titled as attraction, individuality, gentleness, and cuteness. The mass media resulted in correlation with the clothing image, make-up image, and hair image. The mass media had a influence on the clothing image, make-up image, and hair image. The study results are highly expected to be used as useful sources in one's image formation and a marketing plan.

• Journal of Korean Academy of Nursing
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• v.35 no.1
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• pp.47-55
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• 2005

Purpose: This study was to evaluate the validity of the Pediatric Index of Mortality Ⅱ(PIM Ⅱ). Method: The first values on PIM Ⅱ variables following ICU admission were collected from the patient's charts of 548 admissions retrospectively in three ICUs(medical, surgical, and neurosurgical) at P University Hospital and a cardiac ICU at D University Hospital in Busan from January 1, 2002 to December 31, 2003. Data was analyzed with the SPSSWIN 10.0 program for the descriptive statistics, correlation coefficient, standardized mortality ratio(SMR), validity index(sensitivity, specificity, positive predictive value, negative predictive value), and AUC of ROC curve. Result: The mortality rate was 10.9% (60 cases) and the predicted death rate was 9.5%. The correlation coefficient(r) between observed and expected death rates was .929(p<.01) and SMR was 1.15. Se, Sp, pPv, nPv, and the correct classification rate were .80, .96, .70, .98, and 94.0% respectively. In addition, areas under the curve (AUC) of the receiver operating characteristic(ROC) was 0.954 (95% CI=0.919～0.989). According to demographic characteristics, mortality was underestimated in the medical group and overestimated in the surgical group. In addition, the AUCs of ROC curve were generally high in all subgroups. Conclusion: The PIM Ⅱ showed a good, so it can be utilized for the subject hospital. better.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.129-137
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• 2018

The present paper study investigates the relationship between social exclusion and donation intention among specific social groups in Korea. Social exclusion refers to non-participation in social experiences by the socially disadvantaged. Data were analyzed using two sources; first was the evidence of behaviors arising from social exclusion of the university students and then socially excluded reactions of the elderly responses from the survey were compared with the first research findings. The reason of using multi-sources of data is that the outcome from the experimental design of the university student is imperative to clarify what the conclusions will be the same result with the other demographic characteristic of the elderly. The research design was three excluded elderly individuals of a self-excluded group and two other excluded groups divided such as "ignored" and "rejected" individuals to compare the differences among three groups of different sources of exclusion. The conclusion of this study is that those with high social exclusion exhibited a more negative donation intention than those with lower social exclusion, but that those who perceived themselves as self-excluded were more likely to give donations than those excluded by others, regardless of the level of their social exclusion.

• The Research Journal of the Costume Culture
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• v.16 no.4
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• pp.681-695
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• 2008

This study was accomplished to investigate the preference of clothing materials and the clothing demand performance for underwear and everyday dress of atopic patients. As this study was the research study by a use of a questionnaire, the finally total 987 copies of the collected questionnaires were used to analyze the data. SPSS was used for the statistical analysis of data. To analyze the data, frequency analysis, percentage, $X^2$-test, reliability analysis, factor analysis, t-test, ANOVA and Duncan's multiple comparisons were used. The results obtained are as follows. In factor analysis for clothing materials and the demand performance which atopic patients favor, the preference factors for underwear materials were classified as pliability/a sense of weight, a sense of cold and warmth, tactility, and elasticity. Those for everyday wear were classified as pliability/surface roughness, a sense of cold and warmth, a sense of weight, and elasticity. And the demand performance factors for underwears were classified as thermophysiology, care convenience, and skin contact. Those for everyday wear were classified as comfortableness and care convenience. In the difference analysis for the preference and the demand performance, Both everyday wear and underwear showed a significant difference for the preference and the demand performance according to gender, age, income, education level, and occupation.

• The Journal of Korean Association of Computer Education
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• v.19 no.5
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• pp.55-71
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• 2016

Recently, Internet addiction problem has arised due to increasing negative effects about excessive internet use among youth. In this study, by utilizing the '11th youth health behaviors online survey data', we discuss the countermeasures for excessive internet usage of adolescence based on various analysis. we examined the effects of demographic characteristic factors, psychological factors, behavioral factors on internet usage of adolescence. As a result, it was confirmed that there were various variables that influenced adolescent internet usage which were not approached in previous researches. And through these results, we can confirm these variables. In addition, we can also provide countermeasures on excessive internet usages by that of adolescents.