• Korean Journal of Community Nutrition
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• v.2 no.5
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• pp.721-727
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• 1997

This study investigated whether dietary factors are more influential factor than other health behavior such as drinking, smoking and exercise on abnormal serum cholesterol level inspite of Korean dietary pattern differences compared to Europeans and Americans. A double case control study model has been used for the study design. One model consisted of high blood cholesterol cases and control. the other model consisted of low blood cholesterol cased and controls. 5.398 sedentary male workers who had taken medical examinations at a university hospital were used as the study subjects. Out of the study subjects, 36individuals with high blood cholesterol cases and 30 individuals with low blood cholesterol cases were selected. For the 66 individual control selection, the individual control selection, the individuals matching method was adopted. The food frequency method was used to collect the data for assessment of the dietary factors. A standardized questionnaire was used to investigate other health behavior. logistic regression analysis was employed to measure the relative importance between the factors considered. There were no statistically significant differences observed in nutrients consumption or other health behavior among the low, normal and high blood cholesterol groups, An overmatching effect had been suspected as the cause of those findings. However, the results of logistic regression analysis to identify the factors influencing high serum cholesterol showed that odd ratios of dietary factors such as tocopherol(3.0) and saturated fatty acid(1.6) were higher than I. I of smoking and 1.2 of drinking. Similar results were also observed incases of low serum cholesterol. The above findings imply that although the dietary pattern is quite different from that of Europeans and America, the dietary factor is still a significant factor for abnormal blood cholesterol in Koreans. Therefore, the dietary risk factor identified in high fat consumption populations are still relevant for the relatively healthy Korean as guideline for preventive health practices. (Korean J Community Nutrition 2(5) : 721∼727, 1997)

• Tunnel and Underground Space
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• v.29 no.5
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• pp.356-366
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• 2019

Various TBM performance prediction models have been developed and most of them were considered penetration rate only. Despite the fact that some models have suggested equations and charts for estimating the utilization factor, but there are a few studies to estimate the TBM utilization factor. Utilization factor is affected by the type of TBM machine, operation, maintenance of machine, geological conditions, contractor experience and other factors. In this study, more than 100 case studies are analyzed to determine the relationship between the utilization factor and RMR, geological conditions, TBM types, tunnel length, and TBM diameter. Simple and multiple linear regression analysis are performed to develop predictive models for the utilization factor. The predictive model with explanatory variables of geological conditions, TBM types, tunnel length, and TBM diameter does not give a good correlation. The predictive models with explanatory variable of RMR give higher values of the coefficient of determination.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.293-298
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• 2015

The vessel encounter data collected from the vessel trajectories in the maritime traffic situation is possible to analyze vessel collision and near-collision risk using statistical method. In this study, analyzing variables extracted from the vessel encounter data using factor analysis, we determine main factors effecting vessel collision risk from vessel encounter data. In order to calculate each factor, it used principal component analysis for factor analysis after normalization and standardization of vessel encounter variables. As a result of the factor analysis, main effect factors are summarized into the vessel approach factor and collision avoidance variance factor.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.115-125
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• 2015

This study is to analyze the preference of experiential activities and behavioral intention on rural tourism, with special focus on parents group of elementary students. The result can be utilized as basic data for demanding aspect of rural experiencing tourism. Two-step questionnaire survey was conducted, during May to July, 2915. Sample group was selected at 4 elementary school in Daegu city. 347 valid responses were analyzed with SPSS. Major results are as follows. Firstly, suggested model for 23 experiential activities in 7 types, were verified as valid by verifying factor analysis. Factor 1 was verified and named as 'Rual Life Experience', Factor 2 was verified and named as 'Health/Healing Experience', Factor 3, as 'Agricultural Product Experience', Factor 4, as 'Eco-Cultural Experience', Factor 5, as 'Leisure/Sports Experience', Factor 6, as 'Traditional Wellbeing Food Experience', and Factor 7, as 'Traditional Culture Experience'. All 7 factors explained 75.39% of total variance. Secondly, mean score of preference by each activity showed high in 'Health-care experience', 'Traditional food experience' and comparatively low in 'Collecting experience', 'Agricultural experience'. Thirdly, all 7 types(factors) of experience showed significant affecting relation to satisfaction, intention to participation and recommendation. Specially, 'Eco-Cultural Experience' and 'Rural Life Experience' showed high affecting relation. This could be the characteristics of parents group of elementary students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.654-659
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• 2007

This study suggests a measure method for measuring variables that are used for hotel corporations' CRM performance. For this purpose, I present a combined method between factor analysis and AHP(Analytic Hierarchy Process) analysis. Factor analysis gives us a result that shows a group of highly correlated variables and another group of less correlated variables. Thus, factor analysis can only give information of factor categorization. Although researchers add ANOVA analysis or regression analysis, these efforts can not connect its results with factor analysis. Therefore, In hotel CRM performance analysis, calculation of each factor's importance is strongly required. For that reason, I suggest a method that combines AHP analysis with factor analysis for Hotel CRM performance measurement.

• Journal of the Korean Society of Food Culture
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• v.19 no.1
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• pp.1-11
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• 2004

The specific purposes of this study are that ; 1) to investigate the distinguished selection attributes on performance of Japanese chain restaurant according to general characteristics of the respondent ; 2) to find out relationships between selection attributes on performance for Japanese restaurant and customer's satisfaction Frequency analysis. one-way ANOVA, reliability analysis, factor analysis, multiple regression were used to analyze the data. Total 350 questionnaires were distributed and 312 were replied(89.14%). Selection attributes on performance for Japanese chain restaurant was divided into 7 factors. There are Factor1 'Store Image & Kindness', Factor2 'Sanitation & Taste', Factor3 'Approximation & Children's Menu', Factor4 'Delivery & Business Hours', Factor5 'Food Quantity & Korean Food', Factor6 'Service & Parking' Factor7 'Price & Publicity'. Monthly income, eating-out expense per once and type of companion have significant influences on selection attributes for performance. Customer's total satisfaction is significantly affected by selection attributes on performance. Factor7 'Price & Publicity' has the most significant influence on customer's satisfaction. We expect that the results can be used to provide basic information to plan marketing strategies, and take improved customer's satisfaction for Japanese chain restaurants.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.97-101
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• 2012

Objective: With the background of aging population in China and advances in clinical medicine, the amount of operations on old patients increases correspondingly, which imposes increasing challenges to critical care medicine and geriatrics. The study was designed to describe information on the length of ICU stay from a single institution experience of old critically ill gastric cancer patients after surgery and the framework of incorporating data-mining techniques into the prediction. Methods: A retrospective design was adopted to collect the consecutive data about patients aged 60 or over with a gastric cancer diagnosis after surgery in an adult intensive care unit in a medical university hospital in Shenyang, China, from January 2010 to March 2011. Characteristics of patients and the length their ICU stay were gathered for analysis by univariate and multivariate Cox regression to examine the relationship with potential candidate factors. A regression tree was constructed to predict the length of ICU stay and explore the important indicators. Results: Multivariate Cox analysis found that shock and nutrition support need were statistically significant risk factors for prolonged length of ICU stay. Altogether, eight variables entered the regression model, including age, APACHE II score, SOFA score, shock, respiratory system dysfunction, circulation system dysfunction, diabetes and nutrition support need. The regression tree indicated comorbidity of two or more kinds of shock as the most important factor for prolonged length of ICU stay in the studied sample. Conclusions: Comorbidity of two or more kinds of shock is the most important factor of length of ICU stay in the studied sample. Since there are differences of ICU patient characteristics between wards and hospitals, consideration of the data-mining technique should be given by the intensivists as a length of ICU stay prediction tool.

• Journal of Korean Academy of Nursing
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• v.42 no.6
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• pp.819-832
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• 2012

Purpose: This study was conducted to identify risk factors that influence the probability and severity of elder abuse in community-dwelling older adults. Methods: This study was a cross-sectional descriptive study. Self-report questionnaires were used to collect data from community-dwelling Koreans, 65 and older (N=416). Logistic regression, negative binomial regression and zero-inflated negative binomial regression model for abuse count data were utilized to determine risk factors for elder abuse. Results: The rate of older adults who experienced any one category of abuse was 32.5%. By zero-inflated negative binomial regression analysis, the experience of verbal-psychological abuse was associated with marital status and family support, while the experience of physical abuse was associated with self-esteem, perceived economic stress and family support. Family support was found to be a salient risk factor of probability of abuse in both verbal-psychological and physical abuse. Self-esteem was found to be a salient risk factor of probability and severity of abuse in physical abuse alone. Conclusion: The findings suggest that tailored prevention and intervention considering both types of elder abuse and target populations might be beneficial for preventative efficiency of elder abuse.

• The Journal of Pediatrics of Korean Medicine
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• v.25 no.3
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• pp.57-69
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• 2011

Objectives: Purpose of this study is to analyze and to estimate which and how much genetic and environmental factors have affected on growth. Also, a method of final height prediction can be developed from this study results. Methods: Correlation analysis and categorical regression analysis were conducted between genetic and environmental factors correlated with the final adult height, through survey from 171 male. Results: Mid parental height, neonatal body weight, intake frequency of beef, chicken, milk, fruits and coffee, sleep quantity and quality during the elementary school and sleep quantity during the middle school have affected on the final adult height. And a regression equation with 0.494 for coefficient of determination was obtained. Conclusions: Mid-parental-height has the most affected on the final adult height. Among environmental factors, food and sleep have significantly affected, but exercise doesn't. Among foods, meal, beef, and milk intake have remarkably affected on the final height, and chicken and fruit also have affected in some degree, but coffee has affected badly. Among sleep habits, sleep quantity during the elementary school has the most affected, sleep quality during the elementary school and sleep quantity during the middle school also have affected in some degree on final height. The younger the age is, the more sleep have affected and sleep quantity have more affected than sleep quality. Neonatal weight also has remarkably affected on the final height. Through this analysis, the final adult height can be predicted using regression equation which covers 49.4% of genetic and environmental factors.

• Fire Science and Engineering
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• v.28 no.2
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• pp.69-75
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• 2014

This study derives the factors which affect the occurrence of arson from statistical data (population, economic, and social factors) by multiple regression analysis. Multiple regression analysis applies to 4 forms of functions, linear functions, semi-log functions, inverse log functions, and dual log functions. Also analysis respectively functions by using the stepwise progress which considered selection and deletion of the independent variable factors by each steps. In order to solve a problem of multiple regression analysis, autocorrelation and multicollinearity, Variance Inflation Factor (VIF) and the Durbin-Watson coefficient were considered. Through the analysis, the optimal model was determined by adjusted Rsquared which means statistical significance used determination, Adjusted R-squared of linear function is scored 0.935 (93.5%), the highest of the 4 forms of function, and so linear function is the optimal model in this study. Then interpretation to the optimal model is conducted. As a result of the analysis, the factors affecting the arson were resulted in lines, the incidence of crime (0.829), the general divorce rate (0.151), the financial autonomy rate (0.149), and the consumer price index (0.099).