• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.1
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• pp.71-79
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• 2012

This study aims at finding relationships between the competitiveness of cities and the size or distance of them, based on some premises; (1) the competitiveness can be measured on the interval-ratio level, that is, factor scores, (2) a hypothesis that the spatial interaction model is valid for the relationships can be generally accepted. Based on the general recognition a research hypothesis that the more is the population or the nearer is the distance from a central city the higher is the competitiveness score is constructed. According to the premises 5-factor scores and composite score are calculated by means of regression method, and the scores are regressed on cities' populations and distances from Seoul city. Using bootstrapping method for the tests of significance is effective due to small sample of 21 cities. Results of the analyses show that most aspects of the hypothesis should be rejected or adjusted. Scores on Health-welfare factor, public service factor, and commercial vitality factor have no relation to the cities' sizes or distances. But the results also find the facts that the strong (negative) relationships exist between (1) educational base factor score and population, (2) density factor score and distance. Although this study improves systematic and analytic understanding of spatial interaction patterns, the understanding should be invalid for the general context because it has used the data on 21 cities in the capital region at the time of 2009.

• Korean Journal of Occupational Health Nursing
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• v.29 no.3
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• pp.173-183
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• 2020

Purpose: The purpose of this study was to identify factors associated with the mental health-related quality of life (MHQoL) of Korean workers. Methods: This was a cross-sectional study of 192 Korean pay workers who worked in the Daegu and Gyeongbuk Province, Korea. Data were collected from May 15 to July 2, 2019, through selfreported questionnaires. The survey had a total of 87 questions including individual, organizational, and psychosocial factors. MHQoL was measured using short form-36 version 1. Data were divided into four domains of MHQoL and analyzed using a hierarchical linear regression model. Results: From the hierarchical linear regression analysis, when the psychosocial factors were included in the regression model, the R² change in the four domains of MHQoL increased significantly by 19~47%. A common predicting factor associated with the four domains of MHQoL was identified as perceived stress symptoms. Other factors affecting MHQoL showed slight differences in each domain. Conclusion: Based on the study results, it is necessary to monitor the psychosocial symptoms to improve MHQoL of Korean workers. Considering each factor affecting the four areas of MHQoL, workplace-based interventions to improve MHQoL should be provided to workers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3039-3056
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• 2020

Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks.

• Journal of the Korea Construction Safety Engineering Association
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• s.51
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• pp.93-105
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• 2010

The object of this study is to understand the psychological factor of the worker on safety and recommend experimental factor of safety education program. The following are the methods of this study. We analyzed the statistical data from survey to workers(N=139) about the psychological factor on safely. The survey consisted of 34 questions about 4 factors like private external characteristic, psychological characteristic, characteristics on behavior, and experience and reason of disaster. As the result of the analysis of the multi regression model on the base of correlation of each of the major factors, psychological health, effort on practicing, and satisfaction on their life were the variables with high influence on the safety mind of workers. So, it is good safety strategy for effective working to maintain healthy life with optimistic minds, and try to practice actively as usual. After considering the result, for the development of safety education program for working, we have to consider psychological factors of our workers that influence their safety and try to improve the experimental education opportunity, and it will be effective.

• 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)

• Journal of the Korean Society for Aviation and Aeronautics
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• v.5 no.1
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• pp.51-63
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• 1997

Generally, air freight forecasting model used to major factor GNP(GDP), Yield, Exchange rate, as its independent variables. We studied about the factors that affect to Air Freight in Korea, and we found six affective variables. Those are GNP, Exchange rate, Flight routes, Flight numbers, Sum of dollars Export and import. To find the relationship between the Air Freight and GNP, Exchange rate, Flight routes, Flight numbers, Sum of dollars Export and import we used regression analysis. Through the regression analysis, we found some problems in the model. There are collieneraities between the variables, so we took the variables selection model to choose the best affective variables of air cargo. We have defined the the Korean air freight forecasting model with two variables and forecast far the $1996{\sim}2010$ period were made by using this model.

• Journal of the military operations research society of Korea
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• v.31 no.1
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• pp.26-41
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• 2005

The ROK TRANSCOM and Army Logistics Command have established wartime overland transportation plans. They have to mobilize several wartime overland transportation troops in order to meet the wartime transportation requirement. But there are some uncertainties in the process of transportation such as the number of vehicles to mobilize, the vehicle utilization factor, and round trip time. Here, we established two models. One is the simulation model to evaluate the transportation capability considering uncertain factors. The simulation model is executed with two scenarios and then the results are analyzed through a sensitivity analysis. The other model is the regression model to analyze the effects of transportation factors toward capability.

• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• The Journal of Engineering Geology
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• v.14 no.2
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• pp.211-222
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• 2004

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The seven landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The seven factors consist of two topographic factors and five geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 90.74% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

• Korean Security Journal
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• no.48
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• pp.177-206
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• 2016

The purpose of this study is to verify the factors that affect the fear of crime by applying the risk interpretation model. Especially, whereas previous studies have not proven micro individual factor that the risk interpretation model had presented, This study includes micro individual elements such as neighborhood factor, perceived risk of crime, fears of crime as main variables. This study utilized secondary data of the National Crime Victimization Survey 2012, conducted by the Korean Institute of Criminology. In this study, multiple regression analysis of two stages and Sobel Test were conducted for verifying the individual influence of each independent variables and identifying the causal relationship between the variables set out in the risk analysis model. As the result, it appeared that the higher level of perceived risk of crime, neighborhood factor, crime experience, education, income cause the higher degree of the fear of crime. On the other hand, the lower degree of age was found to induce the higher level of the fear of crime. In addition, female showed the higher degree of the fear of crime than man. The causal relationship between the variables set out in the risk interpretation model was presented significantly in all variables, except for education.