• Journal of Korean Society of Transportation
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• v.30 no.4
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• pp.21-32
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• 2012

Exclusive bus lane (EBL) is typically located in the roadway median, and is accessed by weaving across the GPLs(general purpose lanes) before entering from the left lane of the GPLs. To maximize the potential for successful EBL operations, a critical design issue that requires special attention is the length of bus weaving section before entering EBL. The process of developing guidelines for the length of bus weaving section can be supported by a sensitivity analysis of performance measure (safety) with respect to the bus weaving distance. However, field data are difficult to obtain due to inherent complexity in creating performance measure (safety) samples under various interesting flows and bus weaving distance that are keys to research success. In this paper, VISSIM simulation is applied to simulate the operation of roadway weaving areas with EBL, and based on vehicle trajectory data from microscopic traffic simulation models, the Surrogate Safety Assessment Model (SSAM) computes the number of surrogate conflicts (or degree of safety) with respect to the bus weaving distance. Then, a multiple linear regression (MLR) model using safety data (number of surrogate conflicts) is developed. Finally, guidelines for bus weaving distance are established based on the developed MLR. Developed guidelines explicitly indicate that a longer bus weaving distance is required to maintain desired safety as weaving volume increases.

• The Journal of Engineering Geology
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• v.4 no.3
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• pp.297-309
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• 1994

For a total of 210 city and Kun areas in Korea, a model was developed to predict the amount of groundwater use at each area. At first, the total areas were classified into 3 groups by the characteristics of groundwater use: residential(87), industrial(27) and agricultural (96) areas. Among them, type areas, represented by the dominant groundwater usage for typical purposes, were selected: residential(22), industrial(8) and agricultural(32) areas. Data for the various factors possibly related to the groundwater use were statistically analyzed. The factors include, 1) agricultural area, 2) industrial area, 3) adininistrative unit area(city or Kun), 4) population, 5) groundwater capadty for community water supply, 6) average water supply for a person per day, 7) agricultural water-use, 8) industrial water-use, 9) residential wateruse, 10) rates of community water supply. The data were correlated to the total amount of groundwater use, and the correlations tested at the 95% and 99% significance levels. Influential, significantly related, factors were identified from the tests. Using the multiple regression method with the influential factors, predictive equations were drawn to calculate the amount of groundwater use for residential-industrial and agricultural areas, respectively. The equations were calibrated to minimize the RMS(root mean square) of the differences between predicted and observed groundwater use. After the validation with future data, the model can be utilized in the regional development plans to predict the maximum groundwater demand at each area.

• Health Policy and Management
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• v.23 no.1
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• pp.35-43
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• 2013

Background: Diagnosis procedure combination (DPC) has recently been introduced in Korea as a demonstration project and it has aimed the improvement of accuracy in bundled payment instead of Diagnosis related group (DRG). The purpose of this study is to investigate that the model of end-stage liver disease (MELD) score as the severity classification of liver diseases is adequate for improving reimbursement of DPC. Methods: The subjects of this study were 329 patients of liver disease (Korean DRG ver. 3.2 H603) who had discharged from National Health Insurance Corporation Ilsan Hospital which is target hospital of DPC demonstration project, between January 1, 2007 and July 31, 2010. We tested the cost differences by severity classifications which were DRG severity classification and clinical severity classification-MELD score. We used a multiple regression model to find the impacts of severity on total medical cost controlling for demographic factor and characteristics of medical services. The within group homogeneity of cost were measured by calculating the coefficient of variation and extremal quotient. Results: This study investigates the relationship between medical costs and other variables especially severity classifications of liver disease. Length of stay has strong effect on medical costs and other characteristics of patients or episode also effect on medical costs. MELD score for severity classification explained the variation of costs more than DRG severity classification. Conclusion: The accuracy of DRG based payment might be improved by using various clinical data collected by clinical situations but it should have objectivity with considering availability. Adequate compensation for severity should be considered mainly in DRG based payment. Disease specific severity classification would be an alternative like MELD score for liver diseases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.258-269
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• 2017

This study was conducted to examine the predictive factors for health promotion behaviors of breast cancer patients, focusing on Pender's health promotion model (1996). Data were collected from 121 patients using a structured questionnaire from September 18 to October 26 in 2015. The data were analyzed with a t-test, ANOVA, Pearson's correlation coefficients, and hierarchical multiple regression analysis using SPSS 20.0 for Windows. The predictive factors for the health promotion behavior of the participants were social support, commitment to a plan of action, prior behavior, activity related effects, perceived self-efficacy, family function, perceived benefits of action, and situational influences. The total explanatory power of these factors was 57.8%. Development and application of a nursing intervention plan that enhances patient compliance with health promotion behavior is needed to enable breast cancer patients undergoing rehabilitation to maintain their optimal health and live a high-quality life. Patients who showed a low degree of predictive factors identified in this study are in particular need of attention.

• Management & Information Systems Review
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• v.28 no.3
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• pp.1-23
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• 2009

Prior bankruptcy studies have established that bankrupt firm's pre-filing financial ratios are different from those of healthy firms or of randomly selected going concerns. However, they may not be sufficiently different from the financial ratios of other firms in financial distress to allow the development of a ratio-based model that predicts bankruptcy with reasonable accuracy. As the result, in the multiple discriminant model, independent variables divided firms into bankrupt firms and healthy firms are retained earnings to total asset, receivable turnover, net income to sales, financial expenses, inventory turnover, owner's equity to total asset, cash flow to current liability, and current asset to current liability. Moreover four variables Retained earnings to total asset, net income to sales, total asset turnover, owner's equity to total asset indicate that these valuables classify bankrupt firms and distress firms. On the other hand, Owner's Equity to borrowed capital, Ordinary income to Net Sales, Operating Income to Total Asset, Total Asset Turnover and Inventory Turnover are selected to predict bankruptcy possibility in the Logistic regression model.

• Korean Journal of Occupational Health Nursing
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• v.9 no.2
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• pp.94-109
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• 2000

The chances of disease pattern increased the importance of Health-promoting Lifestyle and a large part of the Health-promoting Lifestyle is associated with individual's habit. Health-promoting Lifestyle among nurses is very important because nurses could be a role model of patients and possibly influence many patients. The purpose of this study was oat on1y to assess how hospital nurses practice their Health-promoting Lifestyle but also to identify those affecting determinants. The subjects were 392 nurses working at 3 different hospital in Seoul. These data were collected by self administered questionnaire from April 27 to May 20, 2000. This study examined Health-promoting Lifestyle using In Sook Park's model, individual characteristics. Behavior-specific Cognitions and Affect factors using Pender's model and tried to fine out their relationships. The instruments used in this study were Health-promoting Lifestyle Profile developed by In Sock Park(1995). Likert's four-point scale was used also in this research. The percentage, mean standard deviation, AVNOVA, Pearson's correlation coefficient and multiple regression in the SAS package were used to analyze the data. The results of this study were as follows; 1. 52.3% of sample were aged between 25 and 29, 67.1% were single, 55.6% were university graduates, 51.8% earned 1.5 to 2.0 million won, 57.9% slept for d to 8 hours, 74.5% stated they were healthy. 2. 32.7% of sample worked in surgical gird department, 82.4% worked in 3 shift, 26.3% have been working as nurses for 5 to 7 years. Average score of Perceived self-efficacy was 3.63, Perceived benefits of action was 3.25, Social support was 2.75, and Perceived barriers to action was 1.87 which was the lowest score. 3. The average score if the performance in Health-promoting Lifestyle variable was 2.45 which was lower than previous study. The sanitary life Was 3.18 which was the highest score, harmonious relationship 3.13, emotional support 2.90. The variable with the highest degree of performance was the sanitary life, whereas the one with the west degree was the health diet. 4. There were no significant difference in perceived benefits of action with individual's a character, but in Perceived bait his of action there were significant differences with age(p<.01), marital status(p<.05), housing(p<.05), and Perceived health status(p<.05). In Perceived self-efficacy, there were significant differences with educational level(p<05), sleeping hours(p<.05), and BMI(p<.05). In Social support here were significant difference with housing and sleeping hours.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.441-449
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• 2005

The purpose of this research is to present the improvement measure of lagging behind coastal shipping system to be a logistic hub-nation with a competitive edge. For this purpose, this research tries to find out major northeast asia environment factors and accordingly the effects of its. The effects of coastal shipping system's development strategy is analysed by structural equation model and multiple regression model. Research results show that three types of coastal shipping developing strategy(connected transportation system, structure of coastal shipping system, governmental support policy) will contribute much to be logistic hub-nation. The contribution effects is increasing cargo from strengthened feeder transport system and maximizing logistic service &minimizing logistic costs. From the result, some implications are derived as follow. First, familiar environmental balanced ocean-coastal transport system is required. Second the one-stop logistic service system is necessary to build excusive feeder port, and to establish Ro-Ro ship & high-speed ship, etc.. Third, governmental support policy and subsidy(tax exempted oil & various tax benefits) are required to bring up lagging behind coastal shipping system to be a logistic hub-nation with a competitive edge.

• The Journal of Internal Korean Medicine
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• v.37 no.1
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• pp.47-64
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• 2016

Objectives: In the present study, a genetic analysis was conducted to investigate the association of the expression of SNPs of EDN1 gene polymorphism with the clinical phenotype in bronchial asthma patients with either excess or deficiency syndrome.Methods: Ninety-four healthy control subjects and 52 asthma patients were included in this study. The asthma patients were divided into two groups: those with deficiency syndrome and those with excess syndrome. We searched the exonic and promoter areas of the EDN1 gene in the NCBI website SNPs with <0.01 minor allele frequency (MAF) and <0.01 heterozygosity. Pro programs were performed to obtain the odds ratio, 95% confidence interval, and p-value. Multiple logistic regression models were conducted to analyze the genetic data.Results: In our genotype and allele analyses, there were significant differences in the codominant 2 model of the rs3087459 SNP genotype and also in the CGG haplotype between the control group and the asthma group. Genotype and allele analyses were conducted between the deficiency and excess syndrome group. There were significant differences in the dominant and log-additive model and also in the frequency of C-alleles of rs3087459 SNP genotype. There were significant differences in codominant 1, dominant and log-additive model and T-allele of rs5370 SNP genotype. The AGG haplotype also revealed significant differences.Conclusions: EDN1 SNPs (rs3087459, rs5370) showed a significant association with symptomatic excess syndrome in Korean asthmatic patients.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6273-6278
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• 2015

Objective: This study assessed the association between subjective body image or objective body mass index (BMI) and the risk of daily smoking in Korean adolescents, with a purpose of identifying the most suitable models. Materials and Methods: Using the 2013 9th Korea Youth Risk Behavior Web-based Survey data for 72,435 students, odds ratios were calculated for daily smoking in the past month, according to the subjective body image and calculated BMI using a respective multiple logistic regression model. The combined effect of these two factors was also analyzed by pairing a BMI category with a subjective body image category, using odds ratios for the same event within each sex group. Results: Among the surveyed students, 7.2% of boys and 1.8% of girls were classified as daily smokers. Students who perceived themselves as being very obese tended to be at lower risk of daily smoking (OR=0.61 in boys with 95% CI=0.47 to 0.79; OR=0.66 in women with 95% CI=0.47 to 0.93). In addition, boys within the obese or overweight BMI category showed a lower risk of daily smoking (OR=0.86, 95% CI: 0.77-0.96). Lean BMI was significantly associated with higher odds ratios for daily smoking only in female students (OR=1.24, 95% CI: 1.02-1.52). When pairing these two objective and subjective factors, results suggested that subjective body image has a greater effect on daily smoking than BMI in both boys and girls. Conclusions: In both male and female students, subjective body image had a greater effect on daily smoking than body mass index. A model using the combination of BMI and subjective body image was the best fit in girls, in contrast to the model using subjective body image only best suitable in boys, for the prediction of daily smoking. These results including several factors associated with daily smoking in Korean students, provide useful data for the development and implementation of smoking intervention and cessation programs for adolescents.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1427-1435
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• 2017

The smart farm is a remarkable system because it utilizes information and communication technologies in agriculture to bring high productivity and excellent qualities of crops. It automatically measures the growth environment of the crops and accumulates huge amounts of environmental information in real time growing in smart farms using multi-variable control of environmental factors. The statistical model using the collected big data will be helpful for decision making in order to control optimal growth environment of crops in smart farms. Using data collected from a smart farm of tomato, we carried out multiple regression analysis to determine the relationship between yield and environmental factors and to predict yield of tomato. In this study, appropriate parameter modification was made for environmental factors considering tomato growth. Using these new factors, we fit the model and derived the optimal environmental factors that affect the yields of tomato. Based on this, we could predict the yields of tomato. It is expected that growth environment can be controlled to improve tomato productivities by using statistical model.