• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.513-525
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• 2020

Purpose: The purpose of this study is to analyze the characteristics of local factors affecting number of tuberculosis death by urban and rural areas. Method: The Partial Least Square(PLS) Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The number of tuberculosis deaths in urban and rural areas is about three times as large. As a result of analysis about Regional Characteristics Factor, In general, children, elderly people, and economically vulnerable populations are more likely to be exposed to tuberculosis. In differential results, it shows that environmental factors such as ultrafine dust and sulfur dioxide have a significant impact on the number of tuberculosis deaths in urban areas and social factors such as depression experience rate in rural areas. Conclusion: The Tuberculosis prevention and management policies that reflect the characteristics of urban and rural areas are needed in the future.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.627-640
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• 2001

Generally, the synthetic unit hydrograph method is presented to estimate the design flood in the ungaged watershed. However, due to the lack of rainfall-runoff data, the models developed in other countries such as U.S.A. and Japan have been widely used in Korea. Therefore, it may be essential to develope the rainfall-runoff model suitable for the hydrological char-acteristics in Korea. In this study, the representative unit hydrographs are derived from rainfall-runoff data at 19 basins in Selma-Cheon and 3-IHP experimental watersheds using ridge-regression method and Nash model. And a new synthetic unit hydrograph for Korea is suggested by integrating the described results and previous studies on unit hydrograph. The newly developed method is represented as two regression forms with three independent variables of watershed area, channel length, and channel slope by multiple regression analysis is carried out for each watershed, the coefficients of determination are not improved in all cases compared out for each watershed, the coefficients of determination are not improved n all cased the synthetic unit hydrograph for each watershed. Therefore, when the new method is applied to some watersheds, the result analyzed for all data has to be used.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.31-36
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• 2014

In this study, the methodologies for evaluating the low-flow at the ungauged watershed are reviewed and assessed. The ungauged watershed can be classified into different situations such as the partially recorded watershed and the completely ungauged watershed. The extension method and the percentile method are used to evaluated the low-flow at the partially recorded watershed. The drainage-area ratio method and the regional regression method are used at the completely ungauged watershed. These four methods are applied and validated based on the hydrological and geometric data acquired from unit watersheds in Han River basin for TMDLs. In case of partially recorded watershed, the values of low-flow evaluated by the extension method are in better agreement with measured flow-rate rather than those by the percentile method. In case of completely ungauged watershed, the drainage-area method is broadly used to estimate the low-flow. It must be paid attention to consider the treated sewage discharge produced at watersheds when applying the method.

• Journal of Korean Society on Water Environment
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• v.28 no.6
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• pp.923-932
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• 2012

The purpose of this study was to determine parameters of surface cover materials and evaluation the effects on runoff and sediment reductions with rice straw mat with PAM at watershed scale using the SWAT model. In this study, 1) regression equation of CN for rice straw mat + PAM using SCS curve number method was developed, 2) the USLE P factor, being able to reflect simulation of rice straw mat + PAM in the agricultural field, was estimated for various slope scenarios with VFSMOD-w. Then regression equation for CN and USLE P factor were used as input data in the SWAT model. Assuming rice straw mat + PAM is applied to radish and potato fields, occupying 24% of agricultural fields at the study watershed. Result of direct runoff without rice straw mat + PAM was $65,964,368\;m^3,$ with rice straw mat + PAM, direct runoff was $65,637,336\;m^3$, $327,031.8\;m^3$ reductions compared without it. Also, result of sediment without rice straw mat + PAM was 163,531 ton, with rice straw mat + PAM, sediment was 84,779 ton, 78,752 ton reduction compared without it. This analysis showed that about 48% sediment reductions would be expected with rice straw mat + PAM. As shown in this study, rice straw mat + PAM would be used as an efficient site-specific BMPs to reduce runoff and sediment discharge from field.

• Journal of Korea Water Resources Association
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• v.49 no.8
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• pp.645-656
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• 2016

The study performed a regional flood frequency analysis and proposed a regression equation to estimate design floods corresponding to return periods for ungauged basins in Geum-river basin. Five preliminary tests were employed to investigate hydrological independence and homogeneity of streamflow data, i.e. the lag-one autocorrelation test, time homogeneity test, Grubbs-Beck outlier test, discordancy measure test ($D_i$), and regional homogeneity measure (H). The test results showed that streamflow data were time-independent, discordant and homogeneous within the basin. Using five probability distributions (generalized extreme value (GEV), three-parameter log-normal (LN-III), Pearson type 3 (P-III), generalized logistic (GLO), generalized Pareto (GPA)), comparative regional flood frequency analyses were carried out for the region. Based on the L-moment ratio diagram, average weighted distance (AWD) and goodness-of-fit statistics ($Z^{DIST}$), the GLO distribution was selected as the best fit model for Geum-river basin. Using the GLO, a regression equation was developed for estimating regional design floods, and validated by comparing the estimated and observed streamflows at the Ganggyeong station.

• Journal of Microbiology and Biotechnology
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• v.10 no.4
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• pp.476-481
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• 2000

A linear correlation, by the stepwise multiple regression analysis, was found between the sensory test of Sigumjang aroma and the gas chromatographic data which were transformed with logarithm. GC data is the most objective method to evaluate Sigumjang aroma. A multiple correlation coefficient and a determination coefficient of more than 0.9 were obtained at the 9th and 13th steps, respectively. At step 31, the coefficient of determination level of 0.95 was attained. The accuracy of its estimation became higher as the number of the variables entered into the regression model increased. Over 90% of the Sigumjang aroma was explained by 13 compounds indentified on GC. The contributing proportion of the peak 26 was the highest followed by peaks 57 (9.27%), 29 (7.51%), 54 (6.01%), 8 (5.99%), 49 (4.97%), and 13 (4.11%).

• The Korean Journal of Health Service Management
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• v.11 no.1
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• pp.117-130
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• 2017

Objectives : In this study, 3,107 patients were used to evaluate the impact based on raw data of 2014 and the health status and medical expenses income quintile was collected and data was analyzed. Methods : Analysis method was the average comparison, ANOVA, subjected to a multiple logistic regression analysis, the statistical test was the t-test and the scheffe post verification. Results : Gender(p<.000), age(p<.000), marital status(p<.000) educational status (p<.000), easement(p<.000), medication(p<.000), subjective health status(p<.005) were analyzed. First quintile identified that the highest amount was spent in the Chungcheong region, the 2nd quintile showed that the highest output was in the Gyeongsang region. The 3rd and 4th quintiles indicated that the highest expenditure was in the Seoul metropolitan region. The 5th quintile showed that the Chungcheong was the highest once again and the Jeolla region was the lowest in terms of expediture. Conclusions : Future medical research on income will require the government's Big Data collection to create the primary basis for policy making in order to improve the efficiency, effectiveness and equity of medicine spending.

• Korea Trade Review
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• v.46 no.2
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• pp.281-299
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• 2021

This paper analyzes the feasibility of using machine learning methods to forecast the employment. The machine learning methods, such as decision tree, artificial neural network, and ensemble models such as random forest and gradient boosting regression tree were used to forecast the employment in Busan regional economy. The following were the main findings of the comparison of their predictive abilities. First, the forecasting power of machine learning methods can predict the employment well. Second, the forecasting values for the employment by decision tree models appeared somewhat differently according to the depth of decision trees. Third, the predictive power of artificial neural network model, however, does not show the high predictive power. Fourth, the ensemble models such as random forest and gradient boosting regression tree model show the higher predictive power. Thus, since the machine learning method can accurately predict the employment, we need to improve the accuracy of forecasting employment with the use of machine learning methods.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.585-596
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• 2013

The objective of this study is to evaluate the hybrid downscaling method combined Step-Wise Scaling (SWS) method with Regional Climate Model (RCM) simulation data for climate change impact study on hydrology area. The SWS method is divided by 3 categories (extreme event, dry event and the others). The extreme events, wet-dry days and the others are corrected by using regression method, quantile mapping method, mean & variance scaling method. The application and evaluation of SWS method with 3 existing and popular statistical techniques (linear scaling method, quantile mapping method and weather generator method) were performed at the 61 weather stations. At the results, the accuracy of corrected simulation data by using SWS are higher than existing 3 statistical techniques. It is expected that the usability of SWS method will grow up on climate change study when the use of RCM simulation data are increasing.

• Tuberculosis and Respiratory Diseases
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• v.72 no.5
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• pp.433-440
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• 2012

Background: The pulmonary function test is the most basic test method to diagnosis lung disease. The purpose of this study was to research the correlation of the body mass index (BMI), the fat percentage of the body mass (fat%), the muscle mass, the fat-free mass (FFM) and the fat-free mass index (FFMI), waist-hip ratio (WHR), on the forced expiratory volume curve. Methods: Between March and April 2009, a total of 291 subjects were enrolled. There were 152 men and 139 female (mean age, $46.3{\pm}9.92$ years), and they were measured for the following: forced vital capacity (FVC), forced expiratory volume at 1 second ($FEV_1$), and forced expiratory flow during the middle half of the FVC ($FEF_{25-75}$) from the forced expiratory volume curve by the spirometry, and the body composition by the bioelectrical impedance method. Correlation and a multiple linear regression, between the body composition and pulmonary function, were used. Results: BMI and fat% had no correlation with FVC, $FEV_1$ in male, but FFMI showed a positive correlation. In contrast, BMI and fat% had correlation with FVC, $FEV_1$ in female, but FFMI showed no correlation. Both male and female, FVC and $FEV_1$ had a negative correlation with WHR (male, FVC r=-0.327, $FEV_1$ r=-0.36; p<0.05; female, FVC r=-0.175, $FEV_1$ r=-0.213; p<0.05). In a multiple linear regression of considering the body composition of the total group, FVC explained FFM, BMI, and FFMI in order ($r^2$=0.579, 0.657, 0.663). $FEV_1$ was explained only fat% ($r^2$=0.011), and $FEF_{25-75}$ was explained muscle mass, FFMI, FFM ($r^2$=0.126, 0.138, 0.148). Conclusion: The BMI, fat%, muscle mass, FFM, FFMI, WHR have significant association with pulmonary function but $r^2$ (adjusted coefficient of determination) were not high enough for explaining lung function.