• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.403-410
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• 2014

Binary logistic regression analysis is a statistical technique that explains binary response variable by quantitative or qualitative explanatory variables. In the binary logistic regression model, the probability that the response variable equals, say 1, one of the binary values is to be explained as a transformation of linear combination of explanatory variables. This is one of big barriers that non-statisticians have to overcome in order to understand the model. In this study, an educational tool is developed that explains the need of the binary logistic regression analysis using Excel VBA. More precisely, this tool explains the problems related to modeling the probability of the response variable equal to 1 as a linear combination of explanatory variables and then shows how these problems can be solved through some transformations of the linear combination.

• Korean Journal of Ecology and Environment
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• v.34 no.3 s.95
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• pp.215-222
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• 2001

A statistical analysis was performed to evaluate relationships among the pollutant concentrations in non-urban area. The data obtained from two subcatchments in Hwa-Ong watershed during 1999 was used for correlation and regression analyses. Strong correlations were observed among the SS, COD, and TP, while it was not significant with TN. The reason fer weak correlation with TN might be that TN was high in dry-days and runoff in wet-days could not increase enough to change it substantially like in other pollutants. The correlations were stronger for the data in wet-days than in dry-days, and it was influenced by watershed characteristics. While TP-COD showed linear relationship from the regression analysis, SS-TP and SS-COD shelved intrinsically linear relationship between log-transformed TP and COD data and non-transformed SS data. The TP-COD showed strong relationship for all the combinations of monitored data, which implies that these two constituent concentrations varied in a similar pattern. The regression equations reported in the paper might be used to estimate one pollutant concentration from the other in pollutant loading estimates, and its application could be expanded to other non-urban watersheds if their characteristics are not significantly different from the study area. In water quality management projects, rigorous monitoring and its thorough evaluation are recommended to develop more reliable relationships among the pollutant concentrations which could be used in other area.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.51.1-51.15
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• 2023

Background: Recently, there has been increasing worldwide concern about outdoor air pollution, especially particulate matter (PM), which has been extensively researched for its harmful effects on the respiratory system. However, sufficient research on its effects on cardiovascular diseases, such as hypertension, remains lacking. In this study, we examine the associations between PM levels and hypertension and hypothesize that higher PM concentrations are associated with elevated blood pressure. Methods: A total of 133,935 adults aged ≥ 40 years who participated in the Korean Genome and Epidemiology Study were analyzed. Multiple linear regression analyses were conducted to investigate the short- (1-14 days), medium- (1 and 3 months), and long-term (1 and 2 years) impacts of PM on blood pressure. Logistic regression analyses were conducted to evaluate the medium- and long-term effects of PM on blood pressure elevation after adjusting for sex, age, body mass index, health-related lifestyle behaviors, and geographic areas. Results: Using multiple linear regression analyses, both crude and adjusted models generated positive estimates, indicating an association with increased blood pressure, with all results being statistically significant, with the exception of PM levels over the long-term period (1 and 2 years) in non-hypertensive participants. In the logistic regression analyses on non-hypertensive participants, moderate PM₁₀ (particulate matter with diameters < 10 ㎛) and PM_2.5 (particulate matter with diameters < 2.5 ㎛) levels over the long-term period and all high PM₁₀ and PM_2.5 levels were statistically significant after adjusting for various covariates. Notably, high PM_2.5 levels of the 1 year exhibited the highest odds ratio of 1.23 (95% confidence interval: 1.19-1.28) after adjustment. Conclusions: These findings suggest that both short- and long-term exposure to PM is associated with blood pressure elevation.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.55-72
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• 1987

The work analyzes the existing situation and defines special problems concerning traffic accidents in the two countries. The report is divided into three parts: 1) Using the global approach of SMEED, the data were evaluated using multiple regression analysis, and homogeneous groups of countries were defined by cluster analysis. In the global approach, the linear model is better than SMEED's non-linear model in explaining the number of fatalities. Among the different groups of countries, the linear approach was found to be better suited for industrialized countries and the non-linear approach better for the developing countries. T도 comparison of traffic fatality data for the Federal Republic the developing countries. The comparison of traffic fatality data for the Federal Republic of Germany and the Republic of Korea showed different regression equations during the same time period. 2) The BOX/JENKINS time series analysis on a monthly basis points out clearly similar seasonal patterns for the two countries over the years studied. The decrease in traffic accidents following the intensification of the safety belt requirement was proved in the ARIMA model. It amounts to 7 to 8 percent fewer personal injury accidents and fatal accidents. The identified increase in safety in the Federal Republic of Germany since the 1970s is mainly due to the reduction of accident severity in residential areas. 3) Speeds and headways on motorways in th3e two countries were also compared. The measurements point out that German road users drive faster, take more risks, and accept shorter time gaps than Korean road users. However, the accident statistics show accident rates for Korea that are several times higher than those in the Federal Republic of Germany.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.41-47
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• 2009

This study deals with the side-swipe accidents of 4-legged signalized intersections in Cheongju. The objectives are to analyze the characteristics of the accidents and to develop the related models. In pursuing the above, this study gives particular emphasis to finding the appropriate methodology to modelling. The main results are as follows. First, injuries were analyzed to be twice than property-only accidents in the side-swipe accidents. The accidents were evaluated to occur more in inside-intersection. Also, the accidents were analyzed to be almost the auto-related accidents and to be occurred by the unsafely-driving activity. Second, multiple linear regression models were evaluated to be more statistically significant than multiple non-linear. The most fitted models were analyzed to be the models with the number of accidents as the dependent variable. The factors of side-swipe accidents analyzed in this study were ADT, area of intersection, right-turn-only-lane, number of pedestrian crossings, limited speed of main road, maximum grade and number of signal phase.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.835-842
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• 2020

The study aims to investigate the impact of debt on corporate profitability in the context of Vietnam. The paper investigates the impact of debt on corporate profitability in non-finance listed companies on the Vietnam stock market. The panel data of the research sample includes 118 non-financial listed companies on the Vietnam stock market for a period of nine years, from 2009 to 2017. The Generalized Method of Moments (GMM) is employed to address econometric issues and to improve the accuracy of the regression coefficients. In this research, corporate profitability is measured as the return of EBIT on total assets. The debt ratio is a ratio that indicates the proportion of a company's debt to its total assets. Firm sizes, tangible assets, growth rate, and taxes are control variables in the study. The empirical results show that debt has a statistically significant negative effect on corporate profitability. The result also shows this effect is stronger in a non-linear (concave) way, we show that the debt ratio has nonlinear effects on corporate profitability. From this, experimental evidence shows that the optimal debt ratio is 38.87%. This evidence provides a new insight to managers of the non-finance companies on how to improve the firm's profitability with debt.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1231-1234
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• 2003

A sensor working in outdoor may generate some faulty signal owing to dust and high temperature. This paper describes an intelligent sensor system and controller which has a reconstruction mechanism for faulty signal. The faulty signals are dievided into two types as linear distortion and non linear distortion, respectively. The linear distorted signal is due to dust, and non linear distorted signal is due to physical breakdown of sensor or high temperature. These distorted signal have been reconstructed by the proposed method based on polynomial regression method and principal component analysis approach.. The proposed method has been applied to sun tracking system working in outdoor. For a robust and precision control of sun tracker, a fuzzy controller was also proposed. The fuzzy controller controls the tracker by using the collected sensor signal. The tolerance of the position control is within 1.5 degree. To show the validity of the developed system, some experiments in the field were illustrated.

• Analytical Science and Technology
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• v.12 no.5
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• pp.375-381
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• 1999

Near infrared spectrophotometry(NIR) was developed as a non-invasive determination of blood alcohol. The first pure alcohol/water samples were prepared with ethanol concentration from 0.01 to 0.1%(w/w). Analysis of the second-derivative data was accomplished with multilinear regression(MLR). The standard error of calibration(SEC) of ethanol in ethanol/water solutions was approximately 0.0039%. The calibration models were established from the blood alcohol spectra by MLR and PLSR analysis. The best calibration was built with the second-derivative spectra of 2266 and 2326 nm by MLR. Second-derivative spectra in the spectral ranges of 1100~1340, 1500~1796 and 2064~2300 nm with four PLSR factors provided the standard error of prediction(SEP) of 0.030%(w/w). These results indicate that NIR may be applied for a fast non-invasive determination of alcohol in the blood.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.354-362
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• 2010

This paper presents a non-linear control chart based on support vector machine regression (SVM-R) to improve the accuracy of fault detection of cyclic signals. The proposed algorithm consists of the following two steps. First, the center line of the control chart is constructed by using SVM-R. Second, we calculate control limits by variances that are estimated by perpendicular and normal line of the center line. For performance evaluation, we apply proposed algorithm to the industrial data of the chemical vapor deposition process which is one of the semiconductor processes. The proposed method has better fault detection performance than other existing method

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.5123-5125
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• 2013

Background: Breast cancer is one the most common cause of cancer-related deaths among women worldwide. The aims of this study were to investigate the impact of dietary factors and health status indicators on breast cancer (BC) incidence. Materials and Methods: Risk factor data (RFD) of 89,404 individuals (15-64 years old) were gathered by questionnaire and laboratory examinations through a cross sectional study from the Non-Communicable Disease Surveillance Centre (NCDSC) of Iran. BC incidences of all provinces through 2001-2006 segregated by age and gender were obtained from the Cancer Registry Ministry of Health (CRMH). Results: a significant positive relationship was seen between diabetes mellitus, fish comsupmption, percent of academic education and non-consumption of fruit, and breast cancer in women. However, non fish consumption, percent age illiteracy and taking fruit showed a significant negative relationship with the incidence of breast cancer. In addition, multiple linear regression analysis showed associations among percentage with academic education, fruit consumption and diabetes. Conclusions: We conclude that dietary factors such as fish and furit consumption, dairy products, health status indicators, academic education, and some diseases like diabetes mellitus can affect the BC incidence, although the results of ecologic studies like this must naturally be interpreted with caution.