• Annals of Occupational and Environmental Medicine
• /
• 제35권
• /
• pp.5.1-5.14
• /
• 2023

Background: Perfluoroalkyl substances (PFAS) are chemicals widely used in various products in everyday life. Due to its unique strong binding force, the half-life of PFAS is very long, so bioaccumulation and toxicity to the human body are long-standing concerns. In particular, effects on kidney function have recently emerged and there are no studies on the effect of PFAS on kidney function through epidemiological investigations in Korea. From 2018 to 2020, the Korean National Environmental Health Survey (KoNEHS) cycle 4, conducted an epidemiological investigation on the blood concentration of PFAS for the first time in Korea. Based on this data, the relationship between PFAS blood concentration and kidney function was analyzed for adolescents. Methods: We investigated 5 types of PFAS and their total blood concentration in 811 middle and high school students, living in Korea and included in KoNEHS cycle 4, and tried to find changes in kidney function in relation to PFAS concentration. After dividing the concentration of each of the 5 PFAS and the total concentration into quartiles, multivariable linear regression was performed to assess the correlation with kidney function. The bedside Schwartz equation was used as an indicator of kidney function. Results: As a result of multivariable linear regression, when observing a change in kidney function according to the increase in the concentration of each of the 5 PFAS and their total, a significant decrease in kidney function was confirmed in some or all quartiles. Conclusions: In this cross-sectional study of Korean adolescents based on KoNEHS data, a negative correlation between serum PFAS concentration and kidney function was found. A well-designed longitudinal study and continuous follow-up are necessary.

• 응용통계연구
• /
• 제14권1호
• /
• pp.71-80
• /
• 2001

로지스틱 회귀모형은 이항 반응자료에 대한 가장 보편적인 일반화 선형모형으로 독립변수에 대한 확률함수를 추정하는데 이용된다. 많은 실제적 상황에서 확률함수가 종형의 곡선형태로 표현되는데 이 경우에는 2차항을 포함한 로지스틱 회귀모형을 이용한 분석은 대칭성을 갖는 확률함수에 대한 가정으로 인해 비대칭 형태의 종형곡선에서는 확률함수의 신뢰성이 저하되고, 2차항을 포함하기 때문에 독립변수의 효과를 설명하기가 쉽지 않다는 제한점을 가지고 있다. 본 논문에서는 이러한 문제점을 해소하기 위해서 로지스틱 회귀분석과 반복적 이분법을 이용하여 종형의 형태에 관계없이 확률곡선을 추정하는 방법론을 제안하고 모의 실험을 통해 2차항을 포함한 로지스틱 회귀모형과 비교하고자 한다.

• Journal of Biosystems Engineering
• /
• 제31권3호
• /
• pp.194-202
• /
• 2006

Using a multi-variable linear regression technique and SUR(seemingly unrelated regression) model, the demand functions of tractor, combine and rice transplanter were estimated. The demand was regarded as an annual supply of each machine and modeled as a function of 11 independent variables which reflect the actual farmer's income, actual prices of farm machines, previous supply, previous stock, actual amount of available subsidy, actual amount of available loan, arable land, import of farm machines and rice price. The actual amount of available loan affects most significantly the demand functions. The actual farmer's income, actual farmer's asset, loan coverage, and rice price affect the demand positively while prices of farm machines and import negatively. The annual demands of tractor, combine and rice transplanter estimated using the demand functions were also presented over the next 4 years.

• 한국농공학회논문집
• /
• 제56권4호
• /
• pp.29-39
• /
• 2014

In this study, we performed a non-stationary frequency analysis using a power model and the model was applied for Seoul, Daegu, Daejeon, Mokpo sites in Korea to estimate the probable precipitation amount at the target years (2020, 2050, 2080). We used the annual maximum precipitation of 24 hours duration of precipitation using data from 1973 to 2009. We compared results to that of non-stationary analyses using the linear and logistic regression. The probable precipitation amounts using linear regression showed very large increase in the long term projection, while the logistic regression resulted in similar amounts for different target years because the logistic function converges before 2020. But the probable precipitation amount for the target years using a power model showed reasonable results suggesting that power model be able to reflect the increase of hydrologic extremes reasonably well.

• Communications for Statistical Applications and Methods
• /
• 제30권6호
• /
• pp.605-629
• /
• 2023

This paper proposes some diagnostics procedures for the skew-t linear regression model with censored response. The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and student's-t distributions as special cases. Inspired by the power and wide applicability of the EM-type algorithm, local and global influence analysis, based on the conditional expectation of the complete-data log-likelihood function are developed, following Zhu and Lee's approach. For the local influence analysis, four specific perturbation schemes are discussed. Two real data sets, from education and economics, which are right and left censoring, respectively, are analyzed in order to illustrate the usefulness of the proposed methodology.

• Computers and Concrete
• /
• 제11권3호
• /
• pp.237-252
• /
• 2013

This paper presents the application of artificial neural network (ANN) to predict deep beam deflection using experimental data from eight high-strength-self-compacting-concrete (HSSCC) deep beams. The optimized network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of ten and four neurons in first and second hidden layers using TRAINLM training function predicted highly accurate and more precise load-deflection diagrams compared to classical linear regression (LR). The ANN's MSE values are 40 times smaller than the LR's. The test data R value from ANN is 0.9931; thus indicating a high confidence level.

• 한국지하수토양환경학회:학술대회논문집
• /
• 한국지하수토양환경학회 2003년도 총회 및 춘계학술발표회
• /
• pp.217-220
• /
• 2003

In the case of the remediation studies, push pull test is a more time and cost effective mettled than multi-well tracer test. It also gives Just as much or more information than the traditionally used methods. But the data analysis for the hydraulic parameters, there have been some defections such as underestimation of dispersivity, requirement for effective porosity, and calculation of recovery of center of mass to estimate linear velocity. In this research, Weibull distribution function is proposed to estimate the center of mass of breakthrough curve for Push pull test. The hydraulic parameter estimation using Weibull function showed more exact values of center of mass than those of exponential regression for field test data.

• 성인간호학회지
• /
• 제27권1호
• /
• pp.52-62
• /
• 2015

Purpose: The purpose of this study was to examine the relationships between frailty, nutritional status, positive thinking, family function, and health conservation and to identify the factors influencing health conservation of the elderly at home. Methods: The research design was a descriptive survey using a convenience sampling. Data were collected from 142 elders using self-reported questionnaires. Data were analyzed using the SPSS/WIN 20.0 program for descriptive statistics, Pearson's correlation coefficients, and multiple linear regression. Results: The average health conservation score was 98.85. There were significant correlations between frailty, nutritional status, positive thinking, family function and health conservation. As a result of the multiple linear regression analysis, positive thinking, perceived health status, spouse and frailty accounted for 69% of the variance in health conservation of the elderly at home. Conclusion: These influencing factors on health conservation can be taken into account in the development of nursing intervention programs for improving health conservation of the elderly at home.

• 대한원격탐사학회지
• /
• 제32권2호
• /
• pp.171-183
• /
• 2016

2013년부터 2014년까지 관측된 Landsat 8 위성자료로부터 지표면 온도를 산출하였고 산출된 지표면 온도는 지상에서 관측된 지표면 온도를 이용하여 보정하였다. 지표면 온도지도는 Landsat 8로부터 산출된 지표면 온도를 지상에서 관측된 지표면 온도와의 선형 회귀식을 이용하여 계산되었다. 계절과 년에 대한 지표면 온도는 각각 계절과 년에 대하여 사례들을 평균하여 계산되었다. 지표면 온도는 도시의 공업 또는 상업지역에서 높은 온도가 나타나는 반면, 서울주변의 높은 고도의 산악과 해양, 강 등에서 낮은 지표면 온도가 나타났다. 위성에서 산출된 지표면 온도를 보정하기 위하여 서울을 포함한 수도권지역에서 관측되는 기상청 종관측소 3개 지점 (서울(지점번호: 108), 인천(지점번호: 119), 수원(지점번호: 112))의 지표면 관측 자료를 이용하여 선형회귀방법을 적용하였다. Landsat 8의 지표면 온도는 모든 자료에서 기울기가 0.78이었고 5개의 흐린날을 제외한 맑은 상태의 자료에서 0.88이었다. 그리고 초기 지표면온도에서 상관계수는 0.88이었고 평방근 오차 (Root Mean Sqare Error (RMSE))는 $5.33^{\circ}C$이었다. 지표면 온도 보정이후에는 상관계수는 0.98 그리고 RMSE는 $2.34^{\circ}C$이었으며 회귀식의 기울기는 0.95로 개선되었다. 계절 및 년 지표면 온도는 상업지역과 공업지역 그리고 도시와 주변지역을 잘 표현하였다. 결과적으로 지상에서 관측된 지표면 온도를 이용하여 위성에서 산출된 지표면온도를 보정하였을 때 실제 상태와 유사한 분포를 보였다.

• 전기학회논문지
• /
• 제64권12호
• /
• pp.1748-1755
• /
• 2015

A linear regression is widely used for prediction problem, but it is hard to manage an irregular nature of nonlinear system. Although nonlinear regression methods have been adopted, most of them are only fit to low and limited structure problem with small number of independent variables. However, real-world problem, such as weather prediction required complex nonlinear regression with large number of variables. GP(Genetic Programming) based evolutionary nonlinear regression method is an efficient approach to attach the challenging problem. This paper introduces the improvement of an GP based nonlinear regression method using ADF(Automatically Defined Function). It is believed ADFs allow the evolution of modular solutions and, consequently, improve the performance of the GP technique. The suggested ADF based GP nonlinear regression methods are compared with UM, MLR, and previous GP method for 3 days prediction of wind speed using MOS(Model Output Statistics) for partial South Korean regions. The UM and KLAPS data of 2007-2009, 2011-2013 years are used for experimentation.