• International Journal of Quality Innovation
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• 제3권2호
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• pp.174-182
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• 2002

System identification and controller formulation are essential in dynamic process control. In system identification, data for system identification are obtained, and then they are analyzed so that the system model of the process is built, identified, and diagnosed. In controller formulation, the control equation is derived based on the result of the system identification. There has been much theoretical research on system identification and controller formulation. These theories are very useful when they are appropriately applied. To our regret, however, these theories are not always effectively applied in practice because the engineers and the operators who manage the process often do not have the necessary understanding of required time series analysis methods. On the other hand, because of widespread use of statistical packages, system identification such as estimating ARMA models can be done with little understanding of time series analysis methods. Therefore, it might be said that the most theoretically difficult part in practice is the controller formulation. In this paper, lists of control equations are proposed as a useful tool for practitioners to use. The tool supports bridging the gap between theory and practice in dynamic process control. Also, for some models, the generalized control equations are obtained.

• Journal of the Korean Data and Information Science Society
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• 제25권1호
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• pp.211-218
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• 2014

Qu et. al. (2000) proposed the quadratic inference functions (QIF) method to marginal model analysis of longitudinal data to improve the generalized estimating equations (GEE). It yields a substantial improvement in efficiency for the estimators of regression parameters when the working correlation is misspecified. But for the longitudinal data with time-dependent covariates, when the implicit full covariates conditional mean (FCCM) assumption is violated, the QIF can not provide more consistent and efficient estimator than GEE (Cho and Dashnyam, 2013). Lai and Small (2007) divided time-dependent covariates into three types and proposed generalized method of moment (GMM) for longitudinal data with time-dependent covariates. They showed that their GMM type II and GMM moment selection methods can be more ecient than GEE with independence working correlation (GEE-ind) in the case of type II time-dependent covariates. We develop upgraded QIF method for type II time-dependent covariates. We show that this upgraded QIF method can provide substantial gains in efficiency over QIF and GEE-ind in the case of type II time-dependent covariates.

• Journal of the Korean Data and Information Science Society
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• 제24권3호
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• pp.651-658
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• 2013

For the marginal model and generalized estimating equations (GEE) method there is important full covariates conditional mean (FCCM) assumption which is pointed out by Pepe and Anderson (1994). With longitudinal data with time-varying stochastic covariates, this assumption may not necessarily hold. If this assumption is violated, the biased estimates of regression coefficients may result. But if a diagonal working correlation matrix is used, irrespective of whether the assumption is violated, the resulting estimates are (nearly) unbiased (Pan et al., 2000).The quadratic inference functions (QIF) method proposed by Qu et al. (2000) is the method based on generalized method of moment (GMM) using GEE. The QIF yields a substantial improvement in efficiency for the estimator of ${\beta}$ when the working correlation is misspecified, and equal efficiency to the GEE when the working correlation is correct (Qu et al., 2000).In this paper, we interest in whether the QIF can improve the results of the GEE method in the case of FCCM is violated. We show that the QIF with exchangeable and AR(1) working correlation matrix cannot be consistent and asymptotically normal in this case. Also it may not be efficient than GEE with independence working correlation. Our simulation studies verify the result.

• 사회복지연구
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• 제48권4호
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• pp.33-57
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• 2017

본 연구는 점증하는 가계부채에 대한 관심과 우려가 커지는 상황에서 가계부채가 부부폭력의 위험에 미치는 영향을 분석하였다. 자료는 한국복지패널 4~11차(2009~2016년) 데이터를 활용하였으며, 분석방법으로는 일반화추정방정식(Generalized Estimating Equations)을 사용하였다. 분석 결과, 가계부채비(가처분소득 대비 총부채액)와 부채상환비(가처분소득 대비 부채상환액)가 높아질수록 부부폭력의 위험도 증가하는 경향이 있었 다. 비빈곤층에서는 높은 부채상환비가, 빈곤층에서는 높은 비우량부채비가 부부폭력의 위험을 높이는 것으로 나타났다. 물질적 결핍의 매개효과 역시 빈곤지위에 따라 달랐는데, 빈곤층에서는 물질적 결핍이 비우량부채비와 부부폭력의 관계를 매개하는 것으로 보이나, 비빈곤층에서는 그러한 관계가 관찰되지 않았다. 이 연구는 경제적 곤란이 부부관계의 질에 영향을 미친다는 가족스트레스모델을 가계부채의 역할에 초점을 맞추어 적용하고, 경제적 곤란을 야기하는 다양한 요인 중 부채 부담 수준이 부부폭력의 위험에 미치는 영향을 실증분석 하였다는데 의미가 있다.

• ETRI Journal
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• 제35권5호
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• pp.849-858
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• 2013

In this paper, we propose a new adaptive single model to track a maneuvering target with abrupt accelerations. We utilize the stochastic differential equation to model acceleration of a maneuvering target with stochastic volatility (SV). We assume the generalized autoregressive conditional heteroscedasticity (GARCH) process as the model for the tracking procedure of the SV. In the proposed scheme, to track a high maneuvering target, we modify the Kalman filtering by introducing a new GARCH model for estimating SV. The proposed tracking algorithm operates in both the non-maneuvering and maneuvering modes, and, unlike the traditional decision-based model, the maneuver detection procedure is eliminated. Furthermore, we stress that the improved performance using the GARCH acceleration model is due to properties inherent in GARCH modeling itself that comply with maneuvering target trajectory. Moreover, the computational complexity of this model is more efficient than that of traditional methods. Finally, the effectiveness and capabilities of our proposed strategy are demonstrated and validated through Monte Carlo simulation studies.

• 한국환경보건학회:학술대회논문집
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• 한국환경보건학회 2005년도 가을학술대회
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• pp.126-129
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• 2005

본 연구는 서울지역 초등학교 학생 4, 5, 6학년 남 ${\cdot}$ 녀 초등학생들을 대상으로 봄철 대기오염농도와 일별 자각증상 과의 관련성에 대한 패널연구를 수행하였다. 로지회귀분석방법 중 일반화 추정 방정식(generalized estimating equations:GEE)모델을 이용하여 통계분석을 실시한 결과로는 서울지역 초등학교 학생들은 호흡기 증상보다는 피부가려움이나 눈의 따가움 등의 자극증상에 호흡성먼지(PM10)와 아황산가스 그리고 이산화질소 등의 대기오염물질 농도와 관련성이 있는 것으로 추정되었다.

• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2001년도 춘계학술대회
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• pp.73-86
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• 2001

본 논문은 복합표본조사 분석에서 회귀모형 접근법으로 사용되는 모형 기반 접근법, 설계 기반접근법과 일반화 추정 방정식 접근법을 설명하고, 이들을 실증적으로 비교한 것이다. 또한 설계 기반 접근법과 일반화 추정 방정식 접근법에 대해서 설계효과와 가중치 효과 분석을 통해서 표본 설계가 모수 추정에 미치는 영향을 살펴보았다.

• Journal of Preventive Medicine and Public Health
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• 제50권6호
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• pp.377-385
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• 2017

Objectives: Although mercury (Hg) exposure is known to be neurotoxic in humans, its effects on liver function have been less often reported. The aim of this study was to investigate whether total Hg exposure in Korean adults was associated with elevated serum levels of the liver enzymes aspartate aminotransferase (AST), alanine transaminase (ALT), and gamma-glutamyltransferase (GGT). Methods: We repeatedly examined the levels of total Hg and liver enzymes in the blood of 508 adults during 2010-2011 and 2014-2015. Cross-sectional associations between levels of blood Hg and liver enzymes were analyzed using a generalized linear model, and nonlinear relationships were analyzed using a generalized additive mixed model. Generalized estimating equations were applied to examine longitudinal associations, considering the correlations of individuals measured repeatedly. Results: GGT increased by 11.0% (95% confidence interval [CI], 4.5 to 18.0%) in women and 8.1% (95% CI, -0.5 to 17.4%) in men per doubling of Hg levels, but AST and ALT were not significantly associated with Hg in either men or women. In women who drank more than 2 or 3 times per week, AST, ALT, and GGT levels increased by 10.6% (95% CI, 4.2 to 17.5%), 7.7% (95% CI, 1.1 to 14.7%), and 37.5% (95% CI,15.2 to 64.3%) per doubling of Hg levels, respectively, showing an interaction between blood Hg levels and drinking. Conclusions: Hg exposure was associated with an elevated serum concentration of GGT. Especially in women who were frequent drinkers, AST, ALT, and GGT showed a significant increase, with a significant synergistic effect of Hg and alcohol consumption.

• 보건행정학회지
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• 제31권1호
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• pp.125-139
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• 2021

Background: In Korea, the health gap widens due to the number of medical resources and access to medical services between metropolitan and rural. The purpose of this study is to identify the impact of residential migration on medical utilization and accessibility. Methods: This study extracted 528,516 claimed cases in the National Health Insurance Service-Cohort Sample Database from 2006 to 2015. Subjects were classified into two groups by the magnitude of the region, the metropolitan and the rural. The inversed probability weights were calculated for each group. And coefficients of the two-part model were estimated by generalized estimation equation. Results: Those who moved region from metropolitan to rural tend to increase the length of stay and inpatients with ambulatory care sensitive conditions (ACSC) disease. Contrariwise, those who moved areas from rural to metropolitan tend to decrease the total medical cost, the adjusted patient days, the number of outpatients and the number of outpatients and inpatients with ACSC disease. Conclusion: This study identified that between the residents who continued to reside in the region and the migrants, there were significant differences in the medical accessibility, quality of primary care, and unmet medical need.

• Structural Engineering and Mechanics
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• 제16권2호
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• pp.219-240
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• 2003

One of the most versatile approaches for analyzing the dynamic behavior of structural systems is direct time integration of semi-discrete equations of motion. However responses computed by time integration are generally inexact and hence the corresponding errors would rather be studied in advance. In spite of the various error estimation formulations that exist in the literature, it is accepted practice to repeat the analyses with smaller time steps, followed by a comparison between the results. In this paper, after a review of this simple method and disregarding the round-off errors, a more efficient, reliable and yet simple method for estimating errors and enhancing the accuracy is proposed. The main objectives of this research are more realistic error estimation based on the concept of convergence, approximately controlling the reliability by comparing the actual rate of convergence with the integration method's order of accuracy, and enhancement of reliability by applying Richardson's extrapolation. Starting from the errors at specific time instants, the study is then generalized to cases in which the errors should be estimated and decreased at specific events e.g. peak responses. Numerical study illustrates the efficacy of the proposed method.