• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.121-129
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• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.123-127
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• 2002

In this paper, we propose spatial prediction model for landslide hazard mapping that can account for the fuzziness of boundaries in thematic maps showing the different environmental impacts, depending on the scales and the resolutions of them. The fuzziness or uncertainty of boundary is represented in favourability function based on fuzzy object concept and the effects of them are quantitatively evaluated with the help of cross validation procedures. To illustrate the proposed schemes, a case study from Boeun, Korea was carried out. As a result, the proposed schemes are helpful to account for intrinsic uncertainties in categorical maps and can be effectively adopted in spatial prediction models for other purposes.

• Communications for Statistical Applications and Methods
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• v.21 no.4
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• pp.285-296
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• 2014

The quantile residual life function has been effectively used to interpret results from the analysis of the proportional hazards model for censored survival data; however, the quantile residual life function is not always estimable with currently available semi-parametric regression methods in the presence of heavy censoring. A parametric regression approach may circumvent the difficulty of heavy censoring, but parametric assumptions on a baseline hazard function can cause a potential bias. This article proposes a Bayesian semi-parametric regression approach for inference on an unknown baseline hazard function while adjusting for available covariates. We consider a model-based approach but the proposed method does not suffer from strong parametric assumptions, enjoying a closed-form specification of the parametric regression approach without sacrificing the flexibility of the semi-parametric regression approach. The proposed method is applied to simulated data and heavily censored survival data to estimate various quantile residual lifetimes and adjust for important prognostic factors.

• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.2 s.2
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• pp.75-83
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• 2001

In this study, the maintenance problems were investigated through checking the creeks which were improved by close-to-nature river improvement technique. The characteristics of flow were measured at Changsa Creek in Suwon city. The computational results of numerical model with kinematic wave theory was evaluated through observation data about precipitation, velocity, and flow depth. Furthermore, SCS, Clark, and RRL models were compared to the actual observations. As a result, the kinematic wave theory's calculated peak time of discharge concentration occurred little earlier than the actual observation, but the tendency of hydrograph coincided with observation.

• Korea Journal of Hospital Management
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• v.23 no.2
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• pp.42-53
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• 2018

Purpose: this study investigates the effect of private health insurance on healthcare utilization. Methodology: For the analysis, we employed the three level nested two part model. Findings: the private health insurance adoption was associated with higher health care utilization. In particular, indemnity and fixed insurances adoption was associated with higher probability of outpatient visit, the number of outpatient visit and outpatient cost. While indemnity insurance adoption was associated with higher inpatient admission probability and inpatient days, fixed insurance adoption was associated only with higher inpatient admission probability. Practical Implications: indemnity and fixed insurance adoption were related with the adverse selection as well as moral hazard.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.533-542
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• 2002

In this paper, a covariate adjusted logrank test is considered for censored paired data under the Cox proportional hazard model. The proposed score test resembles the adjusted logrank test of Tsiatis, Rosner and Tritchler (1985), which is derived from the partial likelihood. The dependence structure for paired data is accommodated into the test statistic by using' sum of square type' variance estimators. Several weight functions are also considered, which produce a class of covariate adjusted weighted logrank tests. Asymptotic normality of the proposed test is established and simulation studies with moderate sample size show the proposed test works well, particularly when there are dependence structure between treatment and covariates.

• Journal of the Korean Home Economics Association
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• v.42 no.1
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• pp.69-79
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• 2004

This study has examined factors of young married women's new entry in labor market after the birth of their first child. For the dynamic analysis, the Cox Regression Hazard Model is applied. The following results are obtained： First, about 33％ of married women who did not have a job at the pre-birth enter in labor market at the post-birth. Second, compared to those out of the labor force, women who succeeded in finding their first jobs after the birth of their first child are more likely to be younger, have baby-sitters, have working experiences in the past, and have lower level of household income. Third, age, having baby-sitter and the experience of job transition are vital factors in entering the labor market after the first child birth.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.247-250
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• 2006

Based on the possibility theory and the fuzzy set, the Maximum Possibility Estimation method and its applications in kinematic GPS positioning are presented in this paper. Firstly, the principle and the optimal criterion of the Maximum Possibility Estimation method are explained. Secondly, the kinematic GPS positioning model of single epoch single frequency with baseline length constraint is developed. Then, the authors introduce the artificial immune algorithm and use this algorithm to search the global optimum of the Maximum Possibility Estimation model. The results of some examples show that the method is efficient for kinematic GPS positioning.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.265-269
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• 2005

Cox's proportional hazards model (PHM) has been widely applied in the analysis of lifetime data, and it can be characterized by the baseline hazard function and covariates influencing systems' lifetime, where the covariates describe operating environments (e.g. temperature, pressure, humidity). In this article, we consider the constant baseline hazard function and a discrete random variable of a covariate. The estimation procedure is developed in a parametric framework when there are not only complete data but also incomplete one. The Expectation-Maximization (EM) algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.9-15
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• 2023

The Severe Disaster Punishment Act had recently been established in order to promote safety and health (OSH) management system for severe accident prevention. OSH management system is primarily designed based on risk assessments; however, companies in industries have been experiencing difficulties in hazard identification and selecting proper measures for risk assessments and accident prevention. This study intended to introduce an accident analysis method based on epidemiological model in finding hazard and preventive measures. The accident analysis method employed in this study was proposed by the U.S. Department of Energy. To demonstrate the effectiveness of the accident analysis method, this study applied it to two accident cases occurred in construction and manufacturing industries. The application process and results of this study can be utilized in improving OSH management system and preventing severe accidents.