• Health Policy and Management
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• v.31 no.4
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• pp.451-461
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• 2021

Background: Readmissions related to lack of quality care harm both patients and health insurance finances. If the factors affecting readmission are identified, the readmission can be managed by controlling those factors. This paper aims to identify factors that affect readmissions of convalescent rehabilitation patients. Methods: Health Insurance Review and Assessment Service claims data were used to identify readmissions of convalescent patients who were admitted in hospitals and long-term care hospitals nationwide in 2018. Based on prior research, the socio-demographics, clinical, medical institution, and staffing levels characteristics were included in the research model as independent variables. Readmissions for convalescent rehabilitation treatment within 30 days after discharge were analyzed using logistic regression and generalization estimation equation. Results: The average readmission rate of the study subjects was 24.4%, and the risk of readmission decreases as age, length of stay, and the number of patients per physical therapist increase. In the patient group, the risk of readmission is lower in the spinal cord injury group and the musculoskeletal system group than in the brain injury group. The risk of readmission increases as the severity of patients and the number of patients per rehabilitation medicine specialist increases. Besides, the readmission risk is higher in men than women and long-term care hospitals than hospitals. Conclusion: "Reducing the readmission rate" is consistent with the ultimate goal of the convalescent rehabilitation system. Thus, it is necessary to prepare a mechanism for policy management of readmission.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.373-383
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• 2006

The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.4
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• pp.469-482
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• 2013

This study identified problems of the existing ecosystem-based fisheries assessment approach, and suggested new methods for scoring risk and for the estimation of fishery risk index. First, risk scores of zero to two for target and limit reference points for each indicator were replaced by those of zero to three, and the risk scores were calculated from new formulae which were developed in this study. Second, a new method for estimating fishery risk index (FRI) was developed in this study, considering the level of indicators. New method was applied to the Korean large purse seine fishery, large pair trawl fishery and drag net fishery. More precise and detailed risk scores were obtained from the new method, which can explain the risks by the wider range of both risk levels for 'better than target' and 'beyond limit'. The new method for estimating FRI could avoid the basic problem related with duplicated computations of fishery-level indicators, which improved the estimated FRI to be more accurate. Also, a method for estimating variance of FRI using the bootstrap was proposed in this study.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.291-311
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• 2007

With a series of unexpected huge losses in the financial markets around the world recently, especially in the insurance market with extreme loss cases such as catastrophes, there is an increasing demand for risk management for extreme loss exposures due to high unpredictability of those risks. For extreme risk management, to make a maximum use of the information concerning the tail part of a loss distribution, EVT(Extreme Value Theory) modelling nay be the best to analyze extreme values. The Extreme Value Theory is widely used in practice and, especially in financal markets, EVT modelling is getting popular to analyBe the effects of extreme risks. This study is to review the significance of the Extreme Value Theory in risk management and, focusing on analyzing insurer's risk capital, extreme risk is measured using the real fire loss data and insurer's specific amount of risk capital is figured out to buffer the extreme risk.

• Environmental Analysis Health and Toxicology
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• v.10 no.1_2
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• pp.21-35
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• 1995

Risk assessment processes, which include processes for the estimation of human cancer potency using animal bioassay data and calculation of human exposure, entail uncertainties. In the exposure assessment process, exposure scenarios with various assumptions could affect the exposure amount and excess cancer risk. We compared risk estimates among various exposure scenarios of vinyl chloride, trichloroethylene and tetrachloroethylene in tap water. The contaminant concentrations were analyzed from tap water samples in Seoul from 1993 to 1994. The oral and inhalation cancer potencies of the contaminants were estimated using multistage, Weibull, lognormal, and Mantel-Bryan model in TOX-RISK computer software. In the first case, human excess cancer risk was estimated by the US EPA method used to set the MCL(maximum contaminant level). In the second and third case, the risk was estimated for multi-route exposure with and without adopting Monte-Carlo simulation, respectively. In the second case, exposure input parameters and cancer potencies used probability distributions, and in the third case, those values used point estimates(mean, and maximum or 95% upper-bound value). As a result, while the excess cancer risk estimated by US EPA method considering only direct ingestion tended to be underestimated, the risk which was estimated by considering multi-route exposure without Monte-Carlo simulation and then using the maximum or 95% upper-bound value as input parameters tended to be overestimated. In risk assessment for volatile organic compounds, considering multi-route exposure with adopting Monte-Carlo analysis seems to provide the most reasonable estimations.

• Environmental and Resource Economics Review
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• v.16 no.3
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• pp.683-699
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• 2007

This study applied the choice experiment (CE) method to measure values of statistical lives from multi-attributed mortality risk reduction choices. The four characteristics of mortality risk (i.e. cause of death, voluntariness of mortality risk, timing of death, magnitude of mortality risk reduction) are utilized to design the alternatives of choice sets. The estimation results for the multinomial logit model show that individuals are willing to pay 27,930 won per year for a change from the status quo to a $\frac{1}{100}$ mortality risk reduction for 10 years, 116,773 won per year for mortality risk reduction associated with adults, 97,682 won per year for voluntary mortality risk reduction, 77,234 won per year for involuntary mortality risk reduction. There were several estimates of VSL related to different attributes of mortality risk. The mean VSLs of infant/child/young adult ranged from 1,165 million won to 1,367 million won. The mean VSLs ranged from 1,631 million won to 1,833 million won for adult, and were between 1,128 million won and 1,330 million won for old person.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.57-68
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• 2009

Recently, damage scale of human-induced disaster is sharply increased but its occurrences and damages are so uncertain that it is hard to construct a resonable response & mitigation plan for infrastructures. Therefore, the needs for a advanced risk management technique based on a probabilistic and stochastic risk evaluation theory is increased. In this study, these evaluation methods were investigated and a advanced disaster risk evaluation method, which is based on the probabilistic or stochastic risk assessment theory and also is a quantitative evaluation technique, was suggested. With this method, the safety changes as the result of fire damage management for recent 40 years was analyzed. And the result was compared with that of Japan. Through the consilience of the traditional risk assessment method and this method, a stochastical estimation technique for the uncertainty of future disaster's damage could support a cost-effective information for a resonable decision making on disaster mitigation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.239-248
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• 2022

Risks in construction projects are increasing remarkably due to recent changes in the construction environment. Active risk management is required to recognize risks as opportunities. The purpose of this study is to propose a risk management model of the importance determination method through comparative analysis using Kano model, Timko CSC (Customer Satisfaction Coefficient), and ASC (Average Satisfaction Coefficient). Based on previous studies, the validity of risk management factor determination is reviewed through a questionnaire modified Kano model through interviews with working-level workers using the Delphi technique. Through this, a suitable risk management model is presented by selecting key risk management factors recognized by domestic construction project practitioners. As a result of the study, the Kano model developed to verify risk management of construction projects was evaluated to be effective in verifying the risk management of practitioners. It is expected that the Kano model presented in this study will be actively used to verify the importance of risk management for construction projects.

• Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.16-25
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• 2015

Since construction projects are large and complex, it is especially important to provide concurrent construction process to BIM models with construction automation. In particular, the schematic Quantity Take-Off (QTO) estimation on the BIM models is a strategy, which can be used to assist decision making in just minutes, because 70-80% of construction costs are determined by designers' decisions in the early design stage. This paper suggests a QTO process and a QTO prototype system within the building frame of Open BIM to improve the low reliability of estimation in the early design stage. The research consists of the following four steps: (1) analyzing Level of Detail (LOD) at the early design stage to apply to the QTO process and system, (2) BIM modeling for Open BIM based QTO, (3) checking the quality of the BIM model based on the checklist for applying to QTO and improving constructability, and (4) developing and verifying a QTO prototype system. The proposed QTO system is useful for improving the reliability of schematic estimation through decreasing risk factors and shortening time required.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.6
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• pp.424-430
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• 2021

Fire localization is a key mission that must be preceded for an autonomous fire suppression system. Although studies using a variety of sensors for the localization are actively being conducted, the fire localization is still unfinished due to the high cost and low performance. This paper presents the modeling and simulation of the fire localization estimation using Bayesian estimation to determine the probabilistic location of the fire. To minimize the risk of fire accidents as well as the time and cost of preparing and executing live fire tests, a 40m × 40m-virtual space is created, where two ultraviolet sensors are simulated to rotate horizontally to collect ultraviolet signals. In addition, Bayesian estimation is executed to compute the probability of the fire location by considering both sensor errors and uncertainty under fire environments. For the validation of the proposed method, sixteen fires were simulated in different locations and evaluated by calculating the difference in distance between simulated and estimated fire locations. As a result, the proposed method demonstrates reliable outputs, showing that the error distribution tendency widens as the radial distance between the sensor and the fire increases.