• Journal of Chest Surgery
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• v.57 no.3
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• pp.302-311
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• 2024

Background: Unexpected conversion to thoracotomy during planned video-assisted thoracoscopic surgery (VATS) can lead to poor outcomes and comparatively high morbidity. This study was conducted to assess preoperative risk factors associated with unexpected thoracotomy conversion and to develop a risk scoring model for preoperative use, aimed at identifying patients with an elevated risk of conversion. Methods: A retrospective analysis was conducted of 1,506 patients who underwent surgical resection for non-small cell lung cancer. To evaluate the risk factors, univariate analysis and logistic regression were performed. A risk scoring model was established to predict unexpected thoracotomy conversion during VATS of the lung, based on preoperative factors. To validate the model, an additional cohort of 878 patients was analyzed. Results: Among the potentially significant clinical variables, male sex, previous ipsilateral lung surgery, preoperative detection of calcified lymph nodes, and clinical T stage were identified as independent risk factors for unplanned conversion to thoracotomy. A 6-point risk scoring model was developed to predict conversion based on the assessed risk, with patients categorized into 4 groups. The results indicated an area under the receiver operating characteristic curve of 0.747, with a sensitivity of 80.5%, specificity of 56.4%, positive predictive value of 1.8%, and negative predictive value of 91.0%. When applied to the validation cohort, the model exhibited good predictive accuracy. Conclusion: We successfully developed and validated a risk scoring model for preoperative use that can predict the likelihood of unplanned conversion to thoracotomy during VATS of the lung.

• Journal of Industrial Technology
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• v.29 no.A
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• pp.101-110
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• 2009

Due to frequent occurrence of a localized torrential downpour caused by global warming and change of outflow tendency caused by rapid urbanization and industrialization, risk analysis must be carried out in levee design with uncertainty. In this study, reliability analysis was introduced to quantitatively evaluate the overtopping risk of levee by the uncertainty. First of all, breaking function was established as a function of flood stage and height of levee. All variables of breaking function were considered as random variables following any distribution functions, and the risk was defined as the possibility that the flood stage is formed higher than height of levee. The risk evaluation model was developed with AFDA (Approximate Full Distribution Approach). The flood stage computed by 2-D numerical model FESWMS-2DH was used as input data for the model of levee risk evaluation. Risk for levee submergence were quantitatively presented for levee of Wol-Song-Cheon.

• Communications of the Korean Mathematical Society
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• v.23 no.1
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• pp.141-151
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• 2008

In this paper, we derive the nonlinear equation for European option pricing containing liquidity risk which can be defined as the inverse of the partial derivative of the underlying asset price with respect to the amount of assets traded in the efficient market. Numerical solutions are obtained by using finite element method and compared with option prices of KOSPI200 Stock Index. These prices computed with liquidity risk are considered more realistic than the prices of Black-Scholes model without liquidity risk.

• Nuclear Engineering and Technology
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• v.35 no.1
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• pp.64-79
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• 2003

In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.173-186
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• 2014

This study outlines possible risk factors in the SCM of a company and correlates risk assessment, the strategy of risk management, and the supply chain performance. The data is surveyed from an international Korean company and is analyzed by the structure equation model of actual proof. The research model verifies the correlation between the risk assessment, the strategy of risk management, and the supply chain performance as dependent variables after the risk factors of the SCM are defined as independent variables. The research shows that there are consecutive links among the risk factors of the SCM, the risk assessment, and the strategy of risk management. The strategy of risk management was conclusively determined to have an effect on supply chain performance. Therefore, improving the supply chain performance of a company requires the constructive process for risk management based on a correlation between risk assessment and the strategy of risk management.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.936-943
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• 2009

In this study, a risk assessment model based on the ETA (Event Tree Analysis) and FTA (Fault Tree Analysis) is developed according to the procedure of hazard analysis and risk assessment in order to estimate the risk quantitatively. The FTA technique is applied to estimate the branch probability (frequency) and the ETA technique is applied to estimate the consequence for each branch path on the ET (Event Tree). A risk assessment model is developed by the combination of those ETA and FTA. In addition, the reliability and the validity of the risk assessment model are verified by comparing the risk estimated through the developed model with the actual equivalent fatality.

• Fashion & Textile Research Journal
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• v.13 no.3
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• pp.390-397
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• 2011

This study investigates the influences of shopping enjoyment and risk reduction on customers' attitude and the behavioral intention in the Internet shopping mall using a moving virtual model. For this study, we produced a moving virtual model to present a fashion product. The virtual model walks for about one minute on the stage. After respondents viewed it, they completed a questionnaire. The questionnaire consists of online shopping enjoyment, risk reduction, customers' attitude and behavioral intention. Respondents are limited to females aged in their 20s and 30s, who have experienced Internet shopping and are highly interested in fashion products. 411 samples were used for the final analysis. Cronbach's alpha, factor analysis, and multiple regression analysis were conducted. The results are as follows. Online shopping enjoyment and risk reduction influenced the behavioral intention directly as well as through the attitude. However, the size of the influence indicated that online shopping enjoyment is larger than risk reduction. Therefore, Internet malls should utilize the moving virtual model to provide customers with enjoyment and risk reduction, which will increase customers' favorable attitudes and the behavioral intention such as purchase intention and word of mouth.

• KIEAE Journal
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• v.17 no.5
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• pp.33-41
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• 2017

Purpose: Indoor air quality in residential buildings needs to be evaluated over the long term. In previous research, there has been an attempt to perform the health risk assessment of pollutants by using numerical models as a method of long-term evaluation. However, the numerical model of this precedent study has limitations that do not reflect the actual concentration distribution. Therefore, this study introduces the CRPS index, constructs a numerical model that can reflect the concentration distribution, and then presents a more accurate health risk assessment method using it. At this time, the pollutants are toluene, which is a typical material released from building materials. Method: CRPS index was applied to existing numerical model to reflect concentration distribution. This was used to calculate concentrations at adult breathing area and to use them for exposure assessment in a health risk assessment. After that, we entered adult data and conducted a health risk assessment of toluene. Results: The non-carcinogenic risk of toluene was calculated to be 0.0060. This is 5% smaller than the existing numerical model, meaning that it is more accurate to predict the pollutant risks. This value is also lower than the US EPA reference value of 1. Therefore, under the conditions of this study, long-term exposure of adults to toluene has no impact on health.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.99-100
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• 2022

As the danger of exposure to the asbestos has been revealed, the importance of demolition asbestos in existing buildings has been raised. Extensive body of study has been conducted to evaluate the risk of demolition asbestos, but there were confined types of variables caused by not reflecting categorical information and limitations in collecting quantitative information. Thus, this study aims to derive a model that predicts the risk in workplace of demolition asbestos by collecting categorical and continuous variables. For this purpose, categorical and continuous variables were collected from asbestos demolition reports, and the risk assessment score was set as the dependent variable. In this study, the influence of each variable was identified using logistic regression, and the risk prediction model methodologies were compared through decision tree regression and artificial neural network. As a result, a conditional risk prediction model was derived to evaluate the risk of demolition asbestos, and this model is expected to be used to ensure the safety of asbestos demolition workers.

• Archives of design research
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• v.16 no.4
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• pp.69-78
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• 2003

Risk Management is one of the most important factors in web design project management. The purpose of risk management is to identify reasons of risk to avoid risky situation and successfully achieve final goal of the project. This paper first describes concept of the web design project management and its processes. Secondly this study presents planning principles for systematic risk management process. Also it suggests a model of risk management. Finally this paper demonstrates utility of the risk management model through case studies based on the suggested risk management model.