• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.247-253
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• 2021

The outbreak of the deadly virus COVID-19 is said to infect 17.3Cr people around the globe since 2019. This outbreak is continuously affecting a lot of new people till this day and, most of it is said to under control. However, vaccines introduced around the world can help mitigate the risk of the virus. Apart from medical professionals, prediction models are also said to combinedly help predict the risk of infection based on given datasets. This paper is based on publication of a machine learning approach using regression models to predict the output based on dataset which have indictors grouped based on active, tested, recovered and critical cases along with regions and cities covering most of it from Dubai. Hence, the active cases are tested based on the other indicators and other attributes. The coefficient of the determination (r²) is 0.96, which is considered promising. This model can be used as an frame work, among others, to predict the resources related to the dangerous outbreak.

• 아태비즈니스연구
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• 제11권4호
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• pp.37-48
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• 2020

Purpose - This study empirically investigates whether the risk property included in fat-tails of return distributions is systematic or unsystematic based on the devised statistical methods. Design/methodology/approach - This study devised empirical designs based on two traditional methods: principal component analysis (PCA) and the testing method of portfolio diversification effect. The fatness of the tails in return distributions is quantitatively measured by statistical probability. Findings - According to the results, the risk property in the fat-tails of return distributions has the economic meanings of eigenvalues having a value greater than 1 through PCA, and also systematic risk that cannot be removed through portfolio diversification. In other words, the fat-tails of return distributions have the properties of the common factors, which may explain the changes of stock returns. Meanwhile, the fatness of the tails in the portfolio return distributions shows the asymmetric relationship of common factors on the tails of return distributions. The negative tail in the portfolio return distribution has a much closer relation with the property of common factors, compared to the positive tail. Research implications or Originality - This empirical evidence may complement the existing studies related to tail risk which is utilized in pricing models as a common factor.

• 아태비즈니스연구
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• 제15권2호
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• pp.71-88
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• 2024

Purpose - This study provides an overview of existing research and practices related to market risk premiums(MRP), and empirically estimates the MRP in Korea, particularly using the related option prices. We also seek to improve the current MRP practices and explore alternative solutions. Design/methodology/approach - We present the option price-based MRP estimation method, as proposed by Martin (2017), and implement it within the context of the Korean stock market. We then juxtapose these results with those derived from other methods, and compare the characteristics with those of the United States. Findings - We found that the lower limit of the MRP in the Korean stock market shows a much lower value compared to the US. There seems to be the possibility of a market crash, exchange rate volatility, or a lack of option trading data. We investigated the predictive power of the estimated values and discovered that the weighted average of the results of various methodologies using the Principal Component Analysis (PCA) is superior to the individual method's results. Research implications or Originality - It is required to explore various methods of estimating MRP that are suitable for the Korean stock market. In order to improve the estimation methodology based on option prices, it is necessary to develop the methods using the higher-order(third order or above) moments, or consider additional risk factors such as the possibility of a crash.

• 한국산학기술학회논문지
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• 제14권8호
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• pp.3804-3814
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• 2013

본 연구는 여자 청소년의 생물학적 위험성향, 사회문화적 위험요인, 자기통제, 사회적지지 및 자살생각의 관계에 대한 구조모형의 부합도를 검증하고자 시도되었다. 자료수집은 2012년 12월 3일부터 2013년 3월 28일까지 D광역시의 여자 중고등학생 343명을 대상으로 하였다. 자료는 SPSS 및 AMOS 프로그램을 이용하여 분석하였다. 연구결과, 여자 청소년의 자살생각에 대해 생물학적 위험성향, 사회문화적 위험요인, 자기통제 및 사회적지지는 직접효과, 생물학적 위험성향과 사회문화적 위험요인은 간접효과가 있었다. 여자 청소년의 생물학적 위험성향과 사회문화적 위험요인은 자기통제와 사회적지지에 직접효과가 있었다. 이러한 결과에서 여자 청소년의 자살생각을 예방하기 위해 생물학적 위험성향과 사회적 위험요인을 감소시키고 자기통제와 사회적지지를 증진시키는 중재 프로그램 개발이 필요하다.

• 한국지하수토양환경학회지:지하수토양환경
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• 제17권5호
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• pp.1-9
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• 2012

The purpose of ecological risk assessment in soil ecosystem is to protect ecological receptors and to provide a scheme of efficient management for soil contaminants. Developed countries have already prepared the methodologies of ecological risk assessment by considering their soil properties, land use, and ecological receptors. In this study, we compared the soil ecological risk assessment processes in the similarity and differences in methodology. Four countries, except for USA, adjusted the toxicological data for ecological risk assessment, based on their representative soil properties because the soil properties affect toxic effects to ecological receptors. The soil ecological risk assessment methodology of Netherlands and UK was based on 'Technical guidance document on risk assessment (TGD)' of European Chemical Bureau (ECB). Australia, USA, and Canada developed their autonomous methodology. In the Netherlands, UK, Australia, and Canada, they employed the species sensitivity distribution (SSD) approach if sufficient toxicity data are available. The USA determined the ecological soil screening level by obtaining the geometric mean of toxicological data for three species. Furthermore, all countries consider secondary poisoning in their soil ecological risk assessment. The latest risk assessment methodology of soil ecosystem that this study investigated can be used to explore what Korea needs to develop the Korean ecological risk assessment methodology of soil ecosystem in the future.

• Safety and Health at Work
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• 제12권3호
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• pp.396-402
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• 2021

Background: Styrene is one of the aromatic compounds used in acetonitrile-butadiene-styrene (ABS) producing petrochemicals, which has an impact on health of workers. Therefore, this study aimed to investigate the health risks of styrene emitted from the petrochemical industry in Iran. Methods: Air samples were collected based on NIOSH 1501 method. The samples were analyzed by the Varian-cp3800 gas chromatograph. Finally, risk levels of styrene's health effects on employees were assessed by the quantitative method of the U.S. Environmental Protection Agency (U.S. EPA) and the semiquantitative way by the Singapore Occupational Safety and Health Association. Results: Based on the results, the employees had the highest average exposure to styrene vapors (4.06 × 10^-1mg.(kg - day)^-1) in the polybutadiene latex (PBL) unit. Therefore, the most top predictors of cancer and non-cancer risk were 2.3×10^-4 and 7.26 × 10^-1, respectively. Given that the lowest average exposure (1.5 × 10^-2mg.(kg - day)^-1) was in the dryer unit, the prediction showed a moderate risk of cancer (0.8 × 10^-6) and non-cancer (2.3 × 10^-3) for the employees. The EPA method also predicted that there would be a definite cancer risk in 16% and a probable risk in 76% of exposures. However, according to the semiquantitative approach, the rate of risk was at the "low" level for all staff. The results showed that there was a significant difference (p < 0.05) between the units in exposure and health risk of styrene (p < 0.05). Conclusion: Given the high risk of styrene's health effects, appropriate control measures are required to reduce the exposure level.

• Earthquakes and Structures
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• 제24권4호
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• pp.275-288
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• 2023

Based on the crucial role of high-speed railway bridges (HSRBs) in the safety of high-speed railway operations, it is an important approach to mitigate earthquake hazards by proceeding with seismic risk assessments in their whole life. Bridge seismic risk assessment, which usually evaluates the seismic performance of bridges from a probabilistic perspective, provides technical support for bridge risk management. The seismic performance of bridges is greatly affected by the degradation of material properties, therefore, material damage plays a nonnegligible role in the seismic risk assessment of the bridge. The effect of material damage is not considered in most current studies on seismic risk analysis of bridges, nevertheless. To fill the gap in this area, in this paper, a nonlinear dynamic time-history analysis has been carried out by establishing OpenSees finite element model, and a seismic vulnerability analysis is carried out based on the incremental dynamic analysis (IDA) method. On this basis, combined with the site risk analysis, the time-dependent seismic risk analysis of an offshore three-span HSRB in the whole life cycle has been conducted. The results showed that the seismic risk probabilities of both components and system of the bridge increase with the service time, and their seismic risk probabilities increase significantly in the last service period due to the degradation of the material strength, which demonstrates that the impact of durability damage should be considered when evaluating the seismic performance of bridges in the design and service period.

• Communications for Statistical Applications and Methods
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• 제13권3호
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• pp.685-699
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• 2006

Commercial banks and other related areas have developed internal models to better quantify their financial risks. Since an appropriate credit risk model plays a very important role in the risk management at financial institutions, it needs more accurate model which forecasts the credit losses, and statistical inference on that model is required. In this paper, we propose a new method for estimating a default rate. It is a Bayesian approach using the power prior which allows for incorporating of historical data to estimate the default rate. Inference on current data could be more reliable if there exist similar data based on previous studies. Ibrahim and Chen (2000) utilize these data to characterize the power prior. It allows for incorporating of historical data to estimate the parameters in the models. We demonstrate our methodologies with a real data set regarding SOHO data and also perform a simulation study.

• Journal of Communications and Networks
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• 제16권6호
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• pp.667-676
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• 2014

Connectivity is a crucial quality of service measure in wireless sensor networks. However, the network is always at risk of being split into several disconnected components owing to the sensor failures caused by various factors. To handle the connectivity problem, this paper introduces an in-advance mechanism to prevent network partitioning in the initial deployment phase. The approach is implemented in a distributed manner, and every node only needs to know local information of its 1-hop neighbors, which makes the approach scalable to large networks. The goal of the proposed mechanism is twofold. First, critical nodes are locally detected by the critical node detection (CND) algorithm based on the concept of maximal simplicial complex, and backups are arranged to tolerate their failures. Second, under a greedy rule, topological holes within the maximal simplicial complex as another potential risk to the network connectivity are patched step by step. Finally, we demonstrate the effectiveness of the proposed algorithm through simulation experiments.