• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.483-491
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• 2010

This study provides the explicit computation of the ruin probability of a Le￠vy process on finite time horizon in Theorem 1 with the help of a fluctuation identity. This paper also gives the numerical results of the ruin probability in Variance Gamma(VG) and Normal Inverse Gaussian(NIG) models as illustrations. Besides, the paths of VG and NIG processes are simulated using the same parameter values as in Madan et al. (1998).

• Bulletin of the Korean Mathematical Society
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• v.40 no.4
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• pp.663-669
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• 2003

This paper investigates the tail asymptotic behavior of the severity of ruin (the deficit at ruin) in the renewal model. Under the assumption that the tail probability of the claimsize is dominatedly varying, a uniform asymptotic formula for the tail probability of the deficit at ruin is obtained.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.3
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• pp.135-145
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• 2020

Recently, the disaster rate of the construction industry has increased with high-rise, and complexity of the building, unlike the decrease in the disaster rate in other industries. Although risk assessment is performed to reduce the occurrence of disasters, it is difficult to estimate the risks accurately due to activity in which no disaster has occurred, and inconsistencies in the level of details of work. In this study, in order to evaluate the risk of the major activity for the apartment construction work, the activity was identified by referring to the risk assessment model of construction industry type by the KOSHA. The construction work types and activities were consistently organized in level of work into nine work types and 82 activities were through experts consultation. Analyzing the disaster types that occurred during work through KOSHA disaster cases, calculating the probability of disaster occurrence according to the type of disaster, and combining the probability of disaster with the severity of disaster to estimate the risk assessment method was presented. Using the daily report of the construction site of the apartment, the results of a case study confirmed the validity of the risk calculation method presented in this study.

• Food Science of Animal Resources
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• v.38 no.5
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• pp.1043-1054
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• 2018

Salmonellosis caused by chicken consumption has been a critical issue in food safety worldwide, including in Korea. The probability of illness from consumption of chicken was simulated in study, based on the recipe of Dakgalbi, a commonly eaten chicken dish in Korea. Additionally, the processing stage at slaughterhouses to decrease Salmonella concentration in broilers was modeled to explore its effect on the likelihood of illness. A Monte Carlo simulation model was created using @RISK. Prevalence of Salmonella in chickens at the retail stage was found to be predominantly important in determining the probability of illness. Other than the prevalence, cooking temperature was found to have the largest impact on the probability of illness. The results also demonstrated that, although chlorination is a powerful tool for decreasing the Salmonella concentration in chicken, this effect did not last long and was negated by the following stages. This study analyzes the effects of variables of the retail-to-table pathway on the likelihood of salmonellosis in broiler consumption, and also evaluates the processing step used to decrease the contamination level of Salmonella in broilers at slaughterhouses. According to the results, we suggest that methods to decrease the contamination level of Salmonella such as chlorination had little effect on decreasing the probability of illness. Overall, these results suggest that preventing contamination of broiler with Salmonella must be a top priority and that methods to reduce the concentration of Salmonella in broilers at slaughterhouses hardly contribute to safe consumption of Salmonella-contaminated chicken.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.3
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.142-151
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• 2017

Spontaneous intracerebral hemorrhage (sICH) has a high mortality rate. Research has demonstrated that sICH occurrence is related to weather conditions; therefore, this study used the decision tree method to explore the impact of climatic risk factors on sICH at different ages. The Taiwan National Health Insurance Research Database (NHIRD) and other open-access data were used in this study. The inclusion criterion was a first-attack sICH. The decision tree algorithm and random forest were implemented in R programming language. We defined a high risk of sICH as more than the average number of cases daily, and the younger, middle-aged and older groups were calculated as having 0.77, 2.26 and 2.60 cases per day, respectively. In total, 22,684 sICH cases were included in this study; 3,102 patients were younger (<44 years, younger group), 9,089 were middle-aged (45-64 years, middle group), and 10,457 were older (>65 years, older group). The risk of sICH in the younger group was not correlated with temperature, wind speed or humidity. The middle group had two decision nodes: a higher risk if the maximum temperature was >$19^{\circ}C$ (probability = 63.7%), and if the maximum temperature was <$19^{\circ}C$ in addition to a wind speed <2.788 (m/s) (probability = 60.9%). The older group had a higher risk if the average temperature was >$23.933^{\circ}C$ (probability = 60.7%). This study demonstrated that the sICH incidence in the younger patients was not significantly correlated with weather factors; that in the middle-aged sICH patients was highly-correlated with the apparent temperature; and that in the older sICH patients was highly-correlated with the mean ambient temperature. "Warm" cold ambient temperatures resulted in a higher risk of sICH, especially in the older patients.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.2
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• pp.70-78
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• 2013

Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.19-28
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• 2006

To develop a crisis management for aviation safety, this study has defined crisis management includes risk management which is eliminates or lowers risks prior to accidents and emergency response after the accidents. This study takes a look at different kinds of crisis managements, risk managements and statistical methods of other nations and fields in order to develop a risk management model. Through surveys which have 102 risk factors that include air traffic control, maintenance and airport sectors, the weight of each risk factor was calculated and the probability was divided to develop a model for risk management. The risk management model of this study is conducted using four steps (risk management plan, risk factor identification, weight and probability analysis, decision making) and 4 standards of weight along with 5 standards of probability This study takes a look at Predictions through a quantitative method using a risk index for the risk management model An effective risk management model should have a wide and continuous collection of data and adopt various methods using this model. The crisis management could not be very effective only using a pre-active risk management. So it should also be conducted by using a pro-active response system to protect additional damage and to prevent accidents of the same nature. From the results, the most important points were the establishment of command and control accountabilities, and cooperation of related organizations.

• Safety and Health at Work
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• v.8 no.2
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• pp.206-211
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• 2017

Background: Self-reported low back pain (LBP) has been evaluated in relation to material handling lifting tasks, but little research has focused on relating quantifiable stressors to LBP at the individual level. The National Institute for Occupational Safety and Health (NIOSH) Composite Lifting Index (CLI) has been used to quantify stressors for lifting tasks. A chemical exposure can be readily used as an exposure metric or stressor for chemical risk assessment (RA). Defining and quantifying lifting nonchemical stressors and related adverse responses is more difficult. Stressor-response models appropriate for CLI and LBP associations do not easily fit in common chemical RA modeling techniques (e.g., Benchmark Dose methods), so different approaches were tried. Methods: This work used prospective data from 138 manufacturing workers to consider the linkage of the occupational stressor of material lifting to LBP. The final model used a Bayesian random threshold approach to estimate the probability of an increase in LBP as a threshold step function. Results: Using maximal and mean CLI values, a significant increase in the probability of LBP for values above 1.5 was found. Conclusion: A risk of LBP associated with CLI values > 1.5 existed in this worker population. The relevance for other populations requires further study.

• Fisheries and Aquatic Sciences
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• v.25 no.9
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• pp.463-472
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• 2022

In this study, a microbial risk assessment was performed for the bacteria Vibrio parahaemolyticus, which causes a foodborne illness following the consumption of Jeotgal, a fermented seafood in South Korea. The assessment comprised of six stages: product, market, home, consumption, dose-response, and risk. The initial contamination level (IC) was calculated based on the prevalence of V. parahaemolyticus in 90 Jeotgal samples. The kinetic behavior of V. parahaemolyticus was described using predictive models. The data on transportation conditions from manufacturer to market and home were collected through personal communication and from previous studies. Data for the Jeotgal consumption status were obtained, and an appropriate probability distribution was established. The simulation models responding to the scenario were analyzed using the @RISK program. The IC of V. parahaemolyticus was estimated using beta distribution [Beta (1, 91)]. The cell counts during transportation were estimated using Weibull and polynomial models [δ = 1 / (0.0718 - 0.0097 × T + 0.0005 × T²)], while the probability distributions for time and temperature were estimated using Pert, Weibull, Uniform, and LogLogistic distributions. Daily average consumption amounts were assessed using the Pareto distribution [0.60284,1.32,Risk Truncate(0,155)]. The results indicated that the risk of V. parahaemolyticus infection through Jeotgal consumption is low in South Korea.