• Geomechanics and Engineering
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• v.21 no.2
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• pp.143-152
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• 2020

Korean society experienced successive earthquakes exceeding 5.0 magnitude in the past three years resulting in an increasing concern about earthquake stability of urban infrastructures. This study focuses on the significant aspects of earthquake risk assessment for the cut-and-cover underground railway station based on two-dimensional dynamic numerical analysis. Presented are features from a case study performed for the railway station in Seoul, South Korea. The PLAXIS2D was employed for numerical simulation and input of the earthquake ground motion was chosen from Pohang earthquake records (M5.4). The paper shows key aspects of earthquake risk for soil-structure system varying important parameters including embedded depth, supported ground information, and applied seismicity level, and then draws several meaningful conclusions from the analysis results such as seismic risk assessment.

• The Journal of Korean Academic Society of Nursing Education
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• v.21 no.1
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• pp.86-94
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• 2015

Purpose: The purpose of this study was to compare practice stress and practice satisfaction between clinical practice and simulation-based practice groups. Methods: A total of 159 nursing students (85 in the simulation group and 74 in the NICU group) participated in the study. Research tools measuring practice stress and practice satisfaction were used. Data was analyzed utilizing a t-test, Mann Whitney U-test, and descriptive statistics. Results: The simulation group showed a lower level of practice stress(practice instruction, practice evaluation, interpersonal relationship) a higher level of practice satisfaction compared with the NICU group. Conclusion: Simulation-based practice is an effective learning method for high-risk newborn nursing and can be used as an alternative to clinical practice.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.401-409
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• 2006

We consider a generalized partly-parametric additive risk model which generalizes the partly parametric additive risk model suggested by McKeague and Sasieni (1994). As an estimation method of this model, we propose to use the weighted least square estimation, suggested by Huffer and McKeague (1991), for Aalen's additive risk model by a piecewise constant risk. We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least squares method.

• 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.

• Korean Journal of Veterinary Research
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• v.47 no.2
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• pp.259-263
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• 2007

The choice of input distribution in quantitative risk assessments modeling is of great importance to get unbiased overall estimates, although it is difficult to characterize them in situations where data available are too sparse or small. The present study is particularly concerned with accommodation of uncertainties commonly encountered in the practice of modeling. The authors applied parametric and non-parametric bootstrap simulation methods which consist of re-sampling with replacement, in together with the classical Student-t statistics based on the normal distribution. The implications of these methods were demonstrated through an empirical analysis of trade volume from the amount of chicken and pork meat imported to Korea during the period of 1998-2005. The results of bootstrap method were comparable to the classical techniques, indicating that bootstrap can be an alternative approach in a specific context of trade volume. We also illustrated on what extent the bias corrected and accelerated non-parametric bootstrap method produces different estimate of interest, as compared by non-parametric bootstrap method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.83-89
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• 2015

Selection of efficient supplier is a very important process as risk or uncertainty of a supply chain and its environment are increasing. Previous deterministic DEA and probabilistic DEAs are very limited to handle various types of risk and uncertainty. In this paper, I propose an improved probabilistic DEA which consists of two steps; Monte Carlo simulation and statistical decision making. The simulation results show that the proposed method is proper to distinguish supplier's performance and provide statistical decision background.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.1-13
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• 2021

Fuel costs represent one of the most substantial expenses for airlines, accounting for 20% - 36% of the airline's total operating cost. The present study discusses the so-called discretionary fuel that is additionally loaded at the discretion of airlines to cover unforeseen variations from the planned flight operations. The proper range of the discretionary fuel to be loaded for economic flight operations was estimated by applying Monte Carlo simulation technique. With this simulation model for loading discretionary fuel, airlines cannot only reduce the total amount of fuel to be consumed but also minimize the risk of unplanned flight disruptions caused by insufficient fuel on board. Airlines should be able to guarantee proper risk management processes for fuel boarding by carrying enough fuel to high-risk airports. This study would provide a practical guideline for loading proper amounts of discretionary fuel. Future researchers should be encouraged to improve this study by elaborating the weather variable.

• Architectural research
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• v.22 no.4
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• pp.105-112
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• 2020

The purpose of this study is to establish a method for assessing a building's risk against disaster, tentatively named the Korean integrated disaster evaluation simulator (K-IDES). Based on previous studies, FEMA's risk management series and FEMA IRVS are selected as case studies for developing a frame work of K-IDES, through the comparative analysis of domestic building design guides, codes, and special acts related to disasters, in order to develop a risk assessment methodology for quantitative results. The assessment method consists of a classification system and calculating risk, and a simulation applying the developed checklist in K-IDES to similar types of high-rise buildings will be conducted to validate its accuracy. The final goal is to systemize an integrated risk management in a high-rise building against disasters for the purpose of recognizing vulnerable areas from the beginning of the design process and reinforcing it from potential threats after construction.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.485-490
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• 2003

Nowadays the rapid change in construction environment getting more globalized and complicated has caused lots of unexpected risks from inside and out of the country, so more sophisticated construction management strategies are being strongly needed. This paper suggests a risk management model with which we can estimate the appropriate contingency by quantifying the amount of probable risks immanent in large construction projects, which have a high degree of uncertainty in the anticipation of the total construction cost. To develop the model, the risk factors that make cost variations are elicited based on the real data of the contingencies assigned to the past projects. Furthermore, the influential relationship of risk factors is structured by applying the CRM(Cost Risk Model) which is the synthetic model of Monte Carlo Simulation, Influence Diagram and Decision Tree. The ultimate outcome of this research can by validated by tile case study with a large construction project performed.

• Journal of the Korea Institute of Building Construction
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• v.17 no.3
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• pp.287-294
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• 2017

Recently the construction project is becoming large-sized, complicated, and modernize. This has increased the uncertainty of construction risk. Therefore, studies should be followed regarding scientifically identifying the risk factors, quantifying the frequency and severity of risk factors in order to develop a model that can quantitatively evaluate and manage the risk for response the increased risk in construction. To address the problem, this study analyze the probability distribution of risk causes, the probability of occurrence and frequency of the specific risk level through Monte Carlo simulation method based on the accident data caused at construction sites. In the end, this study derives quantitative analysis by analyzing the amount of risk and probability distributions of accident causes. The results of this study will be a basis for future quantitative risk management models and risk management research.