• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.465-474
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• 2013

Purpose: To provide a variety of stable military supplies, risk should be avoided or removed. This paper aims to provide an objective method of risk assesment for risk matrix to evaluate risk level. Methods: According to previous results of risk assesment through risk matrix, some parameters and probability density functions, which include characteristics of military supplies, are selected and Risk matrix is modelled based on that. Results: Results show that a proposed method can evaluate objectively risk level through the stochastic modelling and provide well-balanced risk assessments by categorizing into 3 levels such as high, middle and low level risk. Conclusion: A current risk assessment method includes substantial subjectivity of risk assessment and as a problem about military supplies comes up, we can not show any appropriate evidences for decision of risk assessment. We propose an objective scheme employing stochastic modelling with parameters and probability density functions.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.140-149
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• 2007

Indian construction companies have only 0.05% market share in the 3-4 trillion dollar global construction business and only two Indian construction companies figure in the ENR "Top 225 Global Contractors 2006" list. Hence, while enormous scope for growth exists, international construction experience is limited. This study explores the risks as perceived by Indian companies venturing abroad since risks in international construction differ from home market risks. Literature survey identified a number of risk factors that were evaluated by the experts, highlighting fourteen important risk factors. Interpretive Structural Modelling (ISM) was used to develop a hierarchical model showing the relationships between the different risk factors, thus helping to focus on the key risks for effective risk management. The study shows that poor project management is a key risk forming the hub of the system, while political instability has maximum influence. The results of the study can be used by managers to visualise the risks in perspective and prioritise the mitigation effort.

• Nuclear Engineering and Technology
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• v.44 no.5
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• pp.471-482
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• 2012

To assess the risk of nuclear power plant operation and to determine the risk impact of digital systems, there is a need to quantitatively assess the reliability of the digital systems in a justifiable manner. The Probabilistic Risk Analysis (PRA) is a tool which can reveal shortcomings of the NPP design in general and PRA analysts have not had sufficient guiding principles in modelling particular digital components malfunctions. Currently digital I&C systems are mostly analyzed simply and conventionally in PRA, based on failure mode and effects analysis and fault tree modelling. More dynamic approaches are still in the trial stage and can be difficult to apply in full scale PRA-models. As basic events CPU failures, application software failures and common cause failures (CCF) between identical components are modelled.The primary goal is to model dependencies. However, it is not clear which failure modes or system parts CCF:s should be postulated for. A clear distinction can be made between the treatment of protection and control systems. There is a general consensus that protection systems shall be included in PRA, while control systems can be treated in a limited manner. OECD/NEA CSNI Working Group on Risk Assessment (WGRisk) has set up a task group, called DIGREL, to develop taxonomy of failure modes of digital components for the purposes of PRA. The taxonomy is aimed to be the basis of future modelling and quantification efforts. It will also help to define a structure for data collection and to review PRA studies.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.185-202
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• 2000

Uncertainty and variability in Life Cycle Assessment(LCA) have been significant key issues in LCA methodology with techniques in other research area such as social and political science. Variability is understood as stemming from inherent variations in the real world, while uncertainty comes from inaccurate measurements, lack of data, model assumptions, etc. Related articles in this issues were reviewed for classification, distinguish and elaboration of probabilistic/stochastic health risk analysis application in LCA. Concept of focal zone, streamlining technique, scenario modelling and Monte Carlo/Latin Hypercube risk analysis were applied to the uncertainty/variability analysis of health risk in LCA. These results show that this general framework of multi-disciplinary methodology between probabilistic health risk assessment and LCA was of benefit to decision making process by suppling information about input/output data sensitivity, health effect priority and health risk distribution. There should be further research needs for case study using this methodology.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.11-16
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• 2007

Since the seminal work of Engle (1982), many researchers and practitioners have developed ARCH-type models to deal with volatility modelling, which, for instance, is crucial to perform the task of derivative pricing, measuring risk, and risk hedging. In this paper, we base the GARCH(1,1) model to analyze the KOSPI200 data, and perform the CUSUM test for detecting parameter changes in the GARCH model. It is shown that the data suffers from a parameter change.

• Proceedings of the KSEEG Conference
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• 2000.04a
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• pp.59-60
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• 2000

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.167-167
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• 2020

Annual sediment deposition in reservoirs behind weirs poses flood risk, while its accurate prediction remains a challenge. Sediment management by hydraulic flushing is an effective method to maintain reservoir storage. In this study, an integrated approach to predict sediment inflow and sediment flushing simulation in reservoirs is presented. The annual sediment inflow prediction was carried out with Artificial Neural Networks (ANN) modelling. RESCON model was applied for quantification of sediment flushing feasibility criteria. The integrated approach was applied on Sangju Weir and also on estuary of Nakdong River (NREB). The mean annual sediment inflow predicted at Sangju Weir and NREB was 400,000 ㎥ and 170,000 ㎥, respectively. The sediment characteristics gathered were used to setup RESCON model and sediment balance ratio (SBR) and long term capacity ratio (LTCR) were used as flushing efficiency indicators. For Sangju Weir, the flushing discharge, Q_f = 140 ㎥/s with a drawdown of 5 m, and flushing duration, T_f = 10 days was necessary for efficient flushing. At NREB site, the parameters for efficient flushing were Q_f = 80 ㎥/s, T_f = 5 days, N = 1, El_f = 2.24 m. The hydraulic flushing was concluded feasible for sediment management at both Sangju Weir and NREB.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.233-234
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• 2022

In order to minimize casualties in case of a fire in a building, it is necessary to anticipate the time required for evacuation of occupants and the delay in evacuation in advance, and prepare countermeasures for possible occurrences. In fact, various factors that cannot be predicted exist and cannot be considered by excluding them, so the risk is predicted and evaluated through quantitative evacuation modeling. In order to understand this, we analyzed domestic and international evacuation modeling research trends. For about 40 years, starting with the characteristics of human movement, an evacuation modeling technique based on scientific methods has been developed through actual fire accident cases and various real-world experiments with humans. Then, in order to analyze the natural reaction of humans, which has a decisive influence in the recognition and decision-making phase, evacuation modelling studies have been conducted in depth using psychological and physical experimental methods.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2000.12a
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• pp.20-27
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• 2000

• 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.