• International conference on construction engineering and project management
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• 2015.10a
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• pp.4-5
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• 2015

Owning to rapid infrastructure development, Asia is experiencing dramatic economic growth. There are not a few cases in which, however, economic growth is achieved by increasing the external diseconomy. Pursuit of sustainable development is one of the most important issues for mankind. Under the post-industrial capitalism society, however, there seems a big risk of increase in the external diseconomy worldwide. The objectives of this manuscript are to discuss importance of risk management of construction practice in present and future. Regarding the latter, a particular attempt is made to discuss how project risk communication should be done to reduce the external diseconomy. Presently, one of the important issues in implementation of infrastructure projects is practice of risk management to properly manage time, cost, quality, and safety: mainly maximization of internal economy. Multi-party risk and uncertainty management process (MRUMP) is one of tolls to assist it. The idea on MRUMP can be used to reduce the external diseconomy through identifying, sharing, and tuning people's rhythms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.167-177
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• 2000

The problem of system reliability is very important issue in the nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and quality loss. This paper therefore proposes a normalized scoring model by the qualitative factors order to evaluate the robust reliability of nuclear power plants under uncertainty. Especially, the qualitative factors including risk, functional, human error, and quality function factors for the robust justification has been also introduced. Finally, the analytical reliability and safety assessment model developed in this paper can be used in the real nuclear power plant.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.5 s.142
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• pp.637-648
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• 2005

The purpose of this study was to investigate the differences among internet and TV home-shopping perceived risk segments in regard to clothing shopping orientations and purchase intention. The subjects used for the study were 290 female consumers aged from 20 to 40 living in Seoul. The study used factor analysis, cluster analysis, ANOVA, Duncan test, and $\chi^2-test$. The results showed that the Internet and TV home-shopping perceived risks consisted of 9 factors: Products uncertainty risk, Internet shopping mall trust risk, account-related risk, delivery risk, social risk, size risk, exchange/return risk, TV watching-related risk, and price risk. The cluster analysis showed that there were five groups segmented: Size risk/TV watching risk group, Social risk/Internet trust risk group, Return risk/TV watching low-risk group, Delivery risk/product trust group, and Product risk group. The clothing shopping orientations were classified by 5 factors: Planned shopping, pleasure shopping, sales/fashion oriented shopping, time saving shopping, and credit card preference/in-store oriented shopping. The results showed that the five segmented perceived risk groups differed in regard to clothing shopping orientations, purchase intention, and demographics. Further group differences and implications of the results were discussed.

• Journal of the Korean Society of Safety
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• v.37 no.1
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• pp.78-87
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• 2022

In the risk assessment of urban railway systems, a hazard log is created by identifying hazards from accident and failure data. Then, based on a risk matrix, evaluators analyze the frequency and severity of the occurrence of the hazards, conduct the risk assessment, and then establish safety measures for the risk factors prior to risk control. However, because subjective judgments based on the evaluators' experiences affect the risk assessment results, a more objective and automated risk assessment system must be established. In this study, we propose a risk assessment model in which an adaptive neuro-fuzzy inference system (ANFIS), which is combined in artificial neural networks (ANN) and fuzzy inference system (FIS), is applied to the risk assessment of urban railway systems. The newly proposed model is more objective and automated, alleviating the limitations of risk assessments that use a risk matrix. In addition, the reliability of the model was verified by comparing the risk assessment results and risk control priorities between the newly proposed ANFIS-based risk assessment model and the risk assessment using a risk matrix. Results of the comparison indicate that a high level of accuracy was demonstrated in the risk assessment results of the proposed model, and uncertainty and subjectivity were mitigated in the risk control priority.

• Journal of the Korean Society of Safety
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• v.16 no.3
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• pp.125-134
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• 2001

The Advanced Pressurized rater Reactor 1400(APR1400) system is advanced of the successful Korean Nuclear Power Plants(KSNP) design which meets functional needs for safety enhancement reliability improvement, and control in the human-computer monitoring system. Therefore this paper describes the scoring model in order to justify the reliability and safety in APR 1400 under uncertainty. The structure of this paper consists of the human engineering, risk safety, quality function, safety organization management factors of the qualitative factors in chapter 2, and the expectation results of the normalized scoring model in chapter 3. Finally, the proposed reliability model have provided the technical flexibility not only for functional control fields but also for accidents protection systems in APR 1400 under uncertainty.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.3-6
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• 2006

Methods for risk engineering is a bundle of engineering tools including fundamental concepts and approaches of soft computing with application to real issues of risk management. In this talk fundamental concepts and soft computing approaches of risk engineering will be introduced. As the term of risk implies both advantageous and hazardous uncertainty in its origins, a fundamental theory to describe uncertainties is introduced that includes traditional probability and statistical models, fuzzy systems, as well as less popular modal logic. In particular, modal logic capabilities to express various kinds of uncertainties are emphasized and relations with rough sets and evidence theory are described. Another topic is data mining related to problems in risk management. Some risk mining techniques including fuzzy clustering are introduced and a recently developed algorithm is overviewed. A numerical example is shown.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1176-1182
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• 2009

Due to recession in real estate market, interest of risk analysis is increasing. Feasibility study in the first stage takes a great role in a project. There are not objectified tools which are able to cope with uncertainty of project, and feasibility study based on selected method of determinism does not include liquidity of weight risk. Also, shortage of consideration for subjective and atypical external factors causes inappropriate results. Therefore, this study proposes feasibility study model focused on risk factor influences in construction cost and sales cost. Considering effective level of cost based on objective risk factors and probable weight of risk by this model, real workers are able to bring correct and scientific decisions better than former method based on selective analysis of real estate development.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.440-449
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• 1994

Current risk assessment practices largely reflect the need for a consistent set of relatively rapid, first-cut procedures to assess 'plausible upper limits' of various risks. These practices have important roles to play in 1) screening candidate hazards for initial attention and 2) directing attention to cases where moderate-cost measures to control exposures are likely to be warranted, in the absence of further extensive (and expensive) data gathering and analysis. A problem with the current practices, however, is that they have led assessors to do a generally poor job of analyzing and expressing uncertainties, fostering 'One-Number Disease' (in which everything from one's social policy position on risk acceptance to one's technical judgment on the likelihood of different cancer dose-response relationships is rolled into a single quantity). At least for analyses that involve relatively important decisions for society (both relatively large potential health risks and relatively large potential economic costs or other disruptions), we can and should at least go one further step - and that is to assess and convey both a central tendency estimate of exposure and risk as well as our more conventional 'conservative' upper-confidence-limit values. To accomplish this, more sophisticated efforts are needed to appropriately represent the likely effects of various sources of uncertainty along the casual chain from the release of toxicants to the production of adverse effects. When the effects of individual sources of uncertainty are assessed (and any important interactions included), Monte Carlo simulation procedures can be used to produce an overall analysis of uncertainties and to highlight areas where uncertainties might be appreciably reduced by further study. Beyond the information yielded by such analyses for decision-making in a few important cases, the value of doing several exemplary risk assessments in. this way is that a set of benchmarks can be defined that will help calibrate the assumptions used in the larger number of risk assessments that must be done by 'default' procedures.

• Journal of the Korean Home Economics Association
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• v.23 no.1
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• pp.49-57
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• 1985

The central problem of purchasing houses is choice, which is accompanied by perception of risk. Perceived risk is defined as a risk perceived by a consumer subjectively in choice situations. The components of perceived risk are uncertainty and consequence. There are seven types of perceived risk in purchasing houses. Those are financial risk, functional risk, social risk, psychological risk, physical risk, time risk and future opportunity lost risk. The empirical survey about comsumer's purchasing Public Apartment suggests : 1) In general, rspondents perceive relatively high risk in purchasig Public Apartment. 2) Of seven risk types, financial, functionalm, future opportunity lost, time, and social risk correlate highest with overall perceived risk and explain the variance of it. 3) Physical and psychological risks don't correlate significantly with overall perceived risk. From the findings in empirical analysis, consumers are recommended to device riskreduction activities in purchasing Public Apartment. 1. Active information search is needed in purchasing Public Apartment in order to reduce overall perceived risk. 2. Housing concept should change from ownership to rental thinking. 3. Consumers should be accustomed to Housing Loans by bank. 4. Purchasing goals should be established clearly before purchasing houses. 5. Careful deliberation is required and informations from personal sources are useful.

• Korean Journal of Food Science and Technology
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• v.38 no.4
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• pp.589-593
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• 2006

The objective of this study was to evaluate the use of fuzzy math strategy to calculate variability and uncertainty in quantitative risk assessment. We compared the propagation of uncertainty using fuzzy math simulation with Monte Carlo simulation. The risk far Listeria monocytogenes contamination was estimated for carcass and processed pork by fuzzy math and Monte Carlo simulations, respectively. The data used in these simulations were taken from a recent report on pork production. In carcass, the mean values for the risk from fuzzy math and Monte Carlo simulations were -4.393 log $CFU/cm^2$ and -4.589 log $CFU/cm^2$, respectively; in processed pork, they were -4.185 log $CFU/cm^2$ and -4.466 log $CFU/cm^2$ respectively. The distribution of values obtained using the fuzzy math simulation included all of the results obtained using the Monte Carlo simulation. Consequently, fuzzy math simulation was found to be a good alternative to Monte Carlo simulation in quantitative risk assessment of pork production.