• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.327-348
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• 2008

A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.493-513
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• 2014

With the development of related technologies, Location-Based Services (LBS) are growing fast and being used in many ways. Past LBS studies have focused on adoption of LBS because of the fact that LBS users have privacy concerns regarding revealing their location information. Meanwhile, the number of LBS users and revenues from LBS are growing rapidly because users can get some benefits by revealing their location information. Little research has been done on how LBS affects consumers' information search behavior in product purchase. The purpose of this paper is examining the effect of LBS information filtering on buyers' uncertainty and their information search behavior. When consumers purchase a product, they try to reduce uncertainty by searching information. Generally, there are two types of uncertainties - knowledge uncertainty and choice uncertainty. Knowledge uncertainty refers to the lack of information on what kinds of alternatives are available in the market and/or their important attributes. Therefore, consumers having knowledge uncertainty will have difficulties in identifying what alternatives exist in the market to fulfil their needs. Choice uncertainty refers to the lack of information about consumers' own preferences and which alternative will fit in their needs. Therefore, consumers with choice uncertainty have difficulties selecting best product among available alternatives.. According to economics of information theory, consumers narrow the scope of information search when knowledge uncertainty is high. It is because consumers' information search cost is high when their knowledge uncertainty is high. If people do not know available alternatives and their attributes, it takes time and cognitive efforts for them to acquire information about available alternatives. Therefore, they will reduce search breadth. For people with high knowledge uncertainty, the information about products and their attributes is new and of high value for them. Therefore, they will conduct searches more in-depth because they have incentive to acquire more information. When people have high choice uncertainty, people tend to search information about more alternatives. It is because increased search breadth will improve their chances to find better alternative for them. On the other hand, since human's cognitive capacity is limited, the increased search breadth (more alternatives) will reduce the depth of information search for each alternative. Consumers with high choice uncertainty will spend less time and effort for each alternative because considering more alternatives will increase their utility. LBS provides users with the capability to screen alternatives based on the distance from them, which reduces information search costs. Therefore, it is expected that LBS will help users consider more alternatives even when they have high knowledge uncertainty. LBS provides distance information, which helps users choose alternatives appropriate for them. Therefore, users will perceive lower choice uncertainty when they use LBS. In order to test the hypotheses, we selected 80 students and assigned them to one of the two experiment groups. One group was asked to use LBS to search surrounding restaurants and the other group was asked to not use LBS to search nearby restaurants. The experimental tasks and measures items were validated in a pilot experiment. The final measurement items are shown in Appendix A. Each subject was asked to read one of the two scenarios - with or without LBS - and use a smartphone application to pick a restaurant. All behaviors on smartphone were recorded using a recording application. Search breadth was measured by the number of restaurants clicked by each subject. Search depths was measured by two metrics - the average number of sub-level pages each subject visited and the average time spent on each restaurant. The hypotheses were tested using SPSS and PLS. The results show that knowledge uncertainty reduces search breadth (H1a). However, there was no significant correlation between knowledge uncertainty and search depth (H1b). Choice uncertainty significantly reduces search depth (H2b), but no significant relationship was found between choice uncertainty and search breadth (H2a). LBS information filtering significantly reduces the buyers' choice uncertainty (H4) and reduces the negative relationship between knowledge uncertainty and search breadth (H3). This research provides some important implications for service providers. Service providers should use different strategies based on their service properties. For those service providers who are not well-known to consumers (high knowledge uncertainty) should encourage their customers to use LBS. This is because LBS would increase buyers' consideration sets when the knowledge uncertainty is high. Therefore, less known services have chances to be included in consumers' consideration sets with LBS. On the other hand, LBS information filtering decrease choice uncertainty and the near service providers are more likely to be selected than without LBS. Hence, service providers should analyze geographically approximate competitors' strength and try to reduce the gap so that they can have chances to be included in the consideration set.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.10c
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• pp.103-122
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• 2001

For prediction of ground movement per the excavation step, observational results of ground movement during the construction was very different with prediction during the analysis of design. step because of the uncertainty of the numerical analysis modelling, the soil parameter, and the condition of a construction field, etc. however accuratly numerical analysis method was applied. Therefore, the management system through the construction field measurement should be achieved for grasping the situation during the excavation. Until present, the measurement system restricted by ‘Absolute Value Management system’only analyzing the stability of present step was executed. So, it was difficult situation to expect the prediction of ground movement for the next excavation step. In this situation, it was developed that ‘The Management system TOMAS-EXCAV’ consisted of ‘Absolute value management system’ analyzing the stability of present step and ‘Prediction management system’ expecting the ground movement of next excavation step and analyzing the stability of next excavation step by‘Back Analysis’. TOMAS-EXCAV could be applied to all uncertainty of earth retaining structures analysis by connecting ‘Forward analysis program’ and ‘Back analysis program’ and optimizing the main design variables using SQP-MMFD optimization method through measurement results. The application of TOMAS-EXCAV was confirmed that verifed the three earth retaing construction field by back analysis.

• Korean Journal of Environmental Agriculture
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• v.33 no.1
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• pp.30-36
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• 2014

BACKGROUND: Best management practices are often implemented to control nonpoint source pollutants. Best management practices need to be simulated and analyzed for effective Best management practices implementations. Filter strip is one of effective Best management practices in agricultural areas. METHODS AND RESULTS: Soil and Water Assessment Tool model was selected to explore the effectiveness of filter strip to control total phosphorous in Golji watershed. Soil and Water Assessment Tool model was calibrated for flow and total phosphorous by Sequential Uncertainty Fittin ver.2 algorithm provided in Soil and Water Assessment Tool-Calibration and Uncertainty Procedures. Three scenarios defined by filter strip width were applied. The filter strip width of 5 m was able to reduce the most amount of total phosphorous. In other words, the total phosphorous reduction by filter strip of 5 m was 28.0%, while the reduction was 17.5% by filter strip of 1 m. However, the reduction per unit filter strip width were 17.4%, 8.0%, and 4.5% for 1 m, 3 m, and 5 m of filter strips, respectively. CONCLUSION: Best management practices need to be simulated and analyzed so that the BMP scenario can be cost-effective. A large size of BMP might be able to control large amount of pollutants, however it would not be indicated as a cost-effective strategy.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.81-87
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• 2001

In a dynamically changing environment, the manager of a maintenance and remodeling (M/R) program is confronted with an increasing complexity of coordinating and cooperating multi-resource constrained multiple projects. The root causes of the complexity, uncertainty and interdependence, cause an internal disruption of an activity and chain reactions of disturbance propagation that deteriorate the stability and manageability of the program. This paper evaluates previous endeavors to apply production control and management techniques to the construction industry, and investigates the possibility of applying other management concepts and theories to organizational program management. In particular, this paper proposes a buffer allocation model by which periodic buffers are allocated in the flows of program constraint resources to stabilize a program master schedule instead of protecting individual activities. Comparative experiments by Monte Carlo simulations illustrate improved performance of the proposed model in terms of program's goals: productivity, flexibility, and long-term stability.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.170-170
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• 1998

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• Journal of Wetlands Research
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• v.11 no.1
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• pp.49-64
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• 2009

Rainfall-runoff models are used for efficient management, distribution, planning, and design of water resources in accordance with the process of hydrologic cycle. The models simplify the transition of rainfall to runoff as rainfall through different processes including evaporation, transpiration, interception, and infiltration. As the models simplify complex physical processes, gaps between the models and actual rainfall events exist. For more accurate simulation, appropriate models that suit analysis goals are selected and reliable long-term hydrological data are collected. However, uncertainty is inherent in models. It is therefore necessary to evaluate reliability of simulation results from models. A number of studies have evaluated uncertainty ingrained in rainfall-runoff models. In this paper, Meta-Gaussian method proposed by Montanari and Brath(2004) was used to assess uncertainty of simulation outputs from rainfall-runoff models. The model, which estimates upper and lower bounds of the confidence interval from probabilistic distribution of a model's error, can quantify global uncertainty of hydrological models. In this paper, Meta-Gaussian method was applied to analyze uncertainty of simulated runoff outputs from $Vflo^{TM}$, a physically-based distribution model and HEC-HMS model, a conceptual lumped model.

• Journal of Industrial Convergence
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• v.20 no.2
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• pp.11-19
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• 2022

This study examines the role of economic uncertainty in stock price determination in the domestic stock market. To this end, we analyzed the relationship between economic uncertainty indices at home and abroad (USA, China) and stock returns for non-financial companies in Korea from January 2000 to 2017. For the analysis model, the 3-factor model of Fama and French (1992) and the 5-factor model including momentum and liquidity were used. As a result of the analysis, a portfolio with a high beta of economic uncertainty showed higher stock returns than a portfolio with a low beta. This was the same as the US analysis result. Also, the analysis results using the US uncertainty index were more significant than the regression analysis results using the Korean economic uncertainty index.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.233-243
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• 2020

This study aims to assess the impacts of COVID-19 on International Financial Reporting Standards (IFRS), because of the problems associated with changing and amending the financial reports according to the policies established based on the circumstances of the epidemic. The study sample targeted several international financial reports that were amended based on epidemic conditions. The revised financial reporting period provides standardized reporting procedures for financial transactions worldwide despite the pandemic. Therefore, IFRS has been used to reduce challenges in financial reporting by monitoring the duration of social distancing while reporting matters to eliminate confirmed uncertainty and judgment. After analyzing the data obtained through global search engines, the results conducted provided evidence that COVID-19 affects financial reporting in companies around the world. Therefore, companies face difficulty reporting finances based on the challenging environment that the pandemic represents. Besides, IFRS fair value measurements consider the prices that were predicted according to current market values. The contexts of the changing the standards by IFRS to curb the effects of the COVID19 financial reporting was attained through evaluation of the online files that were randomly selected and filtered to obtain valid data.