• Earthquakes and Structures
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• v.10 no.2
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• pp.389-408
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• 2016

Recently, seismic hazard analysis has become a very significant issue. New systems and available data have been also developed that could help scientists to explain the earthquakes phenomena and its physics. Scientists have begun to accept the role of uncertainty in earthquake issues and seismic hazard analysis. However, handling the existing uncertainty is still an important problem and lack of data causes difficulties in precisely quantifying uncertainty. Ground Motion Prediction Equation (GMPE) values are usually obtained in a statistical method: regression analysis. Each of these GMPEs uses the preliminary data of the selected earthquake. In this paper, a new fuzzy method was proposed to select suitable GMPE at every intensity (earthquake magnitude) and distance (site distance to fault) according to preliminary data aggregation in their area using ${\alpha}$ cut. The results showed that the use of this method as a GMPE could make a significant difference in probabilistic seismic hazard analysis (PSHA) results instead of selecting one equation or using logic tree. Also, a practical example of this new method was described in Iran as one of the world's earthquake-prone areas.

• The Journal of Information Systems
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• v.15 no.1
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• pp.191-213
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• 2006

The purpose of this research is to identify the structure among determining factors focusing on knowledge transfer and analyze and prove the causal relation on knowledge transfer in Korean companies and public corporations. The results from the analysis of data collected in this study are as follows. First, forum among organization related factors has the positive relation with uncertainty in a significant level. Second, the higher the knowledge presentation and the ease of use are among information systems related factors, the lower the ambiguity and uncertainty are. Third, among process related factors, unification has the negative relation with ambiguity and uncertainty in a significant level. Fourth, a better manpower employment contributes to a worse ambiguity and uncertainty. Fifth, ambiguity has a negative relation with knowledge transfer. In conclusion, the factors that lower the ambiguity and facilitate knowledge transfer include information systems, unification, and manpower employment. These factors, however, influence on uncertainty, which turns out to be nothing to do with knowledge transfer.

• The Research Journal of the Costume Culture
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• v.8 no.1
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• pp.30-39
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• 2000

The purpose of this study were to 1) identify types and levels of production environments, 2) classify apparel manufacturers based on production environments and 3) investigate relationship between characteristics of apparel manufacturers and production environment. Apparel manufacturer's characteristics included product line and the number of employees. For this study, the questionnaires were administered to 215 apparel manufacturers in seoul and Kyung-gi region from Feb. to Mar. 1998. Employing a sample of 201, data were analyzed by factor analysis, descriptive statistics, cluster analysis, cluster analysis, discriminant Analysis, and multivariate analysis of variance. The following are the results of this study : 1. The production environment was identified as three types such as complexity of product environment, uncertainty of demand/supply environment and uncertainty of worker environment. 2. Based on three types of the production environment, apparel manufacturers were classified into stable group, uncertain group and complicated group. 3. With respect to product line, men's wear manufacturers were lied the most high complexity of product environment, casual wear and knit wear were lied the most frequently uncertainty of worker environment. With respect to the number employees, apparel manufacturers comprising 50∼99 employees were lied the most high complexity of product environment, while those comprising 100∼299 employees the most high demand/supply environment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.272-288
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• 1990

The uncertainty quantification process in probabilistic Risk Assessment usually involves a specification of the uncertainty in the input data and the propagation of this uncertainty to the final risk results. The distributional sensitivity analysis is to study the impact of the various assumptions made during the quantification of input parameter uncertainties on the final output uncertainty. The uncertainty importance of input parameters, in this case, should reflect the degree of changes in the whole output distribution and not just in a point estimate value. A measure of the uncertainty importance is proposed in the present paper. The measure is called the distributional sensitivity measure(DSM) and explicitly derived from the definition of the Kullback's discrimination information. The DSM is applied to three typical discrimination information. The DSM is applied to three typical cases of input distributional changes: 1) Uncertainty is completely eliminated, 2) Uncertainty range is increased by a factor of 10, and 3) Type of distribution is changed. For all three cases of application, the DSM-based importance ranking agrees very well with the observed changes of output distribution while other statistical parameters are shown to be insensitive.

• The KSFM Journal of Fluid Machinery
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• v.14 no.1
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• pp.42-47
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• 2011

Measurement uncertainty analysis of fuel flow using turbine flowmeter was performed for the case of altitude engine test. SAE ARP4990 was used as the fuel flow calculation procedure, as well as the mathematical model for the measurement uncertainty assessment. The assessment was performed using Sensitivity Coefficient Method. 11 parameters involved in the calculation of the flow rate were considered. For the given equipment setup, the measurement uncertainty of fuel flow was assessed in the range of 1.19~1.86 % for high flow rate case, and 1.47~3.31 % for low flow rate case. Fluctuation in frequency signal from the flowmeter had the largest influence on the fuel flow measurement uncertainty for most cases. Fuel temperature measurement had the largest for the case of low temperature and low flow rate. Calibration of K-factor and the interpolation of the calibration data also had large influence, especially for the case of very low temperature. Reference temperature, at which the reference viscosity of the sample fuel was measured, had relatively small contribution, but it became larger when the operating fuel temperature was far from reference temperature. Measurement of reference density had small contribution on the flow rate uncertainty. Fuel pressure and atmospheric pressure measurement had virtually no contribution on the flow rate uncertainty.

• Journal of muscle and joint health
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• v.23 no.2
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• pp.114-124
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• 2016

Purpose: The purpose of this study was to investigate the level of uncertainty, physiological risk factors, self-efficacy, and self-management among stroke patients and to identify factors influencing their self-management. Methods: A descriptive correlational design was used for this study. A convenience sample of 149 patients with stroke were enrolled at C national university hospital from February to April in 2016. Data were collected using a structured questionnaire and electronic medical record. Collected data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlations, and multiple regression analysis with the SPSS/WIN 21.0 program. Results: There were significant negative correlations between uncertainty and self-efficacy (r=-.56, p<.001); between uncertainty and self-management (r=-.56, p<.001); and between total cholesterol and self-management (r=-.23, p=.005). There were significant positive correlations between self-efficacy and self-management (r=.78, p<.001); between uncertainty and total cholesterol (r=.24, p=.003). The significant factors influencing self-management were uncertainty and self-efficacy. Theses variables explained 62.7% of the variance in self-management. Conclusion: The results suggest that intervention programs to reduce the level of uncertainty and to increase the level of self-efficacy among patients would improve the self-management of stroke patients.

• Women's Health Nursing
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• v.11 no.4
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• pp.316-323
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• 2005

Purpose: The purpose of this study was to explore the relationships among women's total symptom distress, uncertainty and quality of life in women with endometriosis. Method: A total of 121 women who had been diagnosed with endometriosis was given a questionnaire. Data was collected from August 2004 to January 2005. The data was analyzed by frequency, mean, t-test, ANOVA, Pearson correlation coefficient, and multiple linear regression analysis using SPSS WIN 10.0 software. Result: The mean score of TSD was 3.23. 'Menstrual cramping' showed the highest score. The mean score of uncertainty, and quality of life of the subject was 56.6, and 38.3 respectively. TSD was significantly related with coffee intake and uncertainty was significantly related with marital status, economic status, alcohol intake, diagnosis after period, and family history. Quality of life was significantly related with age, and dysmenorrhea. There were significant relationships between total symptom distress and uncertainty, and quality of life. There were significant relationship between uncertainty and quality of life. Conclusion: Endometriosis symptoms showed a significant relationship with uncertainty and quality of life. This study will help to manage women with endometriosis.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.2
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• pp.91-99
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• 2016

To estimate design floods for hydraulic structures, statistical methods has been used in the analysis of rainfall data. However, due to the lack of rainfall data in some regions, it is difficult to apply the statistical methods for estimation of design rainfall. In addition, increased uncertainty of design rainfall arising from the limited rainfall data can become an important factor for determining the design floods. The main objective of this study was to assess the uncertainty of the future design floods under RCP (representative concentration pathways) scenarios using a bootstrap technique. The technique was used in this study to quantify the uncertainty in the estimation of the future design floods. The Yongdang watershed in South Korea, 2,873 ha in size, was selected as the study area. The study results showed that the standard errors of the basin of Yongdang reservoir were calculated as 2.0~6.9 % of probable rainfall. The standard errors of RCP4.5 scenario were higher than the standard errors of RCP8.5 scenario. As the results of estimation of design flood, the ranges of peak flows considered uncertainty were 2.3~7.1 %, and were different each duration and scenario. This study might be expected to be used as one of guidelines to consider when designing hydraulic structures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1163-1170
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• 2009

Reliability analysis is of great importance in the advanced product design, which is to evaluate reliability due to the associated uncertainties. There are three types of uncertainties: the first is the aleatory uncertainty which is related with inherent physical randomness that is completely described by a suitable probability model. The second is the epistemic uncertainty, which results from the lack of knowledge due to the insufficient data. These two uncertainties are encountered in the input variables such as dimensional tolerances, material properties and loading conditions. The third is the metamodel uncertainty which arises from the approximation of the response function. In this study, an integrated method for the reliability analysis is proposed that can address all these uncertainties in a single Bayesian framework. Markov Chain Monte Carlo (MCMC) method is employed to facilitate the simulation of the posterior distribution. Mathematical and engineering examples are used to demonstrate the proposed method.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1626-1637
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• 2020

This work covers an important point of the benchmark released by the expert group on Uncertainty Analysis in Modeling of Light Water Reactors. This ambitious benchmark aims to determine the uncertainty in light water reactors systems and processes in all stages of calculation, with emphasis on multi-physics (coupled) and multi-scale simulations. The Gesellschaft für Anlagen und Reaktorsicherheit methodology is used to propagate the thermal-hydraulic uncertainty of macroscopic parameters through TRACE5.0p3/PARCSv3.0 coupled code. The main innovative points achieved in this work are i) a new thermal-hydraulic model is developed with a highly-accurate 3D core discretization plus an iterative process is presented to adjust the 3D bypass flow, ii) a control rod insertion occurrence -which data is obtained from a real PWR test- is used as a transient simulation, iii) two approaches are used for the propagation process: maximum response where the uncertainty and sensitivity analysis is performed for the maximum absolute response and index dependent where the uncertainty and sensitivity analysis is performed at each time step, and iv) RESTING MATLAB code is developed to automate the model generation process and, then, propagate the thermal-hydraulic uncertainty. The input uncertainty information is found in related literature or, if not found, defined based on expert judgment. This paper, first, presents the Gesellschaft für Anlagen und Reaktorsicherheit methodology to propagate the uncertainty in thermal-hydraulic macroscopic parameters and, then, shows the results when the methodology is applied to a PWR reactor.