• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.105-117
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• 2001

This paper models supply uncertainty in the dynamic Newsboy problem context. The system consists of one supplier and one retailer who places an order to the supplier every period to meet stochastic demand. Supply uncertainty is modeled as the uncertainty in quantities delivered by the supplier. That is, the supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of (1-$\beta$). We formulate the problem as a dynamic programming problem and prove that retailer’s optimal replenishment policy is a stationary base-stock policy. Through a numerical study, we found that the cost increase due to supply uncertainty is significant and that the costs increase more rapidly as supply uncertainty increases. We also identified the effects of various system parameters. One of the interesting results is that as retailer’s demand uncertainty, the other uncertainty in our model, increases, the cost increase due to supply uncertainty becomes less significant.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.137-137
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• 2022

Evaluating interpolated rainfall uncertainty of hydrological models caused by different interpolation methods for basins where can not fully collect rainfall data are necessary. In this study, the adaptive MCMC method under effects of ILFs was used to analyze the interpolated rainfall uncertainty of the SURR model for Gunnam basin, Korea. Three events were used to calibrate and one event was used to validate the posterior distributions of unknown parameters. In this work, the performance of four ILFs on uncertainty of interpolated rainfall was assessed. The indicators of p_factor (percentage of observed streamflow included in the uncertainty interval) and r_factor (the average width of the uncertainty interval) were used to evaluate the uncertainty of the simulated streamflow. The results showed that the uncertainty bounds illustrated the slight differences from various ILFs. The study confirmed the importance of the likelihood function selection in the application the adaptive Bayesian MCMC method to the uncertainty assessment of the SURR model caused by interpolated rainfall.

• Journal of the Korean Society of Tobacco Science
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• v.26 no.2 s.52
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• pp.168-178
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• 2004

Uncertainty of final measurement results considering main uncertainty sources being in nicotine of mainstream smoke was estimated. This study was accomplished by using the ISO 'The Guide to the Expression of Uncertainty in Measurement'. Using the two point re-calibration method, uncertainty for nicotine concentration was calculated considering the uncertainty sources of each step. The concentration and uncertainty of nicotine in mainstream smoke was estimated as $153.95{\pm}17.84\;{\mu}g/mL\;(0.77\pm0.089 mg/cig)$. The expanded uncertainty was $17.84 {\mu}g/mL(\pm0.089 mg/cig).$ The reported expanded uncertainty of the measurement is stated as the standard uncertainty of measurement multiplied by a coverage factor of 2, which for a normal distribution corresponds to a coverage probability of approximately $95\%$ The former expression indicates the conversion concentration into the sample.

• Korean Journal of Adult Nursing
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• v.17 no.2
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• pp.230-238
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• 2005

Purpose: The purposes of this study were to explore the concept of uncertainty and to examine the relationships among uncertainty, appraisal of uncertainty, depression, anxiety, and perceived health status in patients with atrial fibrillation. Method: The study utilized a descriptive correlational survey design using a face to face interview method. A convenience sample of 49 subjects were recruited from K university hospital over 8 months. The data were analyzed by t-test, ANOVA, Pearson correlation and partial correlation analysis. Results: 1) Subjects perceived with moderately high uncertainty(M=65.98); moderate physical health(M=39.80), mental health(M=47.38), and general health(M=2.94); moderate anxiety(M= 44.78); and slightly low depression(M=15.33). 2) There were significant differences in uncertainty by gender and education. 3) Uncertainty and danger appraisal were significantly correlated(r=.32, p=.03) while the uncertainty was not associated with opportunity appraisal. 4) Uncertainty was significantly correlated with mental health(r=-.31, p=.04), anxiety(r=.38, p=.01), and depression(r=.37, p=.01). Conclusion: This study was the first trial to explore uncertainty and to examine the relationships among its associated factors in Korean patients with atrial fibrillation. Thus, based on the findings of this study, directions for nursing practice and further nursing research for patients with atrial fibrillation were suggested.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.245-258
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• 2005

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population outside the plant boundary due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR with 144 meteorological sequences were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence. This could provide valuable insights into areas for further research aiming at reducing the uncertainties.

• Journal of muscle and joint health
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• v.4 no.2
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• pp.277-296
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• 1997

This study was conducted to investigate the influencing factors on the appraisal of uncertainty in patients having rheumatoid arthritis. Subjects of the study constituted 528 patients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. Self report questionnaires were used to measure the variables influencing the appraisal of uncertainty. Reliability coefficients of these instruments were found Cronbach's Alpha=$.70{\sim}.96$. In data analysis, SPSS PC 6.0 program was utilized for descriptive statistics, Pearson's correlation, logistic and multiple regression analysis. The results of logistic and multiple regression analysis were as follows 1) Among the independent variables, significant factors to explain the appraisal of uncertainty in patients were uncertainty(p<.001), severity of illness(p<.05), educational level (p<.05) and age (p<.05). 2) When patients appraised uncertainty as "Danger", significant factors to explain the appraisal of uncertainty were uncertainty(p<.0001), age(p<.0005), severity of illness(p<.001), educational level (p<.05). 3) When patients appraised uncertainty as "Opportunity", significant factors to predict the appraisal of uncertainty were uncertainty(p<.0005), social support(p<.0005), severity of illness(p<.005), credible authority(p<.05), age(p<.05) and educational level (p<.05).

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.790-802
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• 2022

Large-scale reactor simulation often requires the use of Monte Carlo calculation techniques to estimate important reactor parameters. One drawback of these Monte Carlo calculation techniques is they inevitably result in some uncertainty in calculated quantities. The present study includes parametric uncertainty quantification (UQ) and sensitivity analysis (SA) on the Advanced Test Reactor Critical (ATRC) facility housed at Idaho National Laboratory (INL) and addresses some complications due to Monte Carlo uncertainty when performing these analyses. This approach for UQ/SA includes consideration of Monte Carlo code uncertainty in computed sensitivities, consideration of uncertainty from directly measured parameters and a comparison of results obtained from brute-force Monte Carlo UQ versus UQ obtained from a surrogate model. These methodologies are applied to the uncertainty and sensitivity of k_eff for two sets of uncertain parameters involving fuel plate geometry and fuel plate composition. Results indicate that the less computationally-expensive method for uncertainty quantification involving a linear surrogate model provides accurate estimations for k_eff uncertainty and the Monte Carlo uncertainty in calculated k_eff values can have a large effect on computed linear model parameters for parameters with low influence on k_eff.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.354-359
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• 2002

The new piston prover was developed and the flow measurement uncertainty of this piston prover was evaluated according to ISO/IEC 17025. The laser interferometer was employed to measure accurately the testing time. Uncertainty was calculated with evaluation of various uncertainty factors affected in flow measurement. The expanded uncertainty(U) of the piston Over was $1.3{\times}10^{-3}$ (at the confidence level of $95\%$). This evaluation example will be useful in flow measurement uncertainty determination of other gas flow measurement system.

• Corrosion Science and Technology
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• v.8 no.5
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• pp.193-196
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• 2009

For the estimation of uncertainty in potentiodynamic polarization resistance measurement, the type A uncertainty was measured using type 316 stainless steel in an acidified NaCl solution. Sensitivity coefficients were determined for measurand such as scan rate of potential, temperature of solution, concentration of NaCl, concentration of HCl, surface roughness of specimen and flow rate of purging gas. Sensitivity coefficients were large for the measurand such as the scan rate of potential, temperature of solution and roughness of specimen. However, the sensitivity coefficients were not the major factors influencing the combined standard uncertainty of polarization resistance due to the low values of uncertainty in measurements of the measurands. A major influencing factor was the concentration of NaCl. The value of type A uncertainty was 1.1 times the value of type B uncertainty, and the combined standard uncertainty was 10.5 % of the average value of polarization resistance.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.