• Journal of Radiation Protection and Research
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• v.43 no.1
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• pp.29-38
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• 2018

Background: Radon contributing about 42% of annual average dose, mainly comes from soil. In this paper, standard measurement procedures for soil radon exhalation rate are suggested and their measurement uncertainties are analyzed. Materials and Methods: We used accumulation method for estimating surface exhalation rate. The closed-loop measurement system was made up with a RAD7 detector and a surface chamber. Radon activity concentrations in the system were observed as a function of time, with data collection of 5 and 15-minute and the measurement time of 4 hours. Linear and exponential fittings were used to obtain radon exhalation rates from observed data. Standard deviations of measurement uncertainties for two approaches were estimated using usual propagation rules. Results and Discussion: The exhalation rates (E) from linear approach, with 30 minutes measurement time were $44.8-48.6mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.14-2.32atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with relative measurement uncertainty of about 10%. The contributions of fitting parameter A, volume (V) and surface (S) to the estimated measurement uncertainty of E were 59.8%, 30.1% and 10.1%, in average respectively. In exponential fitting, at 3-hour measurement we had E ranged of $51.6-69.2mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.46-3.30atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with about 15% relative uncertainty. Fitting with 4-hour measurement resulted E about $51.3-68.2mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.45-3.25atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with 10% relative uncertainty. The uncertainty contributions in exponential approach were 75.1%, 13.4%, 8.7%, and 2.9% for total decay constant k, fitting parameter B, V, and S, respectively. Conclusion: In obtaining exhalation rates, the linear approach is easy to apply, but by saturation feature of radon concentrations, the slope tends to decrease away from the expected slope for extended measurement time. For linear approach, measurement time of 1-hour or less was suggested. For exponential approach, the obtained exhalation rates showed similar values for any measurement time, but measurement time of 3-hour or more was suggested for about 10% relative uncertainty.

• Journal of Environmental Science International
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• v.20 no.12
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• pp.1541-1551
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• 2011

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.

• Korean Journal of Construction Engineering and Management
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• v.8 no.5
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• pp.191-200
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• 2007

This paper introduces a tool for predicting potential cost overrun during project execution and for quantifying the uncertainty on the expected project cost, which is occasionally changed by the unknown effects resulted from project's complications and unforeseen environments. The model proposed in this stuff is useful in diagnosing cost performance as a project progresses and in monitoring the changes of the uncertainty as indicators for a warning signal. This model is intended for the use by project managers who forecast the change of the uncertainty and its magnitude. The paper presents a mathematical approach for modifying the costs of incomplete work packages and project cost, and quantifying reduced uncertainties at a consistent confidence level as actual cost information of an ongoing project is obtained. Furthermore, this approach addresses the effects of actual informed data of completed work packages on the re-estimates of incomplete work packages and describes the impacts on the variation of the uncertainty for the expected project cost incorporating Multivariate Probabilistic Analysis (MPA) and Bayes' Theorem. For the illustration purpose, the Introduced model has employed an example construction project. The results are analyzed to demonstrate the use of the model and illustrate its capabilities.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.419-434
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• 2023

Purpose: Measurement results obtained under non-ideal measurement environment conditions may contain uncertain factors. As a result, the reliability of measurement results may be deteriorated. In this study, we tried to find ways to improve quality by evaluating and applying measurement uncertainty based on GUM. Methods: In the flatness measurement of semiconductor parts, uncertainty factors that could occur under actual environmental conditions of workers were derived, and measurement uncertainties were calculated, and methods for minimizing the main factors affecting the measurement results were analyzed. Results: Depending on the part and the coordinate measuring machine, it was shown that the effect of dispersion caused by repeated measurements as type A uncertainty and the effect of the calibration results of equipment as type B uncertainty have the main influence. Conclusion: Depending on the uncertainty factors of type A and type B and the influence of the total expanded uncertainty, the central value and confidence interval of the initial measurement results showed fluctuations. It is considered that analysis and measures for the main uncertainty factors are needed as quality improvement in the industrial field.

• International Commerce and Information Review
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• v.17 no.1
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• pp.89-114
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• 2015

We investigate the structural relationships between quality of service from Trade Promotion Agency(TPA), environmental uncertainty, and firms' uses of the service, export market orientation and export performance, using data from Korean export firms, Seoul Metropolitan export firms and local export firms. In particular, this article attempts to analyze how firms' uses of service from TPA may be influenced by their export market orientation, environmental uncertainty, and the service quality. The results from the study show that in Seoul Metropolitan export firms, TPA's service quality, environmental uncertainty, and their export market orientation have positive effects on their uses of service from TPA, which leads to increase in their export performance. The study also finds a solid evidence that, in Seoul Metropolitan export firms, environmental uncertainty has a positive effect on their export market orientation, which enhances their export performance. The study, however, finds that in local export firms, environmental uncertainty and export market orientation do not significantly affect their uses of service from TPA and export performance, respectively.

• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.69-81
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• 2012

Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

• Journal of the Korea Society for Simulation
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• v.25 no.3
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• pp.125-132
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• 2016

This study intended to exploratively depict the influence of interaction between Environmental Uncertainty and Learning Orientation of Korean IT companies on Marketing Capability which was adopted as one of the organizational performance indicator. Statistical Results based on AMOS and SPSS showed that smaller-sized companies under 500 employees are more inclined to desperately and flexibly meet and adapt to their environmental uncertainty, resulting positive performance, that is, marketing capabilities. On the other hand, larger-sized companies over 500 employees showed no significant interaction effect. This result of the study induces the reasoning that the differences in competitive environment and market leadership accrued by organizational size may also incur differences in environmental adaptive mechanism. However, this reasoning can have some limitation in that the types and traits of IT firms are so different. Therefore, this topic suggests the necessity of follow-up researches using enlarged samples in IT industry and comparative studies in other industries.

• Analytical Science and Technology
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• v.16 no.6
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• pp.475-482
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• 2003

Uncertainty of final measurement results considering main uncertainty sources being in dioxin analysis of a blood sample was estimated. 'The Guide to the Expression of Uncertainty in Measurement' was suggested for accomplishment of this study. After uncertainties for the 11 compounds detected in this experiment of the 17 target compounds of dioxin and furan were calculated considering the uncertainty sources of each step, uncertainty for the total dioxin concentration was estimated by combining these values. The concentration of dioxin in blood sample was expressed as $0.0746{\pm}0.0074pg$ I-TEQ/g weight or $20.68{\pm}2.04pg$ I-TEQ/g lipid, including the uncertainty values obtained in this way. The former expression indicates the conversion concentration into the sample weight and the latter one indicates the conversion concentration into the lipid weight. The quality of measured analytical results could be assured quantitatively by estimating uncertainty of measurement results and showing the range of measurand.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2007.05a
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• pp.199-202
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• 2007