• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.619-632
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• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• Korean Journal of Veterinary Research
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• v.47 no.2
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• pp.259-263
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• 2007

The choice of input distribution in quantitative risk assessments modeling is of great importance to get unbiased overall estimates, although it is difficult to characterize them in situations where data available are too sparse or small. The present study is particularly concerned with accommodation of uncertainties commonly encountered in the practice of modeling. The authors applied parametric and non-parametric bootstrap simulation methods which consist of re-sampling with replacement, in together with the classical Student-t statistics based on the normal distribution. The implications of these methods were demonstrated through an empirical analysis of trade volume from the amount of chicken and pork meat imported to Korea during the period of 1998-2005. The results of bootstrap method were comparable to the classical techniques, indicating that bootstrap can be an alternative approach in a specific context of trade volume. We also illustrated on what extent the bias corrected and accelerated non-parametric bootstrap method produces different estimate of interest, as compared by non-parametric bootstrap method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.403-407
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• 2003

This paper studies the error of pressure, particle velocity, and intensity which are distributed in a space. Errors may be amplified when other sound field variables are predicted. We theoretically derive their bias error and random error. The analysis shows that many samples do not always guarantee good results. Random error of the velocity and intensity are increased when many samples are used. The characteristics of the amplification of the random error are analyzed in terms of the sample spacing. The amplification was found to be related to the spatial differential of random noise. The numerical simulations are performed to verify theoretical results.

• Journal of the Korean Society of Safety
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• v.27 no.3
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• pp.131-140
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• 2012

Though there might exist not a few differences between cyclic works and atypical works, many researchers have applied the same assessment techniques that used for repetitive works, which may result introduce bias in their conclusions. This research aimed to verify whether there exist non-negligible work characteristics and/or dissimilarity among works with different work nature and whether one of the most prevalent assessment techniques for assessing ergonomic hazards of musculoskeletal disorders, REBA, can be applied to atypical works. For a general hospital, an automobile repair shop, and two auto-part assembly plants which manufactures quite different parts, a questionnaire survey and field investigation and ergonomic assessment were carried out and analyzed statistically with reference to the 3rd Quantification technique. The results showed that there exist remarkable difference between physical factors in cyclic works and atypical non-cyclic works. As for repetitive work, body posture was significant factors affecting on musculoskeletal disorders while atypical works seemed to have none which implied that the necessity of taking psychosocial factors into account for assessment of hazards. Complain rate in repetitive works was highest shoulder, back, and neck or wrist in sequence. However, there existed no consistent trend in complain rate in atypical works. And, though weight of manufacturing objects was a common factor that can partly explain musculoskeletal complain, time duration was significant in atypical work whereas repeatability and body posture were significant in repetitive works. As being the results, to summarize, it could be said that application of conventional ergonomic assessment techniques regardless of repetitiveness would be fruitless, and that the necessity of a unique methodology focused on atypical non-cyclic works should not be neglected.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.439-449
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• 2018

Many potential sources of bias are used in several steps of the radar-rainfall estimation process because the hydrological and meteorological radars measure the rainfall amount indirectly. Previous studies on radar-rainfall uncertainties were performed to reduce the uncertainty of each step by using bias correction methods in the quantitative radar-rainfall estimation process. However, these studies do not provide comprehensive uncertainty for the entire process and the relative ratios of uncertainty between each step. Consequently, in this study, a suitable approach is proposed that can quantify the uncertainties at each step of the quantitative radar-rainfall estimation process and show the uncertainty propagation through the entire process. First, it is proposed that, in the suitable approach, the new concept can present the initial and final uncertainties, variation of the uncertainty as well as the relative ratio of uncertainty at each step. Second, the Maximum Entropy Method (MEM) and Uncertainty Delta Method (UDM) were applied to quantify the uncertainty and analyze the uncertainty propagation for the entire process. Third, for the uncertainty quantification of radar-rainfall estimation at each step, two quality control algorithms, two radar-rainfall estimation relations, and two bias correction methods as post-processing through the radar-rainfall estimation process in 18 rainfall cases in 2012. For the proposed approach, in the MEM results, the final uncertainty (from post-processing bias correction method step: ME = 3.81) was smaller than the initial uncertainty (from quality control step: ME = 4.28) and, in the UDM results, the initial uncertainty (UDM = 5.33) was greater than the final uncertainty (UDM = 4.75). However uncertainty of the radar-rainfall estimation step was greater because of the use of an unsuitable relation. Furthermore, it was also determined in this study that selecting the appropriate method for each stage would gradually reduce the uncertainty at each step. Therefore, the results indicate that this new approach can significantly quantify uncertainty in the radar-rainfall estimation process and contribute to more accurate estimates of radar rainfall.

• The Korean Journal of Nuclear Medicine
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• v.27 no.2
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• pp.170-174
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• 1993

The quantitative methods for the assessment of the cerebral blood flow using $^{99m}Tc$-HMPAO brain SPECT utilize the measured count distribution in some specific reconstructed tomographic slice or in algebraic summation of a few neighboring slices, rather than the true volumetric distribution, to estimate the relative regional cerebral blood flow, and consequently produce the biased estimates of the true regional cerebral blood flow. This kind of biases are thought to originate mainly from the arbitrarily irregular shape of the cerebral region of interest(ROI) which are analyzed. In this study, a semi-automated method for the direct quantification of the volumetric regional cerebral blood flow estimate is proposed, and the results are compared to those calculated by the previous planar approaches. Bias factors due to the partial volume effect and the uncertainty in ROI determination are not considered presently for the methodological comparison of planar/volumetric assessment protocol.

• Nuclear Engineering and Technology
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• v.26 no.3
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• pp.389-400
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• 1994

The predictability of KAERI version of RELAP5/MOD3 on reflood peak cladding temperature during large break loss-of-coolant accident is assessed against 18 test runs in FLECHT SEASET test data. The associated uncertainty is statistically quantified. The selected test runs include a gravity feed test and several forced feed tests with wide range of the parameters such as flooding rate, system pressure, initial clad temperature, rod bundle power. The results show that the code under-predicts the peak cladding temperature by 7.56 K on average. The upper limit of the associated uncertainty at 95% confidence level is evaluated to be about 99 K, It including the bias due to the under-prediction.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.795-807
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• 2022

The development and commercialization of industrial genetically modified (GM) organisms is actively progressing worldwide, highlighting an increased need for improved safety management protocols. We sought to establish an environmental monitoring method, using real-time polymerase chain reaction (PCR) and propidium monoazide (PMA) treatment to develop a quantitative detection protocol for living GM microorganisms. We developed a duplex TaqMan quantitative PCR (qPCR) assay to simultaneously detect the selectable antibiotic gene, ampicillin (AmpR), and the single-copy Escherichia coli taxon-specific gene, D-1-deoxyxylulose 5-phosphate synthase (dxs), using a direct cell suspension culture. We identified viable engineered E. coli cells by performing qPCR on PMA-treated cells. The theoretical cell density (true copy numbers) calculated from mean quantification cycle (Cq) values of PMA-qPCR showed a bias of 7.71% from the colony-forming unit (CFU), which was within ±25% of the acceptance criteria of the European Network of GMO Laboratories (ENGL). PMA-qPCR to detect AmpR and dxs was highly sensitive and was able to detect target genes from a 10,000-fold (10^-4) diluted cell suspension, with a limit of detection at 95% confidence (LOD_95%) of 134 viable E. coli cells. Compared to DNA-based qPCR methods, the cell suspension direct PMA-qPCR analysis provides reliable results and is a quick and accurate method to monitor living GM E. coli cells that can potentially be released into the environment.

• Journal of the Mineralogical Society of Korea
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• v.26 no.1
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• pp.27-34
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• 2013

X-ray powder diffraction is one of the most powerful techniques for qualitative and quantitative analysis of crystalline compounds. Thus, there exist a number of different methods for quantifying mineral mixtures using X-ray diffraction pattern. We present here the use of Rietveld and PONKCS (partial or no known crystal structure) methods for quantification of amorphous and crystallized mineral phases in synthetic mixtures of standard minerals (amorphous silica, quartz, mullite and corundum). Pawley phase model of amorphous silica was successfully built from the pattern of 100 wt% amorphous silica and internal standard-spiked samples by PONKCS approach. The average of absolute bias for quantities of amorphous silica was 1.85 wt%. The larger bias observed for lower quantities of amorphous silica is probably explained by low intensities of diffraction pattern. Averages of absolute bias for minerals were 0.53 wt% for quartz, 0.87 wt% for mullite and 0.57 wt% for corundum, respectively. The PONKCS approach achieved improved quantitative results compared with classical Rietveld method by using an internal standard.

• Journal of Life Science
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• v.20 no.11
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• pp.1738-1741
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• 2010

Caliper measurements of tumor volume have been widely used in the assessment of tumors in animal models. However, experiments based on caliper data have resulted in unreliable estimates of tumor growth, due to necrotic areas of tumor mass. To overcome this systematic bias, we engineered a new luciferase-expressing rat prostate cancer cell line (MLL-Luc) that produces bioluminescence from viable cancer cells. MLL-Luc cells showed a strong correlation between bioluminescence intensity and cell number ($R^2$=0.99) and also accurately quantified tumor growth, with reduced bioluminescence signals caused by necrotic cells in a subcutaneous MLL-Luc xenograft model. The accurate quantification of tumor growth with bioluminescence imaging (BLI) was confirmed by a better antitumor effect of combination chemotherapy, compared to that based on caliper measurements with a correlation between the bioluminescence signal and tumor volume ($R^2$=0.84). These data suggest that bioluminescent MLL xenografts are a powerful and quantitative tool for monitoring tumor growth and are useful in evaluating the efficacy of anticancer drugs, with less systematic bias.