• Mass Spectrometry Letters
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• v.5 no.2
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• pp.57-61
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• 2014

A gravimetric standard addition method combined with internal standard calibration has been successfully developed for the accurate analysis of total arsenic in a laver candidate reference material. A model equation for the gravimetric standard addition approach using an internal standard was derived to determine arsenic content in samples. Handlings of samples, As standard and internal standard were carried out gravimetrically to avoid larger uncertainty and variability involved in the volumetric preparation. Germanium was selected as the internal standard because of its close mass to the arsenic to minimize mass-dependent bias in mass spectrometer. The ion signal ratios of $^{75}As^+$ to $^{72}Ge^+$ (or $^{73}Ge^+$) were measured in high resolution mode ($R{\geq}10,000$) to separate potential isobaric interferences by high resolution ICP/MS. For method validation, the developed method was applied to the analysis of arsenic content in the NMIJ 7402-a codfish certified reference material (CRM) and the result was $37.07mg{\cdot}kg^{-1}{\pm}0.45mg{\cdot}kg^{-1}$ which is in good agreement with the certified value, $36.7mg{\cdot}kg^{-1}{\pm}1.8mg{\cdot}kg^{-1}$. Finally, the certified value of the total arsenic in the candidate laver CRM was determined to be $47.15mg{\cdot}kg^{-1}{\pm}1.32mg{\cdot}kg^{-1}$ (k = 2.8 for 95% confidence level) which is an excellent result for arsenic measurement with only 2.8 % of relative expanded uncertainty.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.7
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• pp.46-52
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• 2001

This study describes the precision control of the torque standard machine using a self-tuning fuzzy controller. The torque standard machine should generate the accurate torque for calibrating a torque sensor. In order to reduce the relative expanded uncertainty of the torque standard machine, when a weight is hanged to the end of the torque arm for generating the torque, the sloped torque arm should be accurately controlled to the horizontal level. If the slope of the torque arm is larger from the inaccurate control, the uncertainty of the torque standard machine due to control will be larger. This applies the inaccurate torque to a torque sensor to calibrate, and the measuring error of the torque sensor generate from it. Therefore the torque arm of the torque standard machine is accurately controlled. In this paper, the self-tuning fuzzy controller was designed using a fuzzy theory, and the torque arm of the torque standard machine was accurately controlled. The control gain of the fuzzy controller, that is the membership function size of the error, the membership function size of the error change and the membership function size of the controller were determined from the self-tuning. The control results of the torque standard machine were the overshoot within 0.0076mm, the rise time within 16.70sec and the steady state error within 0.0076mm.

• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.149-154
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• 2016

Background: Any real application of Bayesian inference must acknowledge that both prior distribution and likelihood function have only been specified as more or less convenient approximations to whatever the analyzer's true belief might be. If the inferences from the Bayesian analysis are to be trusted, it is important to determine that they are robust to such variations of prior and likelihood as might also be consistent with the analyzer's stated beliefs. Materials and Methods: The robust Bayesian inference was applied to atmospheric dispersion assessment using Gaussian plume model. The scopes of contaminations were specified as the uncertainties of distribution type and parametric variability. The probabilistic distribution of model parameters was assumed to be contaminated as the symmetric unimodal and unimodal distributions. The distribution of the sector-averaged relative concentrations was then calculated by applying the contaminated priors to the model parameters. Results and Discussion: The sector-averaged concentrations for stability class were compared by applying the symmetric unimodal and unimodal priors, respectively, as the contaminated one based on the class of ${\varepsilon}$-contamination. Though ${\varepsilon}$ was assumed as 10%, the medians reflecting the symmetric unimodal priors were nearly approximated within 10% compared with ones reflecting the plausible ones. However, the medians reflecting the unimodal priors were approximated within 20% for a few downwind distances compared with ones reflecting the plausible ones. Conclusion: The robustness has been answered by estimating how the results of the Bayesian inferences are robust to reasonable variations of the plausible priors. From these robust inferences, it is reasonable to apply the symmetric unimodal priors for analyzing the robustness of the Bayesian inferences.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.135-143
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• 2014

In this study, Chungju inflow was simulated for climate change considering the uncertainties of GCMs and a stochastic model. TFN (Transfer Function Noise) model and 4 different GCMs (CNRM, CSIRO, CONS, UKMO) based on IPCC AR4 A2 scenario were used. In order to evaluate uncertainty of TFN model, 100 cases of noises are applied to the TFN model. Thus, 400 cases of inflow results are simulated. Future inflows according to the GCMs show different rates of changes for the future 3 periods relative to the past 30-years reference period. As the results, the summer inflow shows increasing trend and the spring inflow shows decreasing trend based on AR4 A2 scenario.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.139-144
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• 2008

Generally, real system that is the object of decision-making is very variable and sometimes it lies situations with uncertainty. To solve these problem, it has used statistical methods as significance level, certainty factor, sensitivity analysis and so on. In this paper, we propose a method for fuzzy decision-making based on MFAC(Multiple Fuzzy Alpha Cut) to improve the definiteness of classification results with similarity evaluation. In the proposed method, MFAC is used for extracting multiple a ${\alpha}$-level with proximity degree at proximity relation between relative Hamming distance and max-min method and for minimizing the number of data which are associated with the partition intervals extracted by MFAC. To determine final alternative of decision-making, we compute the weighted value between extracted data by MFAC From the experimental results, we can see the fact that the proposed method is simpler and more definite than classification performance of the conventional methods and determines an alternative efficiently for decision-maker by testing significance of sample data through statistical method.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.329-337
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• 2017

In this study, land-use changes from 1990 to 2010 in Jeju Island by different approaches were produced and compared to suggest a more efficient approach. In a sample-based method, land-use changes were analyzed with different sampling intensities of 2 km and 4 km grids, which were distributed by the fifth National Forest Inventory (NFI5), and their uncertainty was assessed. When comparing the uncertainty for different sampling intensities, the one with the grid of 2 km provided more precise information; ranged from 6.6 to 31.3% of the relative standard error for remaining land-use categories for 20 years. On the other hand, land-cover maps by a wall-to-wall approach were produced by using time-series Landsat imageries. Forest land increased from 34,194 ha to 44,154 ha for 20 years, where about 69% of total forest land were remained as forest land and 19% and 8% within forest lands were converted to grassland and cropland, respectively. In the case of grassland, only about 40% of which were remained as grassland and most of the area were converted to forest land and cropland. When comparing land-cover area by land-use categories with land-use statistics, forest areas were underestimated while areas of cropland and grassland were overestimated. In order to analyze land use change, it is necessary to establish a clear and consistent definition on the six land use classification.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1165-1203
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• 2024

In the paper we validate theoretical models of the pulse against experimental data from the Jozef Stefan Institute TRIGA Mark II research reactor. Data from all pulse experiments since 1991 have been collected, analysed and are publicly available. This paper summarizes the validation study, which is focused on the comparison between experimental values, theoretical predictions (Fuchs-Hansen and Nordheim-Fuchs models) and calculation using computational program Improved Pulse Model. The results show that the theoretical models predicts higher maximum power but lower total released energy, full width at half maximum and the time when the maximum power is reached is shorter, compared to Improved Pulse Model. We evaluate the uncertainties in pulse physical parameters (maximum power, total released energy and full width at half maximum) due to uncertainties in reactor physical parameters (inserted reactivity, delayed neutron fraction, prompt neutron lifetime and effective temperature reactivity coefficient of fuel). It is found that taking into account overestimated correlation of reactor physical parameters does not significantly affect the estimated uncertainties of pulse physical parameters. The relative uncertainties of pulse physical parameters decrease with increasing inserted reactivity. If all reactor physical parameters feature an uncorrelated uncertainty of 10 % the estimated total uncertainty in peak pulse power at 3 $ inserted reactivity is 59 %, where significant contributions come from uncertainties in prompt neutron lifetime and effective temperature reactivity coefficient of fuel. In addition we analyse contribution of two physical mechanisms (Doppler broadening of resonances and neutron spectrum shift) that contribute to the temperature reactivity coefficient of fuel. The Doppler effect contributes around 30 %-15 % while the rest is due to the thermal spectrum hardening for a temperature range between 300 K and 800 K.

• Journal of the Korean Institute of Gas
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• v.22 no.2
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• pp.46-51
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• 2018

Hydrogen sulfide from landfill and sewage treatment plant is a major odor component and causes many civil petitions. Rapidly developing industries release hydrogen sulfide, an odorous gas, to the atmosphere. This study aims to develop a $10{\mu}mol/mol$ concentration level hydrogen sulfide primary standard gas for odor measurement. The hydrogen sulfide gas was prepared at a nominal concentration of $10{\mu}mol/mol$ in nitrogen using the gravimetric method described in ISO 6142. Replicate standard gases were produced in 4 aluminium cylinders, and their concentrations were verified by GC-AED. The uncertainty of production was less than 0.50 %, and the variation of the 4 replicates was 0.22 %. The wall adsorption of hydrogen sulfide in cylinders was 0.10 % at 1500 psi, and the concentration was estimated to be long-term stable for one year. The relative expanded uncertainty of the preparation consistency, adsorption and long-term stability of this hydrogen sulfide standard gas was less than 1.05 % (95 % of confidence level, k=2).

• Analytical Science and Technology
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• v.27 no.6
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• pp.357-363
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• 2014

Isoprene is a one of the biogenic volatile organic compounds (BVOCs) and it is known as a source of the tropospheric ozone and formaldehyde. In addition, isoprene is a trace component of the exhaled breath and it is a potential biomarker for the diagnosis of diseases such as lung cancer. In these regards, isoprene gas standards are required for the accurate measurement of isoprene in air samples. To establish a standard for isoprene gas, gravimetric preparation and characterization of primary gas standards were studied. The primary gas standards were produced independently in 4 aluminum cylinders and concentrations were examined by GC-FID. As a result, the uncertainty of the gravimetric preparations including purity of the raw material was 0.01% and reproducibility of the preparation of independent 4 cylinders was 0.08%. The primary gas standards for isoprene showed 14 months of long-term stability. The relative expended uncertainty of 2.8% (95% of confidence level, k=1.96) was assigned to the certified value of 10 ${\mu}mol$/mol level of isoprene based on the quantitative evaluation of the purity, weighing, reproducibility, adsorption and long-term stability.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.132-139
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• 2007

The Moderate Resolution Imaging Spectroradiometer (MODIS) regularly provides the eight-day gross primary productivity (GPP) at 1 km resolution. In this study, we evaluated the uncertainties of MODIS GPP caused by errors associated with the Data Assimilation Office (DAO) meteorology and a biophysical variable (fraction of absorbed photosynthetically active radiation, FPAR). In order to recalculate the improved GPP estimate, we employed ground weather station data and reconstructed cloud-free FPAR. The official MODIS GPP was evaluated as +17% higher than the improved GPP. The error associated with DAO meteorology was identified as the primary and the error from the cloud-contaminated FPAR as the secondary constituent in the integrative uncertainty. Among various biome types, the highest relative error of the official MODIS GPP to the improved GPP was found in the mixed forest biome with RE of 20% and the smallest errors were shown in crop land cover at 11%. Our results indicated that the uncertainty embedded in the official MODIS GPP product was considerable, indicating that the MODIS GPP needs to be reconstructed with the improved input data of daily surface meteorology and cloud-free FPAR in order to accurately monitor vegetation productivity in Korea.