• Journal of the Korean Magnetic Resonance Society
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• v.24 no.2
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• pp.53-58
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• 2020

Free radicals including reactive oxygen species (ROS) are important chemicals in the research area of biology, pharmaceutical, medical, and environmental science as well as human health risk assessment as they are highly involved in diverse metabolism and toxicity mechanisms through chemical reactions with various components of living bodies. Electron spin resonance (ESR) spectroscopy is a powerful tool for detecting and quantifying those radicals in biological environments. In this work we observed the ESR signal of 2,2,6,6-Tetra-methyl piperidine 1-oxyl (TEMPO) in aqueous solution at various concentrations to estimate the uncertainty factors arising from the experimental conditions and signal treatment methods. As the sample position highly influences the signal intensity, dual ESR tube geometry (consists of a detachable sample tube and a position fixed external tube) was adopted. This type of measurement geometry allowed to get the relative uncertainty of signal intensity lower than 1% when triple measurements are averaged. Linear dependence of signal intensity on the TEMPO concentration, which is required for the quantification of unknown sample, could be obtained over a concentration range of ~10³ by optimizing the signal treatment method depending on the concentration range.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2019.05a
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• pp.157-158
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• 2019

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.860-865
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• 2021

A data-based model, such as an AAKR model is widely used for monitoring the drifts of sensors in nuclear power plants. However, since a training dataset and a test dataset for a data-based model cannot be constructed with the data from all the possible states, the model uncertainty cannot be good enough to represent the uncertainty of estimations. In fact, the errors of estimation grow much bigger if the incoming data come from inexperienced states. To overcome this limitation of the model uncertainty, a new measure of uncertainty for a data-based model is developed and the predicted uncertainty is introduced. The predicted uncertainty is defined in every estimation according to the incoming data. In this paper, the AAKR model is used as a data-based model. The predicted uncertainty is similar in magnitude to the model uncertainty when the estimation is made for the incoming data from the experienced states but it goes bigger otherwise. The characteristics of the predicted model uncertainty are studied and the usefulness is demonstrated with the pressure signals measured in the flow-loop system. It is expected that the predicted uncertainty can quite reduce the false alarm by using the variable threshold instead of the fixed threshold.

• Architectural research
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• v.8 no.1
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• pp.37-45
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• 2006

A fungal spore transportation model that accounts for the concentration of airborne indoor spores and the amount of spores deposited on interior surfaces has been developed by extending the current aerosol model. This model is intended to be used for a building with a mechanical ventilation system, and considers HVAC filter efficiency and ventilation rate. The model also includes a surface-cleaning efficiency and frequency that removes a portion of spores deposited on surfaces. The developed model predicts indoor fungal spore concentration and provides an indoor/outdoor ratio that may increase or decrease mold growth risks in real, in-use building cases. To get a more useful outcome from the model simulation, an uncertainty analysis has been conducted in a real building case. By including uncertainties associated with the parameters in the spore transportation model, the simulation results provide probable ranges of indoor concentration and indoor/outdoor ratio. This paper describes the uncertainty quantification of each parameter that is specific to fungal spores, and uncertainty propagation using an appropriate statistical technique. The outcome of the uncertainty analysis showed an agreement with the results from the field measurement with air sampling in a real building.

• Geomechanics and Engineering
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• v.12 no.6
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• pp.871-882
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• 2017

Indirect measure of the tensile strength of laboratory samples is an important topic in rock engineering. One of the most important tests, the Brazilian strength test is performed to obtain the tensile strength of rock, concrete and other quasi brittle materials. Because the measurements are provided indirectly and the inspected rock materials may have heterogeneous properties, uncertainty quantification is required for a reliable test evaluation. In addition to the conventional measurement evaluation uncertainty methods recommended by the Guide to the Expression of Uncertainty in Measurement (GUM), such as Taylor's and Monte Carlo Methods, a fuzzy set-based approach is also proposed and resulting uncertainties are discussed. The results showed that when a tensile strength measurement is measured by a laboratory test, its uncertainty can also be expressed by one of the methods presented.

• Journal of the Korea Convergence Society
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• v.4 no.2
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• pp.35-41
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• 2013

Data management with fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem. Calculation of certainty or uncertainty for data, fuzzy entropy and similarity measure are designed and proved. Proposed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration.Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.275-280
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• 2010

Verification of efficiency in data management fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem and numerical data similarity evaluation. In order to calculate the certainty or uncertainty fuzzy entropy and similarity measure are designed and proved. Designed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration. Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• Korean Journal of Food Science and Technology
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• v.53 no.6
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• pp.682-687
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• 2021

The purpose of this study was to validate a high-performance liquid chromatography (HPLC) method for the quantitative analysis of quercetin in various foods. The method was based on HPLC-UV (360 nm). The method was validated using candy, beverage, and sausage which were tested for specificity, linearity, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy, and the measurement uncertainty was assessed. Matrix-matched calibration was also applied. The calibration curves (0.5-50 mg/L) showed good linearity (r²≥0.9998). LOD and LOQ ranged from 0.15 to 0.31 mg/kg and from 0.44 to 0.93 mg/kg, respectively. The average accuracy and precision at 0.5, 2.5, and 10 mg/kg ranged from 84.3 to 102.0% and 0.7 to 3.0 relative standard deviation (RSD%), respectively. This study confirmed the applicability of the proposed method by applying it to commercial products, such as teas and beverages. Thus, the proposed analytical method is suitable for quantifying quercetin in various foods.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.5
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• pp.73-80
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• 2018

At the early stages of development of high-speed propulsion systems, associated uncertainties cannot be easily modeled into probabilistic distributions, owing to the lack of test data, cost, and difficulty of simulating real-flight environments on the ground. To tackle this issue, in this research, the combustion efficiencies of dual-combustion ramjet engines are assumed to have been provided by experts and quantified by evidence theory. Using quantified uncertainty, the inlet area and combustor exit are optimized while satisfying reliability margins of thrust and thermal choking. The result shows a reasonable design of the engine under uncertain circumstances.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.503-516
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• 2011

Uncertainty in concrete properties, including concrete modulus of elasticity and modulus of rupture, are predicted by developing a microstructural homogenization model. The homogenization model is developed by analyzing a concrete representative volume element (RVE) using the finite element (FE) method. The concrete RVE considers concrete as a three phase composite material including: cement paste, aggregate and interfacial transition zone (ITZ). The homogenization model allows for considering two sources of variability in concrete, randomly dispersed aggregates in the concrete matrix and uncertain mechanical properties of composite phases of concrete. Using the proposed homogenization technique, the uncertainty in concrete modulus of elasticity and modulus of rupture (described by numerical cumulative probability density function) are determined. Deflection uncertainty of reinforced concrete (RC) beams, propagated from uncertainties in concrete properties, is quantified using Monte Carlo (MC) simulation. Cracked plane frame analysis is used to account for tension stiffening in concrete. Concrete homogenization enables a unique opportunity to bridge the gap between concrete materials and structural modeling, which is necessary for realistic serviceability prediction.