• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2690-2692
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identifcation. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identifcation are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identify the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.492-492
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• 2005

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.783-784
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• 2010

• Korean Journal of Food Science and Technology
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• v.49 no.6
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• pp.591-598
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• 2017

This study aimed to evaluate the measurement uncertainty for the quantitative determination of chlorite and chlorate in ready-to-eat fresh-cut vegetables using ion chromatography with a hydroxide-selective column. One gram of the homogenized sample in deionized water was sonicated and centrifuged at 8,500 rpm. The supernatant was purified by passing it through a Sep-Pak tC18 cartridge, followed by chromatographic determination using a Dionex IonPac AS27 column. The linearity of the calibration curves, recovery, repeatability, and reproducibility of the method were satisfactory. The method detection limit was estimated to be approximately 0.5 mg/kg. Each uncertainty component was evaluated separately, and the combined and expanded uncertainty values were calculated at the 95% confidence level. The measured concentrations for 3 mg/kg of chlorite and chlorate standard materials were $3.18{\pm}0.32$ and $3.10{\pm}0.42mg/kg$, respectively. These results confirmed the reliability of the developed method for measuring the two chlorine-based oxyanions in fresh-cut vegetables.

• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.89-94
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• 2011

In this study, we measured the wind data as new and renewable energy resources and carried out the evaluation of uncertainty about these data with the authentic standards. These data collected at the 20 locations in korea. We carried out the processing and evaluation about these data with standards as ISO, GUM, and IEC. Whereby these data become standards data and the credibility are gained. These data include some information as direction, humidity, pressure, temperature, and energy density. The annual average of wind speed(in Hamo) was measured as 9.5m/s, then the uncertainty was evaluated as ${\pm}0.88m/s$. We judge the credibility of data by expression of reliability quantitatively. In additional, the standards data is able to approach anywhere and it will be used to support of related research and industry.

• Journal of Environmental Science International
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• v.15 no.4
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• pp.319-324
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• 2006

Release rate is one of the important items for the environmental impact assessment caused by radioactive materials in case of an accidental release from the nuclear facilities. In this study, the uncertainty of the estimated release rate is evaluated using Monte Carlo method. Gaussian plume model and linear programming are used for estimating the release rate of a source material. Tracer experiment is performed at the Yeoung-Kwang nuclear site to understand the dispersion characteristics. The optimized release rate was 1.56 times rather than the released source as a result of the linear programming to minimize the sum of square errors between the observed concentrations of the experiment and the calculated ones using Gaussian plume model. In the mean time, 95% confidence interval of the estimated release rate was from 1.41 to 2.53 times compared with the released rate as a result of the Monte Carlo simulation considering input variations of the Gaussian plume model. We confirm that this kind of the uncertainty evaluation for the source rate can support decision making appropriately in case of the radiological emergencies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.434-437
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• 2003

Evaluation or the patterning accuracy of e-beam lithography machines requires a high precision inspection system that is capable of measuring the true xy-locations of fiducial marks generated by the e-beam machine under test. Fiducial marks are fabricated on a single photo mask over the entire working area in the form of equally spaced two-dimensional grids. In performing the evaluation, the principles of self-calibration enable to determine the deviations of fiducial marks from their nominal xy-locations precisely, not being affected by the motion errors of the inspection system itself. It is. however, the fact that only repeatable motion errors can be eliminated, while random motion errors encountered in probing the locations of fiducial marks are not removed. Even worse, a random error occurring from the measurement of a single mark propagates and affects in determining locations of other marks, which phenomenon in fact limits the ultimate calibration accuracy of e-beam machines. In this paper, we describe an uncertainty analysis that has been made to investigate how random errors affect the final result of self-calibration of e-beam machines when one uses an optical inspection system equipped with high-resolution microscope objectives and a precision xy-stages. The guide of uncertainty analysis recommended by the International Organization for Standardization is faithfully followed along with necessary sensitivity analysis. The uncertainty analysis reveals that among the dominant components of the patterning accuracy of e-beam lithography, the rotationally symmetrical component is most significantly affected by random errors, whose propagation becomes more severe in a cascading manner as the number of fiducial marks increases

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.591-595
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• 2010

Conventional methods of model evaluation usually rely only on model performance based on a comparison of simulated variables to corresponding observations. However, this type of model evaluation has been criticized because of its insufficient consideration of the various uncertainty sources involved in modeling processes. This study aims to propose an extended model evaluation method using multiple assesment indices (MAIs) that consider not only the model performance but also the model structure and parameter uncertainties in rainfall-runoff modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250m, 500m, and 1km digital elevation models) were developed and assessed by three MAIs for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. In addition, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. Numerous parameter sets could lead to indistinguishable hydrographs. This result supports that while making a model complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty. The proposed model evaluation process can provide an effective guideline for identifying a reliable hydrologic model.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.4
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• pp.40-45
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• 2010

Evaluation of uncertainty is an ongoing process that can consume time and resources. It can also require the service of someone who is familiar with data analysis techniques. Therefore, it is important for laboratory personnel who are approaching uncertainty analysis for the first time to be aware of the resources required. International inclination of measurement filed to guarantee the traceability and confidence of measurement results discards the error concept and instead analyzes the measurement uncertainty. In this paper, we analyzed the elements of measurement uncertainty on surface roughness test which are the important things in mechanical parts test. Repeat the test by 3 men, the measurement uncertainty could be calculated.