• Analytical Science and Technology
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• v.24 no.1
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• pp.1-9
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• 2011

We described an estimation of measurement uncertainty in quantitative analysis of 11-nor-9-carboxy-${\Delta}^9$-tetrahydrocannabinol (THC-COOH), the metabolite of ${\Delta}^9$-tetrahydrocannabinol, in hair samples by using the bead-assisted liquid-liquid extraction and gas chromatography-tandem mass spectrometric (GC-NCI-MS/MS) detection. Traceability of measurement was established through the use of reference materials, calibrated volumetric tubes, volume measuring devices, and measuring instruments. The analytical results were compared and the different contributions to the uncertainty were evaluated. Inter-day variation was performed by using statistical analysis of several indicative factors. Measurement uncertainty associated with the analyte in real forensic hair samples were estimated using QC data. The major factor of contribution to combined standard uncertainty was inter-day repeatability, while those associated with preparation of analytical standard and also sample of weight were insignificant considering the degree of contribution. Relative uncertainty of relative extended standard uncertainty divided into the measured concentration of the analyte was 17% in a hair sample. The uncertainty of result evaluation will be invaluable to improve quality of the analysis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1365-1372
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• 2012

This paper presents a methodology to accurately evaluate the spectral components of impulse signals which are delivered from an impulse generator through the measurement system. The complicated terms for uncertainty measurement of impulse spectrum amplitude and their analysis methods and experimental results are discussed. The expanded uncertainty of the impulse spectrum measurement is 0.015, which is believed to be the best domestic measurement capability and comparable to those of world class.

• Fire Science and Engineering
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• v.27 no.2
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• pp.75-79
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• 2013

The present study measured the light transmission to quantify the smoke density(smoke mass concentration) through the doorway in a compartment fire and performed the uncertainty analysis to evaluate the reliability of the measurement technique. The optical light extinction method based on Bourguer's law was applied to estimate the smoke density of doorway exhausting smoke flow in upper layer of a compartment for methane gas fires. The measurement uncertainty of the light extinction measurement was evaluated for the light transmittance, path length, and specific mass extinction coefficient and the expanded uncertainty was estimated about 20% with confidence level of 95%. The mean smoke density through the doorway for the methane fire was calculated for quasi-steady fire and the smoke density linearly increased as the GER increased.

• Bulletin of the Korean Chemical Society
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• v.22 no.3
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• pp.251-252
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• 2001

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.346-354
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• 2020

Nowadays, it is required to apply low observable technology to weapon systems in operation or under development. Radar Cross Section(RCS) is a measure of the scattered power in an given direction when a target is illuminated by an incident wave and used as a parameter to estimate the low observable performance of weapon system. RCS of a target can be calculated by various numerical methods. However, measurement is also needed to estimate RCS of a complex target because it is difficult to estimate theoretically. To acquire reliable measurement results, an analysis of measurement uncertainty is essential. In this paper, error components and uncertainties of near-field RCS measurement system which was constructed in ASTEC(Aerospace System Test & Evaluation Center) were analyzed based on the IEEE recommended practice for radar cross-section test procedures(IEEE Std. 1502-2007) which describes the uncertainty of RCS measurement and unique error components of this near-field measurement system were also identified.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.713-723
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• 2019

Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.10 s.241
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• pp.1130-1138
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• 2005

A national standard system for the petroleum field has been developed to calibrate and test the oil flow meters in Korea. The operating system and the uncertainty of the system were evaluated by the peer reviewers of foreign national metrology institutes in 2002. Since the characteristics of the system might be changed by time, the uncertainty of the system is reevaluated with the consideration of the long term stability of the system. It is found that the system has a relative expanded uncertainty of 0.048 $\%$ in the range of $15\~120\;m^3/h$. According to the uncertainty budget, the uncertainties of the fluid density and the final mass measurement, which are temperature dependent, contribute about $94\%$ of the total uncertainty in the oil flow standard system

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.521-535
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• 2017

Acoustic Doppler Current Profilers (ADCPs) have been widely utilized for assessing streamflow discharge, yet few comprehensive studies were conducted to evaluate discharge uncertainty in consideration of individual uncertainty components. It could be mostly because it was not easy to determine which uncertainty framework can be appropriate to rigorously analyze streamflow discharge driven by ADCPs. In this regard, considerable efforts have been made by scientific and engineering societies to develop a standardized theoretical framework for uncertainty analysis in hydrometry. One of the well-established UA methodology based on sound statistical and engineering concepts is Guide to the Expression of Uncertainty Measurement (GUM) adopted widely by various scientific and research communities. This research fundamentally adapted the GUM framework to assess individual uncertainty components of ADCP discharge measurements, and subsequently provided results of a customized experiment in a controllable real-scale artificial river channel. We focused particularly upon sensitivities of uncertainty components in the GUM framework driven by ADCPs direct measurements such as depths, edge distance, submerged depth, velocity gap, sampling time, repeatability, bed roughness and so on. Section-by-Section method for ADCP discharge measurement was applied for uncertainty analysis for this study. All of measurements were carefully compared with data using other instrumentations such as ADV to evaluate individual uncertainty components.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.331-343
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• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Journal of Korean Society on Water Environment
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• v.29 no.5
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• pp.681-690
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• 2013

Watershed models have been increasingly used to support an integrated management of land and water, non-point source pollutants, and implement total daily maximum load policy. However, these models demand a great amount of input data, process parameters, a proper calibration, and sometimes result in significant uncertainty in the simulation results. For this reason, uncertainty analysis is necessary to minimize the risk in the use of the models for an important decision making. The objectives of this study were to evaluate three different uncertainty analysis algorithms (SUFI-2: Sequential Uncertainty Fitting-Ver.2, GLUE: Generalized Likelihood Uncertainty Estimation, ParaSol: Parameter Solution) that used to analyze the sensitivity of the SWAT(Soil and Water Assessment Tool) parameters and auto-calibration in a watershed, evaluate the uncertainties on the simulations of runoff and sediment load, and suggest alternatives to reduce the uncertainty. The results confirmed that the parameters which are most sensitive to runoff and sediment simulations were consistent in three algorithms although the order of importance is slightly different. In addition, there was no significant difference in the performance of auto-calibration results for runoff simulations. On the other hand, sediment calibration results showed less modeling efficiency compared to runoff simulations, which is probably due to the lack of measurement data. It is obvious that the parameter uncertainty in the sediment simulation is much grater than that in the runoff simulation. To decrease the uncertainty of SWAT simulations, it is recommended to estimate feasible ranges of model parameters, and obtain sufficient and reliable measurement data for the study site.