• 한국환경농학회지
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• 제39권3호
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• pp.237-245
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• 2020

BACKGROUND: The closed chamber method is the most commonly used for measuring greenhouse gas emissions from upland fields. This method has the advantages of being simple, easily available and economical. However, uncertainty estimation is essential for accurate assessment of greenhouse gas emissions and verification of emission reductions. The nitrous oxide emissions from upland field is very important for the nitrogen budget in the agriculture sectors. Although assessment of uncertainty components affecting nitrous oxide emission from upland field is necessary to take account of dispersion characteristics, research on these uncertainty components is very rare to date. This study aims at elucidation of influencing factors on measurement uncertainty of nitrous oxide concentrations measured by an automated open closed chamber method from upland field. METHODS AND RESULTS: The nitrous oxide sampling system is located in the upland field in Gyeonggi-do Agricultural Research and Extension Services (37°13'22"N, 127°02'22"E). The primary measurement uncertainty components influencing nitrous oxide concentrations (influencing factors) investigated in this research are repeatability, reproducibility and calibration in the aspects of nitrous oxide sampling and analytical instrumentation. The magnitudes of the relative standard uncertainty of each influencing factor are quantified and compared. CONCLUSION: Results of this study show what influencing factors are more important in determination of nitrous oxide concentrations measured using the automated open closed chambers located in the monitoring site. Quantifying the measurement uncertainty of the nitrous oxide concentrations in this study would contribute to improving measurement quality of nitrous oxide fluxes.

• 한국정밀공학회지
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• 제21권12호
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• pp.109-118
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• 2004

Life cycle assessment (LCA) usually involves some uncertainty. These uncertainties are generally divided in two categories such lack of data and data inaccuracy in life cycle inventory (LCI). This paper explo.es a methodology on dealing with uncertainty due to lack of data in LCI. In order to treat uncertainty of LCI data, a model for data uncertainty is proposed. The model works with probabilistic curves as inputs and with Monte Carlo Simulation techniques to propagate uncertainty. The probabilistic curves were derived from the results of survey in expert network and Monte Carlo Simulation was performed using the derived probabilistic curves. The results of Monte Carlo Simulation were verified by statistical test. The proposed approach should serve as a guide to improve data quality and deal with uncertainty of LCI data in LCA projects.

• 기본간호학회지
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• 제14권2호
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• pp.213-220
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• 2007

Purpose: This study was conducted to investigate uncertainty, anxiety and nursing needs in mothers of hospitalized children. Method: Self report questionnaires were used to measure the variables. Variables were uncertainty, anxiety and nursing needs. In data analysis, SPSSWIN 12.0 program was utilized for descriptive statistics, Pearson's correlation coefficients, and regression analysis. Results: Cronbach's alphas of .84 to .97 indicate reliability of the instruments. Uncertainty positively correlated with anxiety (r=.624, p<.001) and nursing needs (r=.147, p<.05), and anxiety positively correlated with nursing needs (r=.262, p<.01). In regression analysis of anxiety, uncertainty, nursing assessment of nursing needs and duration of hospitalization were significant predictors, explaining 45.1% of variance. Conclusion: Uncertainty was a significant predictor of anxiety in mothers whose children were hospitalized. Therefore, nursing interventions which decrease uncertainty must be developed for these mothers.

• 산업경영시스템학회지
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• 제23권54호
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• pp.167-177
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• 2000

The problem of system reliability is very important issue in the nuclear power plant, because the failure of its system brings about extravagant economic loss, environment destruction, and quality loss. This paper therefore proposes a normalized scoring model by the qualitative factors order to evaluate the robust reliability of nuclear power plants under uncertainty. Especially, the qualitative factors including risk, functional, human error, and quality function factors for the robust justification has been also introduced. Finally, the analytical reliability and safety assessment model developed in this paper can be used in the real nuclear power plant.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.151-151
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• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

• Steel and Composite Structures
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• 제20권6호
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• pp.1345-1368
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• 2016

This paper presents the probabilistic-based assessment of composite steel-concrete structures through an innovative framework. This framework combines model identification and reliability assessment procedures. The paper starts by describing current structural assessment algorithms and the most relevant uncertainty sources. The developed model identification algorithm is then presented. During this procedure, the model parameters are automatically adjusted, so that the numerical results best fit the experimental data. Modelling and measurement errors are respectively incorporated in this algorithm. The reliability assessment procedure aims to assess the structure performance, considering randomness in model parameters. Since monitoring and characterization tests are common measures to control and acquire information about those parameters, a Bayesian inference procedure is incorporated to update the reliability assessment. The framework is then tested with a set of composite steel-concrete beams, which behavior is complex. The experimental tests, as well as the developed numerical model and the obtained results from the proposed framework, are respectively present.

• 한국산업보건학회지
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• 제22권3호
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• pp.175-183
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• 2012

Objectives: This study developed a harmonized method for risk assessment based on the Hazard & Risk Evaluation of Chemicals (HREC) according to the Industrial Safety and Health Act (ISHA). Methods: Three preliminary studies, performed during 2010 and 2011 by the Occupational Safety and Health Research Institute and three academic research groups, were compared. The differences in risk assessment, especially in the dose-response assessment method, were analyzed. A new harmonized method for dose-response assessment was suggested and its applicability for the HREC was examined. Results: Considering the various steps of each dose-response assessment, the equivalent steps in quantitative correction, uncertainty factor 2 (UF2) for intra-species uncertainty, and UF3 for the experimental period in the uncertainty correction were relatively high. Using our new method, the total correction values (quantitative correction plus uncertainty correction) ranged from 72~15,789 to 30~60, and the ratio of the threshold limit value (TLV) to the reference concentration decreased from 12.8~1900 to 5.4~11.8. Furthermore, when we performed risk characterization by our new method, hazard quotient (HQ) values for chloroethylene, epichlorohydrin, and barium sulfate became 3.0, 14.1, and 1.13 respectively, whereas three previous studies reported HQ values of 7.1, 4580, and 87.3 considering reasonable maximum exposure (RME) conditions. HQs of the three chemicals were calculated to be 0.6, 2.4, and 0.1 respectively, when compared to their TLVs. Conclusions: Our new method could be applicable for the HREC because the total correction values and the ratio of TLVs were within reasonable ranges. It is also recommended that additional risk management measures be applied for epichlorohydrin, for which the HQ values were greater than 1 when compared with both reference values and the TLV. Our proposed method could be used to harmonize dose-response assessment methods for the implementation of risk assessment based on the HREC according to ISHA.

• Nuclear Engineering and Technology
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• 제43권2호
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• pp.175-186
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• 2011

Previous evaluations of the safety of the Ulchin Nuclear Power Plant in the event of a tsunami have the shortcoming of uncertainty of the tsunami sources. To address this uncertainty, maximum and minimum wave heights at the intake of Ulchin NPP have been estimated through a parametric study, and then assessment of the safety margin for the intake has been carried out. From the simulation results for the Ulchin NPP site, it can be seen that the coefficient of eddy viscosity considerably affects wave height at the inside of the breakwater. In addition, assessment of the safety margin shows that almost all of the intake water pumps have a safety margin over 2 m, and Ulchin NPP site seems to be safe in the event of a tsunami according to this parametric study, although parts of the CWPs rarely have a margin for the minimum wave height.

• 한국환경과학회지
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• 제20권3호
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• pp.321-327
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• 2011

Bootstrap methods is the computer-based resampling method that estimates the standard errors and confidence intervals of summary statistics using the plug-in principle for assessing the accuracy or uncertainty of statistical estimates, and the BCa method among the Bootstrap methods is known much superior to other Bootstrap methods in respect of the standards of statistical validation. Therefore this study suggests the method of the representation and treatment of uncertainty in flood risk assessment and water resources planning from the construction and application of rainfall frequency analysis model considersing the uncertainty based on the nonparametric BCa method among the Bootstrap methods for the assessement of the estimation of probability rainfall and the effect of uncertainty considering the uncertainty of the parameter estimation of probability in the rainfall frequency analysis that is the most fundamental in flood risk assessement and water resources planning.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2005년도 춘계학술발표회
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• pp.787-788
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• 2005