• Journal of Korean Society on Water Environment
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• v.36 no.4
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• pp.300-313
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• 2020

The Bayesian approach can be used to estimate hydrologic model parameters from the prior expert knowledge about the parameter values and the observed data. The purpose of this study was to compare the performance of the two Bayesian methods, the Metropolis-Hastings (MH) algorithm and the Generalized Likelihood Uncertainty Estimation (GLUE) method. These two methods were applied to the TANK model, a hydrological model comprising 13 parameters, to examine the uncertainty of the parameters of the model. The TANK model comprises a combination of multiple reservoir-type virtual vessels with orifice-type outlets and implements a common major hydrological process using the runoff calculations that convert the rainfall to the flow. As a result of the application to the Nam River A watershed, the two Bayesian methods yielded similar flow simulation results even though the parameter estimates obtained by the two methods were of somewhat different values. Both methods ensure the model's prediction accuracy even when the observed flow data available for parameter estimation is limited. However, the prediction accuracy of the model using the MH algorithm yielded slightly better results than that of the GLUE method. The flow duration curve calculated using the limited observed flow data showed that the marginal reliability is secured from the perspective of practical application.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.168-180
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• 2013

Based on the strategic contingency theory, this study empirically examines Korean TV drama producers' changing adaptive behaviors in terms of genre variety given different levels of environmental uncertainty. The extant literature has suggested that firms tend to increase product variety in order to cope with increasing environmental uncertainty. This study attempted to verify the hypothesis that TV drama producers would employ wider variety of genre in the period with more uncertain environment(2003-2009) than the period with stable environment(1994-2002). Empirical results support the hypothesis, implying that TV drama producers tend to repeatedly produce dramas with the same genre in order to pursue efficiency in stable environment whereas they tend to employ a variety of different genre in order to cope with increasing environmental uncertainty.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.47-53
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• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

• Atmosphere
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• v.25 no.1
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• pp.1-18
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• 2015

The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

• Journal of the Korean GEO-environmental Society
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• v.13 no.4
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• pp.93-104
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• 2012

Efforts to understand and develop reasonable analysis methods for the uncertainty of ground have been made since the 20th century, and the concept of safety factor has been used. However, this concept has limitation in measuring the relative reliability of ground structures because the representative values of the actually used factors have uncertainty. Nevertheless, there is no method to completely remove uncertainty. In most cases, the ground investigation results in Korea are not enough for applying such statistical methods. Furthermore, performing a design without accurate investigation of consolidation state even though consolidation characteristics such as settlement and consolidation velocity vary greatly by the consolidation history can lead to many problems. Therefore, in this paper, as part of the effort to reduce the uncertainty of design around over consolidation ratio among the consolidation factors, the consolidation state was assessed on the basis of the results of high-quality laboratory tests that were performed in Gwangyang and Busan in the southern coast of Korea. Furthermore, consolidation characteristics such as over consolidation ratio by depth were proposed for different regions through statistical processes such as the test of normality and the removal of abnormal values to reduce the uncertainty of design parameters.

• Korean Journal of Environmental Agriculture
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• v.35 no.3
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• pp.223-233
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• 2016

BACKGROUND: This study was to develop a analytical reference material including twenty pesticides in tomato. To use it for proficiency test, the suitability of homogeneity, storage stability, assigned values and uncertainty for analytical reference material were important.METHODS AND RESULTS: In order to develop a analytical reference material of tomato for multi-residue analysis of pesticides, twenty-pesticides were treated in tomato and the samples were frozen and homogenized. The homogeneity, stability, assigned value and uncertainty were calculated according to the requirements of the KS A ISO Guide 35, KS Q ISO 13528 and EURL-PT protocol. The values of the within-bottle standard variation(s_wb) and the between-bottle standard variation(s_bb) were 0.9~6.5% of assigned value and the uncertainty(u*_bb) due to inhomogeneity was also calculated as 0.6~1.9% for all pesticides. This indicated that it was satisfactory to be used as a analytical reference material. The storage stabilities of twenty-pesticides at room temperature and freezing conditions were assessed according to the requirement of the KS Q ISO Guide 35. All pesticides were stable at room temperature (20~30℃) for 8 days and freezing (-20℃) for 23 days.CONCLUSION: The feasibility of analytical reference material for pesticide multi-residue analysis in a tomato matrix was investigated. Homogeneity of within/between-bottle, uncertainty and stabilities at room temperature and freezing condition were satisfactory for a use of proficiency test and quality control. From these results, a analytical reference material would be applicable to monitor the proficiency test of pesticide analysis organizations to improve the reliability and consistency.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.3
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• pp.535-546
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• 2000

Juam lake is a major water resource for the industrial and agricultural activities as well as the resident life of Kwangju and Chonnam area. However, the water quality of the lake is getting worse due to a large quantity of pollutant inflowing to the lake. As a preliminary step in making the countermeasure to achieve the water quality goal of the lake. it is necessary to understand how the water quality of the lake will be in future. Several computer programs can be used to predict the water quality of lake. Each of these programs requires a number of input data such as hydrological and meteorological data. and the quantity of the pollutant inflowed. but some or most of the input data contain uncertainty. which eventually results in the uncertainty of prediction value (future level of water quality). Generally. the uncetainty stems from the lack of information available. the randomness of future situation. and the incomplete knowledge of expert. Thus. the purpose of this study is to present a method for representing the degree of the uncertainty contained in input data by applying fuzzy theory and incorporating it directly into the water quality modeling process. By using the method. the prediction on the future water quality level of Juam lake can be made that is more appropriate and realistic than the one made without taking uncertainty in account.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.107-113
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• 2015

This study analyzed the effect of the factors of introducing information technology(organizational and environmental characteristics) on non-financial performance. As detailed variables of each characteristic, the technical support/task force, users' IT capability, and education/training were used for the organizational characteristics while the degree of competition, external pressure, and uncertainty of environment were used for the environmental characteristics. In the results of the analysis, such factors like technical support/task force, users' IT capability, and education/training of the organizational characteristics had significant influence on non-financial performance. Also, factors such as degree of competition, external pressure, and uncertainty of environment of the environmental characteristics had significant influence on non-financial performance.

• Journal of Soil and Groundwater Environment
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• v.18 no.5
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• pp.15-25
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• 2013

In this study, two kinds of soil-based proficiency testing materials (PTMs), NICE-012L and NICE-012R were prepared and certified for Benzen, Toluene, Etylbenzene and Xylene with evaluation of uncertainties. In order to analyse BTEX (Benzen Toluene Etylbenzene Xylene) for the candidate materials, GC/MS was used after pretreatment according to methods of soil analysis by Ministry of Environment. For the homogeneity test among bottles in terms of candidate materials, ISO 13528 and IUPAC Protocol were used and according to the result, both candidate materials showed sufficient homogeneity. Also, the stability test over the candidate materials was accessed according to the ISO Guide 35 by classifying short-term and long-term stability and the result showed that both candidate materials showed decent stability. The reference values of the two candidate materials depending on BTEX components were derived from the average of the 11 samples that were used for verification of the samples' homogeneity. Uncertainty of measurement was combined by uchar that was caused by a characteristic value, $u_{bb}$ that was caused by between-bottle homogeneity, and $u_{stab}$ that was caused by stability, and then combined uncertainty ($u_{PTM}$) was multiplied to the coverage factor (k) derived from the effective degree of freedom from each factor that leads to expanded uncertainty (U) in about 95% of confidence level. The proficiency testing materials developed through this study were supplied to National Institute of Environmental Research (NIER) and utilized as an external proficiency testing materials for evaluating analysis capacity of soil agencies with specialty in terms of soil analysis approved by Minister of Environment.

• Journal of Climate Change Research
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• v.5 no.3
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• pp.199-208
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• 2014

According to "IPCC guide line for national greenhouse gas inventories" each country should develop the 'Country-specific emission factor' and apply it to estimate greenhouse gases emissions from landfill. It could reflect properties of country and make estimation more accurate. For that accuracy, developed country-specific emission factor should be assessed and be verified consistently. Developed emission factors should be assessed in terms of Representative, Emission Property, Accuracy and Uncertainty, but there is no study about weighted assessment factors under each emission variable. This study do survey targeting public officials, professors and other experts for Analytical Hierarchy Process(AHP), mostly use to make decisions, to weight assessment factors. We investigated the weighted values per Emission factor for Representative, Emission property, Accuracy and Uncertainty on AHP survey, and Representative factor was the highest, and then in the order of Emission property (0.26), Accuracy(0.22), Uncertainty (0.15).