• International Commerce and Information Review
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• v.12 no.3
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• pp.311-332
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• 2010

This study investigate the effects of environmental and organizational characteristics on e-business competence and the influence of e-business competence on export performance in the small and medium sized firms. The development of the research model is based on the literature of e-business and the empirical studies of information technology competence. The data from the survey was analyzed using Partial Least Squares(PLS). The results from the empirical model suggest that e-business competence is affected by environmental uncertainty and market diversity as well as top management support and learning orientation. And, export performance is enhanced by e-business competence.

• Journal of Environmental Impact Assessment
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• v.15 no.1
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• pp.35-43
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• 2006

The eutrophication in lakes is caused by the inflow of excessive nitrogen and phosphorus, which are not only pollutants to reduce the value of water resource but also nutrients for algae growth that debases water quality. Several methods have been used to judge the eutrophication grades of lakes, but the judgment results can be different with one another even under same coditions because each method is different in judgment items and their standards. A method for overcoming the problem with the judgment of eutrophication grades is, therefore, developed in this study with the application of fuzzy theory. This method allows decision makers to represent the uncertainties (differences) of results by the existing judgment methods and also incorporate associated uncertainties directly into the judgment process, so the judgment results can be made that are more realistic and consistent than those made without taking uncertainty in account.

• Journal of the Korean Geotechnical Society
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• v.28 no.1
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• pp.17-27
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• 2012

Since geologic data are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations but also to assess the uncertainty attached to the prediction. In this study the assessment of the local uncertainty of prediction for the thickness of the consolidation layer was performed by using the indicator approach. A conditional cumulative distribution function (ccdf) was first modeled, and then E-type estimates and the conditional variance were computed for the spatial distribution of the thickness of the consolidation layer. These results could be used to estimate the spatial distribution of secondary compression and to assess the local uncertainty of secondary compression for Songdo New City.

• Journal of Environmental Health Sciences
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• v.37 no.1
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• pp.1-11
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• 2011

Recent advances in Geographic Information Systems and spatial statistical and analytical methods, along with the availability of spatially referenced health and environmental data, have created unique opportunities to investigate spatial associations between environment exposures and health outcomes at multiple spatial scales and resolutions. However, the increased use of spatial data also faces challenges, one of which is to ensure certainty and accuracy of locational data that meets the needs of a study. This article critically reviews the use of spatially referenced data in epidemiologic studies, focusing on the issue of locational uncertainty generated from the process of geocoding health and environmental data. Primarily, major issues involving the use of spatially referenced data are addressed, including completeness and positional accuracy, potential source of bias and exposure misclassification, and implications for epidemiologic studies. The need for critical assessment and caution in designing and conducting spatial epidemiology studies is briefly discussed.

• Journal of Environmental Health Sciences
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• v.46 no.2
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• pp.136-149
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• 2020

Objectives: The purpose of this study was to perform an aggregate human risk assessment for benzene in an industrial complex using the CalTOX model and to improve the reliability and predictability of the model by analyzing the uncertainty and sensitivity of the predicted assessment results. Methods: The CalTOX^TM 4.0 beta model was used to evaluate a selected region, and @Risk 7.6 software was used to analyze uncertainty and sensitivity. Results: As a result of performing the aggregate risk assessment on the assumption that 6.45E+04 g/d of benzene would be emitted into the atmosphere over two decades, 3% of the daily source term to air remained in the selected region, and 97% (6.26E+04 g/d) moved out of the region. As for exposure by breathing, the predicted LADD_inhalation was 2.14E-04 mg/kg-d, and that was assessed as making a 99.99% contribution to the LADD_total. Regarding human Risk_cancer assessment, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was identified as the most influential variable, followed by 'exposure time, active indoors (h/day)', and 'exposure duration (years)'. Conclusions: As for the results of the human cancer risk assessment for the selected region, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile, corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was found to be most influential.

• Korean Journal of Environmental Agriculture
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• v.30 no.2
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• pp.169-178
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• 2011

BACKGROUND: This study aimed to estimate the measurement uncertainty associated with determination of cadmium and lead from tomato paste by ICP/MS. The sources of measurement uncertainty (i.e. sample weight, final volume, standard weight, purity, molecular weight, working standard solution, calibration curve, recovery and repeatability) in associated with the analysis of cadmium and lead were evaluated. METHODS AND RESULTS: The guide to the expression of uncertainty was used for the GUM (Guide to the expression of Uncertainty in Measurement) and Draft EURACHEM/CITAC (EURACHEM: A network of organization for analytical chemistry in Europe/Co-Operation on International Traceability in Analytical Chemistry) Guide with mathematical calculation and statistical analysis. The uncertainty components were evaluated by either Type A or Type B methods and the combined standard uncertainty were calculated by statistical analysis using several factors. Expected uncertainty of cadmium and lead was $0.106{\pm}0.015$ mg/kg (k=2.09) and $0.302{\pm}0.029$ mg/kg (k=2.16), on basis of 95% confidence of Certified Reference Material (CRM) which was within certification range of $0.112{\pm}0.007$ mg/kg for cadmium (k=2.03) and $0.316{\pm}0.021$ mg/kg for lead (k=2.01), respectively. CONCLUSION(s): The most influential components in the uncertainty of heavy metals analysis were confirmed as recovery, standard calibration curve and standard solution were identified as the most influential components causing uncertainty of heavy metal analysis. Therefore, more careful consideration is required in these steps to reduce uncertainty of heavy metals analysis in tomato paste.

• Analytical Science and Technology
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• v.16 no.3
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• pp.185-190
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• 2003

We applied modified least square method (MLS) and ordinary least square method (OLS) to 1st order equation for the comparison of the uncertainties calculated by these methods. The uncertainty calculated by OLS covered statistically safe interval because it was over-estimated in many cases of measurement and concentration level. But, if the uncertainty of the concentration as a reference value was comparably large (about 5% of the relative standard deviation of random scattering from the regression line and about 7% of relative standard uncertainty of reference values), then uncertainty calculated by OLS was seriously under-estimated at high concentration level. It was revealed that the calculated uncertainty didn't cover statistically safe interval at the stated confidence level. It was found that the method, MLS, described in the previously article would be valid for this calculation of uncertainty.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.285-292
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• 2024

When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.355-361
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• 2023

Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.

• Environmental and Resource Economics Review
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• v.29 no.2
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• pp.145-170
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• 2020

This study analyzes the dependence structure between energy (crude oil, natural gas, coal) prices and economic (real and financial) uncertainty. Summary of the results of the dependence structure between energy prices and economic uncertainty analysis is as follows. First, the results of model selection show that the BB7 copula model for the pair of crude oil price and economic uncertainty, the Joe copula model for the pair of natural gas price and economic uncertainty, and the Clayton copula model for the pair of coal price and economic uncertainty were chosen. Second, looking at the dependency structure, it showed that the pair of energy (crude oil, natural gas, coal) prices and real market uncertainty show positive dependence. Whereas, the only pair of financial market uncertainty-crude oil price shows positive dependency. In particular, crude oil price was found to have the greatest dependence on economic uncertainty. Third, looking at the results of tail dependency, the pair of real market uncertainty-crude oil price and pair of real market uncertainty-natural gas price have an asymmetric relationship with the upper tail dependency. It can be seen that the only pair of financial market uncertainty-crude oil represents asymmetric relationships with the upper tail dependencies. In other words, combinations with asymmetric relationships have shown strong dependence when negative extreme events occur. On the other hand, tail dependence between economic uncertainty and coal price be not found.