• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.225-228
• /
• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.

• Korean Management Science Review
• /
• v.29 no.3
• /
• pp.67-80
• /
• 2012

This study analyzes the relationship among environment uncertainty, local infrastructure, flexible-open firm culture, operations performance and marketing performance focus on SMEs. This research has revealed that the relation among firm size, firm type, firm culture, operations performance and marketing performance as well. The findings show that firm has its culture which is preparing environment uncertainty and local infrastructure influence on forming firm culture. Change-oriented and leaning-oriented firm cultures affect operations performance and marketing performance. In conclusion, this study suggests implication and limitations for further research.

• Nuclear Engineering and Technology
• /
• v.33 no.2
• /
• pp.121-131
• /
• 2001

An investigation of the sensitivity depletion laws for rhodium SPNDs was performed to reduce the uncertainty of the sensitivity depletion laws used in Combustion Engineering (CE) reactors and to develop calculational tools that provide the sensitivity depletion laws to interpret the signal of the newly designed rhodium SPND into the local neutron flux. The calculational tools developed in this work are computer programs for a time-dependent neutron flux distribution in the rhodium emitter during depletion and for a time-dependent beta escape probability that a beta particle generated in the emitter escapes into the collector. These programs provide the sensitivity depletion laws and show the reduction of the uncertainty by about 1 % compared to that of the method employed by CE in interpreting the signal into the local neutron flux. A reduction in the uncertainty by 1 % in interpreting the signal into the local neutron flux reduces the uncertainty tv about 1 % in interpreting the signal into the local power and lengthens the lifetime of the rhodium SPND by about 10% or more.

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

• Korean Journal of Adult Nursing
• /
• v.17 no.5
• /
• pp.743-752
• /
• 2005

Purpose: The purposes of this study were to identify the level of total symptom distress, uncertainty, depression and ways of coping in women with endometriosis based on Mishel's model of Uncertainty in Chronic illness, and to exam the relationships among symptom distress, depression and ways of coping and the mediating effect of ways of coping between uncertainty and depression. Method: The research was used for correlational research design and data were collected with 123 women with endometriosis who live in a local area by convenience sampling. Results: The finding showed that the levels of symptom distress and uncertainty were moderate and the depression was above the middle level. There were positive relationships among symptom distress, uncertainty and depression but a negative relationship between problem focused coping and depression. The significant predictors for depression were symptom distress, uncertainty, and problem focused coping with 40% of explained variance. Problem focused coping showed mediating effect between uncertainty and depression. Conclusion: Therefore, nursing intervention for the strategy of increasing problem focused coping as well as lowering uncertainty and depression is recommended. Further study is needed to conduct a repetitive study with randomized nationwide population and to evaluate the theory with different outcomes for adaptation versus maladaptation.

• Nuclear Engineering and Technology
• /
• v.46 no.3
• /
• pp.353-362
• /
• 2014

The effects of nuclear data uncertainties are studied on a typical PWR fuel assembly model in the framework of the OECD Nuclear Energy Agency UAM (Uncertainty Analysis in Modeling) expert working group. The "Fast Total Monte Carlo" method is applied on a model for the Monte Carlo transport and burnup code SERPENT. Uncertainties on $k_{\infty}$, reaction rates, two-group cross sections, inventory and local pin power density during burnup are obtained, due to transport cross sections for the actinides and fission products, fission yields and thermal scattering data.

• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.20 no.1
• /
• pp.32-38
• /
• 2024

The best estimate plus uncertainty methodologies for loss-of-coolant accident analyses make use of the best-estimate codes and relevant experimental databases. Inherently, best-estimate codes have various uncertainties in the model parameters, which can be quantified by the dedicated experimental database. Therefore, this study was devoted to establishing procedures for identifying the input parameters of predictive models and quantifying their uncertainty ranges. The rod bundle heat transfer experiments were employed as a representative reflood separate effect test, and the TRACE code was utilized as a best-estimate code. In accordance with the present procedure for uncertainty quantification, the integrated list of the influential input parameters and their uncertainty ranges was obtained through local sensitivity calculations and screening criteria. The validity of the procedure was confirmed by applying it to uncertainty analyses, which checks whether the measured data are within computed ranges of the variables of interest. The uncertainty quantification procedure proposed in this study is anticipated to provide comprehensive guidance for the conduct of uncertainty analyses.

• Journal of the Korean Geotechnical Society
• /
• v.28 no.11
• /
• pp.5-16
• /
• 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 paper, the assessment of the local uncertainty of prediction for the depth to weathered soil was performed by using the indicator kriging. A conditional cumulative distribution function (ccdf) was first modeled, and then E-type estimate was computed for the spatial distribution of the depth to the weathered soil. Also, optimal estimate of spatial distribution for the depth to weathered soil was determined by using ccdf and loss function. The design procedure and method considering the minimum expected loss presented in this paper can be used in the decision-making process for geotechnical engineering design.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.155-155
• /
• 2018

Uncertainty in flood forecasting using a coupled meteorological and hydrological model is arisen from various sources, especially the uncertainty comes from the inaccuracy of Quantitative Precipitation Forecasts (QPFs). In order to improve the capability of flood forecast, the uncertainty estimation and mitigation are required to perform. This study is conducted to investigate and reduce such uncertainty. First, ensemble QPFs are generated by using Monte - Carlo simulation, then each ensemble member is forced as input for a hydrological model to obtain ensemble streamflow prediction. Likelihood measures are evaluated to identify feasible member. These members are retained to define upper and lower limits of the uncertainty interval and assess the uncertainty. To mitigate the uncertainty for very short lead time, a blending method, which merges the ensemble QPFs with radar-based rainfall prediction considering both qualitative and quantitative skills, is proposed. Finally, blending bias ratios, which are estimated from previous time step, are used to update the members over total lead time. The proposed method is verified for the two flood events in 2013 and 2016 in the Yeonguol and Soyang watersheds that are located in the Han River basin, South Korea. The uncertainty in flood forecasting using a coupled Local Data Assimilation and Prediction System (LDAPS) and Sejong University Rainfall - Runoff (SURR) model is investigated and then mitigated by blending the generated ensemble LDAPS members with radar-based rainfall prediction that uses McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE). The results show that the uncertainty of flood forecasting using the coupled model increases when the lead time is longer. The mitigation method indicates its effectiveness for mitigating the uncertainty with the increases of the percentage of feasible member (POFM) and the ratio of the number of observations that fall into the uncertainty interval (p-factor).

• Journal of the Society of Naval Architects of Korea
• /
• v.51 no.4
• /
• pp.311-320
• /
• 2014

Test uncertainty of a towed underwater Stereoscopic Particle Image Velocimetry (SPIV) system was assessed in a towing tank. To estimate the systematic error and random error of mean velocity and turbulence properties measurement, velocity field of uniform flow was measured. Total uncertainty of the axial component of mean velocity was 1.45% of the uniform flow speed and total uncertainty of turbulence properties was 3.03%. Besides, variation of particle displacement was applied to identify the change of error distribution. In results for variation of particle displacement, the error rapidly increases with particle movement under one pixel. In addition, a nominal wake of a model ship was measured and compared with existing experimental data by five-hole Pitot tubes, Pitot-static tube, and hot wire anemometer. For mean velocity, small local vortex was identified with high spatial resolution of SPIV, but has serious disagreement in local maxima of turbulence properties due to limited sampling rate.