• Journal of the Korean Geotechnical Society
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• v.27 no.4
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• pp.21-32
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• 2011

A series of in-situ and laboratory tests were performed for the clayey soils of Busan area in order to develop the methods to evaluate the compressibility using CPT and DMT results. The laboratory tests show that the clayey layers of Busan areas are normally consolidated, and their compression indices are turned out to be 0.5~1.3. From the analysis of test results, correlation factors between the cone resistance and constrained modulus (${\alpha}_m$ and ${\alpha}_n$) are observed to decrease with increasing plasticity index, and the correlation factor between the dilatometer modulus and constrained modulus $(R_M)$ increases with $1/I_D$. Based on these relationships, the methods evaluating the constrained modulus from CPT and DMT results are suggested. It is shown that the prediction method by CPT underestimates the constrained modulus of improved ground, whereas the prediction method by DMT is suitable for evaluating the constrained modulus of improved and unimproved ground.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.181-193
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• 2003

Without a sample standard deviation for an estimator of the population standard deviation u in a sample size computations, we often use some functions of a sample range (R) or interquartile range (IQR) by an estimator of $\sigma$. In order to avoid under-powered studies, these estimates must have a high probability of being greater than or equal to $\sigma$. In this paper, these probabilities of being greater than or equal to $\sigma$ are estimated for IQR for various parents distributions, and are compared with the probabilities for R/4 (Browne 2001). Alternative divisors (K) are explored and discussed for which the probabilities of R/K and IQR/K being greater than or equal to $\sigma$ is at least 95%.

• Journal of agriculture & life science
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• v.44 no.4
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• pp.1-7
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• 2010

Data was collected to develop equation for predicting stemp taper for Carpinus laxiflora in Jeju Experimental Forests. The Models tested for choosing the best-fit equations were Max & Burkhart's model, Kozak's model, and Lee's model. Performance of the equations in predicting stem diameter at a specific point along a stem was evaluated with fit and validation statistics and distribution of residuals on predicted values. In result, all the three models gave slightly better values of fitting statistics. In plotting residuals against predicted diameter, Max & Burkhart's model showed underestimation in predicting small diameter and Lee's Model did the same in predicting small diameter. Based on the above analysis of the three models in predicting stem taper, Kozak's model was chosen for the best-fit stem taper equations, and its parameters were given for C. laxiflora. Kozak's model was used to develop a stem volume table of outside bark for C. laxiflora.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1075-1089
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• 2023

Nuclear forensics is an essential part of nuclear material control and nuclear non-proliferation verification. Radiochronometry for nuclear forensics is used to estimate the timing of refinement and production of nuclear materials based on decay chain characteristics and the Bateman equation. The results of radiochronometry have uncertainties because the decay constant and number of nuclides are statistics derived from analyses or repeated experiments and involve uncertainties. The aim of this study was to develop an uncertainty calculation algorithm by performing computational simulation to overcome the limitations of the existing uncertainty calculation method for radiochronometry based on the Bateman equation. The results of the proposed uncertainty calculation algorithm were comparable to those of the existing method. The algorithm allowed for more than two generations of uncertainty calculations and mitigated the underestimation of the decay constant during the uncertainty calculation.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.201-214
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• 2020

This study proposes a bias correction method of dual-pol radar rain rate in real time using the dual Kalman filter. Unlike the conventional Kalman filter, the dual Kalman filter predicts state variables with two systems (state estimation system and model estimation system) at the same time. Bias of rain rate is corrected by applying the bias correction ratio to the rain rate estimate. The bias correction ratio is predicted from the state-space model of the dual Kalman filter. This method is applied to a storm event with long duration occurred in July 2016. Most of the bias correction ratios are estimated between 1 and 2, which indicates that the radar rain rate is underestimated than the ground rain rate. The AR (1) model is found to be appropriate for explaining the time series of the bias correction ratio. The time series of the bias correction ratio predicted by the dual Kalman filter shows a similar tendency to that of observation data. As the variability of the bias correction increases, the dual Kalman filter has better prediction performance than the Kalman filter. This study shows that the dual Kalman filter can be applied to the bias correction of radar rain rate, especially for long and heavy storm events.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.695-707
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• 2010

The frequency and size of typhoon and local severe rainfall are increasing due to the climate change and the damage also increasing from typhoon and severe rainfall. The flood forecasting and warning system to reduce the damage from typhoon and severe rainfall needs forecasted rainfall using radar data and short-term rainfall forecasting model. For this reason, this study examined the applicability of short-term rainfall forecast using translation model with weather radar data to point out that the utilization of flood forecasting in Korea. This study estimated the radar rainfall using Least-square fitting method and estimated rainfall was used as initial field of translation model. The translation model have verified accuracy of forecasted radar rainfall through the comparison of forecasted radar rainfall and observed rainfall quantitatively and qualitatively. Almost case studies showed that accuracy is over 0.6 within 4 hours leading time and mean of correlation coefficient is over 0.5 within 1 hours leading time in Kwanak and Jindo radar site. And, as the increasing the leading time, the forecast accuracy of precipitation decreased. The results of the calculated Mean Area Precipitation (MAP) showed forecast rainfall tend to be underestimated than observed rainfall but the correlation coefficient more than 0.5. Therefore it showed that translation model could be accurately predicted the rainfall relatively. The present results indicate that possibility of translation model application of Korea just within 2 hours leading forecasted rainfall.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1719-1729
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• 2021

Leaf area index (LAI) provides valuable information necessary for sustainable and effective management of forests. Although global high resolution LAI data are provided by European Space Agency using Sentinel-2 satellite images, they have not considered forest characteristics in model development and have not been evaluated for various forest ecosystems in South Korea. In this study, we proposed a LAI estimation model combining machine learning and the PROSAIL radiative transfer model using Sentinel-2 satellite data over a local forest area in South Korea. LAI-2200C was used to measure in situ LAI data. The proposed LAI estimation model was compared to the existing Sentinel-2 LAI product. The results showed that the proposed model outperformed the existing Sentinel-2 LAI product, yielding a difference of bias ~ 0.97 and a difference of root-mean-square-error ~ 0.81 on average, respectively, which improved the underestimation of the existing product. The proposed LAI estimation model provided promising results, implying its use for effective LAI estimation over forests in South Korea.

• Journal of Animal Science and Technology
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• v.44 no.5
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• pp.519-522
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• 2002

Body weight-age data from 60 bulls and 60 steer of Hanwoo in the Korean Native Cattle Improvement Center was used to determine the growth curve parameters with Gompertz equation. Estimated growth curve functions were as follows; Bul l : $W_t$ = 906.1.exp{－3.956.exp(－0.0034t)} Steer : $W_t$ = 823.1.exp{－3.301.exp(－0.0027t} Mature weight estimated with Gompertz equation of bull is higher than earlier studies. And the major factor raising differences from the other is feeding level. Relative body weights of steer to bull were rapidly decreased to 79.2% until 19.5 months of age, and then increased slowly. The ratio was 90.8% at mature state. Body weight was under-estimated for bull at birth, but over-estimated for steer, and the body weight variations of bull were larger than the steer.

• KDI Journal of Economic Policy
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• v.32 no.3
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• pp.71-99
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• 2010

The concept of CoVaR introduced by Adrian and Brunnermeier (2009) is a useful tool to measure the risk spillover effect. It can capture the risk contribution of each institution to overall systemic risk. While Adrian and Brunnermeier rely on the quantile regression method in the estimation of CoVaR, we propose a new estimation method using parametric distribution functions such as bivariate normal and $S_U$-normal distribution functions. Based on our estimates of CoVaR for Korean banking industry, we investigate the practical usefulness of CoVaR for a systemic risk measure, and compare the estimation performance of each model. Empirical results show that bank makes a positive contribution to system risk. We also find that quantile regression and normal distribution models tend to considerably underestimate the CoVaR (in absolute value) compared to $S_U$-normal distribution model, and this underestimation becomes serious when the crisis in a financial system is assumed.