• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.233-242
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• 2019

ZHD (Zenith Hydrostatic Delay) model is important parameter in estimating of GNSS (Global Navigation Satellite System) PWV (Precipitable Water Vapor) along with weighted mean temperature. The ZWD (Zenith Wet Delay) is tend to accumulate the ZHD error, so that biases from ZHD will be affected on the precision of GNSS PWV. In this paper, we compared the accuracy of GNSS PWV with radiosonde PWV using three ZHD models, such as Saastamoinen, Hopfield, and Black. Also, we adopted the KWMT (Korean Weighted Mean Temperature) model and the mean temperature which was observed by radiosonde on the retrieval processing of GNSS PWV. To this end, GNSS observation data during one year were processed to produce PWVs from a total of 5 GNSS permanent stations in Korea, and the GNSS PWVs were compared with radiosonde PWVs for the evaluating of biases. The PWV biases using mean temperature estimated by the KWMT model are smaller than radiosonde mean temperature. Also, we could confirm the result that the Saastamoinen ZHD which is most used in the GNSS meteorology is not valid in South Korea, because it cannot be exclude the possibility of biases by latitude or height of GNSS station.

• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.355-383
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• 2019

This study is to investigate whether averting costs for wearing $anti-PM_{10}$ masks and using air purifiers at home to reduce exposure from $PM_{10}$ are influenced by subjective risk perceptions and/or objective $PM_{10}$ concentration levels, whose estimates will be used to measure the willingness to pay for $PM_{10}$ risk reduction. An empirical analysis was conducted on a sample of 1,224 respondents who participated in the web-based survey in the late October of 2017. As we reflect the potential endogeniety bias in the estimation of averting cost functions of using air purifiers, the coefficients of risk perception were differed by 6~7 times. Respondents. subjective risk perceptions were influenced by individuals' knowledge, attitudes and demographic variables, as well as the levels of $PM_{10}$ concentrations in their residential region. The marginal willingness to pay for risk reductions at the mean levels of their risk perceptions were measured at 1,000 won per month from wearing $anti-PM_{10}$ masks and 6,000 won for using air purifiers respectively.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.427-438
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• 2021

Two-stage sampling allows us to estimate population characteristics by both unit and cluster level together. Given a complex auxiliary information, integrated calibration weighting would better reflect the level-wise characteristics as well as multivariate characteristics between levels. This paper explored the integrated calibration weighting methods by Estevao and Särndal (2006) and Kim (2019) through a simulation study, where the efficiency of those weighting methods was compared using an artificial population data. Two weighting methods among others are shown efficient: single step calibration at the unit level with stacked individualized auxiliary information and iterative integrated calibration at each level. Under both methods, cluster calibrated weights are defined as the average of the calibrated weights of the unit(s) within cluster. Both were very good in terms of the goodness-of-fit of estimating the population totals of mutual auxiliary information between clusters and units, and showed small relative bias and relative mean square root errors for estimating the population totals of survey variables that are not included in calibration adjustments.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.121-131
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• 2023

This study examines the possible problem in the rainfall-runoff analysis process using the VIC (Variable Infiltration Capacity) model caused by using the effective soil depth instead of the soil depth. The parameters of the model are determined as follows. First, parameters that can be determined using available numerical information are fixed. For parameters related to direct runoff and base runoff, the recommended values of the VIC model are applied. In the case of soil depth, four cases are considered: (1) the effective soil depth is applied as the soil depth, (2) 1.5 times of the effective soil depth is applied as the soil depth by reflecting the vertical structure of the soil layer, (3) 1.25 times of the effective soil depth, and (4) 2.0 times of the effective soil depth as alternative soil depths. This study simulates the rainfall-runoff for the period from 1983 to 2020 targeting the Chungju Dam and Soyang River Dam basins of the Han River system. As a result of the study, it is confirmed that when the effective soil depth is applied instead of the soil depth, direct runoff and baseflow have opposite effects, and direct runoff increases by more than 3% while base runoff decreases by the same scale. In addition, the most influential factor in the estimation of the effective soil depth in the Chungju Dam and Soyanggang Dam basins is found to be the proportion of rock outcrop area. The difference between the direct runoff ratio and the base runoff ratio in the two basins is conformed significantly different due to the influence of the rock outcrop area.

• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.720-734
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• 2023

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (M_e) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between M_e and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between M_e and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the M_e, the higher the accuracy of EBV.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.1-13
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• 2024

The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O₂/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O₂ m^-2 d^-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O₂ m^-2 d^-1 and lowest in June and July at 18 mmol O₂ m^-2 d^-1. These seasonal variations were similar to the vertical nitrate flux based on the ³He gas exchange rate and to the particulate organic carbon flux estimated by the ²³⁴Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.

• Korean Journal of Radiology
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• v.20 no.6
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• pp.916-930
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• 2019

Objective: To investigate the relationships of T₂^*-corrected 6-echo Dixon volumetric interpolated breath-hold examination (VIBE) imaging-based fat fraction (FF) and R₂^* values with bone mineral density (BMD); determine their associations with sex, age, and menopause; and evaluate the diagnostic performance of the FF and R₂^* for predicting osteopenia and osteoporosis. Materials and Methods: This study included 153 subjects who had undergone magnetic resonance (MR) imaging, including MR spectroscopy (MRS) and T₂^*-corrected 6-echo Dixon VIBE imaging. The FF and R₂^* were measured at the L4 vertebra. The male and female groups were divided into two subgroups according to age or menopause. Lin's concordance and Pearson's correlation coefficients, Bland-Altman 95% limits of agreement, and the area under the curve (AUC) were calculated. Results: The correlation between the spectroscopic and 6-echo Dixon VIBE imaging-based FF values was statistically significant for both readers (p_c = 0.940 [reader 1], 0.908 [reader 2]; both p < 0.001). A small measurement bias was observed for the MRS-based FF for both readers (mean difference = -0.3% [reader 1], 0.1% [reader 2]). We found a moderate negative correlation between BMD and the FF (r = -0.411 [reader 1], -0.436 [reader 2]; both p <0.001) with younger men and premenopausal women showing higher correlations. R₂^* and BMD were more significantly correlated in women than in men, and the highest correlation was observed in postmenopausal women (r = 0.626 [reader 1], 0.644 [reader 2]; both p < 0.001). For predicting osteopenia and osteoporosis, the FF had a higher AUC in men and R₂^* had a higher AUC in women. The AUC for predicting osteoporosis was highest with a combination of the FF and R₂^* in postmenopausal women (AUC = 0.872 [reader 1], 0.867 [reader 2]; both p < 0.001). Conclusion: The FF and R₂^* measured using T₂^*-corrected 6-echo Dixon VIBE imaging can serve as predictors of osteopenia and osteoporosis. R₂^* might be useful for predicting osteoporosis, especially in postmenopausal women.

• Journal of the Korean earth science society
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• v.33 no.2
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• pp.126-138
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• 2012

Ultrasonic method is widely used for the evaluation of weathering index and of degree of deterioration because it is easily applicable $in$ $situ$. The basic idea of the method is that the ultrasonic velocity decreases as a rock is being weathered. Thus, the difference of ultrasonic velocities between fresh rock and weathered rock indicates the degree of weathering. In this method, the ultrasonic velocity of fresh rock is assumed to be 5,000 m/s. However, this assumption can cause significant errors in estimating weathering index, especially in case that those rocks of the same type have a wide range of ultrasonic velocities such as in Korea. Therefore, we obtained twenty rock specimens and sixty core samples commonly used for stone cultural heritages in Korea, and measured ultrasonic velocities. From the results, we found that the ultrasonic velocities of the same rock type, granite samples range from 3,118 to 5,380 m/s, and that the estimated weathering index can be highly biased if we use the fixed value of 5,000 m/s. We created a database (DB) by combining the measurement data and reported it. We also measured ultrasonic velocities by direct and indirect methods to quantify the calibration coefficient for each sampling site. We found that the calibration coefficients vary widely from site to site (1.31-1.76). Other factors, such as operator bias and temperature did not show any significant effect on errors in ultrasonic velocity measurements. Lastly, we applied our ultrasonic velocity DB and calibration coefficients to a stone cultural heritage, Bonghwang-ri Buddha statue. Our estimation of the weathering index was 0.3, 0.1 smaller than that by conventional method. The degree of deterioration was also different, "moderately weathered", while conventional method gave "highly weathered". Since other independent studies reported that the degree of deterioration of the Buddha statue was "moderately weathered", our estimation seems to be more accurate. Thus our method can help accurately evaluate the weathering index and the conservation planning for a stone cultural heritage.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.