• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.627-644
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• 2009

In the knowledge-based economy highlighting the importance of human capital, there has been a growing interest in human capital externalities as a fundamental engine of growth and development of a region. The purpose of this study is to analyze human capital externalities using 3-level hierarchical linear model(3-HLM), decomposing determinants of wages into three levels involving workers(level-1) nested within firms(level-2) nested within regions(level-3). This study separately estimates the effect of the average education level on the wages by three different schooling groups on the assumption that the intensity of knowledge spillovers varies with each group's schooling level. The main results are as follows; First, the coefficient of the average education level of a region shows 0.044, indicating that one-year increase in the average level of schooling could increase average individual earnings by 4.4%. Secondly, the external effects of human capital on three different schooling groups are considerably different, raising less than high school graduates' wages by 3.0%, college graduates' wages by 4.7%, and graduate schools' wages by 11.8%, respectively. Thirdly, well educated workers are much more sensitive to the variation of the regional education level than less educated ones when we apply the shares of each schooling group as alternative measures for the average level of education. Such findings of this study draw an implication that local governments could speed up regional economic growth in the knowledge-based economy by not only raising total human capital stock in a region but building the close networks that promote productivity-enhancing human capital external effects.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.627-639
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• 2014

Accurate correction of surface effect from back scattered solar radiance is one of key issue to retrieve aerosol information from satellite measurements. In this study, two different methods are applied to retrieve surface reflectance by using single visible channel measurement from meteorological imager onboard COMS. The first one is minimum reflectance method, which composes the minimum value among previously measured reflectances at each pixel over a certain search window length. This method assumes that the darkest pixel corresponds to the aerosol-free condition, and deduces surface reflectance by correcting atmospheric scattering from the measured visible reflectance. The second method, named as the "atmospheric correction method" in this study, estimates the result by correcting aerosol and atmospheric scattering with ground-based observation of aerosol optical properties. The purpose of this study is to investigate the retrieval accuracy of the widelyused minimum reflectance method. Also, the retrieval error caused by the loading of background aerosol is mainly estimated. The comparison between surface reflectances retrieved from the two methods shows good agreement with the correlation coefficient of 0.87. However, the results from the minimum reflectance method are slightly overestimated than the values from the atmospheric correction method when surface reflectance is lower than 0.2. The average difference between the two results is 0.012 without the background aerosol correction. By considering the background aerosol effect, however, the difference is reduced to 0.010.

• Journal of agriculture & life science
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• v.46 no.1
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• pp.113-121
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• 2012

A total of 150,624 records of Holstein milk production collected from 2005 to 2009 were analyzed to investigate the effects of two different contemporary group definitions, parity and somatic cell score (SCS). The first definition (H BY S) of contemporary group was milking cows and heifers born in the same year and season. And the second thing (H CY S) was milking cow and heifers that delivered calves in the same year and season. Effects of contemporary group, parity and regression effect on SCS from two models were highly significant sources of variation. Coverage of variation ($R^2$) was somewhat higher in models with H BY S as contemporary group. From multivariate models with H BY S, phenotypic correlation coefficients of milk components were estimated high and positive. However, the phenotypic correlation coefficient between milk yield and SCS was -0.09, which was low enough to evidence no correlation between them. Phenotypic correlation between SCS and butter fat or between SCS and protein were also negligible but negative. From multivariate models with H CY S as contemporary group, phenotypic correlation among milk traits and SCS were similar to the estimates from models with H BY S. However, SCS in these models were lowly but negatively correlated with milk yield, milk protein, butter fat or SNF, and the phenotypic correlation coefficients of which were -0.10, -0.08, -0.08, -0.11, respectively.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.25 no.4
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• pp.45-56
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• 2012

Objective : This study was done to investigate the correlation between general quality of life(QOL) and disease specific QOL of tinnitus patients. Methods : 2009 National health and nutrition survey(NHNS) data were employed for analyzing the mean estimates of total population and tinnitus sub-group patients, and predicting the regression equation of mapping between EQ-5D and disease severity. Baseline statistical analyses and normality tests were done by using Student t-test, Chi-square test, Shapiro-Wilk test and ladder test. Hierarchial regression analyses were performed using related variables and predicted the optimal regression equations. Statistical significance was achieved if the probability was less than 5%. Results : Firstly, the standardized prevalence of tinnitus patient in South Korea was 18.69% and over 90th age-group was relatively higher than other groups. Mean value of domestic QOL measured by EQ-5D was estimated as 0.9486 and QOL of tinnitus subgroup(0.9169) was lower than the non-tinnitus subgroup(0.9559), significantly. Stratified by age and sex, QOLs of all sub-groups with tinnitus were lower than without tinnitus sub-groups significantly. Regression equations from 2009 NHNS data were developed using hierarchial regression analysis which is as follows. $$Y_{EQ-5D}=0.9224-0.0079{\times}T1-0.0261{\times}T2-0.0951{\times}T3+\sum_{i=1}^{n}{\beta}_i{\times}X_i\\{\hspace{95}}(0.0106){\hspace{3}}(0.0037){\hspace{30}}(0.0072){\hspace{30}}(0.0038)$$ ($X_i$=Other explanatory variables except Tinnitus QOL1, 2, 3, ${\beta}$= Regression Coefficient of Model 4) Conclusion : We confirmed the correlation among THI and EQ-5D and HUI-III, and developed the inference for regression equation of EQ-5D.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1229-1235
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• 2018

We have examined dynamic relationships among water-efficiency, economic growth, electricity generation, and $CO_2$ emissions in Korea using various time-series analysis methods for 1990-2014. While previous studies have been limited to economic growth, $CO_2$ emissions, and electricity generation, this study contributed to explain the relationship between existing variables and water-efficiency. We find that the four variables reach a balanced state in the long run through short-term adjustment, $CO_2$ emissions and economic growth are responsible for water efficiency, and that $CO_2$ emissions, economic growth and water efficiency are the causes of electricity generation. The long-term impact coefficient estimates on water-efficiency show that the increase in electricity generation and the decrease in $CO_2$ emissions increase water-efficiency. Although economic growth has increased water-efficiency, moreover, we have identified an inverted U-shaped relationship between economic growth and water-efficiency, which suggests that economic growth above a certain level reduces the rate of increase in water-efficiency.

• The Journal of Fisheries Business Administration
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• v.49 no.3
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• pp.85-99
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• 2018

This study is to compare and evaluate the estimating method of WTP(willingness to pay) for the valuation of oceans and fisheries resources with non-market goods characteristics using contingent valuation method. In general, when estimating parameters of the WTP function, we should take into account the assumption of probability distribution, inclusion of covariates, method of inducement of payment, and the treatment of 0 payment intention and resistance responses. This study utilizes survey data that was used to estimate the value of fisheries resource protection zones, with a total of 1,200 samples. The main results of this study are summarized as follows: First, the final willness to pay amount is estimated at a statistical significance of less than 1 percent, and the distribution of the final willness to pay amount is from \6,926 of the double bounded dichotomous model to \10,721 of the spike model. Second, the willness to pay amount based on assumptions about the normal and logistic probability distributions are estimated to be \9,429 and \9,370 respectively, so there was no significant difference. Third, the willness to pay amount of the single bounded dichotomous model and the double bounded dichotomous model are estimated to be \8,951 and \6,926 respectively, making a relatively large difference. Fourth, the willness to pay amount of the model without covariates and the model with covariates are estimated to be \9,429 and \8,951, respectively, so the willness to pay amount is underestimated when the covariates are included. Fifth, the Spike model that considers zero payment intention and resistance response estimates \10,405 as the highest payment in this study. Finally, the CVM analysis guidelines proposed by the Korea Development Institute (KDI) are estimated to be \9,749 and \10,405 respectively, depending on including no covariates and with covariates. Compared to other models, the final willness to pay amount is not estimated underestimated. Therefore this study suggests the use of KDI's guidance under government public policy projects. In view of these results, the estimating model for willness to pay amount model will be selected by considering the sample size, the suitability of the model, the sign of the estimated coefficient, the statistical significance, the ratio of the zero payment intention and the payment rejection. And, for CVMs on government public policy projects, it is desirable to estimate by the method proposed by the KDI.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.78-82
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• 2022

Phenology determines the timing of crop development, and the timing of phenological events is strongly influenced by the temperature during the growing season. In process-based model, leaf area is simulated dynamically by coupling of morphology and phenology module. Therefore, the prediction of leaf appearance rate and final leaf number affects the performance of whole crop model. The dataset for the model equation was collected from SPA R chambers with five different temperature treatments. Beta distribution function (proposed by Yan and Hunt (1999)) was used for describing the leaf appearance rate as a function of temperature. The optimum temperature and the critical value were estimated to be 26.0℃ and 35.3℃, respectively. For evaluation of the model, the accumulated number of onion leaves observed in a temperature gradient chamber was compared with model estimates. The model estimate is the result of accumulating the daily increase in the number of onion leaves obtained by inputting the daily mean temperature during the growing season into the temperature model. In this study, the coefficient of determination (R²) and RMSE value of the model were 0.95 and 0.89, respectively.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• Korean Journal of Environment and Ecology
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• v.37 no.1
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• pp.70-75
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• 2023

This study was conducted from October 2021 to October 2022 at Gulup island, Incheon, South Korea, to identify activity patterns of Formosan sika deer (Cervus nippon taiouanus) introduced in island areas, using camera trapping. We described the daily activity patterns of Formosan sika deer in each season by analyzing kernel density estimates of capture frequency and checked seasonal differences in daily activity patterns by analyzing the overlap coefficient between seasons. Formosan sika deers introduced to Gulup island showed a crepuscular behavior pattern only in winter and no distinct pattern from spring to fall. The crepuscular behavior pattern is typical for deers to reduce the risk of predation, and it is determined that Formosan sika deers introduced to Gulup island were affected by population control of the species by the local government in the winter. It was in contrast to the fact that human activities, such as backpacking, frequently carried out from spring to fall, did not affect the behavior of Formosan sika deers. Moreover, low winter temperatures have been shown to affect the nocturnal activities of Formosan sika deers in winter. The behavior patterns of Formosan sika deers overlapped least between summer and winter due to cold winter weather and population control. The relationship between the temporal status of Formosan sika deers and seasonal temperature confirmed in this study can be important basic ecological data for establishing control measures of Formosan sika deers introduced not only in islands but also in inland.

• Journal of Ecology and Environment
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• v.48 no.2
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• pp.196-206
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• 2024

Background: Most of the biomass equations were developed using sample trees collected mainly from pan-tropical and tropical regions that may over- or underestimate biomass. Site-specific models would improve the accuracy of the biomass estimates and enhance the country's measurement, reporting, and verification activities. The aim of the study is to develop site-specific biomass estimation models and validate and evaluate the existing generic models developed for pan-tropical forest and newly developed allometric models. Total of 140 trees was harvested from each diameter class biomass model development. Data was analyzed using SAS procedures. All relevant statistical tests (normality, multicollinearity, and heteroscedasticity) were performed. Data was transformed to logarithmic functions and multiple linear regression techniques were used to develop model to estimate aboveground biomass (AGB). The root mean square error (RMSE) was used for measuring model bias, precision, and accuracy. The coefficient of determination (R² and adjusted [adj]-R²), the Akaike Information Criterion (AIC) and the Schwarz Bayesian information Criterion was employed to select most appropriate models. Results: For the general total AGB models, adj-R² ranged from 0.71 to 0.85, and model 9 with diameter at stump height at 10 cm (DSH₁₀), ρ and crown width (CW) as predictor variables, performed best according to RMSE and AIC. For the merchantable stem models, adj-R² varied from 0.73 to 0.82, and model 8) with combination of ρ, diameter at breast height and height (H), CW and DSH₁₀ as predictor variables, was best in terms of RMSE and AIC. The results showed that a best-fit model for above-ground biomass of tree components was developed. AGB_Stem = exp {-1.8296 + 0.4814 natural logarithm (Ln) (ρD²H) + 0.1751 Ln (CW) + 0.4059 Ln (DSH₃₀)} AGB_Branch = exp {-131.6 + 15.0013 Ln (ρD²H) + 13.176 Ln (CW) + 21.8506 Ln (DSH₃₀)} AGB_Foliage = exp {-0.9496 + 0.5282 Ln (DSH₃₀) + 2.3492 Ln (ρ) + 0.4286 Ln (CW)} AGB_Total = exp {-1.8245 + 1.4358 Ln (DSH₃₀) + 1.9921 Ln (ρ) + 0.6154 Ln (CW)} Conclusions: The results demonstrated that the development of local models derived from an appropriate sample of representative species can greatly improve the estimation of total AGB.