• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.459-469
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• 2010

This study is to develop a grid-based daily runoff model considering seasonal vegetation canopy condition. The model simulates the temporal and spatial variation of runoff components (surface, interflow, and baseflow), evapotranspiration (ET) and soil moisture contents of each grid element. The model is composed of three main modules of runoff, ET, and soil moisture. The total runoff was simulated by using soil water storage capacity of the day, and was allocated by introducing recession curves of each runoff component. The ET was calculated by Penman-Monteith method considering MODIS leaf area index (LAI). The daily soil moisture was routed by soil water balance equation. The model was evaluated for 930 $km^2$ Yongdam watershed. The model uses 1 km spatial data on landuse, soil, boundary, MODIS LAI. The daily weather data was built using IDW method (2000-2008). Model calibration was carried out to compare with the observed streamflow at the watershed outlet. The Nash-Sutcliffe model efficiency was 0.78~0.93. The watershed soil moisture was sensitive to precipitation and soil texture, consequently affected the streamflow, and the evapotranspiration responded to landuse type.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.15-17
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• 2022

In the aftermath of the avian influenza that occurred from the second half of 2020 to the beginning of 2021, 17.8 million laying hens were slaughtered. Although the government invested more than 100 billion won for egg imports as a measure to stabilize prices, the effort was not that easy. The sharp volatility of egg prices negatively affected both consumers and poultry farmers, so measures were needed to stabilize egg prices. To this end, the egg prices were successfully predicted in this study by using the analysis algorithm of a machine learning regression. For price prediction, a total of 8 independent variables, including monthly broiler chicken production statistics for 2012-2021 of the Korean Poultry Association and the slaughter performance of the national statistics portal (kosis), have been selected to be used. The Root Mean Square Error (RMSE), which indicates the difference between the predicted price and the actual price, is at the level of 103 (won), which can be interpreted as explaining the egg prices relatively well predicted. Accurate prediction of egg prices lead to flexible adjustment of egg production weeks for laying hens, which can help decision-making about stocking of laying hens. This result is expected to help secure egg price stability.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.404-414
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• 2023

In this study, digital climate maps with high-resolution (1km, daily) for the period of 1981 to 2020 were produced for the use as reference data within the procedures for statistical downscaling of climate change scenarios. Grid data for the six climate variables including maximum temperature, minimum temperature, precipitation, wind speed, relative humidity, solar radiation was created over Korean Peninsula using statistical downscaling model, so-called IGISRM (Improved GIS-based Regression Model), using global reanalysis data and in-situ observation. The digital climate data reflects topographical effects well in terms of representing general behaviors of observation. In terms of Correlation Coefficient, Slope of scatter plot, and Normalized Root Mean Square Error, temperature-related variables showed satisfactory performance while the other variables showed relatively lower reproducibility performance. These digital climate maps based on observation will be used to downscale future climate change scenario data as well as to get the information of gridded agricultural weather data over the whole Korean Peninsula including North Korea.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.333-341
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• 2008

In this paper, a new interpolation model for the head related transfer function (HRTF) was proposed. In the method herein, we assume that the impulse response of the HRTF for each azimuth angle is given by linear interpolation of the time-delayed neighboring impulse responses of HRTFs. The time delay of the HRTF for each azimuth angle is given by sum of the sound wave propagation time from the ears to the sound source, which can be estimated by using azimuth angle, the physical shape of the underlying head and the distance between the head and sound source, and the refinement time yielding the minimum mean square error. Moreover, in the proposed model, the interpolation intervals were not fixed but varied, which were determined by minimizing the total number of HRTFs while the synthesized signals have no perceptual difference from the original signals in terms of sound location. To validate the usefulness of the proposed interpolation model, the proposed model was applied to the several HRTFs that were obtained from one dummy-head and three human heads. We used the HRTFs that have 5 degree azimuth angle resolution at 0 degree elevation (horizontal plane). The experimental results showed that using only $30\sim40%$ of the original HRTFs were sufficient for producing the signals that have no audible differences from the original ones in terms of sound location.

• Animal Bioscience
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• v.37 no.8
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• pp.1387-1397
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• 2024

Objective: The objective of the current study was to find out the independent and interactive effects of prilled fat supplementation with protein on the production performance of early lactating Nili Ravi buffaloes. Methods: Sixteen early lactating buffaloes (36.75±5.79 d in milk; mean±standard error) received 4 treatments in 4×4 Latin-square design according to 2×2 factorial arrangements. The dietary treatments were: i) low protein low fat, ii) low protein high fat, iii) high protein low fat, and iv) high protein high fat. The dietary treatments contained 2 protein (8.7% and 11.7% crude protein) and fat levels (2.6% and 4.6% ether extract) on a dry matter basis. Results: The yields of milk and fat increased with increasing protein and fat independently (p≤0.05). Energy-, protein-, and fat-corrected milk yields also increased with increasing protein and fat independently (p≤0.05). Increasing dietary protein increased the protein yield by 3.75% and lactose yield by 3.15% and increasing dietary fat supplies increased the fat contents by 3.93% (p≤0.05). Milk yield and fat-corrected milk to dry matter intake ratios were increased at high protein and high fat levels (p≤0.05). Milk nitrogen efficiency was unaffected by dietary fat (p>0.10), whereas it decreased with increasing protein supplies (p≤0.05). Plasma urea nitrogen and cholesterol were increased by increasing protein and fat levels, respectively (p≤0.05). The values of predicted methane production reduced with increasing dietary protein and fat. Conclusion: It is concluded that prilled fat and protein supplies increased milk and fat yield along with increased ratios of milk yield and fat-corrected milk yields to dry matter intake. However, no interaction was observed between prilled fat and protein supplementation for production parameters, body weight, body condition score and blood metabolites. Predicted methane production decreased with increasing protein and fat levels.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.165-179
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• 2024

It is crucial to have a comprehensive understanding of inundation and water cycle in urban areas for mitigating flood risks and sustainable water resources management. In this study, we developed a Cellular Automata-based integrated Water cycle model (CAW). A comparative analysis with physics-based and conventional cellular automata-based models was performed in an urban watershed in Portland, USA, to evaluate the adequacy of spatiotemporal inundation simulation in the context of a high-resolution setup. A high similarity was found in the maximum inundation maps by CAW and Weighted Cellular Automata 2 Dimension (WCA2D) model presumably due to the same diffuse wave assumption, showing an average Root-Mean-Square-Error (RMSE) value of 1.3 cm and high scores of binary pattern indices (HR 0.91, FAR 0.02, CSI 0.90). Furthermore, through multiple simulation experiments estimating the effects of land cover and soil conditions on inundation and infiltration, as the impermeability rate increased by 41%, the infiltration decreased by 54% (4.16 mm/m²) while the maximum inundation depth increased by 10% (2.19 mm/m²). It was expected that high-resolution integrated inundation and water cycle analysis considering various land cover and soil conditions in urban areas would be feasible using CAW.

• 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.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.397-418
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• 2024

The Land Surface Temperature (LST) is a crucial parameter in identifying drought. It is essential to identify how LST can increase its accuracy, particularly in mountainous and hill areas. Increasing the LST accuracy can be achieved by applying early data processing in the correction phase, specifically in the context of topographic correction on the Lambertian model. Empirical evidence has demonstrated that this particular stage effectively enhances the process of identifying objects, especially within areas that lack direct illumination. Therefore, this research aims to examine the application of the Lambertian model in estimating LST using the Multi-Channel Method (MCM) across various physiographic regions. Lambertian model is a method that utilizes Lambertian reflectance and specifically addresses the radiance value obtained from Sun-Canopy-Sensor(SCS) and Cosine Correction measurements. Applying topographical adjustment to the LST outcome results in a notable augmentation in the dispersion of LST values. Nevertheless, the area physiography is also significant as the plains terrain tends to have an extreme LST value of ≥ 350 K. In mountainous and hilly terrains, the LST value often falls within the range of 310-325 K. The absence of topographic correction in LST results in varying values: 22 K for the plains area, 12-21 K for hilly and mountainous terrain, and 7-9 K for both plains and mountainous terrains. Furthermore, validation results indicate that employing the Lambertian model with SCS and Cosine Correction methods yields superior outcomes compared to processing without the Lambertian model, particularly in hilly and mountainous terrain. Conversely, in plain areas, the Lambertian model's application proves suboptimal. Additionally, the relationship between physiography and LST derived using the Lambertian model shows a high average R² value of 0.99. The lowest errors(K) and root mean square error values, approximately ±2 K and 0.54, respectively, were achieved using the Lambertian model with the SCS method. Based on the findings, this research concluded that the Lambertian model could increase LST values. These corrected values are often higher than the LST values obtained without the Lambertian model.

• Journal of the Korean Applied Science and Technology
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• v.41 no.4
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• pp.995-1007
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• 2024

The purpose of this study is to structurally analyze the effect of resilience of college students who took liberal arts and sports classes at private universities on college life satisfaction and grit. For this study, we conducted an online survey of 283 non-sports college students who took liberal arts and physical education classes. In order to process the data of this study, the responses of the questionnaire were converted into data, and statistical programs SPSS 23.0 and AMOS 21.0 were used to analyze it. In SPSS 23.0, frequency analysis, reliability analysis, and correlation analysis were performed. Meanwhile, with AMOS 21.0, confirmatory factor analysis and structural equation model analysis were performed to determine the statistical fit of the research model, and values such as CFI (complementary fit index), Tucker-lewis index (TLI), and RMSEA (root mean square error of approach) derived in this process were reviewed. First, Model 1 showed statistically significant results in the effect of resilience of college students who took liberal arts sports on college life satisfaction and college life satisfaction on Grit's continuity of interest. Second, Model 2 showed statistically significant results in the effect of resilience of college students who took liberal arts sports on college life satisfaction and college life satisfaction on grit's effort. It was found that there were statistically significant results in the effect of resilience of college students who took liberal arts sports on college life satisfaction and college life satisfaction on Grit's continued interest and effort.