• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.29-37
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• 2017

In this study, we analyzed the impacts of land surface characteristics on spatially and temporally distributed soil moisture values at the Yongdam and Soyang-river dam watersheds in 2014 and 2015. The soil moisture, NDVI (Normalized Difference Vegetation Index) and temperature values at the spatio-temporal scales were estimated using satellite-based MODIS (MODerate Resolution Imaging Spectroradiometer) products. Then the Pearson correlations between soil moisture and land surface characteristics (NDVI, temperature and DEM-digital elevation model) were estimated and analyzed, respectively. Overall, the monthly soil moisture values at the time step were highly influenced by the precipitation amounts. Also, the results showed that the soil moisture has the strong correlation with DEM while the temperature was inversely correlated with the soil moisture. However the monthly correlations between NDVI and soil moisture were highly varied along the time step. These findings indicated that water loss near the land surface are highly occurred by soil and plant activities as evapotranspiration and infiltration during the no/less precipitation period. But the high precipitation amounts reduce the impacts of land surface characteristics because of saturated condition of land surface. Thus these results demonstrated that soil moisture values are highly correlated with land surface characteristics. Our findings can be useful for water resources/environmental management, agricultural drought, etc.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.101-109
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• 2015

SMRs (standardized mortality rates) for major diseases, accidents, cancer are considered in small areas of administrative units such as Eup/Myeon/Dong from years 2005 to 2008. Due to small sample issue in small areas, the precision of directly estimated crude SMR for each area can be low. In this study, we consider the HGLM (hierarchical generalized linear model) with MRF (Markov random field) to account for the spatial correlations among the small areas. The effects of covariates for cause of mortality by Dongs in Seoul and disease maps based on the estimated SMR are presented. The results suggest how we analyze and interpret the difference in mortalities by small areas such as Dongs by revealing the spatial patterns.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.12
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• pp.1863-1870
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• 2018

Objective: The Bayesian first-order antedependence models, which specified single nucleotide polymorphisms (SNP) effects as being spatially correlated in the conventional BayesA/B, had more accurate genomic prediction than their corresponding classical counterparts. Given advantages of $BayesC{\pi}$ over BayesA/B, we have developed hyper-$BayesC{\pi}$, ante-$BayesC{\pi}$, and ante-hyper-$BayesC{\pi}$ to evaluate influences of the antedependence model and hyperparameters for $v_g$ and $s_g^2$ on $BayesC{\pi}$.Methods: Three public data (two simulated data and one mouse data) were used to validate our proposed methods. Genomic prediction performance of proposed methods was compared to traditional $BayesC{\pi}$, ante-BayesA and ante-BayesB. Results: Through both simulation and real data analyses, we found that hyper-$BayesC{\pi}$, ante-$BayesC{\pi}$ and ante-hyper-$BayesC{\pi}$ were comparable with $BayesC{\pi}$, ante-BayesB, and ante-BayesA regarding the prediction accuracy and bias, except the situation in which ante-BayesB performed significantly worse when using a few SNPs and ${\pi}=0.95$. Conclusion: Hyper-$BayesC{\pi}$ is recommended because it avoids pre-estimated total genetic variance of a trait compared with $BayesC{\pi}$ and shortens computing time compared with ante-BayesB. Although the antedependence model in $BayesC{\pi}$ did not show the advantages in our study, larger real data with high density chip may be used to validate it again in the future.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.60.1-60.1
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• 2015

High energy photons and mechanical energy produced by the process of star formation result in copious FIR molecular and atomic lines, which are important coolants of the system. Photons thermally or mechanically induced could dissociate water in the dense envelope to change relative abundances among the species of O, OH, and H2O. Here we analyze OH emission lines toward embedded young stellar objects (YSOs) observed as part of the Herschel open time key program, 'Dust, Ice, and Gas In Time (DIGIT)' in order to study the physical conditions of associated gas and the energy budget loaded on the OH line emission. According to our analysis of the Herschel/PACS spectra, OH emission peaks at the central spaxel in most of sources, but several sources show spatially extended emission structures. In the extended emission sources, the distribution of OH emission is correlated with that of [OI] emission and extended along the outflow directions. Considering the diversity of source properties, ratios between detected OH lines are relatively constant among sources. In addition, each OH line has strong correlation with bolometric luminosity. In order to determine the physical conditions of YSOs, we adopt several methods for the analysis of the OH lines: rotational diagram, non-LTE LVG analysis, and a 2-D PDR code. From the simple LVG analysis, we find that the thermal solution with the dense ( > $10^7cm^{-3}$) and warm ( ~ 100 K) OH gas reproduces the ratios of detected OH lines. However, our self-consistent PDR 2-D model, which can deal with the IR-pumping effect from the central protostar as well as the warm dust in situ, cannot fit the observational results, suggesting that an irradiated shock model is necessary for a better interpretation.

• Journal of the Korean GEO-environmental Society
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• v.4 no.3
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• pp.79-88
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• 2003

This paper presents a numerical study of the spatial behavior of a linear absorbing solute in a heterogeneous porous medium. The spatially correlated log-normal hydraulic conductivity field is generated in a given two-dimensional domain by using the geostatistical method (Turning Bands algorithm). The velocity vector field is calculated by applying the two-dimensional saturated groundwater flow equation to the Galerkin finite element method. The simulation of solute transport is carried out by using the random walk particle tracking model with CD(constant displacement) scheme in which the time interval is automatically adjusted. In this study, the spatial behavior of a solute is analyzed by the longitudinal center-of-mass displacement, longitudinal spatial spread moment and longitudinal plume skewness.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Wind and Structures
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• v.13 no.1
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• pp.57-82
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• 2010

The 486m-long roof of Shenzhen Citizens Centre is one of the world's longest spatial lattice roof structures. A comprehensive numerical study of wind effects on the long-span structure is presented in this paper. The discretizing and synthesizing of random flow generation technique (DSRFG) recently proposed by two of the authors (Huang and Li 2008) was adopted to produce a spatially correlated turbulent inflow field for the simulation study. The distributions and characteristics of wind loads on the roof were numerically evaluated by Computational Fluid Dynamics (CFD) methods, in which Large Eddy Simulation (LES) and Reynolds Averaged Navier-Stokes Equations (RANS) Model were employed. The main objective of this study is to explore a useful approach for estimations of wind effects on complex curved roof by CFD techniques. In parallel with the numerical investigation, simultaneous pressure measurements on the entire roof were made in a boundary layer wind tunnel to determine mean, fluctuating and peak pressure coefficient distributions, and spectra, spatial correlation coefficients and probability characteristics of pressure fluctuations. Numerical results were then compared with these experimentally determined data for validating the numerical methods. The comparative study demonstrated that the LES integrated with the DSRFG technique could provide satisfactory prediction of wind effects on the long-span roof with complex shape, especially on separation zones along leading eaves where the worst negative wind-induced pressures commonly occur. The recommended LES and inflow turbulence generation technique as well as associated numerical treatments are useful for structural engineers to assess wind effects on a long-span roof at its design stage.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.75-80
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• 2005

A new antenna shuffling scheme for double space time transmit diversity is proposed. The proposed method obtains the shuffling pattern directly from the estimated channel by maximizing minimum post-processing signal to noise ratio(SNR), while the conventional method minimizes channel correlation. Since the minimum post-processing SNR is directly related with error performance, the proposed method shows better bit error rate performance than the conventional method. Monte Carlo simulations showed that the proposed scheme has more 3 dB SNR gain than the conventional scheme for 10/sup -3/ bit error rate in spatially correlated fadingcaused by a single cluster model.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.18-28
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• 2015

Apple is cultivated under various climatic conditions in many parts of the world. Better understanding of how climate, genotype, soil, and management factors interact to determine crop productivity will improve our ability to optimize crop selection, management strategies, and resource use efficiencies. We developed and applied a physiology-based apple canopy model to evaluate how climatic factors and crop phenotypes interact to determine biomass accumulation, radiation use efficiency (RUE), and water use efficiency (WUE) at multiple production sites between western and eastern states of the US including WA, CA, NY, WV, and PA. Our results indicate that solar radiation is a dominant factor limiting biomass production in the eastern states while VPD is the primary factor governing crop water use across eastern and western states during the peak growing season. Crop RUE and WUE were strongly correlated in the western states but not in the eastern states while VPD showed highly negative correlation with both RUE and WUE across all locations. The RUE improved with increasing fraction of diffuse radiation ($f_{df}$) and the $RUE-f_{df}$ relationships revealed distinctive responses between western and eastern states. Overall, the eastern locations exhibited slightly higher RUE and WUE than the western locations. However, overall productivity and total water use were greater in the western states. A clear decline of productivity with increasing temperature and afternoon VPD past an optimum was predicted in the western locations but this pattern was less clear in the eastern locations. We also discuss potential phenotypes with specific physiological and morphological traits that are differentially suitable for western and eastern locations. Our results provide plausible, spatially explicit explanations and insights to disentangle the complex relationships between crop productivity, resource use efficiencies, phenotype, and climate drivers in apple grown in the US.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.397-408
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• 2009

In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.