• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.235-235
• /
• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.6
• /
• pp.3797-3806
• /
• 2015

A population decline in rural area is correlated with the number of household, with agricultural workers, as a result, affects the farming income. Agricultural population is a foundation of agriculture structure. Agricultural population decline influences agricultural policies to be implemented for the future and there is concern about slowdown in productivity. The purpose of this study is to build the ability to use the model and conduct applied analyses of various kinds and to make rational agricultural policies by forecasting and analyzing agricultural population change. Unlike previous studies, which have some assumptions about the giving-up farming rate (GFR) of the key points on the agricultural population model or, After estimating only one equation with respect to the total population, and then distribute by sex and age. This study was conducted to investigate the reactions are different from the farmhouse, gender, age by estimating giving-up farming rate (GFR) equations each gender & age. Through this research, we can find that Farm Population changes of the simulation can be performed for a variety of agricultural policy in conjunction with existing agricultural simulation models as well.

• Korean Journal of Environmental Biology
• /
• v.30 no.4
• /
• pp.307-313
• /
• 2012

The Oriental White Stork (Ciconia boyciana) is a representative wetland species distributed across East Asia. The species has been declined to face the threat of species extinctions with estimation of at about 3000 individuals. In order to re-introduce the endangered storks in the field, we developed a baseline model using the program VORTEX, performed sensitivity test, and finally suggested an ideal model based on results of the sensitivity test. The baseline model predicted 12.5% extinction probability with mean time to first extinction of 82.0 year. Sensitivity test revealed that two demographic variables (first-year mortality and percent of adult female breeding) had the greatest impacts on population persistence. Thus, corrected model improved the population persistence, where the extinction probability decreased to 1.0% in 100 years by changing values of two variables within a range of applicable to the population. Our models for stork re-introduction suggest this population will be stable by improving first-year mortality and adult female fecundity.

• Journal of The Korean Astronomical Society
• /
• v.23 no.1
• /
• pp.71-82
• /
• 1990

Theoretical calculations of the combined radiative transfer and statistical equilibrium equation including the charge-particle conservations have been earned out for a multilevel hydrogen atom in quiescent prominences. Cool and dense models show the steep changes of population and radiation field in the vicinity of the surface, while these physical quantities remain unchanged for models with temperature of 7,300K, regardless of total densities. Ionization rate of hydrogen atom related with metallic line formation varies in considerable amounts from the surface to the center of model prominences cooler than 6,300K. However, such cool models cannot release enough hydrogen line emissions to explain observed intensities. Prominence models with a temperature higher than 8,000K can yield the centrally reversed Lyman line profiles confirmed by satellite EUV observations. We find that queiscent prominence with a density between $2{\times}10^{11}$ and $10^{12}cm^{-3}$ should be in temperature range between 6,300K and 8,300K, in order to explain consistently observed H alpha, beta line emissions and $n_p/n_l$ ratio.

• Advances in Computational Design
• /
• v.8 no.1
• /
• pp.37-59
• /
• 2023

Squat reinforced concrete (SRC) shear walls are a critical part of the structure for both office/residential buildings and nuclear structures due to their significant role in withstanding seismic loads. Despite this, empirical formulae in current design standards and published studies demonstrate a considerable disparity in predicting SRC wall shear strength. The goal of this research is to develop and evaluate hybrid and ensemble artificial neural network (ANN) models. State-of-the-art population-based algorithms are used in this research for hybrid intelligence algorithms. Six models are developed, including Honey Badger Algorithm (HBA) with ANN (HBA-ANN), Hunger Games Search with ANN (HGS-ANN), fitness-distance balance coyote optimization algorithm (FDB-COA) with ANN (FDB-COA-ANN), Averaging Ensemble (AE) neural network, Snapshot Ensemble (SE) neural network, and Stacked Generalization (SG) ensemble neural network. A total of 434 test results of SRC walls is utilized to train and assess the models. The results reveal that the SG model not only minimizes prediction variance but also produces predictions (with R²= 0.99) that are superior to other models.

• Genomics & Informatics
• /
• v.21 no.2
• /
• pp.27.1-27.7
• /
• 2023

Recombination events complicate the evolutionary history of populations and species and have a significant impact on the inference of isolation-with-migration (IM) models. However, several existing methods have been developed, assuming no recombination within a locus and free recombination between loci. In this study, we investigated the effect of recombination on the estimation of IM models using genomic data. We conducted a simulation study to evaluate the consistency of the parameter estimators with up to 1,000 loci and analyze true gene trees to examine the sources of errors in estimating the IM model parameters. The results showed that the presence of recombination led to biased estimates of the IM model parameters, with population sizes being more overestimated and migration rates being more underestimated as the number of loci increased. The magnitude of the biases tended to increase with the recombination rates when using 100 or more loci. On the other hand, the estimation of splitting times remained consistent as the number of loci increased. In the absence of recombination, the estimators of the IM model parameters remained consistent.

• IMMUNE NETWORK
• /
• v.21 no.2
• /
• pp.12.1-12.17
• /
• 2021

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the emergence of SARS-CoV-2 in the human population in late 2019, it has spread on an unprecedented scale worldwide leading to the first coronavirus pandemic. SARS-CoV-2 infection results in a wide range of clinical manifestations from asymptomatic to fatal cases. Although intensive research has been undertaken to increase understanding of the complex biology of SARS-CoV-2 infection, the detailed mechanisms underpinning the severe pathogenesis and interactions between the virus and the host immune response are not well understood. Thus, the development of appropriate animal models that recapitulate human clinical manifestations and immune responses against SARS-CoV-2 is crucial. Although many animal models are currently available for the study of SARS-CoV-2 infection, each has distinct advantages and disadvantages, and some models show variable results between and within species. Thus, we aim to discuss the different animal models, including mice, hamsters, ferrets, and non-human primates, employed for SARS-CoV-2 infection studies and outline their individual strengths and limitations for use in studies aimed at increasing understanding of coronavirus pathogenesis. Moreover, a significant advantage of these animal models is that they can be tailored, providing unique options specific to the scientific goals of each researcher.

• KDI Journal of Economic Policy
• /
• v.39 no.2
• /
• pp.25-51
• /
• 2017

This paper employs an Overlapping Generations Model to quantify the impacts of Korea's demographic transition toward an older population on the total output growth rate. The model incorporates the projected population through 2060 according by Statistics Korea. The effects of the low fertility and increased life expectancy rates are studied. The model is considered suitable for analyzing the effects of demographic changes on the Korean economy. Under the assumption that the TFP growth rate will not slow considerably in the future, remaining at 1.3% per annum, the gross output growth rate of the Korean economy is projected to slow to 1.1% per annum in the 2050s, from 4.0% in the 2000s. The shrinking workforce due to the decline in fertility plays a significant role in the deceleration of the Korean economy. The increased life expectancy rate is expected to mitigate the negative effect, but the magnitude of its effect is found to be limited.

• Journal of Environmental Science International
• /
• v.20 no.2
• /
• pp.155-161
• /
• 2011

In application and discussion of population structure and phenotypic divergence in plant community, the classic Lotka-Volterra models of competition and spatial model are conceived as a mechanism that is composed by multiple interacting processes. Both the Lotka-Volterra and spatial simulation formulae predict that species diversity increases with genotypic richness (GR). The two formulae are also in agreement that species diversity generally decreases within increasing niche breadth (NB) and increases with increasing potential genotypic range (PGR). Across the entire parameter space in the Lotka-Volterra model and most of the parameter space in the spatial simulations, variance in community composition decreased with increasing genotypic richness. This was, in large part, a consequence of selecting genotypes randomly from a set pool.

• Journal of the Korean Society for Railway
• /
• v.9 no.3 s.34
• /
• pp.271-276
• /
• 2006

Insight into behaviour of pedestrians as welt as tools to assess passenger flow condition is important in such instances as planning and geometric design of railway station under regular and safety-critical circumstances. Algorithm for passenger flow analysis based on DEM (Discrete Element Method) is newly developed. There are lots of similarity between particle-laden two phase flow and passenger flow. The velocity component of 1st phase corresponds to the unit vector of calculation cell, each particle to passenger, volume fraction to population density and the particle velocity to the walking velocity, etc. And, the walking velocity of passenger is also represented by the function of population density. Key algorithms are developed to determine the position of passenger, population density and numbering to each passenger. To verify the effectiveness of new algorithm, passenger flow analysis for the basic models of railway station is conducted.