• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.115-126
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• 2023

Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

• Animal Bioscience
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• v.37 no.4
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• pp.576-590
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• 2024

Objective: The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. Methods: A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-year-season, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. Results: A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Conclusion: Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

• Animal Bioscience
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• v.37 no.5
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.337-347
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• 2019

This study proposes the framework to select the representative general circulation model (GCM) for climate change projection. The grid-based results of GCMs were transformed to all considered meteorological stations using inverse distance weighted (IDW) method and its results were compared to the observed precipitation. Six quantile mapping methods and random forest method were used to correct the bias between GCM's and the observation data. Thus, the empirical quantile which belongs to non-parameteric transformation method was selected as a best bias correction method by comparing the measures of performance indicators. Then, one of the multi-criteria decision techniques, TOPSIS (Technique for Order of Preference by Ideal Solution), was used to find the representative GCM using the performances of four GCMs after the bias correction using empirical quantile method. As a result, GISS-E2-R was the best and followed by MIROC5, CSIRO-Mk3-6-0, and CCSM4. Because these results are limited several GCMs, different results will be expected if more GCM data considered.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.38 no.6
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• pp.499-506
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• 1993

The contents of sulfur, sulfur-containing protein and amino acids of soybean seeds of 518 genotypes as well as their inheritance and selection efficiency in early breeding generation were measured to facilitate breeding for soybean with high sulfur-containing amino acids. Average seed sulfur content of 518 cultivars was 0.33%, and ranged from 0.20 to 0.45%, and that of 30 wild soybeans was 0.35%, and ranged form 0.19 to 0.62%. Correlation coefficients between seed sulfur content and sulfur-containing protein and amino acids were 0.924$^{**}$ and 0.974$^{**}$, respectively. Seed sulfur content was tended to be high in soybean genotypes with late maturity, seed coat bloom, or green cotyledon. Sulfur content had -0.312$^{**}$ correlation coeficient with sugar content and -0.384$^{**}$ with 100 seed weight. Seed sulfur content was inherited quantitatively, in which additive effect was greater than dominant one, and proportion of genes with positive effects was similar to those with negative ones. Estimated narrow- and broad-sense heritabilities were 0.75 and 0.88 for seed sulfur content, respectively. Heritability measured from selection in early breeding lines for high or low seed sulfur content was 60～62.5% or 50～62,5%, respectively. And selection for high sulfur content increased by 14.7～18.8%, whereas that for low one decreased by 8.8～15.6%, when compared to that of random population. Therefore selection in early generation seemed to be clearly effective.

• Asian-Australasian Journal of Animal Sciences
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• v.5 no.4
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• pp.623-628
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• 1992

Records on weaning (3803) and yearling weight (2990) of beef cattle (Bibos banteng) from the Bali Cattle Improvement Project were examined. A mixed model analysis involving all main non-genetic effects (village, year of birth, season of birth, age of dam, sex of calf, all significant interactions and age at weighing as a covariate) as fixed effects and sire nested within village as a random effect was undertaken. Variance components were estimated by Henderson's Method III. Paternal half-sib components of variance and covariance were used to estimate heritabilities of weaning and yearling weights, as well as their genetic and phenotypic correlations. Heritability estimates ($\pm$ standard error) obtained by Henderson's Method III for weaning and yearling weights were $.11{\pm}.03$ and $.13{\pm}.04$, respectively while the phenotypic and genetic correlations were estimated as .32 and $.64{\pm}.10$, respectively. The parameters estimated in this study were at the lower end of the range of reported values from various breeds. It is concluded that further information should be gathered to assist in estimating genetic parameters for other economic traits of Bali beef cattle and to provide more accurate estimates for weaning and yearling weights. These parameters should then be used to formulate a selection program to enable the genetic improvement of Bali Beef cattle.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.359-366
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• 2005

Most engineering optimization are based on numerical linear and nonlinear programming methods that require substantial gradient information and usually seek to improve the solution in the neighborhood of a starting point. These algorithm, however, reveal a limited approach to complicated real-world optimization problems. If there is more than one local optimum in the problem, the result may depend on the selection of an initial point, and the obtained optimal solution may not necessarily be the global optimum. This paper describes a new harmony search(HS) meta-heuristic algorithm-based approach for structural size optimization problems with continuous design variables. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. Two classical space truss optimization problems are presented to demonstrate the effectiveness and robustness of the HS algorithm. The results indicate that the proposed approach is a powerful search and optimization technique that may yield better solutions to structural engineering problems than those obtained using current algorithms.

• Human Ecology Research
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• v.55 no.3
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• pp.289-301
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• 2017

This study was to analyze the effects of the career education program for students with disabilities. The analysis was performed based on two research questions. First, the total effect size on the career program for students with disabilities was considered. Second, the difference of the effect size between the sub-groups regarding dependency variables, types of disabilities, types of schools, number of people, and number of sessions was also included for analysis. For this, the author reviewed a database and analyzed 12 previous studies, presented in five master thesis and seven Korean journals from 2005 to 2015 based on the author's selection criteria. Subsequently, 27 effect size was found. The publication bias was analyzed by Rosenthal's fail-safe N. The overall effect size for all studies on the random effect model was 1.717, which was positive and high in value. Given the heterogeneity among the effect size, the subgroup analysis was conducted, and indicated that the effect size was significantly high when the purpose of the program was related to the student's self-decision ability. The results demonstrated that the programs were specified for students with intellectual disabilities, when the schools were elementary, when the number of students in a group was 1-10, and when program sessions lasted more than 21 times, the effect size was high. Implication for the future research and program implication were discussed on these findings.

• Genomics & Informatics
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• v.15 no.4
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• pp.123-127
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• 2017

Synonymous sites are generally considered to be functionally neutral. However, there are recent contradictory findings suggesting that synonymous alleles might have functional roles in various molecular aspects. For instance, a recent study demonstrated that synonymous single nucleotide polymorphisms have a similar effect size as nonsynonymous single nucleotide polymorphisms in human disease association studies. Researchers have recognized synonymous codon usage bias (SCUB) in the genomes of almost all species and have investigated whether SCUB is due to random nucleotide compositional bias or to natural selection of any functional exposure generated by synonymous mutations. One of the most prominent observations on the non-neutrality of synonymous codons is the correlation between SCUB and levels of gene expression, such that highly expressed genes tend to have a higher preference toward so-called optimal codons than lowly expressed genes. In relation, it is known that amounts of cognate tRNAs that bind to optimal codons are significantly higher than the amounts of cognate tRNAs that bind to non-optimal codons in genomes. In the present paper, we review various functions that synonymous codons might have other than regulating expression levels.