• Journal of Animal Science and Technology
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• v.53 no.5
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• pp.397-408
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• 2011

The study was carried to identify the impact on nation-wide genetic evaluation and to obtain basic materials for the development of strategies in Swine Improvement Network Project (SINP). Data consisted of pedigree records of 235,511 and performance records of 70,747 for Duroc from 1987 to 2010 were collected by Korea Animal Improvement Association. Performance traits included three point back fat thickness (Shoulder, Belly, Waist), loin area, days to 90 kg and average daily gain. Exchange of genetic resources cross the breeding farms was not high, and furthermore the sizable farms which can accommodate genetic evaluation within the farm were scarce. Three data sets (individual farm evaluation: I, two sub-group evaluation: S, and whole eight farm evaluation: P) were used for genetic analysis. Genetic variances were larger in subordinate farms than in joiners farms for connectedness, and consequently the heritabilities were generally higher in subordinate farms than in joiner farms with I. The standard errors of heritability were small in the order of I, S and P. Estimated average inbreeding coefficients were 1.12%, 0.95% and 1.53% for joiner and subordinate group with S and population with P, respectively. The estimated correlations of breeding values with I and P were lowest. The correlations of breeding values with I and P for traits ranged 0.22 to 0.45 for moved parent animals and 0.24 to 0.72 for all animals. The results in the study suggest that nation-wide evaluation uses more pedigree information and improves accuracy. Furthermore SINP for connectedness could help to improve the accuracy of evaluation.

• Proceedings of the Botanical Society of Korea Conference
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• 1995.07a
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• pp.133-170
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• 1995

The major objectives of fruit breeding lie in improvement of cultivar, easy to be cultivated and of high quality, in order to produce unexpensive, delicious fruit both for fresh fruit market and processing. Recently, fruit breeding in Korea has contributed to breeding of several superior cultivars in major fruit crops, resulting in appreciable improvement in qualities such as skin color, taste and fruit-bearing habit concerned with productivity. In spite of accomplishments mentioned above, the need for both highly disease-resistant cultivars and long-keeping, physiological disorder-resistant cultivars to meet long distance transsportation in the temperate fruit crops of apples, oriental pears, stone fruits such as peaches, and grapes grown in Korea is rapidly pressing more than ever, as cultivars of today susceptible to pests and diseases and vulnerable to physiological disorders are very expensive and time-consuming in post-harvest handling and management. Thus, imporvements made in the above problems through breeding level will lead to the really enhanced productivity in fruit industry. The major impediments of tree size, the long length of juvenile period and the highly heterogeneous genetic composition to the improvement of fruit crops are responsible for the lower amount and rate of improvements of fruit crops as compared to annuals. Considering the expected limitations of the above problems to be solved through conventional breeding methods and strategy, a turning point of breeding a near perfect cultivar would be laid down if innovative breakthroughs in biological technology will be realized in applying some of the techniques of genetic manipulation at the molecular level to the cultivar improvement of fruit crops, such as the selective insertion of DNA carrying genes that govern desirable characteristics. More than anything else, those traits such as fruiting habit deciding productivity, elements of fruit qualities conditioned by monogene, and disease-and pest-resistance of vital importance for successful fruit growing are urgently desired to be improved by advancement of biotechnology for they are more than difficult and need long period to be attained through conventional breeding method.

• Journal of agriculture & life science
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• v.44 no.2
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• pp.29-38
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• 2010

This study looked into estimation of variance component over swine's economic traits by multiple animal model and maternal effect model using on-farm test data of total 31,455 swine of Duroc, Landrace and Yorkshire species that were born between 2000 and 2008. Heritability by estimated additive genetic effect showed higher than one by maternal genetic effect using multivariate maternal animal model in each trait examined by each breed and most heritability when considering only additive genetic effect in multiple traits animal model was estimated to be higher than one by estimated additive genetic effect in multivariate maternal animal model. In correlation between breeding value by estimated maternal genetic effect and phenotypic value using multivariate maternal animal model, rank correlation and simple correlation of breeding value and phenotypic value by maternal genetic effect also showed low positive correlation or strong negative correlation, which can be considered that if correlation with phenotype were increased properly considering maternal genetic effect in each trait by each breed, even better improvement could be promoted.

• ANNALS OF ANIMAL RESOURCE SCIENCES
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• v.29 no.4
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• pp.142-149
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• 2018

In this study, 844 Hanwoo proven bulls in South Korea (called KPN) were classified into 8 groups based on their birth year. Microsatellite (MS) marker information for paternity identification of each individual is provided at the homepage of the National Agricultural Cooperation Federation, Korea (NACF) and is mainly for the analysis of genetic diversity and structural changes. The polymorphism analysis of KPN whole groups revealed the average number of alleles in each marker (number of alleles), the expected heterozygosity ($H_{ex}$), the observed heterozygosity ($H_{ob}$), the polymorphism information content (PIC) and the $F_{is}$ mean as 10.54, 0.764, 0.773, 0.727 and -0.014, respectively. For group D, with the birth year 2004-2005, the $H_{ex}$ and $H_{ob}$ were 0.777 and 0.792 respectively and the PIC was 0.740. The $H_{ex}$ of group C and D, with birth years 2003-2004 and 2007-2008, respectively, were greater than $H_{ob}$. In all the other groups, $H_{ob}$ was greater than $H_{ex}$. Genetic composition and structure were analyzed using STRUCTURE software. According to the analyzed results, the generation of Hanwoo groups showed changes in specific genetic components according to the flow. It was confirmed that the continuous improvement in the Hanwoo affects the genetic structure of the proven bulls group. The results of this study are expected to be used for enhancing the efficiency of Hanwoo improvement project.

• Computers and Concrete
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• v.14 no.4
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• pp.479-501
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• 2014

This paper presents the improvement of the EC-2 and EHE-08 shear strength formulations for concrete beams with shear reinforcement. The employed method is based on the genetic programming (GP) technique, which is configured to generate symbolic regression from a set of experimental data by considering the interactions among precision, accuracy, safety and simplicity. The size effect and the influence of the amount of shear reinforcement are examined. To develop and verify the models, 257 experimental tests on concrete beams from the literature are used. Three expressions of considerable simplicity, which significantly improve the shear strength prediction with respect to the formulations of the different studied codes, are proposed.

• Korean Journal of Animal Reproduction
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• v.20 no.4
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• pp.365-370
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• 1997

Historical programs for genetic improvement of dairy cattle are discussed in the context of new genetic technologies resulting in a hetero zygous gain of function. Concepts are outlined pointing to the importance of breaking the well established genetic correlation between fat content and protein content of milk to provide flexibility in the dairy industry. The concept of value added genetics is introduced and the econ omic mpetitiveness of the mammary glands of livestock are considered in relationship to mammalian cell culture bacterial fermentation technology.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.430-438
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• 2004

Among the optimization method, GA (genetic algorithm) is a very powerful searching method enough to compete with design sensitivity analysis method. GA is very easy to apply, since it dose not require any design sensitivity information. However, GA has been computationally not efficient due to huge repetitive computation. In this study, parallel computation is adopted to Improve computational efficiency, Paralleled GA is introduced on a clustered LINUX based personal computer system.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.67-70
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• 2009

Nesting and cutting path optimization have a great effect on the improvement of productivity in many industries such as shipbuilding, automotive, clothing, and so on. However, few researches have been carried out for the optimization of a cutting path algorithm. This study proposed a new method for cutting optimization using gravity center of cutting pieces and a genetic algorithm. The proposed method was tested for a sample plate including many different shapes of cutting pieces and compared to 2 other conventional methods. The test results showed that the new method had the shortest cutting path and the best effectiveness among the 3 methods.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.182-191
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• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.175-184
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• 2009

In this paper, a method for optimal measurement placement in the problem of static harmonic state estimation in power systems is proposed. At first, for achieving to a suitable method by considering the precision factor of the estimation, a procedure based on Genetic Algorithm (GA) for optimal placement is suggested. Optimal placement by regarding the precision factor has an evident solution, and the proposed method is successful in achieving the mentioned solution. But, the previous applied method, which is called the Sequential Elimination (SE) algorithm, can not achieve to the evident solution of the mentioned problem. Finally, considering both precision and economic factors together in solving the optimal placement problem, a practical method based on GA is proposed. The simulation results are shown an improvement in the precision of the estimation by using the proposed method.