• Title/Summary/Keyword: Genetic evaluation

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Evaluation of Riverine Microbial Diversity using the Culture-Independent Genetic Fingerprinting Technique (T-RFLP) (유전자지문분석법(T-RFLP)을 이용한 하천 미생물의 다양성 평가)

  • Jeong, Ju-Yong;Lee, Kyong-Hee
    • Journal of Korean Society on Water Environment
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    • v.24 no.2
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    • pp.195-200
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    • 2008
  • To analyze the riverine microbial community structure, genetic fingerprints and ecological indexes such as species abundances, diversity, evenness, dominance of targeted rivers in Gyeonggi Province were acquired and evaluated using terminal restriction fragment length polymorphism (T-RFLP) technique. Genetic fingerprinting technique such as T-RFLP, which is able to show the microbial community clearly unlike traditional culture-dependent techniques, was thought to be useful to analyse the riverine microbial ecosystem under various factors. Riverine ecosystem evaluation using visible organisms would give biased results with time, targeted organism and researcher. But, T-RFLP, which can exclude the subjected biases such as culture condition and identification, would be an option to understand natural ecosystem by including the microorganisms that defy culture but perform important functions.

An Optimum Design Method of Hypoid Gear by Minimizing Volume (하이포이드 기어의 체적 최소화 최적 설계)

  • Lee, Ki-Hun;Lee, Geun-Ho;Bae, In-Ho;Chong, Tae-Hyong
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.6
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    • pp.55-61
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    • 2007
  • The hypoid gear has advantage for the high reduction ratio and compactness. But, geometry design and strength evaluation of the hypoid gear depend on the machine tool of specific production companies because the geometry design and strength evaluation of the hypoid gear are complex and difficult. This paper proposes the development of the design programs to satisfying the geometry and strength of a hypoid gear through optimization technique using the genetic algorithm. The genetic algorithm is designed to optimize a method for minimizing volume. The existing design of hypoid gear in the forklift truck axle is compared with the results of developed optimum design program.

Challenges for QTL Analysis in Crops

  • Long, Yan;Zhang, Chunyu;Meng, Jinling
    • Journal of Crop Science and Biotechnology
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    • v.11 no.1
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    • pp.7-12
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    • 2008
  • Quantitative trait loci, a genetic concept for explaining the inheritance of non-Mendelian traits in 1940s, have been realized as particular fragments of chromosome even unique genes in most crops in 21st century. However, only very a small portion of QTL has been screened out by geneticists comparing to a great number of genes underneath the quantitative traits. These identified QTL even have been seldom used into breeding program because crop breeders may not find the QTL in their breeding populations in their field station. Several key points will be proposed to meet the challenges of QTL analysis today: a fine mapping population and the related reference genetic map, QTL evaluation in multiple environments, recognizing real QTL with small genetic effect, map integration.

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A Study on Optimal Design of Rocker Arm Shaft Using Improved Genetic Algorithm (개선된 유전자 알고리즘을 이용한 로커암 축의 최적설계에 관한 연구)

  • Lee Soo Jin;An Yong Su;Lee Dong Woo;Cho Seok Swoo;Joo Won Sik
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.6 s.237
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    • pp.835-841
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    • 2005
  • This study proposes a new optimization algorithm which is combined with genetic algorithm and ANOM. This improved genetic algorithm is not only faster than the simple genetic algorithm, but also gives a more accurate solution. The optimizing ability and convergence rate of a new optimization algorithm is identified by using a evaluation function which have several local optimum and an optimum design of rocker arm shaft. The calculation results are compared with the simple genetic algorithm.

Second-trimester fetal genetic ultrasonography to detect chromosomal abnormalities

  • Hong, Seong-Yeon
    • Journal of Genetic Medicine
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    • v.11 no.2
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    • pp.49-55
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    • 2014
  • Genetic ultrasonography refers to the evaluation of risk of chromosomal abnormalities via various soft sonographic markers. Although the maternal serum test is the primary screening method for chromosomal abnormalities, genetic ultrasonography is also widely used and can help increase detection rates. To date, many soft markers, including choroid plexus cysts, echogenic intracardiac foci, mild ventriculomegaly, nuchal fold thickening, echogenic bowel, mild pyelectasis, short femur and humerus length, and absent or hypoplastic nasal bone, have been reported. An aberrant right subclavian artery was the most novel soft marker introduced. Because these soft markers involve diverse relative risks of chromosomal abnormalities, it is difficult to apply them to clinical practice. To optimize the efficacy of genetic ultrasonography, it is important to understand the precise relative risks of chromosomal abnormalities innumerous soft markers and integrate these risks with each other and the results of maternal serum screening.

Genetic and Phenotypic Evaluation of Milk and Fat Production Traits and Their Interrelationship in (Zebu×European) Crossbred Cattle Using Parent Group Mixed Model

  • Singh, D.;Yadav, A.S.;Dhaka, S.S.
    • Asian-Australasian Journal of Animal Sciences
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    • v.16 no.9
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    • pp.1242-1246
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    • 2003
  • Data pertained to 335 crossbred cows comprising of 1/2 Friesian (F) + 1/2 Hariana (H), 1/2 F + 1/4 Jersey (J) + 1/4 H, 1/2 F + 1/4 Brown Swiss (BS) + 1/4 H, 1/2 F + 1/4 Red Dane (R) + 1/4 H, FR (I) and FRH (I) genetic groups extending over a period of 21 years (1970-1990) maintained at Animal Farm of CCS HAU, Hisar. The averages for first lactation milk yield was $2,486.24{\pm}80.26kg$ and peak yield of first three lactation were $11.35{\pm}0.72kg$, $13.97{\pm}0.60kg$ and $16.02{\pm}0.42kg$, respectively. The lifetime milk production was observed as $11,305.16{\pm}1,004.52kg$ in crossbred cattle. The average first lactation fat yield was observed as $102.06{\pm}0.01kg$ and peak fat yield of first three lactation were $0.458{\pm}0.01$, $0.490{\pm}0.01$ and $0.500{\pm}0.02kg$, respectively. The lifetime fat production was estimated as $502.31{\pm}45.90kg$. LTMP and LTFP had reasonably good additive genetic variance which could be exploited either through mass selection/combined with family or pedigree selection. FLMY, peak yields and LTMP had significant positive phenotypic correlation with FLFY and LTFP and the correlation at the genetic level were also higher and positive for these traits. Finally, peak week milk yield of first lactation (PMY1) was the earliest available trait having desirable and significant correlation at phenotypic and positive at genetic level with FLFY, PFY1 and PFY2, PFY3 and LTFP and selection for this trait will help in early evaluation of sires and dams and will increase genetic advancement per unit of time.

Genetic diversity and relationship of Korean chicken breeds using 12 microsatellite markers

  • Kim, Yesong;Yun, Ji Hye;Moon, Seon Jeong;Seong, Jiyeon;Kong, Hong Sik
    • Journal of Animal Reproduction and Biotechnology
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    • v.36 no.3
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    • pp.154-161
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    • 2021
  • A number of Korean Chicken breeds were registered in Domestic Animal Diversity Information System (DAD-IS, http://dad.fao.org/) of the Food and Agriculture Organization (FAO). Evaluation of genetic diversity and relationship of local breeds is an important factor towards the identification of unique and valuable genetic resources. Therefore, this study aimed to analysis the genetic diversity and relationship of 22 Korean Chicken breeds using 12 microsatellite (MS) markers. The mean number of alleles for each variety was 5.52, ranging from a 3.75 (Leghorn F; NF) to a 7.0 (Ross). The most diverse breed was the Hanhyup3 (HCC), which had the highest expected heterozygosity (HExp) (0.754) and polymorphic information content (PIC) (0.711). The NF was the least diverse population, having the lowest HExp (0.467) and PIC (0.413). As a result of the principal coordinates analysis (PCoA) and factorial correspondence analysis (FCA) confirmed that Hy-line Brown (HL) and Lohmann Brown (LO) are very close to each other and that Leghorn and Rhode Island Red (RIR) are clearly distinguished from other groups. Thus, the reliability and power of identification using 12 types of MS markers were improved, and the genetic diversity and probability of individual discrimination were confirmed through statistical analysis. This study is expected to be used as basic data for the identification of Korean chicken breeds, and our results indicated that these multiplex PCR marker sets will have considerable applications in population genetic structure analysis.

Fuzzy DEA via Genetic Algorithms (Genetic Algorithm을 적용한 Fuzzy DEA에 관한 연구)

  • Choi, Hong;Son, So-Yeong
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.04a
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    • pp.569-572
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    • 2000
  • DEA has been effectively applied to various areas which need the evaluation of relative efficiency. We propose a DEA model based on fuzzy LP combined with Genetic Algorithm in order to consider uncertain synergy effects due to M&A of existing organization. We apply the suggested approach to forecasting the efficiency of merged academic departments in a university in Korea. We expect that our approach can be utilized to effectively realign existing departments.

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A Study of Data Mining Optimization Model for the Credit Evaluation

  • Kim, Kap-Sik;Lee, Chang-Soon
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.825-836
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    • 2003
  • Based on customer information and financing processes in capital market, we derived individual models by applying multi-layered perceptrons, MDA, and decision tree. Further, the results from the existing single models were compared with the results from the integrated model that was developed using genetic algorithm. This study contributes not only to verifying the existing individual models and but also to overcoming the limitations of the existing approaches. We have depended upon the approaches that compare individual models and search for the best-fit model. However, this study presents a methodology to build an integrated data mining model using genetic algorithm.

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