• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.297-300
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• 1997

This paper uses genetic algorithm (GA) for optimal control. GA can find optimal control profile, but the profile may be oscillating feature. To make profile smooth, fuzzy genetic algorithm (FGA) is proposed. GA with fuzzy logic techniques for optimal control can make optimal control profile smooth. We describe the Fuzzy Genetic Algorithm that uses a fuzzy knowledge based system to control GA search. Result from the simulation example shows that GA can find optimal control profile and FGA makes a performance improvement over a simple GA.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.229-232
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them..

• Transactions of Materials Processing
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• v.16 no.4 s.94
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• pp.250-253
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.12
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• pp.1718-1734
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• 2009

The aim of this review is to address some characteristics that influence meat quality. Genetic groups, nutrition, finishing systems and gender are the major factors that change carcass characteristics, chemical composition and fatty acid profile. Genetic groups that have zebu genes in their composition show higher hot carcass dressing than genetic groups without zebu genes. Genetic groups that have European breeds in their composition have higher marbling scores. On the other hand, genetic groups that have zebu breeds show low marbling scores. Bulls finished in feedlots present higher final weight than steers, cull cows and heifers. Fat thickness is one of the principal parameters that are affected by different gender. Cull cows (4.72 mm) and heifers (4.00 mm) present higher values than bulls (1.75 mm) and steers (2.81 mm). The major effects observed by different systems of termination are fat thickness and marbling. Crude protein presents variation due to nutrition. Nutrition influences variation of fatty acid profile. Genetic groups also influence fatty acid profile. Genetic groups that have zebu genes in their composition show high percentage of PUFA. The major class of fatty acids that is changed with nutrition is PUFA. The better ratios of PUFA/SFA and n-6/n-3 are found in Longissimus muscle of animals finished in pasture systems.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1035-1039
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• 2000

This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1986-1989
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• 2003

This paper proposes the information retrieval improvement for the Web using the structure and hyperlinks of HTML documents along with user profile. The method bases on the rationale that terms appearing in different structure of documents may have different significance in identifying the documents. The method partitions the occurrence of terms in a document collection into six classes according to the tags in which particular terms occurred (such as Title, H1-H6 and Anchor). We use genetic algorithm to determine class importance values and expand user query. We also use this value in similarity computation and update user profile. Then a genetic algorithm is used again to select some terms from user profile to expand the original query. Lastly, the search engine uses the expanded query for searching and the results of the search engine are scored by similarity values between each result and the user profile. Vector space model is used and the weighting schemes of traditional information retrieval were extended to include class importance values. The tested results show that precision is up to 81.5%.

• Korean Journal of Plant Taxonomy
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• v.53 no.1
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• pp.14-24
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• 2023

Saussurea dorogostaiskii Palib. (Asteraceae) is a critically endangered medicinal plant in Mongolia and Russia. We studied the genetic variation of S. dorogostaiskii from three mountains of northern Mongolia. The genetic profile was assessed in 70 individuals from eight populations using five inter-simple sequence repeat markers, producing 53 loci with 96.4% polymorphism across all bands. Shannon's index (I) and Nei's gene diversity (H) value at the species level of S. dorogostaiskii are 0.25 and 0.17, respectively. An AMOVA showed high genetic variation among the populations (22% of populations and 32% of mountains), consistent with the high genetic differentiation (G_ST = 0.49) and low gene flow (N_m = 0.51) in S. dorogostaiskii populations. Eight populations were clustered into two groups, corresponding to their geographic locations. The low within-population genetic diversity and high genetic differentiation among S. dorogostaiskii populations factor into their endangered designation. This genetic analysis reveals that all populations are equally threatened, and community-based conservation is appropriate for these species.

• Journal of Life Science
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• v.16 no.2 s.75
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• pp.345-351
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• 2006

Streptococcus sp. were isolated from cultured flounder (Paralichthys olivaceus) having Streptococcosis during 2004 to 2005 in Jeju Island. Ninety four Streptococcus iniae strains were isolated using biochemical test and multiplex PCR assay. Three genotypes (A, B, C-type) of S. iniae were appeared in the RAPD analysis and they showed international or local genetic polymorphism. Presently, S. iniae having A-type is a dominant S. iniae genotype in Jeju and showed band patterns at about 550, 850, 1000, 1300 and 2000 base pares. In this study, the reported P14 random primer, that used to distinguish serotypes of S. iniae could not be applied to distinguish Jeju island S. iniae's genetic polymorphism.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.90-96
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• 1996

This paper presents a method that determines the stern profile dimensions for full, slwo-speed ship using fuzzy modeling, which is applied the genetic algorithm and the Hooke & Jeeves method. The infreed stern profile dimensions have compared with real ships.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.6
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• pp.607-612
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• 2012

The wear problem of wheel flange occurs at sharp curves of rail. This paper proposes a procedure for optimum design of a wheel profile wherein flange wear is reduced by improving an interaction between wheel and rail. Application of optimization method to design problem mainly depends on characteristics of design space. This paper compared local optimization method with global optimization according to sensitivity value of objective function for design variables to find out which optimization method is appropriable to minimize wear of wheel flange. Wheel profile is created by a piecewise cubic Hermite interpolating polynomial and dynamic performances are analyzed by a railway dynamic analysis program, VAMPIRE. From the optimization results, it is verified that the global optimization method such as genetic algorithm is more suitable to wheel profile optimization than the local optimization of SQP (Sequential Quadratic Programming) in case of considering the lack of empirical knowledge for initial design value.