• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.355-359
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• 2003

In this paper, an identification method for a first order dead time process is proposed. This method used the genetic algorithm for parameter identification of process. The proposed method gives a better identification result than the existing methods under step testing. The effectiveness of the identification method has been demonstrated through a number of simulation examples.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.9-11
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• 2005

We propose a optimal identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally identity we use genetic algorithm (GAs) sand Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the selected input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. Numerical example is included to evaluate the performance of the proposed model.

• Korean Journal of Organic Agriculture
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• v.12 no.4
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• pp.451-461
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• 2004

In an animals, identification system has been widely used by ear tag with dummy code and blood typing for parernity. Also, genotyping methods were using for useful mean of individual identification for live animals. In the case of genotyping estimation of gene in population of korean native chicken. In this study, we tested for development of genetic markers used it possible to determination of individual identification system. The candidate genetic markers were used already bow 10 of microstalite DNA sequence information in chromosome No. 1 and 14. Result of analysis for genotyping, the number of alleles of those microstatelites DNA was shown minimal 3 to 12 and the heterozygote expression frequency range was shown from 0.617 to 0.862. In our result, effective number of allele for each microsatellites DNA was shown 3~7, and the accuracy of individual identification was shown nearly 100%, when used with 6 genetic marker. This study was about genotyping method for identification used specific genetic marker form microsatellite DNA in the brand marketing of korean native chicken. Our results suggest that genotyping method used specific genetic marker from microsatellite DNA might be very useful for determination of individual identification.

• The Korea Journal of Herbology
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• v.37 no.5
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• pp.9-16
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• 2022

Objectives : The purpose of this study is to report that applying the genetic discrimination method to Pinelliae Tuber is suitable as a countermeasure for the limitations of morphological identification announced publicly in the Ministry of Food and Drug Safety(MFDS). Methods : Randomly selected fifty samples in Pinelliae Tuber imported from China were used for morphological and genetic identification. The morphological identification was applied method announced publicly by the MFDS. The traits of morphological identification were classified as Pinellia ternata, P. tripartita, Pinellia pedatisecta, and Typhonium flagelliforme, according to the formation of tuberous root and tuber morphology. The genetic identifications were conducted by Sequence Characterized Amplified Region(SCAR) marker and DNA barcoding analysis for cross-validation, respectively. SCAR marker was verified according to the presence or absence of amplicon through PCR amplification using species-specific primers. DNA barcoding analysis used sequence information of the matK region. Results : As a result of the morphological identification, 27 out of 50 samples were identified as original species 'P. ternata' of genuine 'Pinelliae Tuber', and 23 were identified as adulterant species 'P. pedatisecta'. Unlike this, the genetic identification was identified as the original species 'P. ternata' in all 50 samples in the SCAR marker and matK regional sequence analysis. Conclusions : Pinelliae Tuber of morphological mutant that can not be classified by morphological identification is imported from China. The SCAR marker would be used as accurate and efficient assays for species identification of the morphological mutant.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.1
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• pp.25-30
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• 2007

The capability of microsatellite markers for individual identification and their potential for breed assignment of individuals was evaluated in two Indian horse breeds. The strength of these individual assignment methods was also evaluated by increasing the number of loci in increments of five. The probability of identity of two random horses from the two breeds at all twenty five studied loci was as low as $1.08{\times}10^{-32}$ showing their suitability to distinguish between individual horses and their products. In the phylogenetic approach for individual assignment using Nei's genetic distances, 10.81% of horses associated with breed other than the major cluster of the source breed horses when all twenty five microsatellite loci were implemented. Similar results were obtained when the maximum likelihood approach for individual assignment was used. Based on these results it is proposed that, although microsatellite markers may prove very useful for individual identification, their utility for breed assignment of horses needs further evaluation.

• Journal of Microbiology and Biotechnology
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• v.31 no.2
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• pp.280-289
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• 2021

Genetic markers currently used for the discrimination of Lactobacillus delbrueckii subspecies have low efficiency for identification at subspecies level. Therefore, our objective in this study was to select novel genetic markers for accurate identification and discrimination of six L. delbrueckii subspecies based on pangenome analysis. We evaluated L. delbrueckii genomes to avoid making incorrect conclusions in the process of selecting genetic markers due to mislabeled genomes. Genome analysis showed that two genomes of L. delbrueckii subspecies deposited at NCBI were misidentified. Based on these results, subspecies-specific genetic markers were selected by comparing the core and pangenomes. Genetic markers were confirmed to be specific for 59,196,562 genome sequences via in silico analysis. They were found in all strains of the same subspecies, but not in other subspecies or bacterial strains. These genetic markers also could be used to accurately identify genomes at the subspecies level for genomes known at the species level. A real-time PCR method for detecting three main subspecies (L. delbrueckii subsp. delbrueckii, lactis, and bulgaricus) was developed to cost-effectively identify them using genetic markers. Results showed 100% specificity for each subspecies. These genetic markers could differentiate each subspecies from 44 other lactic acid bacteria. This real-time PCR method was then applied to monitor 26 probiotics and dairy products. It was also used to identify 64 unknown strains isolated from raw milk samples and dairy products. Results confirmed that unknown isolates and subspecies contained in the product could be accurately identified using this real-time PCR method.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.146-148
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• 2005

In this paper, we propose a genetically optimized identification of information granulation(IG)-based fuzzy model. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the genetic algorithms and the least square method. And also, we exploite consecutive identification of fuzzy model in case of identification of structure and parameters. Numerical example is included to evaluate the performance of the proposed model.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.125-130
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• 2007

The principal morphological characters used for identification of hydrangea cultivars are often dependent on agroclimatic conditions. Furthermore, information on the selection or the genetic background of the hydrangea breeding is so rare that a molecular marker system for cultivar identification is needed. Amplified fragment length polymorphism (AFLP) markers were employed for fingerprinting Hydrangea macrophylla cultivars and candidate cultivars of H. macrophylla selected in Korea. One AFLP primer combination was sufficient to distinguish 17 H. macrophylla cultivars and 4 candidate cultivars. The profile of 19 loci that can minimize the error of amplification peak detection was constructed. AFLP markers were efficient for identification, estimation of genetic distances between cultivars, and cultivar discrimination. Based on the observed AFLP markers, genetic relationship was reconstructed by the UPGMA method. Seventeen H. macrophylla cultivars and H. macrophylla for. normalis formed a major cluster, and candidate cultivars selected in Korea formed another cluster.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.18-21
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• 1995

In this paper we describe a new method for multimodal function optimization using genetic algorithms(GAs). We propose adaptation rules for GA parameters such as population size, crossover probability and mutation probability. In the self organizing genetic algorithm(SOGA), SOGA parameters change according to the adaptation rules. Thus, we do not have to set the parameters manually. We discuss about SOGA and those of other approaches for adapting operator probabilities in GAs. The validity of the proposed algorithm will be verified in a simulation example of system identification.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.15-17
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of nonlinear IIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate nonlinear IIR filter parameter using the genetic algorithm.