• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.159-166
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• 2009

A nature immunity system responds sensitively to an external invasion with various functions in a lot of bodies, besides it there is a function to remember information to have been currently infected. we propose a hybrid model similar to immune system which combine with the antibody which applied genetic algorithm as select antibody and the arbitrary abnormal system call sequence that applied negative selection of a nature immunity system. A proposed model uses an arbitrary abnormal system Kol sequence in order to reduce a positive defect and a negative defect. Data used to experiment are send mail data processed UNM (University of New Maxico). The negative defect that an experiment results proposal model judged system call more abnormal than the existing negative selection to normal system call appeared 0.55% low.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.236-242
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• 2008

In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

• Molecules and Cells
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• v.26 no.2
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• pp.193-199
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• 2008

The pro-apoptotic Bcl-2 family member Bim acts as a sensor for apoptotic stimuli and initiates apoptosis through the mitochondrial pathway. To identify novel regulators of Bim, we employed the yeast two-hybrid system and isolated the human gene encoding macrophage migration inhibitory factor (MIF), a ubiquitously expressed proinflammatory mediator that has also been implicated in cell proliferation, the cell cycle and carcinogenesis. The interaction between MIF and Bim was confirmed by both in vitro and in vivo protein interaction assays. Intriguingly, protein complexes between MIF and the three major Bim isoforms (BimEL/BimL/BimS) could be detected in HEK293 and K562 cells, especially in cells undergoing apoptosis. Moreover, exogenous expression of MIF partially inhibited Bim-induced apoptosis in HEK293 cells. SiRNA-mediated knockdown of MIF increased apoptosis in K562 cells exposed to the chemical oxidant diamide. Endogenous MIF may regulate the pro-apoptotic activity of Bim and inhibit the release of cytochrome c from mitochondria.

• Korean Journal of Medicinal Crop Science
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• v.27 no.6
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• pp.376-382
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• 2019

Background: Angelica gigas Nakai has been used as an herbal medicine in Eastern Asia for treating disorders in women for a long time. To date there are no studies on the genetic diversity of A. gigas. The present study aimed to study the genetic diversity of A. gigas variants using genome-wide simple sequence repeat (SSR) markers. Methods and Results: The genetic diversity of 199 variants of A. gigas cultivated in of different regions, was analyzed using 5 genome-wide SSR markers. The results revealed that the genetic variants were very diverse, and genetic analysis using the 5 SSR markers revealed high diversity among the variants. Conclusions: It is expected that the development of the true Angleical cultivar, by studying the system and group selection, can be achieved by genetic analysis using the developed markers, for generating a genetically fixed lineage and group selection.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.8
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• pp.1217-1223
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• 2020

Objective: Eggshells with a uniform color and intensity are important for egg production because many consumers assess the quality of an egg according to the shell color. In the present study, we evaluated the influence of dominant effects on the variations in eggshell color after 32 weeks in a crossbred population. Methods: This study was conducted using 7,878 eggshell records from 2,626 hens. Heritability was estimated using a univariate animal model, which included inbreeding coefficients as a fixed effect and animal additive genetic, dominant genetic, and residuals as random effects. Genetic correlations were obtained using a bivariate animal model. The optimal diagnostic criteria identified in this study were: L^🟉 value (lightness) using a dominance model, and a^🟉 (redness), and b^🟉 (yellowness) value using an additive model. Results: The estimated heritabilities were 0.65 for shell lightness, 0.42 for redness, and 0.60 for yellowness. The dominance heritability was 0.23 for lightness. The estimated genetic correlations were 0.61 between lightness and redness, -0.84 between lightness and yellowness, and -0.39 between redness and yellowness. Conclusion: These results indicate that dominant genetic effects could help to explain the phenotypic variance in eggshell color, especially based on data from blue-shelled chickens. Considering the dominant genetic variation identified for shell color, this variation should be employed to produce blue eggs for commercial purposes using a planned mating system.

• Journal of Ginseng Research
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• v.33 no.4
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• pp.249-255
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• 2009

The oxidation of glycolate to glyoxylate, a key step in plant photorespiration, is carried out by the peroxisomal flavoprotein glycolate oxidase (EC 1.1.3.15). To investigate the altered gene expression and the role of GOX in ginseng plant defense system, a cDNA clone containing a GOX gene designated as PgGOX was isolated and sequenced from Panax ginseng. The cDNA was 692 nucleotides long and have an open reading frame of 552 bp with a deduced amino acid sequence of 183 residues. A GenBank BlastX search revealed that the deduced amino acid of PgGOX shares a high degree homology with the Glycine max (95% identity). In the present study we analyzed the expression of PgGOX under various environmental stresses at different times using real time-PCR. The results showed that the expressions of PgGOX increased after various treatments involving salt, light, cold, ABA, SA, and copper treatment.

• Korean Journal of Plant Taxonomy
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• v.49 no.4
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• pp.324-333
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• 2019

Neutral genetic diversity found in plant species usually leaves an indelible footprint of historical events. Korea's main mountain range (referred to as the Baekdudaegan [BDDG]), is known to have served as a glacial refugium primarily for the boreal and temperate flora of northeastern Asia. In addition, life-history traits (life forms, geographic range, and breeding systems) influence the within- and among-population genetic diversity of seed plant species. For example, selfing species harbor significantly less within-population genetic variation than that of predominantly outcrossers. A previous study of two Liparis species (L. makinoana and L. kumokiri) emphasizes the role of the abovementioned factors shaping the levels of genetic diversity. Liparis makinoana, mainly occurring on the BDDG and self-incompatible, harbors high levels of within-population genetic diversity (expected heterozygosity, H_eP = 0.319), whereas there is no allozyme variation (H_eP = 0.000) in L. kumokiri, which is self-compatible and mainly occurs in lowland hilly areas. To determine if this trend is also found in other congeners, we sampled five populations of L. krameri from the southern part of the Korean Peninsula and investigated the allozyme-based genetic diversity at 15 putative loci. The somewhat intermediate levels of within-population genetic variation (H_eP = 0.145) found in L. krameri are most likely due to its occurrence in mountainous areas that, despite being outside of the main ridge of the BDDG, still served as refugia, and a self-incompatible breeding system. Management strategies are suggested for L. krameri and L. makinoana based on the levels and distribution of genetic diversity and inbreeding.

• Animal Bioscience
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• v.34 no.9
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• pp.1451-1459
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• 2021

Objective: The objectives of the study were to evaluate reproductive performance and selection response through genetic trend of community-based breeding programs (CBBPs) of Bonga sheep. Methods: Reproduction traits data were collected between 2012 and 2018 from Bonga sheep CBBPs. Phenotypic performance was analyzed using the general linear model procedures of Statistical Analysis System. Genetic parameters were estimated by univariate animal model for age at first lambing (AFL) and repeatability models for lambing interval (LI), litter size (LS), and annual reproductive rate (ARR) traits using restricted maximum likelihood method of WOMBAT. For correlations bivariate animal model was used. Best model was chosen based on likelihood ratio test. The genetic trends were estimated by the weighted regression of the average breeding value of the animals on the year of birth/lambing. Results: The overall least squares mean±standard error of AFL, LI, LS, and ARR were 375±12.5, 284±9.9, 1.45±0.010, and 2.31±0.050, respectively. Direct heritability estimates for AFL, LI, LS, and ARR were 0.07±0.190, 0.06±0.120, 0.18±0.070, and 0.25±0.203, respectively. The low heritability for both AFL and LI showed that these traits respond little to selection programs but rather highly depend on animal management options. The annual genetic gains were -0.0281 days, -0.016 days, -0.0002 lambs and 0.0003 lambs for AFL, LI, LS, and ARR, respectively. Conclusion: Implications of the result to future improvement programs were improving management of animals, conservation of prolific flocks and out scaling the CBBP to get better results.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.306-316
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• 2013

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.159-165
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• 2002

This paper proposes a GA and Gradient Descent Method-based method for choosing an appropriate set of fuzzy rules for classification problems. The aim of the proposed method is to fond a minimum set of fuzzy rules that can correctly classify all training patterns. The number of inference rules and the shapes of the membership functions in the antecedent part of the fuzzy rules are determined by the genetic algorithms. The real numbers in the consequent parts of the fuzzy rules are obtained through the use of the descent method. A fitness function is used to maximize the number of correctly classified patterns, and to minimize the number of fuzzy rules. A solution obtained by the genetic algorithm is a set of fuzzy rules, and its fitness is determined by the two objectives, in a combinatorial optimization problem. In order to demonstrate the effectiveness of the proposed method, computer simulation results are shown.