• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.1
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• pp.23-32
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• 2007

The nature of genetic variation and diversity among the 65 multivoltine silkworm genotypes was evaluated for 16 post cocoon characters. The components of genetic variation revealed higher PCV (60.487%) and GCV (44.56%) for evenness (variation 1) followed by cohesion (PCV=55.38%, GCV=40.36%) and non-broken filament length (PCV=32.05%, GCV=31.28%). The higher heritability ($h^2$ in broad sense) was observed for boil-off loss (95.6%) followed by non-broken filament length (95.22%). The both genotypic and phenotypic correlation indicated significant positive correlation of filament length with non-broken filament length, silk recovery, raw silk, neatness, and low neatness; and negative correlation with denier, renditta and silk waste. The principal component analysis (PCA) revealed 75.381 % of total variance from the five principal components extracted. On the basis of Mahalonobis' $D^2$ values (Ward's minimum variance), the sixty-five multivoltine silkworm genotypes were classified in to 9 clusters with substantial inter and intra cluster distances. Number of genotypes included in different clusters varied from 3 to 17. The results indicated that the optimum distance obtained in cluster VII (15.059) along with higher cluster mean values especially for filament length, non broken filament length, renditta, silk recovery, silk waste, and raw silk emphasized the utilization of these genotypes in the conventional silkworm breeding programme for improvement of multivoltine silk fibre quality. The possibility of exploiting genetic variation in post cocoon traits for efficient breeding programme is discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.466-471
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• 2006

IAn important problem of pattern recognition is to extract or select feature set, which is included in the pre-processing stage. In order to extract feature set, Principal component analysis has been usually used and SFS(Sequential Forward Selection) and SBS(Sequential Backward Selection) have been used as a feature selection method. This paper applies genetic algorithm which is a popular method for nonlinear optimization problem to the feature selection problem. So, we call it Genetic Algorithm Feature Selection(GAFS) and this algorithm is compared to other methods in the performance aspect.

• Journal of Integrative Natural Science
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• v.8 no.2
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• pp.117-127
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• 2015

Lentil (Lens culinaris Medik.) is one of the important legumes and cheaper source of protein in Bangladesh that displays great biological diversity. Isozyme, one of the most important protein markers to detect genetic polymorphism in lentil, whereas we considered thirteen-isozyme in six varieties viz., BARI masur-1, BARI masur-2, BARI masur-3, BARI masur-4, BARI masur-5 and BARI masur-6. The highest polymorphism was found in tyrosinase isozyme system. UPGMA analysis revealed that the highest similarity between BARI masur-5 and BARI masur-6 whereas, the highest genetic distance between BARI masur-1 and BARI masur-5 reflecting higher intervarietal variation. Principal component analysis (PCA) also revealed the similar results that of unweighted pair group method with arithmetic mean (UPGMA). The first, second and third PCs contributed 81.58%, 11.19% and 4.94% variation respectively, with cumulative variation of the first three PCs was 75.45%. Consequently, Isozyme could clearly assed the genetic diversity at intervarietal levels and these two varieties can be considered as valuable gene resources for future breeding and conservation programs.

• Journal of Ecology and Environment
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• v.36 no.3
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• pp.205-210
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• 2013

Cicuta virosa L. (Apiaceae) is a perennial emergent plant designated as an endangered species in South Korea. According to the former records, only four natural habitats remain in South Korea. A former study suggested that three of four populations (Pyeongchang: PC, Hoengseong: HS, Gunsan: GS) would be classified as different ecotypes based on their different morphological characteristics and life cycle under different environmental conditions. To evaluate this suggestion, we estimated genetic diversity in each population and distance among three populations by random amplification of polymorphic DNA. Seven random primers generated a total of 61 different banding positions, 36 (59%) of them were polymorphic. Nei's gene diversity and the Shannon diversity index increased in the order of PC < HS < GS, which is the same order of population size. In the two-dimensional (2D) plot of first two principal components in principal component analysis with the presence of 61 loci, individuals could be grouped as three populations easily (proportion of variance = 0.6125). Nei's genetic distance for the three populations showed the same tendency with the geographical distance within three populations. And it is also similar to the result of discriminant analysis with the morphological or life-cycle factors from the previous study. From the results, we concluded that three different populations of C. virosa should be classified as ecotypes based on not only morphology and phenology but genetic differences in terms of diversity and distance as well.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.166-171
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design for the application-based exclusive rolling element bearings, this study propose design methodologies by using a genetic-based combinatorial optimization. By the presence of discrete variables such as the number of rolling element (standard component) and by the engineering point of views, the design problem of the rolling element bearing can be characterized by the combinatorial optimization problem as a fully discrete optimization. A genetic algorithm is used to efficiently find a set of the optimum discrete design values from the pre-defined variable sets. To effectively deal with the design constraints and the multi-objective problem, a ranking penalty method is suggested for constructing a fitness function in the genetic-based combinatorial optimization. To evaluate the proposed design method, a robust performance analyzer of ball bearing based on quasi-static analysis is developed and the computer program is applied to some design problems, 1) maximize fatigue life, 2) maximize stiffness, 3) maximize fatigue life and stiffness, of a angular contact ball bearing. Optimum design results are demonstrate the effectiveness of the design method suggested in this study. It believed that the proposed methodologies can be effectively applied to other multi-objective discrete optimization problems.

• Korean Journal of Ichthyology
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• v.12 no.2
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• pp.118-123
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• 2000

Heritabilities of growth traits, and phenotypic and genetic correlations for rearing masu salmon Oncorhynchus masou in adult stage were described. Genetic parameters were estimated for total length, body weight, and head length of masu salmon at 19 and 23 months of age. The heritabilities of growth traits estimated for sire component at 19 months of age was 0.22 in each trait in 1995, and ranged from 0.19 to 0.36 at 23 months of age in 1996. Phenotypic and genetic correlations were high among growth traits(0.85~0.98, 0.67~1.26, respectively). Family selection or that combined with individual selection is proposed to improve growth of masu salmon.

• 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.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.64-66
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• 1995

This paper presents a new approach to evaluate optimal basic reliability indices of electric distribution systems using genetic algorithm. The use of optimal reliability evaluation is an important aspect of distribution system planning and operation to determine adequacy reliability level of each area. In this paper, the reliability model is based on the analytical method, connecting component failure to load point outage in each section. The proposed method applies genetic algorithm to calculate the optimal values of basic reliability indices, ie. failure rate and repair time, for a load point in the power distribution system, subject to minimizing interruption cost. Test results for the model system are reported in the paper compared with a direct optimization method(gradient projection).

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.6
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• pp.53-60
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• 2000

In this paper, we design a GA-fuzzy controller for position control and anti-swing at the destination point. A genetic algorithm is used to complement the demerits such as the difficulty of the component selection of the fuzzy controller, namely, scaling factors, membership functions and control rules. Lagrange equation is used to represent the motion equation of trolley and load in order to obtain mathematical modelling. Simulation results show that the proposed control technique is superior to a conventional optimal control in destination point moving and modification.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.63-71
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• 2006

In this paper, we consider a planning problem arising from printed circuit board manufacturing industries. Given a set of several types of PCBs, component feeders and surface mounting machines in series in a PCB assembly line, the problem is to define the feeder allocation and job sequence with the objective of minimizing the total operation time of the line. We formulate the problem as a mathematical model. And, the problem is proven to be NP-hard, so a genetic algorithm is developed. Finally, we give test results to evaluate the performance of the genetic algorithm.