• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.896-899
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• 2001

본 논문에서는 외판원 문제를 분산 시스템 환경에서, 다중 에이전트를 이용해 수법시간을 단축시키고, 더욱 우수한 근접해를 구할 수 있는 분산 유전 알고리즘을 개발하였다. 다중 후보해를 이용한 분산 유전 알고리즘을 수행할 때, 고려해야 할 중요한 요소는 후보해들 간의 개체들을 어떤 노드의 후보해 개체와 교환할 것인가와 어떤 개체들을 선택해서, 얼마만큼의 개체를 이동시킨 것인가가 중요하게 고려독어야 한다. 따라서 본 논문에서는 교환해야 할 개체의 크기를 동적으로 윈도우 크기를 변경하면서 교환하는 방법을 개발하였고, 교환할 개체들의 위치를 결정하는 새로운 유전 이동 정책 2가지 방법을 개발하고 실험하였다.

• Journal of the Korean Applied Science and Technology
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• v.34 no.1
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• pp.25-32
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• 2017

Such electrical properties (dielectric permittivity and dielectric loss of epoxy resin with the variations of frequency (30 ~ 300k Hz) and temperature ($20{\sim}160^{\circ}C$) have been measured. Dielectric dissipation of three specimen did not occurred below the glass transition temperature (Tg) regardless of frequency, but occurred above its temperature.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.261-262
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• 2008

분산제의 종류와 함량이 무기물-유기물 복합재료의 레올로지 특성 및 유전특성에 미치는 영향에 대하여 고찰하였다. 먼저 Multiple light scattering 방법을 통하여 용액의 입자 이동속도와 용액의 맑은층의 두께변화를 살펴보았으며 이를 통해 적정한 분산제의 선정 및 선정된 분산제의 함량비에 따른 무기물 분말의 분산 특성을 고찰하였다. 그리고 테이프 캐스팅을 통하여 테이프를 제작한 후 1GHz에서 유전특성을 측정하였다. 위 결과들을 통하여 분산제의 종류와 함량비에 따라 용액 및 슬러리의 특성이 다르며 적정한 분산제를 사용하여 유전상수 16.5에 유전손실 0.0058의 복합재료를 제작할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.210-213
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• 2010

최근 사용자의 멀티미디어에 대한 요구의 증가가 VOD (Video-on-Demand) 서비스를 발전시키게 되었다. VOD는 엔터테인먼트나 원격 교육, 광고 및 정보 등 많은 분야에서 사용되고 있다. 이러한 VOD 서비스는 많은 디스크 I/O와 네트워크 I/O를 요구하며 기존 웹 서버 시스템과 비교했을 때 오랜 시간동안 서비스를 해야 하는 특징을 가지고 있다. 또한 VOD 서비스는 많은 네트워크와 디스크의 대역폭을 요구하며, 서비스의 QoS에 민감해서 사용자 응답시간이 길어지면 사용자 요청의 취소율이 높아지게 된다. 따라서 불만족스러운 서비스의 증가로 네트워크 부하만 증가하게 된다. 이러한 기존 웹 서버 환경과는 다른 부하의 패턴이 있는 VOD 서비스 환경에서는 부하를 균형적으로 분배하여 서비스의 QoS를 높이는 것이 매우 중요하다. 본 논문에서는 분산 VOD 시스템 환경에서 부하를 효율적으로 분산하기 위해 계층형 분산 VOD 시스템 모델과 사용자 요청 패턴의 히스토리와 유전 알고리즘을 기반으로 한 스케줄러를 제안한다. 본 논문에서 제안한 계층형 분산 VOD 시스템 모델은 서버들을 지역적으로 분산하고 제어 서버를 지역마다 설치하여 지역에 있는 VOD 서버들을 관리하도록 구성한다. 사용자 요청을 지역 서버군 내에서 분산시키기 위해서 히스토리를 기반으로 한 유전 알고리즘을 사용한다. 이러한 히스토리 정보를 기반으로 유전 알고리즘의 적합도 함수에 적용하여 VOD 시스템을 위한 유전 알고리즘과 유전 연산을 구현한다. 본 논문에서 제안한 부하 분산 알고리즘은 VOD 서비스 환경에서 사용자 요구에 대한 부하를 보다 정확하게 예측하여 부하를 분산할 수 있다. 본 논문에서 제안한 계층형 분산 VOD 시스템의 부하 분산 알고리즘의 성능을 테스트하기 위해 OPNET 기반 시뮬레이터를 구현한다. 라운드로빈(round-robin) 방식과 랜덤(random) 방식과의 비교 실험을 통해 본 논문에서 제안한 부하 분산 알고리즘의 성능을 평가한다. 비교 실험을 통해 본 논문에서 제안한 알고리즘이 보다 안정적인 QoS를 제공하는 것을 보여준다.

• Journal of Embryo Transfer
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• v.29 no.3
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• pp.289-296
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• 2014

The pedigree information and race records of 1,000 m finishing time of Jeju race horses at KRA were used to study the effect of amount of pedigree information and parental misidentification on the estimates of genetic parameters. The modified data sets were made at the range of 2.5 to 25% parental misidentifications or loss of parental information of individuals with an increment of 2.5 percent. For each incremental level, 20 randomly replicated data sets were obtained and analyzed by single-trait analysis with a DF-REML(AI) algorithm. As the rate of misidentification increased or the amount of pedigree information decreased, the estimates of fraction of additive genetics variance component gradually decreased almost linearly (p<0.05), while the estimated fractions of error variance and permanent environmental variance components gradually increased for the finishing time. Regression coefficients of the percentage amount of both parents' information loss and incorrect pedigree information on additive genetic variances were -0.079 and -0.114, respectively (p<0.01). The estimate of heritability decreased by 0.92% for one percent loss of both parents' information and 1.39% for one percent increase of both parental misidentifications of progeny (p<0.01). For the consideration of probable incorrect and missing parent information of progeny in this early population of Jeju horses, the estimates of additive genetic parameters would be biased downward about ten percent. This results indicate that the amount of pedigree information loss and misidentification of progeny would severely affect estimates of genetic parameters and would reduce genetic gains for selection in Jeju horse population.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.99-117
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• 2016

Data on primal cuts were collected from 1,829 steers of Hanwoo progeny testing programs, between 2010 and 2015 for the ssGWAS. SNP data were analyzed by using Illumina Bovine 50K Beadchip. The SNP data that matches with phenotype data was 674 animals. As a first step, the genomic estimated breeding value(GEBV) of the loin and rib cuts were estimated, which was used in the estimation of SNP marker effects and their variances related to the traits. Then, the estimated variance explained by each marker was expressed as a proportion to the total genetic variance. Finally, the SNP loci and their significance to any possible QTL were examined. Among the 20 best SNP loci explaining a larger proportion of SNP variance to the total genetic variance for tender loin yield, the region between 12,812,193 ~ 12,922,313bp on BTA 10 harbored a cluster of SNPs that explained about 7.32 to 7.34% of the total genetic variance. For strip loin yield, a peak for higher effects for multiple SNPs was found in BTA24, between 38,158,543 and 38,347,278bp distances, which explained about 8.36 to 8.56% of the observed variance for this trait. For loin yield had relatively smaller effects in terms of the total genetic variance. Therefore, loin yield might be affected by a few loci with moderate effects and many other loci with smaller effects across the genome.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.157-162
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• 2010

We present a new distributed genetic algorithm that can be used to extract useful information from distributed, large data over the network. The main idea of the proposed algorithms is to determine how many and which individuals move between subpopulations at each site adaptively. In addition, we present a method to help individuals from other subpopulations not be weeded out but adapt to the new subpopulation. We used six data sets from UCI Machine Learning Repository to compare the performance of our approach with that of the single, centralized genetic algorithm. As a result, the proposed algorithm produced better performance than the single genetic algorithm in terms of the classification accuracy with the feature subsets.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.5 no.1
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• pp.51-56
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• 1969

Fourty lines of F4 progenies of an Adzuki bean cross, Jukdoo (Korean local variety) X Nesumimochi (Japanese variety) were used as the material, and these lines were grown in replicated trials in 1967. Phenotypic, genotypic and environmental covariances among all possible traits of eight character are calculated as shown in table 1. Phenotypic, genotypic and environmental correlations among all possible paris of eight characters were calculated as shown in table 2. In general, genotypic correlations were higher than the corresponding phenotypic corresponding phenotypic correlations. The genotypic correlations between seed yield (grain weight per plot) and oter agronomic characters indicated that seed yield was genetically associated with the character of pod number per plant, and grain number per plant, which is closely correlated with pod number pr plant, are affected more in Adzukl bean yield than the other agronomic characteracters.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.21 no.1
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• pp.92-96
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• 1976

Considerably large phenotypic and genotypic variations for the important agronomic traits were found in a soybean population consisted with 825 local lines collected in Korea. Genetic coefficient of variation, heritability, and genetic gain for seed weight, plant height. and number of pods per plant were relatively high. Maturity showed a high heritability value with a low genetic gain and the result may be due to the narrow range of maturity date of the population studied.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.4
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• pp.407-417
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• 2003

Enen though several GA-based optimization algorithms have been successfully applied to complex optimization problems in various engineering fields, GA-based optimization methods are computationally too expensive for practical use in the field of structural optimization, particularly for large- scale problems. Furthermore, a successful implementation of GA-based optimization algorithm requires a cumbersome and trial-and-error routine related to setting of parameters dependent on a optimization problem. Therefore, to overcome these disadvantages, a high-performance GA is developed in the form of distributed hybrid genetic algorithm for structural optimization on a cluster of personal computers. The distributed hybrid genetic algorithm proposed in this paper consist of a simple GA running on a master computer and multiple μ-GAs running on slave computers. The algorithm is implemented on a PC cluster and applied to the minimum weight design of steel structures. The results show that the computational time required for structural optimization process can be drastically reduced and the dependency on the parameters can be avoided.