• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.69-75
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• 2020

Multilayer mirrors have widely been used not only in the industry but also in the medical field. X-ray reflectivity was measured by X-ray diffractometer to evaluate the performance of W/C multilayer mirror with 40 layers. Genetic algorithm are used to obtain thickness, density, and interfacial roughness for each of the 40 layers. The existing uniform random selection causes a problem that the solution does not converge or the error increases even if it convergence. To reduce the time to calculate the fitness of the genetic algorithm, the genetic algorithm was written in C/C++ parallel programming. The genetic algorithm showed excellent scalability of linear time increase with increasing number of generation and population. The genetic algorithm was selected with uniform and Gaussian randomness of 1:1 to improve the convergence of solution. The improved genetic algorithm can be applied to characterize each layer of a sample with more than a few tens of layers, such as a multilayer mirror.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.19-21
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• 2012

모든 암 세포는 체세포 변이를 동반한다. 따라서 암 유전체 변이 분석에 의하여 암을 발생시키는 유전자 및 진단/치료법을 찾아낼 수 있다. 본 연구에서는 차세대 시퀀싱 데이터를 이용하여 암 특이적 단이 반복 변이(copy number variation, CNV) 유형을 밝히는 새로운 알고리즘을 제안한다. 제안하는 방식은 암 환자의 정상 세포와 암세포로부터 얻어진 정상 유전체와 암 유전체를 동시 분석하여 각각 CNV 후보 영역을 추출하며, 통계적 유의성 분석을 통하여 암 특이적 CNV 후보 영역을 선별하고, 다음 후처리 과정에서 참조 표준 서열(reference sequence)에 존재하는 오류 영역 보정 작업을 수행하여 정확한 암 특이적 CNV 영역을 추출해 낸다. 또한 다수의 대용량 유전체 데이터 동시 분석을 위하여 맵리듀스(MapReduce) 기법을 기반으로 하는 병렬 수행 알고리즘을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1183-1186
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• 2002

DNA 의 염기서열 탐색을 위한 유전체학의 다음 세대인 구조유전체학은 유전체 사업으로 인한 인간 게놈지도의 완성과 축적된 생물정보를 이용한 생물정보학의 발달과 함께 급속한 성장을 계속하고 있다. 포스트 게놈 시대를 맞이하여 생명현상에 대한 궁극적인 이해를 위한 노력으로 단백질의 구조와 기능에 대한 연구가 주목을 받게 되었다. 다양한 구조 규명을 위한 도구들과 단백질 정보를 관리하기 위한 데이터베이스 구축에 따른 관련 기술의 발전은, 앞으로 다가올 생물정보의 방대함을 감안할 때, 가치 있는 지식정보를 얻기 위한 데이터 마이닝 기법들을 통해서만 가능하다. 본 논문은 데이터 마이닝의 근간 기술인 연관규칙 마이닝을 응용한 효율적인 서열 연관 규칙 알고리즘을 제안하며, 단백질 구조의 예측을 위한 단백질 서열 및 DNA 서열간의 패턴 비교 및 연관성을 목적으로 한다. 또한, 공간적 시간적 복잡성을 CMS-tree 라는 자료구조를 통해 알고리즘의 확장성 및 병렬화의 기본 알고리즘으로 사용하도록 개발하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1264-1267
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• 2011

시퀀싱 기술의 발달로 최근에는 비교적 저렴한 비용으로 개인의 유전체 시퀀싱 데이터를 산출할 수 있게 되었다. 하지만 이를 기반으로 하는 기존의 분석 방법은 매우 고가의 컴퓨팅 환경을 요구하기 때문에 분석을 위한 비용이 매우 높은 문제가 있다. 본 논문에서 클라우드 컴퓨팅 환경의 병렬 CNV 검출알고리즘을 제안한다. 제안하는 방법은 모양 기반의 CNV 검출 알고리즘인 CNV_shape을 MapReduce 기법으로 개발한 것으로 시퀀싱 데이터를 레퍼런스 서열에 매핑한 결과로부터 리드 커버리지 (read coverage)를 계산하여 커버리지가 감소하거나 증가하는 일정 길이 이상의 영역을 검출하는 방법이다. 클라우드 컴퓨팅 환경에 적용하고 노드의 밸런싱 유지를 위한 방법으로 파티셔닝 기법을 사용하였다. 또한 실 데이터를 이용한 실험을 통해 제안하는 방법의 효율적 데이터 처리를 보인다.

• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.166-168
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• 2002

This paper is concerned with optimal design of BLDC motor using parallel Genetic Algorithm to miminze the motor of weight.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.2
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• pp.135-148
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• 2000

In this paper, we present a linear scheduling method for homogeneous multiprocessor systems using genetic algorithms. In general, genetic algorithms randomly generate initial strings, which leads to long operation time and slow convergence due to an inappropriate initialization. The proposed algorithm considers communication costs among processors and generates initial strings such that successive nodes are grouped into the same cluster. In the crossover and mutation operations, the algorithm maintains linearity in scheduling by associating a node with its immediate successor or predecessor. Linear scheduling can fully utilize the inherent parallelism of a given program and has been proven to be superior to nonlinear scheduling on a coarse grain DAG (directed acyclic graph). This paper emphasizes the usability of the genetic algorithm for real-time applications. Simulation results show that the proposed algorithm rapidly converges within 50 generations in most DAGs.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.48-57
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• 2009

This paper presents optimal design of direct-driven PM wind generator using MADS (Mesh Adaptive Direct Search). Optimal design of the direct-driven PM Wind Generator, combined with MADS and FEM (Finite Element Method), has been performed to maximize the Annual Energy Production (AEP) over the whole wind speed characterized by the statistical model of the wind speed distribution. In particular, the newly applied MADS contributes to reducing the computation time when compared with Genetic Algorithm (GA) implemented with the parallel computing method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.1
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• pp.20-27
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• 2002

Aircraft design requires the intergration of several disciplines, inculding aerodynamics, structures, controls. To achieves advances in performance, each technology, or discipline must be more accurate in analysis and must be more highly intergrated. One of the important interdisciplinary interactions in mordern aircraft design is that of aerodynamics and structures. In this study, for increasing accuracy in each discipline's analysis, CFD for aerodynamic analysis and FEM for structurral analysis was used and, for considering important interdisciplinary interactions, aeroelastic effect was considered. As optimization algorithm, PBIL algorithm was used for global optima and was parallelized to alleviate the computational burden. The efficiency and accuracy of the present method was assesed by range maximiziation of reference of reference wing.

• The KIPS Transactions:PartA
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• v.10A no.1
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• pp.15-24
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• 2003

In this paper, an optimization model for the clustered node allocation systems in the distributed computing environment is presented. In the presented model with a distributed file system framework, the dynamics of system behavior over times is carefully thought over the nodes and hence the functionality of the cluster monitor node to check the feasibility of the current set of clustered node allocation is given. The cluster monitor node of the node allocation system capable of distributing the parallel modules to clustered nodes provides a good allocation solution using Genetic Algorithms (GA). As a part of the experimental studies, the solution quality and computation time effects of varying GA experimental parameters, such as the encoding scheme, the genetic operators (crossover, mutations), the population size, and the number of node modules, and the comparative findings are presented.

• Journal of Korean Society of Steel Construction
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• v.16 no.4 s.71
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• pp.443-452
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• 2004

Recently, the Artificial Neural Network(ANN) which can organize complex non-linear problems by effectively applying the parallel computational model that is similar to the human brain, was adopted in the wide department of technology and resulted in many successful applications. In this study, a more appropriate formal method is suggested for the preliminary structural design stage controlled merely by the designer's experience and intuition. To do so, this study proposes a multi-level ANN according to the general progressive structural design procedure, using Back-Propagation Algorithm (BP) and Genetic Algorithm (GA) for the ANN learning. The preliminary structural design of cable-stayed bridges was applied to illustrate the applicability of the study formulated as stated above, and the results of two different learning methods were compared.