• 한국동물생명공학회지
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• 제35권1호
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• pp.94-101
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• 2020

In the early development of parthenogenetic embryo, cytoplasm and nucleic acid fragmentation may be a cause of lower embryo development. The purpose of this study was to evaluate whether embryonic development and apoptosis factors can be reduced by controlling the in-vitro culture environment by the addition of hormones, pregnancy serum and uterine milk. Our study showed that the activity of Casp-3 increased within the cytoplasm when artificially used hormones to induce the incubation environment, and PCNA's manifestation was low. However, the addition of pregnant serum appeared to lower the Casp-3 activity compared to the other groups. In addition, MMP-9 activity was increased and early embryo development and cytoplasmic fidelity were also increased. Therefore, the results of the present study showed that the use of gestational serum in the development of parthenogenetic embryo inhibit apoptosis and increases cytoplasmic reorganization by natural environmental control in in vitro culture.

• Structural Engineering and Mechanics
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• 제69권1호
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• pp.21-31
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• 2019

Optimizing composite structures to exploit their maximum potential is a realistic application with promising returns. In this research, simultaneous maximization of the fundamental frequency and frequency separation between the first two modes by optimizing the fiber angles is considered. A high-fidelity design optimization methodology is developed by combining the high-accuracy of finite element method with iterative improvement capability of metaheuristic algorithms. Three powerful nature-inspired optimization algorithms viz. a genetic algorithm (GA), a particle swarm optimization (PSO) variant and a cuckoo search (CS) variant are used. Advanced memetic features are incorporated in the PSO and CS to form their respective variants-RPSOLC (repulsive particle swarm optimization with local search and chaotic perturbation) and CHP (co-evolutionary host-parasite). A comprehensive set of benchmark solutions on several new problems are reported. Statistical tests and comprehensive assessment of the predicted results show CHP comprehensively outperforms RPSOLC and GA, while RPSOLC has a little superiority over GA. Extensive simulations show that the on repeated trials of the same experiment, CHP has very low variability. About 50% fewer variations are seen in RPSOLC as compared to GA on repeated trials.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 추계 학술대회논문집
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• pp.1-10
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• 2005

A new approach, Multi-Objective Design Exploration (MODE), is presented to address Multidisciplinary Design Optimization (MDO) problems by CFD-CSD coupling. MODE reveals the structure of the design space from the trade-off information and visualizes it as a panorama for Decision Maker. The present form of MODE consists of Kriging Model, Adaptive Range Multi Objective Genetic Algorithms, Analysis of Variance and Self-Organizing Map. The main emphasis of this approach is visual data mining. An MDO system using high fidelity simulation codes, Navier-Stokes solver and NASTRAN, has been developed and applied to a regional-jet wing design. Because the optimization system becomes very computationally expensive, only brief exploration of the design space has been performed. However, data mining result demonstrates that design knowledge can produce a good design even from the brief design exploration.

• 한국시뮬레이션학회논문지
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• 제32권3호
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• pp.67-74
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• 2023

반도체 제조라인(FAB)은 복잡하고 불확실한 운영환경에서 작동하는 대규모의 제조시스템 중 하나로 반도체 설비 운영을 담당하는 엔지니어들은 직관적이고 신속한 공정 스케줄링을 위해 가중치 기반 스케줄링을 널리 사용하고 있다. 가중치 기반 스케줄링에서 가중치 결정은 FAB 성능에 큰 영향을 미치므로 엔지니어들은 가중치 최적화를 위하여 시뮬레이션 기반 의사결정을 활용할 수 있다. 그러나 대규모 시뮬레이션은 많은 실험 비용을 요구하기 때문에 효과적인 의사결정을 위해서 신중한 실험설계가 요구된다. 본 연구에서는 적은 시뮬레이션 실행 내에서 효율적인 스케줄링을 도출하기 위해 세 가지 샘플링 대안(i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search (DSS))에 대한 비교연구를 수행하였다. 시뮬레이션 실험을 통해 세 가지 대안이 단일 규칙보다 우수한 성능을 보였고, 그중 GA와 DSS가 최적화를 위한 효과적인 대안이 될 수 있음을 확인하였다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2009년 춘계학술대회논문집
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• pp.57-65
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• 2009

An efficient and high-fidelity design approach for wing-body shape optimization is presented. Depending on the size of design space and the number of design of variable, aerodynamic shape optimization process is carried out via different optimization strategies at each design stage. In the first stage, global optimization techniques are applied to planform design with a few geometric design variables. In the second stage, local optimization techniques are used for wing surface design with a lot of design variables to maintain a sufficient design space with a high DOF (Degree of Freedom) geometric change. For global optimization, Kriging method in conjunction with Genetic Algorithm (GA) is used. Asearching algorithm of EI (Expected Improvement) points is introduced to enhance the quality of global optimization for the wing-planform design. For local optimization, a discrete adjoint method is adopted. By the successive combination of global and local optimization techniques, drag minimization is performed for a multi-body aircraft configuration while maintaining the baseline lift and the wing weight at the same time. Through the design process, performances of the test models are remarkably improved in comparison with the single stage design approach. The performance of the proposed design framework including wing planform design variables can be efficiently evaluated by the drag decomposition method, which can examine the improvement of various drag components, such as induced drag, wave drag, viscous drag and profile drag.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권5호
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• pp.423-443
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• 2009

We present the design and implementation of a unique sensing and actuation application -- the Illuminator: a sensor network-based intelligent light control system for entertainment and media production. Unlike most sensor network applications, which focus on sensing alone, a distinctive aspect of the Illuminator is that it closes the loop from light sensing to lighting control. We describe the Illuminator's design requirements, system architecture, algorithms, implementation and experimental results. The system uses the Illumimote, a multi-modal and high fidelity light sensor module well-suited for wireless sensor networks, to satisfy the high-performance light sensing requirements of entertainment and media production applications. The Illuminator system is a toolset to characterize the illumination profile of a deployed set of fixed position lights, generate desired lighting effects for moving targets (actors, scenic elements, etc.) based on user constraints expressed in a formal language, and to assist in the set up of lights to achieve the same illumination profile in multiple venues. After characterizing deployed lights, the Illuminator computes optimal light settings at run-time to achieve a user-specified actuation profile, using an optimization framework based on a genetic algorithm. Uniquely, it can use deployed sensors to incorporate changing ambient lighting conditions and moving targets into actuation. Experimental results demonstrate that the Illuminator handles various high-level user requirements and generates an optimal light actuation profile. These results suggest that the Illuminator system supports entertainment and media production applications.

• International Journal of Fluid Machinery and Systems
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• 제9권3호
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• pp.265-276
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• 2016

Energy systems working coherently in different conditions may not have a specific design which can provide optimal performance. A system working for a longer period at lower efficiency implies higher energy consumption. In this effort, a methodology demonstrated by a jet pump design and optimization via numerical modeling for fluid dynamics and implementation of an evolutionary algorithm for the optimization shows a reduction in computational costs. The jet pump inherently has a low efficiency because of improper mixing of primary and secondary fluids, and multiple momentum and energy transfer phenomena associated with it. The high fidelity solutions were obtained through a validated numerical model to construct an approximate function through surrogate analysis. Pareto-optimal solutions for two objective functions, i.e., secondary fluid pressure head and primary fluid pressure-drop, were generated through a multi-objective genetic algorithm. For the jet pump geometry, a design space of several design variables was discretized using the Latin hypercube sampling method for the optimization. The performance analysis of the surrogate models shows that the combined surrogates perform better than a single surrogate and the optimized jet pump shows a higher performance. The approach can be implemented in other energy systems to find a better design.

• BMB Reports
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• 제48권8호
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• pp.454-460
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• 2015

Naturally occurring reoviruses are live replication-proficient viruses that specifically infect human cancer cells while sparing their normal counterpart. Since the discovery of reoviruses in 1950s, they have shown various degrees of safety and efficacy in pre-clinical or clinical applications for human anti-cancer therapeutics. I have recently discovered that cellular tumor suppressor genes are also important in determining reoviral tropism. Carcinogenesis is a multi-step process involving the accumulation of both oncogene and tumor suppressor gene abnormalities. Reoviruses can exploit abnormal cellular tumor suppressor signaling for their oncolytic specificity and efficacy. Many tumor suppressor genes such as p53, ataxia telangiectasia mutated (ATM), and retinoblastoma associated (RB) are known to play important roles in genomic fidelity/maintenance. Thus, a tumor suppressor gene abnormality could affect host genomic integrity and likely disrupt intact antiviral networks due to the accumulation of genetic defects which in turn could result in oncolytic reovirus susceptibility. This review outlines the discovery of oncolytic reovirus strains, recent progresses in elucidating the molecular connection between oncogene/tumor suppressor gene abnormalities and reoviral oncotropism, and their clinical implications. Future directions in the utility of reovirus virotherapy is also proposed in this review. [BMB Reports 2015; 48(8): 454-460]

• 한국항공우주학회지
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• 제41권3호
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• pp.173-184
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• 2013

본 연구에서는 프로펠러나 헬리콥터 로터와 같은 회전체의 공력 최적 설계를 위한 다단 최적 설계 프레임워크를 제안한다. 이 프레임워크는 플랜폼 설계와 단면의 형상 설계를 반복적으로 수행하는 설계 전략을 통해 회전체의 공력 성능 향상을 목표로 한다. 플랜폼 설계의 단계에서는 유전 알고리즘과 2차원 CFD 데이터베이스 기반의 깃 요소 모멘텀 이론을 이용하여 빠른 시간에 회전체의 공력 특성을 평가하여 최적점을 탐색하였다. 플랜폼 설계 후 단면에 유입되는 유동 조건을 예측하여 단면 형상 최적 설계를 수행하였다. 설계 과정에서 보다 면밀하게 유동 특성이 분석될 수 있도록 2차원 N-S 해석자와 민감도 기반의 최적화 알고리즘을 통해 최적해를 탐색하였다. 단면 형상이 설계된 후에는 최적의 유동 조건을 산출할 수 있도록 플랜폼 설계를 반복적으로 수행하였다. 본 프레임워크를 1kW급 전기추진용 항공기 프로펠러 설계에 적용하여 그 유효성을 3차원 N-S 해석과 풍동 실험을 통해 검증하였다. 설계 후, 풍동 실험 결과를 기준으로 약 5%의 프로펠러 효율 증가를 얻을 수 있었다.