• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.1033-1039
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• 2005

Parallel and distributed simulation is concerned with the efficient execution of large-scale discrete event simulation models on multiprocessors and distributed platforms. After the development of WWW, many efforts in the parallel and distributed simulation have been made for modeling, particularly building simulation languages and creating model libraries that can be assembled and executed over WWW. However, web-based parallel and distributed simulation is restricted by heterogeneous computing environments. Recently, the advent of XML and web services technology has made these efforts enter upon a new phase. Especially, the web services as a distributed information technology have demonstrated powerful capabilities for scalable interoperation of heterogeneous systems. This paper aims to develop and evaluate the parallel and distributed simulation using the web services technology. In particular, a prototype multi-pass simulation framework is implemented using Java-based web services technology. It focuses on the efficiency of multi-pass simulation used for optimization through the distribution of simulation replication to several simulation service providers. The development of parallel and distributed simulation using web services will help solve efficiently large-scale problems and also guarantee interoperability among heterogeneous networked systems.

• 정보관리학회지
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• 제34권4호
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• pp.33-57
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• 2017

본 연구는 새로운 분석법으로 떠오르는 처방적 분석 기법을 소개하고, 이를 분류 기반의 시스템에 효율적으로 적용하는 방안을 제시하는 것을 목적으로 한다. 처방적 분석 기법은 분석의 결과를 제시함과 동시에 최적화된 결과가 나오기까지의 과정 및 다른 선택지까지 제공한다. 새로운 개념의 분석 기법을 도입함으로써 문헌 분류를 기반으로 하는 응용 시스템을 더욱 쉽게 최적화하고 효율적으로 운영하는 방안을 제시하였다. 최적화의 과정을 시뮬레이션하기 위해, 대용량의 학술문헌을 수집하고 기준 분류 체계에 따라 자동 분류를 실시하였다. 처방적 분석 개념을 적용하는 과정에서 대용량의 문헌 분류를 위한 동적 자동 분류 기법과 학문 분야의 지적 구조 분석 기법을 동시에 활용하였다. 실험의 결과로 효과적으로 서비스 분류 체계를 수정하고 재적용할 수 있는 몇 가지 최적화 시나리오를 효율적으로 도출할 수 있음을 보여 주었다.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
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• pp.33-36
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• 2006

As the computing environment is rapidly improved, the interests of CFD are gradually focused on large-scale computation over complex geometry. Keeping pace with the trend, essential computational tools to obtain solutions of complex aerospace flow analysis and design problems are examined. An accurate and efficient flow analysis and design codes for large-scale aerospace problem are presented in this work. With regard to original numerical schemes for flow analysis, high-fidelity flux schemes such as RoeM, AUSMPW+ and higher order interpolation schemes such as MLP (Multi-dimensional Limiting Process) are presented. Concerning the grid representation method, a general-purpose basis code which can handle multi-block system and overset grid system simultaneously is constructed. In respect to design optimization, the importance of turbulent sensitivity is investigated. And design tools to predict highly turbulent flows and its sensitivity accurately by fully differentiating turbulent transport equations are presented. Especially, a new sensitivity analysis treatment and geometric representation method to resolve the basic flow characteristics are presented. Exploiting these tools, the capability of the proposed approach to handle complex aerospace simulation and design problems is tested by computing several flow analysis and design problems.

• 한국정밀공학회지
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• 제29권2호
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• pp.139-146
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• 2012

A multi-tasking machine tool for large scale marine engine crankshafts has been developed together with design technologies for its special devices. Since work pieces, that is, crankshafts to be machined are big and heavy; weight of over 100 tons, length of 10 m long, and diameter of over 3.5 m, several special purpose core devices are necessarily developed such as PTD (Pin Turning Device) for machining eccentric pin parts, face place and steady rest for chucking and resting heavy work pieces. PTD is a unique special purpose device of open-and-close ring typed structure equipped with revolving ring spindle for machining eccentric pins apart from journal. In order to achieve high rigidity of the machine tool, structural design optimization using TMSA (Taguch Method based Sequential Algorithm) has been completed with FEM structural analysis, and a hydrostatic bearing system for the PTD has been developed with theoretical hydrostatic analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권12호
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• pp.5307-5327
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• 2016

Restricted by finite battery energy, traditional wireless sensor networks (WSNs) can only maintain for a limited period of time, resulting in serious performance bottleneck in long-term deployment of WSN. Fortunately, the advancement in the wireless energy transfer technology provides a potential to free WSNs from limited energy supply and remain perpetual operational. A mobile charger called wireless charging vehicle (WCV) is employed to periodically charge each sensor node and keep its energy level above the minimum threshold. Aiming at maximizing the ratio of the WCV's vocation time over the cycle time as well as guaranteeing the perpetual operation of networks, we propose a feasible and optimal solution to this issue within the context of a real-time large-scale deployed WSN. First, we develop two different types of charging cycles: initialization cycles and renewable cycles and give relevant algorithms to construct these two cycles for each sensor node. We then formulate the optimization problem into an optimal construction algorithm and prove its correctness through theoretical analysis. Finally, we conduct extensive simulations to demonstrate the effectiveness of our proposed algorithms.

• 전기학회논문지
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• 제66권2호
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• pp.305-314
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• 2017

Most of the existing researches on systemwide optimization of generator maintenance scheduling do not consider the equivalent operating hours(EOHs) mainly due to the difficulties of calculating the EOHs of the CCGTs in the large scale system. In order to estimate the EOHs not only the operating hours but also the number of start-up/shutdown during the planning period should be estimated, which requires the mathematical model to incorporate the economic dispatch model and unit commitment model. The model is inherently modelled as a large scale mixed-integer nonlinear programming problem and the computation time increases exponentially and intractable as the system size grows. To make the problem tractable, this paper proposes an EOH calculation based on demand grouping by K-means clustering algorithm. Network congestion is also considered in order to improve the accuracy of EOH calculation. This proposed method is applied to the actual Korean electricity market and compared to other existing methods.

• 한국정밀공학회지
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• 제11권4호
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• pp.138-147
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• 1994

Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Improtance of performance management is growing as many function of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to detemine the magnitude and direction of parameter adjustment. This paper is the second part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of decision making which utilizes the principles of stochastic optimization and learning automata. The developed algorithm can adjuxt four timer settings of a token bus protocol based on the result of performance evaluation. The overall performance management has been evaluated for its efficacy on a network testbed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1110-1127
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• 2022

To improve the training efficiency and generalization performance of a support vector machine (SVM) in a large-scale set, an optimal SVM learning method based on adaptive sparse sampling and the granularity shift factor is presented. The proposed method combines sampling optimization with learner optimization. First, an adaptive sparse sampling method based on the potential function density clustering is designed to adaptively obtain sparse sampling samples, which can achieve a reduction in the training sample set and effectively approximate the spatial structure distribution of the original sample set. A granularity shift factor method is then constructed to optimize the SVM decision hyperplane, which fully considers the neighborhood information of each granularity region in the sparse sampling set. Experiments on an artificial dataset and three benchmark datasets show that the proposed method can achieve a relatively higher training efficiency, as well as ensure a good generalization performance of the learner. Finally, the effectiveness of the proposed method is verified.

• Smart Structures and Systems
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• 제30권6호
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• pp.583-599
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• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• 한국항공우주학회지
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• 제33권8호
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• pp.34-41
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• 2005

엔지니어링 분야의 병렬 컴퓨터 시스템은 일반적으로 초대형 구조해석이나 항공분야에 많이 적용되어 대형 설계문제의 긴 해석시간을 단축하였다. 슈퍼컴퓨터나 다수의 컴퓨터를 사용하여 해석시간을 단축하는 효과는 다분야통합최적설계의 설계시간을 줄이는데 사용 할 수가 있다. 하지만 기존의 상용 MDO 프레임워크의 다분야통합최적화 설계 프로세스는 해석 프로그램을 순차적으로 호출하는 방식으로 동작하여 설계 해를 도출하는 방식으로 비효율적이다. 본 연구에서는 이런 문제를 해결하기 위해서 병렬 설계 프로세스를 도입하여 수행할 수 있는 MDO 프레임워크를 개발하였다. 개발된 MDO 프레임워크를 검증하기 위해서 수식 문제 및 모터설계 문제와 헬기설계 문제를 적용하여 유효성을 검증하였으며, 설계 해를 도출하기 까지 걸리는 총 설계시간을 혁신적으로 줄임으로써 기존의 MDO 프레임워크에 비해 우수성을 증명하였다.