• 한국농공학회:학술대회논문집
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• 한국농공학회 2001년도 학술발표회 발표논문집
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• pp.129-135
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• 2001

The optimum design problems for the design of counterforted wall were formulated and computer programing to solve these problems were developed in this study. Both discrete optimization and continuous optimization method were applied to the design of counterforted wall and the results of these optimization methods were compared each other.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1996년도 가을 학술발표회 논문집
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• pp.304-312
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• 1996

Concepts, methods and tools for interactive CAD-based concurrent engineering design optimization of mechanical/structural systems and components which are critical in terms of cost development time, functionality and quality, are presented. The emphasis is on implementation of methods and capabilities for the optimization of composite structural system, and the integration of design process and manufacturing process of composite structures into standard CAD-based concurrent engineering environment The optimization of composite fuselage structures are performed under concurrent engineering environment for the example.

• Journal of Electrical Engineering and Technology
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• 제6권2호
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• pp.182-191
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• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

• Journal of Communications and Networks
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• 제18권5호
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• pp.744-761
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• 2016

For about the past decade and a half research efforts into cognitive radio networks (CRNs) have increased dramatically. This is because CRN is recognized as a technology that has the potential to squeeze the most out of the existing spectrum and hence virtually increase the effective capacity of a wireless communication system. The resulting increased capacity is still a limited resource and its optimal allocation is a critical requirement in order to realize its full benefits. Allocating these additional resources to the secondary users (SUs) in a CRN is an extremely challenging task and integer programming based optimization tools have to be employed to achieve the goals which include, among several aspects, increasing SUs throughput without interfering with the activities of primary users. The theory of the optimization tools that can be used for resource allocations (RA) in CRN have been well established in the literature; convex programming is one of them, in fact the major one. However when it comes to application and implementation, it is noticed that the practical problems do not fit exactly into the format of well established tools and researchers have to apply approximations of different forms to assist in the process. In this survey paper, the optimization tools that have been applied to RA in CRNs are reviewed. In some instances the limitations of techniques used are pointed out and creative tools developed by researchers to solve the problems are identified. Some ideas of tools to be considered by researchers are suggested, and direction for future research in this area in order to improve on the existing tools are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2422-2443
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• 2020

This paper studies a single-user Mobile Edge Computing (MEC) system where mobile device (MD) includes an application consisting of multiple computation components or tasks with dependencies. MD can offload part of each computation-intensive latency-sensitive task to the AP integrated with MEC server. In order to accomplish the application faultlessly, we calculate out the optimal task offloading strategy in a time-division manner for a predetermined execution order under the constraints of limited computation and communication resources. The problem is formulated as an optimization problem that can minimize the energy consumption of mobile device while satisfying the constraints of computation tasks and mobile device resources. The optimization problem is equivalently transformed into solving a nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method. And the proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation. In the outer Bi-Section Search, the proposed algorithm searches for the optimal Lagrangian multiplier variable between the lower and upper boundaries. The inner Bi-Section Search achieves the Lagrangian multiplier vector corresponding to a given variable receiving from the outer layer. Numerical results demonstrate that the proposed algorithm has significant performance improvement than other baselines. The novel scheme not only reduces the difficulty of problem solving, but also obtains less energy consumption and better performance.

• 한국게임학회 논문지
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• 제11권1호
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• pp.147-157
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• 2011

웹캠은 영상 데이터의 전송시간을 줄이기 위해 메모리 정렬은 고려하지 않는다. 메모리 정렬이 되지 않은 영상 데이터는 GPU에서 처리하기 부적합하며 고속의 영상처리를 위해서는 GPU에서 메모리 최적화가 가능한 색상 형식으로 변환되어야 한다. 본 논문은 웹캠 영상의 색상 형식 변환을 NVIDIA CUDA를 이용하여 가속하는 최적화 기법을 제안한다. 메모리 접근과 쓰레드 구성에 대한 최적화를 진행하였고, 제안하는 구조의 성능 측정과 최적화 정도를 분석하기 위해 GPU 메모리와 연산의 성능을 제한하여 실험하였다. 그 결과 최적화 방법에 따라 최대 68% 이상 성능이 향상됐다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2013년도 제48차 하계학술발표논문집 21권2호
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• pp.1-4
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• 2013

본 논문에서는 최신 안드로이드 기반 상용 스마트폰의 모바일 GPU 성능 향상을 위한 방법론을 제안한다. 동일 하드웨어를 가지고 스마트폰을 개발하더라도 제조사의 역량에 따라 소프트웨어 최적화의 정도가 달라서 그래픽 성능 차이가 날 수 있다. 그러므로 우리는 시스템 소프트웨어 레벨에서 그래픽 품질에 아무런 영향을 주지 않고 성능 향상을 이끌어낼 수 있는 기법에 대해 소개한다. 이를 위해 A사, B사 안드로이드 스마트폰을 대상으로 안드로이드 커널에 따른 분석을 수행하였고, GPU 디바이스 드라이버에 따른 분석을 수행하였으며, 마지막으로 타사 휴대폰과의 성능 비교를 통해 이 결과를 비교 분석하였다. 결과적으로 GPU 디바이스 드라이버 변경과 안드로이드 커널 변경을 시도함으로써 B사 대비 68%의 성능을 보인 A사 스마트폰의 성능을 96%까지 향상시킬 수 있었다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2017년도 제56차 하계학술대회논문집 25권2호
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• pp.168-169
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• 2017

중앙 전력과 단절된 독립형 마이크로그리드는 발전된 신재생 에너지를 저장하는 ESS의 효율적인 운영을 통해 블랙아웃을 방지하고 디젤 발전기의 발전 비용을 최소화하는 것이 필요하다. 본 논문에서는 기상 정보를 이용하여 신재생 에너지 발전량을 예측하고, 최적화 알고리즘을 이용해 생성된 후보 계획의 평가 시 ESS의 SOC를 유지하지 못하는 경우 페널티를 부여함으로써 신재생 발전량 예측의 오류에 대비하였다. 시뮬레이션 실험을 통해 제안하는 SOC 유지를 고려한 운영 계획 최적화 방안이 기존의 예측 제어 기반 최적화 방안에 비해 블랙아웃을 방지하면서도 디젤 발전 비용을 절감할 수 있음을 확인하였다.

• 한국컴퓨터정보학회논문지
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• 제24권2호
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• pp.119-126
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• 2019

As interest in augmented reality has increased recently, attempts have been made to incorporate augmented reality into various fields. In implementing augmented reality, the method by which markers are used is to extract feature points of markers to recognize 3D coordinates and, in some cases, it is necessary to recognize multiple markers simultaneously. Therefore, this paper proposes optimization methods for recognising multiple markers at the same time. Unity 3D and augmented reality library Vuforia are used to implement the experimental environment. The augmented reality program produced was implemented in an application form and tested using a mobile camera. We looked for optimization methods for manufacturing markers directly and for recognizing multiple markers through changes in the experimental environment. The results of the experiment can provide a higher recognition rate in an environment where multiple marker recognition is required later.

• 한국BIM학회 논문집
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• 제9권2호
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• pp.1-10
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• 2019

In this research, schedule optimization is defined as balancing the number of workers while keeping the demand and needs of the project resources, creating the perfect schedule for each activity. Therefore, when one optimizes a schedule, multiple potentials of schedule changes are assessed to get an instant view of changes that avoid any over and under staffing while maximizing productivity levels for the available labor cost. Optimizing the number of workers in the scheduling process is not a simple task since it usually involves many different factors to be considered such as the development of quantity take-offs, cost estimating, scheduling, direct/indirect costs, and borrowing costs in cash flow while each factor affecting the others simultaneously. That is why the optimization process usually requires complex computational simulations/modeling. This research attempts to find an optimal selection of daily maximum workers in a project while considering the impacts of other factors at the same time through OPEN BIM based multiple computer simulations in resource leveling. This paper integrates several different processes such as quantity take-offs, cost estimating, and scheduling processes through computer aided simulations and prediction in generating/comparing different outcomes of each process. To achieve interoperability among different simulation processes, this research utilized data exchanges supported by building SMART-IFC effort in automating the data extraction and retrieval. Numerous computer simulations were run, which included necessary aspects of construction scheduling, to produce sufficient alternatives for a given project.