• 제어로봇시스템학회논문지
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• 제8권1호
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• pp.28-36
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• 2002

Regarding efficient development of computer graphic animations, lots of techniques for editing or transforming existing motion data have been developed. Basically, the motion transformation techniques follow optimization process. To make the animation be natural, almost all the techniques utilize kinematics and dynamics in constructing constraints for the optimization. Since the kinematic and dynamic structures of virtual characters to be animated are very complex, the most time-consuming part is known to the optimization process. In order to suggest some guide lines to engineers involved in the motion transformation, in this paper, we analyze the computational complexities for typical motion transformation in quantitative manner as well as the possibility for parallel computation.

• Structural Engineering and Mechanics
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• 제64권1호
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• pp.45-58
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• 2017

This paper presents the application of topology optimization as a design tool for a steel railway bridge. The choice of a steel railway bridge is dictated by the particular situation that it is suitable for topology optimization design. On the one hand, the current manufacturing techniques for steel structures (additive manufacturing techniques not included) are highly appropriate for material optimization and weight reduction to improve the overall structural efficiency, improve production efficiency, and reduce costs. On the other hand, the design of a railway bridge, especially at higher speeds, is dominated by minimizing the deformations, this being the basic principle of compliance optimization. However, a classical strategy of topology optimization considers typically only one or a very limited number of load cases, while the design of a steel railway bridge is characterized by relatively concentrated convoy loads, which may be present or absent at any location of the structure. The paper demonstrates the applicability of considering multiple load configurations during topology optimization and proves that a different and better optimal layout is obtained than the one from the classical strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5614-5633
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• 2018

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

• 한국강구조학회 논문집
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• 제16권6호통권73호
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• pp.819-832
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• 2004

본 연구는 구조물의 형상 최적화를 효율적이면서 보다 용이하게 수행할 수 있는 기법을 제안하고자 하였다. 구조물의 형상 표현과 설계변수 선택을 위해 설계요소 개념을 활용하여 설계변수 수를 과감하게 줄일 수 있었고, 등매개변수 사상기법을 이용하여 최적화 과정 중 형상의 변화에 따른 유한요소망을 자동생성 하였으며 효율적인 최적화 과정 수행을 위하여 결정론적 최적화 기법(개선된 허용방향법)과 스토캐스틱 최적화 기법(유전 알고리즘)을 사용하여 그 결과와 효율성을 비교하였다. 최적화 과정 중 구조해석은 유한요소법을 이용하며 구조물의 부피와 단면적 등을 목적함수로 하여 형상 최적화를 수행하였다. 또한 제작성과 시공성을 위한 최종형상 제시를 위하여 최적형상에 완화곡선 처리를 시도하였다. 이상의 연구를 강구조물을 대상으로 한 몇 가지 수치 예에 적용한 결과 설계과정을 보다 단순화시켰으며, 두 가지 기법 모두 최적해에 수렴함으로써 목적함수 값을 효과적으로 개선시킬 수 있었다. 따라서 본 연구는 그 타당성과 적용성이 있다고 판명된다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.369-375
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• 2001

For Optimization technology Was Developed in 1960, the Optimization Technology have grown into a full-featured, robust, highly rated and highly used. And Optimization techniques, having reached a degree of maturity over the past several years, are being used in a wide spectrum of industries, including aerospace, automotive, chemical, electrical, and manufacturing industries. With rapidly advancing computer technology, computers are becoming more powerful, and correspondingly, the size and the complexity of the problems being solved using Optimization techniques are also increasing. But Optimization techniques with analysis solver have many problems. For instance, the difficulties that a particular interface must be coded for each design problem and that the designer should be familiar with the optimization program as well as the analysis program. The purpose of this paper is Optimal Design Framework for Mechanical systems design. This Design Framework has two Optimizers, ADS (local optimizer) and RSM(Response Surface Method), and graphic user interfaces for formulation and optimum design problem and controlling the design process. Current Design Framework tested by two analysis solver, ADAMS and ANSYS. First this paper focused on the core Framework and their conception. In the second of the paper, I cover subjects such as Design Framework Operation. Next, The validity and effectiveness of Design Framework are shown by applying it to many practical design problems and obtaining satisfactory results. Finally, if you are an advanced Operator, you might want to use Response Surface Method, so that cover the result applied by RSM. here.

• 한국멀티미디어학회논문지
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• 제8권11호
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• pp.1556-1564
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• 2005

원시 프로그램에 대한 컴파일 과정 중 최적화 단계에서는 프로그램의 실행 속도를 개선시키고 코드 크기를 줄일 수 있는 다양한 최적화 기법을 수행한다[17]. 최적화 패턴 매칭 방법 중 스트링 패턴 매칭 방법은 중간 코드에 대응하는 최적의 패턴을 찾기 위한 방법으로 과다한 최적화 패턴 검색 시간으로 비효율적이다. 트리 패턴 매칭은 패턴 결정시 중복 비교가 발생할 수 있으며, 코드의 트리 구성에 많은 비용이 드는 단점을 가지고 있는 방법들이다[16,18]. 본 논문에서는 기존의 최적화 방법들의 단점을 극복하기 위한 방법으로 DFA (Deterministic Finite Automate) 최적화 테이블을 이용한 코드 최적화기를 제안하려고 한다. 이 방법은 다른 패턴 매칭 기법보다 결정적인 오토마타(Automata)로 구성하기 때문에 비용은 적어지고, 오토마타를 통해 결정적으로 패턴이 확정됨에 따른 패턴 선택 비용이 줄어들며, 최적화 패턴 검객 시간도 빨라지는 효율적인 방법의 최적화기이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3512-3528
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• 2016

A network with high mobility nodes or vehicles is vehicular ad hoc Network (VANET). For improvement in communication efficiency of VANET, many techniques have been proposed; one of these techniques is vehicular node clustering. Cluster nodes (CNs) and Cluster Heads (CHs) are elected or selected in the process of clustering. The longer the lifetime of clusters and the lesser the number of CHs attributes to efficient networking in VANETs. In this paper, a novel Clustering algorithm is proposed based on Ant Colony Optimization (ACO) for VANET named ACONET. This algorithm forms optimized clusters to offer robust communication for VANETs. For optimized clustering, parameters of transmission range, direction, speed of the nodes and load balance factor (LBF) are considered. The ACONET is compared empirically with state of the art methods, including Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) based clustering techniques. An extensive set of experiments is performed by varying the grid size of the network, the transmission range of nodes, and total number of nodes in network to evaluate the effectiveness of the algorithms in comparison. The results indicate that the ACONET has significantly outperformed the competitors.

• 한국기계가공학회지
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• 제18권9호
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• pp.36-43
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• 2019

Turning, a main machining process, is a widespread process in metal cutting industries. Many researchers have investigated the effects of process parameters on the machining process. In the turning process, input variables including cutting speed, feed, and depth of cut are generally used. Surface roughness and electric current consumption are used as output variables in this study. We construct a simulation model for the turning process using a neural network, which predicts the output values based on input values. In the neural network, obtaining the appropriate set of weights, which is called training, is crucial. In general, back propagation (BP) is widely used for training. In this study, techniques such as ant colony optimization (ACO) and particle swarm optimization (PSO) as well as BP were used to obtain the weights in the neural network. Particularly, two combined techniques of ACO_BP and PSO_BP were utilized for training the neural network. Finally, the performances of the two techniques are compared with each other.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• 한국CDE학회논문집
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• 제1권3호
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• pp.234-241
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• 1996

Recently, Genetic Algorithms(GAs), which consist of genetic operators named selection crossover and mutation, are widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GAs are very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GAs. So, they can be easily applicable to wide territory of design optimization problems. Also, virtue to multi-point search procedure, they have higher probability of convergence to global optimum compared with traditional techniques which take one-point search method. The introduction of basic theory on GAs, and the application examples in combination optimization of ten-member truss structure are presented in this paper.