• Korean Journal of Materials Research
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• v.29 no.11
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• pp.670-676
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• 2019

We study substrate support structures and materials to improve uptime and shorten preventive maintenance cycles for chemical vapor deposition equipment. In order to improve the rolling of the substrate support, the bushing device adopts a ball transfer method in which a large ball and a small ball are mixed. When the main transfer ball of the bushing part of the substrate support contacts the substrate support, the small ball also rotates simultaneously with the rotation of the main ball, minimizing the resistance that can be generated during the vertical movement of the substrate support. As a result of the improvement, the glass substrate breakage rate is reduced by more than 90 ~ 95 %, and the equipment preventive maintenance and board support replacement cycles are extended four times or more, from once a month to more than four months, and the equipment uptime is at least 15 % improved. This study proposes an optimization method for substrate support structure and material improvement of chemical vapor deposition equipment.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.4
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• pp.9-17
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• 2007

Network Mobility basic support protocol (NEMO Basic) extends the operation of Mobile IPv6 to provide uninterrupted Internet connectivity to the communicating nodes of mobile networks. The protocol uses a mobile router (MR) in the mobile network to perform prefix scope binding updates with its home agent (HA) to establish a bi-directional tunnel between the HA and MR. This solution reduces location-update signaling by making network movements transparent to the mobile nodes (MNs) behind the MR. However, delays in data delivery and higher overheads are likely to occur because of sub-optimal routing and multiple encapsulation of data packets. To manage the mobility of the mobile network, it is important to minimize packet overhead, to optimize routing, and to reduce the volume of handoff signals over the nested mobile network. This paper proposes en aggregate router-assisted route optimization (ARARO) scheme for nested mobile networks support which introduces a local anchor router in order to localize handoff and to optimize routing. With ARARO, a mobile network node (MNN) behind a MR performs route optimization with a correspondent node (CN) as the MR sends a binding update message (BU) to aggregate router (AGR) via root-MR on behalf of all active MNNs when the mobile network moves. This paper describes the new architecture and mechanisms and provides simulation results which indicate that our proposal reduces transmission delay, handoff latency and signaling overhead. To evaluate the scheme, we present the results of simulation.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.719-728
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• 2022

The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1480-1487
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• 2012

Recently, the safety of the coal-mining tunnels has been improved greatly, but accidents occur continually. Most tunnel support failures occur because the fish plate part that connects the I-beams is unable to withstand ground pressure. In the case of XX coal mine, the arch part of tunnel support bends to the upper direction. In such a case, excessive horizontal load as well as vertical load acts on the tunnel support. Horizontal load is caused by the sudden loosing of underground rock mass or the leakage of underground water, so it is fairly complex to predict horizontal loading on a tunnel support. To predict the horizontal load on this component is defined as the problem that determines the horizontal load conditions in wedges of tunnel support. This is an optimization problem in which maximum bending stress and horizontal load are considered by an objective function and design variables, respectively. Therefore, in this study, design of experiments and optimization algorithm were applied to identify the horizontal load in tunnel support.

• Communications of the Korean Mathematical Society
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• v.25 no.1
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• pp.139-147
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• 2010

A generalized nondifferentiable fractional optimization problem (GFP), which consists of a maximum objective function defined by finite fractional functions with differentiable functions and support functions, and a constraint set defined by differentiable functions, is considered. Recently, Kim et al. [Journal of Optimization Theory and Applications 129 (2006), no. 1, 131-146] proved optimality theorems and duality theorems for a nondifferentiable multiobjective fractional programming problem (MFP), which consists of a vector-valued function whose components are fractional functions with differentiable functions and support functions, and a constraint set defined by differentiable functions. In fact if $\overline{x}$ is a solution of (GFP), then $\overline{x}$ is a weakly efficient solution of (MFP), but the converse may not be true. So, it seems to be not trivial that we apply the approach of Kim et al. to (GFP). However, modifying their approach, we obtain optimality conditions and duality results for (GFP).

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2542-2547
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• 2005

In this paper, we propose a support vector machine (SVM) hyper and kernel parameter optimization method which is based on minimizing radius/margin bound which is a kind of estimation of leave-one-error. This method uses dynamic encoding algorithm for search (DEAS) and gradient information for better optimization performance. DEAS is a recently proposed optimization algorithm which is based on variable length binary encoding method. This method has less computation time than genetic algorithm (GA) based and grid search based methods and better performance on finding global optimal value than gradient based methods. It is very efficient in practical applications. Hand-written letter data of MNI steel are used to evaluate the performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.606-609
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• 2015

본 연구에서는 support vector regression (SVR) 및 매개변수 최적화 알고리즘을 이용한 하천수위 예측모델을 구축하고 이를 실제 유역에 적용하여 모델 효율성을 평가하였다. 여기서, SVR은 하천수위를 예측하기 위한 예측모델로서 채택되었으며, 커널함수 (Kernel function)로서는 radial basis function (RBF)을 선택하였다. 최적화 알고리즘은 SVR의 최적 매개변수 (C?, cost parameter or regularization parameter; ${\gamma}$, RBF parameter; ${\epsilon}$, insensitive loss function parameter)를 탐색하기 위하여 적용되었다. 매개변수 최적화 알고리즘으로는 grid search (GS), genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC) 알고리즘을 채택하였으며, 비교분석을 통해 최적화 알고리즘의 적용성을 평가하였다. 또한 SVR과 최적화 알고리즘을 결합한 모델 (SVR-GS, SVR-GA, SVR-PSO, SVR-ABC)은 기존에 수자원 분야에서 널리 적용되어온 신경망(Artificial neural network, ANN) 및 뉴로퍼지 (Adaptive neuro-fuzzy inference system, ANFIS) 모델과 비교하였다. 그 결과, 모델 효율성 측면에서 SVR-GS, SVR-GA, SVR-PSO 및 SVR-ABC는 ANN보다 우수한 결과를 나타내었으며, ANFIS와는 비슷한 결과를 나타내었다. 또한 SVR-GA, SVR-PSO 및 SVR-ABC는 SVR-GS보다 상대적으로 우수한 결과를 나타내었으며, 모델 효율성 측면에서 SVR-PSO 및 SVR-ABC는 가장 우수한 모델 성능을 나타내었다. 따라서 본 연구에서 적용한 매개변수 최적화 알고리즘은 SVR의 매개변수를 최적화하는데 효과적임을 확인할 수 있었다. SVR과 최적화 알고리즘을 이용한 하천수위 예측모델은 기존의 ANN 및 ANFIS 모델과 더불어 하천수위 예측을 위한 효과적인 도구로 사용될 수 있을 것으로 판단된다.

• Nuclear Engineering and Technology
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• v.33 no.5
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• pp.547-555
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• 2001

In pressurized light water reactor fuel assembly, spacer grids support nuclear fuel rods both laterally and vertically. The fuel rods are supported by spacer grid springs and grid dimples that are located in the grid cell. The support system allows for some thermal expansion and imbalance of the fuel rods. The imbalance is absorbed by elastic energy to prevent coolant flow- induced vibration damage. Design requirements are defined and a design process is established. The design process includes mathematical optimization as well as practical design method. The shape of the grid spring is designed to maintain its function during the lifetime of the fuel assembly. A structural optimization method is employed for the shape design. Since the optimization is carried out in the linear range of finite element analysis, the optimum solution is verified by nonlinear analysis. A good design is found and the final design is compared with the initial conceptual design. Commercial codes are utilized for structural analysis and optimization.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.203-210
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• 2008

Because BSP(Basic Support Protocol) of NEMO(Network Mobility) has important limitation of not providing route optimization, several route optimization schemes have been proposed. By analyzing and improving the limitations of the existing schemes. we Propose an advanced integrated route optimization scheme for the communication through both the internal and external routing of nested NEMO. Our proposal includes a secure route optimization protocol which connects TLMR directly to an external node CN without passing through any HAs. and allows TLMR to control the internal path without passing through the internet. Thus, our scheme can strengthen the security as well as improve the path and delay of NEMO communication.

• 연구논문집
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• s.32
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• pp.111-120
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• 2002

In this paper, the design of a decatizing cylinder with uniformly distributed pressure in a decatizing system is investigated by using the Finite Element Method. Particularly, since deflection of a cylinder will not perform to iron the fabrics, the cylinder design insuring uniform pressure is very important. In this paper proposed two improved cylinder model obtained by changing the support type of the bean and the support location. And perform optimization with two improved cylinder model.