• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.5
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• pp.93-102
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• 2003

An optimal design method for hybrid structural control system of building structures subject to earthquake excitation is presented in this paper. Designing a hybrid structural control system may be defined as a process that optimizes the capacities and configuration of passive and active control systems as well as structural members. The optimal design proceeds by formulating the optimization problem via a multi-stage goal programming technique and, then, by finding reasonable solution to the optimization problem by means of a goal-updating genetic algorithm. In the multi-stage goal programming, design targets(or goals) are at first selected too correspond too several stages and the objective function is th n defined as the sum of the normalized distances between these design goals and each of the physical values, that is, the inter-story drifts and the capacities of the control system. Finally, the goal-updating genetic algorithm searches for optimal solutions satisfying each stage of design goals and, if a solution exists, the levels of design goals are consecutively updated to approach the global optimal solution closest too the higher level of desired goals. The process of the integrated optimization design is illustrated by a numerical simulation of a nine-story building structure subject to earthquake excitation. The effectiveness of the proposed method is demonstrated by comparing the optimally designed results with those of a hybrid structural control system where structural members, passive and active control systems are uniformly distributed.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.04a
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• pp.266-269
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• 2006

• Journal of Korean Society of Steel Construction
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• v.12 no.3 s.46
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• pp.317-328
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• 2000

The objective of the research is to develop an algorithm for the optimum design of two-dimensional braced steel frames using an advanced analysis, which considers both material and geometric nonlinearties. Since both nonlinearties are considered in analysis process, Optimum design algorithm which does not require to calculate K-factor is presented. A multi-level discrete optimization technique with two parameters that uses the information of structural system and separate member has been developed. The structural analysis is performed by the relined plastic-hinge method which is based on zero-length plastic hinge theory. Optimization problem are formulated by AISC-LRFD code. The feasibility, validity and efficiency of the developed algorithm is demonstrated by the results of the braced steel frame.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.81-89
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• 1999

Image obtained by incomplete communication always include noise, blur and distortion, etc. In this paper, we propose and apply the new spatial filter algorithm, called an optimal adaptive generalized stack filter(AGSF), which optimizes adaptive generalized stack filter(AGSF) using neural network weight learning algorithm of back-propagation learning algorithm for improving noise removal and edge preservation rate. AGSF divides into two parts: generalized stack filter(GSF) and adaptive multistage median filter(AMMF), GSF improves the ability of stack filter algorithm and AMMF proposes the improved algorithm for reserving the sharp edge. Applied to neural network theory, the proposed algorithm improves the performance of the AGSF using two weight learning algorithms, such as the least mean absolute(LAM) and least mean square (LMS) algorithms. Simulation results of the proposed filter algorithm are presented and discussed.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.574-582
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• 1999

This paper discusses the multi-level optimization method in dynamic optimization problems through stiffened plate of ship structures. In structural optimization the computational cost increases rapidly as the number of design variables increases. And we need a great amount of cal-culation and time on problems of modified dynamic characteristics of large and complicated struc-tures. In this paper the multi-level optimization is proposed which decreases computational time and cost. the dynamic optimum designs of stiffened plate that control the natural frequency and minimize weight subjected to constraints condition are derived. The way to apply the multi-level optimization methods in this study follow: In the first step the dynamic characteristics is controlled for the two-dimensional model of stiffened plate by sensitivity analysis and quasi-least squares methods. In the second step the cross-section of the stiffener is decided so that the weight is minimized under needed constraints by the steepest descent or ascent method. In the third the three-dimensional model is made based on the results of the first step and the second step confirmation and finer tuning of the objective function are carried out. It is shown that the results are effective in the optimum modification for dynamic characteristics of the stiffened plate.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.940-947
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• 2004

In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen for design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size for each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem.

• Journal of IKEEE
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• v.21 no.1
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• pp.100-103
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• 2017

Motion estimation occupies the largest computation in the video compression. Multiple processing elements are often exploited in parallel to meet processing speed. More processing elements increase processing speed, but they also increase hardware area. therefore, it is important to optimize the number of processing element. HEVC (high efficiency video coding) usually exploits multi-stage motion estimation algorithms for low computation and high performance. Since the number and position of search points are different in each stage, the utilization of the processing elements is not always 100% and the utilization is quite different with the number of processing elements. In this paper, the optimizing method is proposed on the number of processing elements. It finds out the optimal number of the processing elements for the given multi-stage motion estimation algorithm by calculating utilization and execution cycle of the processing elements.

• Journal of Korean Society of Steel Construction
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• v.12 no.1 s.44
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• pp.93-102
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• 2000

Substructuring-based hierarchical approach for design analysis and optimization of structural frames is presented in this study. The conceptual framework of this method is in the hierarchical modeling for design processes as well as structural systems and the methodology combining substructuring analysis and multilevel optimization. Mathematical models for analysis and synthesis are established on the common basis of substructuring systems. Modularized behavioral analysis, design sensitivity analysis and optimization are linked and integrated on the mathematical and structural basis of substructuring. Substructures are coordinated with the active constraints for system level and the weight ratio criteria. Numerical examples for test frames show the validity and effectiveness of the present approach.

• Journal of Korea Water Resources Association
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• v.31 no.3
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• pp.327-335
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• 1998

The distribution network is an essential part of all water supply systems. The cost of this portion of any sizable water supply system may amount to most of the entire cost of the project. This study tried to reduce the cost of the distribution system through optimization in system design. To determine pipe diameter considered in water distribution system design, a iterative procedure linked the flow analysis model and optimization model was used. Linear theory was introduced to analyze flowrate and revised-simplex method based on linear programming is used to optimize pipe diameter. This model was applied to wter distribution system with 22 and 35 pipes, and rapidly determine optimized commercial pipe diameters. Keywords : water distribution system, revised simplex method, optimum pipe diameters.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.15-24
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• 2008

For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.