• Journal of Radiation Protection and Research
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• v.19 no.1
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• pp.1-11
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• 1994

Considering the variety of application and other factors in performing the optimization of radiological protection, it is necessary to use well-structured optimization procedure. In this study, an optimization procedure for design stage of nuclear power plant was proposed, and applied in the selection of alternatives for reducing occupational radiation exposure. As an aiding technique for decision-making, multi-criteria technique was used. As a result, priorities of alternatives are determined, and a problem of applying this result to real situation is reviewed. The developed procedure for optimization can be extended to other areas such as radioactive waste management, medical use of radiation, etc.

• Journal of Korean Association for Spatial Structures
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• v.3 no.3 s.9
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• pp.67-74
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• 2003

The purpose of this study is to improve convergence speed of topology optimization procedure using the existing ESO method and to deal with topology decision of the truss structures according to a boundary condition, such as cantilever type. At the existing ESO topology optimization procedure for the truss structures, the adjustment of member sizes according to target stress has been executed by increasing or reducing a very small value from each member size. In this case, it takes too much iteration till convergence. Accordingly, it is practically hard to obtain optimum topology for a large scale structures. For that reason, it is necessary to improve convergence speed of ESO method more effectively. During the topology decision procedure, member sizes are adjusted by calculating approximate solution for member sizes corresponding to the target stress at every step, the new member sizes are adjusted by such method are applied in FEA procedure of next step.

• Earthquakes and Structures
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• v.23 no.1
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• pp.35-57
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• 2022

This article presents a computationally efficient framework for multi-objective seismic design optimization of steel moment-resisting frame (MRF) structures based on the nonlinear dynamic analysis procedure. This framework employs the uniform damage distribution philosophy to minimize the weight (initial cost) of the structure at different levels of damage. The preliminary framework was recently proposed by the authors based on the single excitation and the nonlinear static (pushover) analysis procedure, in which the effects of record-to-record variability as well as higher-order vibration modes were neglected. The present study investigates the reliability of the previous framework by extending the proposed algorithm using the nonlinear dynamic design procedure (optimization under multiple ground motions). Three benchmark structures, including 4-, 8-, and 12-story steel MRFs, representing the behavior of low-, mid-, and high-rise buildings, are utilized to evaluate the proposed framework. The total weight of the structure and the maximum inter-story drift ratio (IDRmax) resulting from the average response of the structure to a set of seven ground motion records are considered as two conflicting objectives for the optimization problem and are simultaneously minimized. The results of this study indicate that the optimization under several ground motions leads to almost similar outcomes in terms of optimization objectives to those are obtained from optimization under pushover analysis. However, investigation of optimal designs under a suite of 22 earthquake records reveals that the damage distribution in buildings designed by the nonlinear dynamic-based procedure is closer to the uniform distribution (desired target during the optimization process) compared to those designed according to the pushover procedure.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.517-527
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• 2011

A topology optimization and shape optimization method are widely used in the design area of engineering field. In this paper, a unified procedure to combine both topology and shape optimization method is used. A material distribution method is used first to extract necessary design parameters of the structure and a shape optimization scheme using genetic algorithm and satisfying all the condition follows. As an example, a GFRP bridge deck is designed and compared with other commercial products. The performance of the designed deck shows that the used design procedure is very efficient and safe. This procedure can be generalized for using in other areas of engineering.

• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.7-12
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• 2001

A large number of methods for the design optimization have been proposed in recent years. However, it is not easy to apply these methods to practical use because of many iterations. So, in the design optimization, physical and engineering investigation of the given model are very important, which results in an overall increase in the optimization speed. This paper describes a novel optimization procedure utilizing the conformal transformation method. This approach consists of two phases and has the advantage of grasping the physical phenomena of the model easily. Some numerical results that demonstrate the validity of the proposed method are also presented.

• Journal of Integrative Natural Science
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• v.12 no.3
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• pp.69-73
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• 2019

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.36-39
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• 1996

In chemical processes, measurement errors reduce the credibility of information and cause inconsistency in material and energy balances. Because multicomposition flows and temperature measurements make material and energy balances nonlinear equations, data reconciliation becomes a nonlinear constrained optimization problem. In multicomposition processes, if we follow general optimization procedure, the number of measurement variables is so large that data reconciliation requires much computation time. We propose the decomposition procedure to reduce the computation time without the decrease of accuracy of data reconciliation. Decomposition procedure finds global variables, that can reduce the nonlinearity of constraints, and divides two sub-optimization problems. Once we optimize the global variables at upper level, we can easily optimize the remain variables at tower level, We can obtain the short computational time and the same accuracy as SQP optimization method.

• Journal of Microbiology and Biotechnology
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• v.21 no.12
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• pp.1250-1256
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• 2011

In this study, Bacillus licheniformis cells were immobilized by entrapment in calcium alginate beads and were used for production of alkaline protease by repeated batch process. In order to increase the stability of the beads, the immobilization procedure was optimized by statistical full factorial method, by which three factors including alginate type, calcium chloride concentration, and agitation speed were studied. Optimization of the enzyme production medium, by the Taguchi method, was also studied. The obtained results showed that optimization of the cell immobilization procedure and medium constituents significantly enhanced the production of alkaline protease. In comparison with the free-cell culture in pre-optimized medium, about 7.3-fold higher productivity was resulted after optimization of the overall procedure. Repeated batch mode of operation, using optimized conditions, resulted in continuous production of the alkaline protease for 13 batches in 19 days.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.235-240
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• 1998

A procedure for the optimal design of high quality rectifiers is introduced in this paper. The procedure is capable of producing different optimal designs for the same rectifier based on the objective performance required from that rectifier. A FORTRAN-based computer system designed to solve large-scale optimization problems was used in this work to obtain the optimal designs. The optimization program uses Wolfe algorithm in conjunction with a quasi-Newton algorithm as well as a projected augmented Lagrangian algorithm to solve the highly nonlinear optimization problem. The paper also introduces a detailed analysis and an application of the procedure on a boost-type zero-current switch (ZCS) single-switch three-phase rectifier introduced recently in the literature. The obtained results are compared with popular simulation packages (i. e. PSPICE and SIMCAD) to support the validity of the proposed concept.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.116-122
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• 2023

Sentiment categorization technique be commonly isolated interested in threes significant classifications name Machine Learning Procedure (ML), Lexicon Based Method (LB) also finally, the Hybrid Method. In Machine Learning Methods (ML) utilizes phonetic highlights with apply notable ML algorithm. In this paper, in classification and identification be complete base under in optimizations technique called sequential minimal optimization with Random Forest algorithm (SMORF) for expanding the exhibition and proficiency of sentiment classification framework. The three existing classification algorithms are compared with proposed SMORF algorithm. Imitation result within experiential structure is Precisions (P), recalls (R), F-measures (F) and accuracy metric. The proposed sequential minimal optimization with Random Forest (SMORF) provides the great accuracy.