• Steel and Composite Structures
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• v.29 no.1
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• pp.67-75
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• 2018

High performance concrete (HPC) depends on various parameters such as the type of cement, aggregate and water reducer amount. Generally, the ready concrete company in various regions according to the requirements and costs, mix design of concrete as well as type of cement, aggregates, and, amount of other components will vary as a result of moment decisions or dynamic optimization, though the ideal conditions will be more applicable for the design of mix proportion of concrete. This study aimed to apply dynamic optimization for mix design of HPC; consequently, the objective function, decision variables, input and output variables and constraints are defined and also the proposed dynamic optimization model is validated by experimental results. Results indicate that dynamic optimization objective function can be defined in such a way that the compressive strength or performance of all constraints is simultaneously examined, so changing any of the variables at each step of the process input and output data changes the dynamic of the process which makes concrete mix design formidable.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.10a
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• pp.145-150
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• 2003

The present study aims to optimize the performance of the Two-Stage Gas Gun by using the experimentally obtained data. RSM(Response Surface Method) was adopted in the optimization process to find the operating parameter than can maximize the projectile speed with the minimum number of tests. To decide the test points which results can consist of the response surface, 3$^{k}$ full factorial method was used, and the design variables were chosen with piston mass and 2$^{nd}$ driver fill pressure. The response surface was composed by nine test results and consequently the optimization was done with GENOCOP III, inherently GA code, in order to seek the optimal test point. The optimal test condition from the response surface was verified by the experiment. Results showed that the optimization process with response surface can successfully predict the test results fairly well. This study shows the possibility of performance optimization for the experimental facilities using numerical optimization algorithm.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4E
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• pp.137-141
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• 2006

This paper presents HE-AAC decoder optimization on TMS320C55x fixed-point DSP core using a DSP-C like FFR code, which provides fast and flexible porting to a DSP core. Our optimization efforts are focused on methodologies that include general optimization methods of FFR code suitable for general DSP or RISC platform in high-level language and software optimization methods in assembly language level. The implementation result requires 48 MIPS and 135 Kbytes memory space to decode 48 Kbps stereo using real Korean S-DMB data.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.9-11
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• 2006

This paper presents JPEG quantization table design using RD optimization and neural network. Using R-D optimization, quantization table with good performance can be obtained. However, it is time-consuming and difficult to adopt to embedded systems. In this paper, a new quantization table design method is proposed using R-D optimization and neural network. Neural network learns the quantization table obtained from R-D optimization and produces a quantization table for the Images. The proposed system is applied to Yale face data. From the simulation results, it has been shown that the proposed codec has better performance than JPEG.

• Advances in Computational Design
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• v.2 no.3
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• pp.241-256
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• 2017

This paper introduces the process for Multi-objective Optimization Framework (MOF) which mediates multiple conflicting design targets. Even though the extensive researches have shown the benefits of optimization in engineering and design disciplines, most optimizations have been limited to the performance-related targets or the single-objective optimization which seek optimum solution within one design parameter. In design practice, however, designers should consider the multiple parameters whose resultant purposes are conflicting. The MOF is a BIM-integrated and simulation-based parametric workflow capable of optimizing the configuration of building components by using performance and non-performance driven measure to satisfy requirements including build programs, climate-based daylighting, occupant's experience, construction cost and etc. The MOF will generate, evaluate all different possible configurations within the predefined each parameter, present the most optimized set of solution, and then feed BIM environment to minimize data loss across software platform. This paper illustrates how Multi-objective optimization methodology can be utilized in design practice by integrating advanced simulation, optimization algorithm and BIM.

• International Journal of Fluid Machinery and Systems
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• v.4 no.1
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• pp.172-178
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• 2011

This paper presents an optimization procedure for high-efficiency design of a mixed-flow pump. Optimization techniques based on a weighted-average surrogate model are used to optimize a vane diffuser of a mixed-flow pump. Validation of the numerical results is performed through experimental data for head, power and efficiency. Three-level full factorial design is used to generate nine design points within the design space. Three-dimensional Reynoldsaveraged Navier-Stokes equations with the shear stress transport turbulence model are discretized by using finite volume approximation and solved on hexahedral grids to evaluate the efficiency as the objective function. In order to reduce pressure loss in the vane diffuser, two variables defining the straight vane length ratio and the diffusion area ratio are selected as design variables in the present optimization. As the results of the design optimization, the efficiency at the design flow coefficient is improved by 7.05% and the off-design efficiencies are also improved in comparison with the reference design.

• Journal of the Korean Home Economics Association
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• v.39 no.11
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• pp.43-62
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• 2001

This study investigated the relationships among Selection, Optimization, and Compensation(SOC) as strategies of life management in mid-life crisis respect to gender and age. The subjects of this study were 170 females and 182 males at the ages between 40 and 60 living in Seoul. Selection, Optimization, and Compensation(SOC) as strategies of life management were assessed by SOC-questionnaire while mid-life crisis was assessed by Mid-Life Crisis Scale. The data were analyzed using frequencies, percentiles, means, standard deviations, Cronbach's $\alpha$, two-way ANOVAS, and Pearson's correlations. Except compensation there was no significant difference in Selection and Optimization as strategies of life management as a function of gender and age. No signigicant difference was found in mid-life crisis as a function of gender and age. There were significant negative correlations among Selection, Optimization, and Compensation(SOC) as strategies of life management and mid-life crisis except the individuation.

• Elastomers and Composites
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• v.57 no.4
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• pp.147-156
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• 2022

In this study, we chose a flat die to optimize a general die geometry. The optimization was aimed at obtaining a uniform velocity distribution across the exit of the die. For the optimization, the input and output design parameters were randomly computed, and response surfaces were generated to obtain statistical data for the minimum and maximum sensitivities computed during optimization. Subsequently, object functions with constraints were numerically computed to obtain the minimum errors in the velocity difference (i.e., variable "Outp" in this study). Finally, we obtained the candidate optimized dataset. Note that the current numerical computations were simultaneously conducted for an entire extruder, i.e., screw plus die. The numerical outlet velocity distributions in the modified die geometry tended to be much more uniform than the conventional distributions in the current optimization processes for this specific flat die.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.1-11
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• 2009

XQuery query proposed by W3C is one of the standard query languages for XML data and is widely accepted by many applications. Therefore the studies for efficient Processing of XQuery query have become a topic of critical importance recently and the optimization of XQuery query is one of new issues in these studies. However, previous researches just focus on the optimization techniques for a specific XML data management system and these optimization techniques can not be used under the any XML data management systems. Also, some previous researches use predefined XML data structure information such as XML schema or DTD for the optimization. In the real situation, however applications do not all refer to the structure information for XML data. Therefore, this paper analyzes only a XQuery query and optimize by using itself of the XQuery query. In this paper, we propose 3 kinds of optimization method that considers the characteristic of XQuery query. First method removes the redundant expressions described in XQuery query second method replaces the processing order of operation and clause in XQuery query and third method rewrites the XQuery query based on FOR clause. In case of third method, we consider FOR clause because generally FOR clause generates a loop in XQuery query and the loop often rises to execution frequency of redundant operation. Through a performance evaluation, we show that the processing time for rewritten queries is less than for original queries. also each method in our XQuery query optimizer can be used separately because the each method is independent.

• International Journal of Contents
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• v.17 no.3
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• pp.74-83
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• 2021

A location-aware algorithm is proposed in this study to optimize the system performance of distributed systems for processing big data with low data reliability and application performance. Compared with previous algorithms, the location-aware data block placement algorithm uses data block placement and node data recovery strategies to improve data application performance and reliability. Simulation and actual cluster tests showed that the location-aware placement algorithm proposed in this study could greatly improve data reliability and shorten the application processing time of I/O interfaces in real-time.