• International Journal of Contents
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• v.16 no.4
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• pp.26-38
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• 2020

Determining the optimal levels of the technical attributes (TAs) of a product to achieve a high level of customer satisfaction is the main activity in the planning process for quality function deployment (QFD). In real applications, the number of customer requirements for developing a single product is quite large, and the number of converted TAs is also high so the size of the house of quality (HoQ) becomes huge. Furthermore, the TA levels are often discrete instead of continuous and the product market can be divided into several market segments corresponding to the number of HoQ, which also unacceptably increases the size of the QFD optimization problem and the time spent on making decisions. This paper proposed a genetic algorithm (GA) solution approach to finding the optimum set of TAs in QFD in the above situation. A numerical example is provided for illustrating the proposed approach. To assess the computational performance of the GA, tests were performed on problems of various sizes using a fractional factorial design.

• Advances in Computational Design
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• v.2 no.4
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• pp.313-331
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• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1262-1269
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• 2005

Thrust of linear motor is one of the important factor to specify motor performance. Maximum thrust can be obtained by increasing the current in conductor and is relative to the sizes of conductor and magnet. But, the current and the size of conductor have an effect on temperature of linear motor. Therefore, it is practically important to find design results that can effectively maximize the thrust of linear motor within limited range of temperature. Finite element analysis was applied to calculate thrust and the temperature of the conductor was calculated by the thermal resistance. The diameter of copper wire among design variables has discrete value and number of turns must be integer. Considering these facts, special techinque for optimum design is presented. To reduce excessive computation time of thrust in optimization, the design variables was redefined by analysis of variance and second order regression model for thrust was determined by response surface metheodology. As a result, it is shown that the proposed method has an advantage in optimum design of linear motor.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.75-87
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• 2009

We propose in this paper a novel approach to image fusion in which the fusion rule is guided by optimizing an image clarity function. A Genetic Algorithm is used to stochastically select, comparative to the clarity function, the optimum block from among the source images. A novel nested Genetic Algorithm with gifted individuals found through bombardment of genes by the mutation operator is designed and implemented. Convergence of the algorithm is analytically and empirically examined and statistically compared (MANOVA) with the canonical GA using 3 test functions commonly used in the GA literature. The resulting GA is invariant to parameters and population size, and a minimal size of 20 individuals is found to be sufficient in the tests. In the fusion application, each individual in the population is a finite sequence of discrete values that represent input blocks. Performance of the proposed technique applied to image fusion experiments, is characterized in terms of Mutual Information (MI) as the output quality measure. The method is tested with C=2 input images. The results of the proposed scheme indicate a practical and attractive alternative to current multi-focus image fusion techniques.

• Journal of the Mineralogical Society of Korea
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• v.27 no.3
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• pp.159-168
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• 2014

Holocene plaeoenvironmental changes were interpreted by grain size and mineral analyses of a piston core (HB 13-2), obtained along the western slope of the Hupo Basin, Korea. The core sediments are characterized by two discrete, sedimentary facies: upper unit (0-0.4 mbsf) dominated by bioturbation structures with weak lamination, and lower unit (0.4-3.3 mbsf) characterized by intensified bioturbation toward bottom. Analysis of sensitive grain size and sortable silt demonstrated that the inflow of the Tsushima Warm Current (TWC) into the Hupo Basin strengthen from the period of sediment deposition over 0.82 mbsf. The minerals of the core sediments are composed mainly of quartz, microcline, orthoclase, albite and clay minerals including chlorite, kaolinite and illite. No noticeable changes of the mineral percentage was observed according to the grain size and depth of the samples. The integral breadth (${\Delta}^{\circ}2{\theta}$) of clay minerals from 1.4 mbsf to top layer shows an increasing trend, which clearly means climate warming from the period of sediment deposition above 1.4 mbsf. This interval correlates with the Holocene climate optimum at Mid Holocene.