• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.421-430
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• 2000

This paper presents a new approach which uses $A^*$ search and genetic algorithms for solving large scale multi-objective shortest path problem. The focus of this paper is motivated by the problem of finding Pareto optimal paths for an advanced traveler information system(ATIS) in the context of intelligent transportation system(ITS) application. The individual description, the decoding rule, the selection strategy and the operations of crossover and mutation are proposed for this problem. The keynote points of the algorithm are how to represent individuals and how to calculate the fitness of each individual. The high performance of the proposed algorithm is demonstrated by computer simulations.

• IE interfaces
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• v.20 no.2
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• pp.103-111
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• 2007

A heterogeneous VRP which considers various capacities, fixed and variable costs was suggested in this study. The transportation cost for vehicle is composed of its fixed and variable costs incurred proportionately to the travel distance. The main objective is to minimize the total sum of transportation costs. A mathematical programming model was suggested for this purpose and it gives an optimal solution by using OPL-STUDIO (ILOG CPLEX). A genetic algorithm which considers improvement of an initial solution, new fitness function with weighted cost and distance rates, and flexible mutation rate for escaping local solution was also suggested. The suggested algorithm was compared with the results of a tabu search and sweeping method by Taillard and Lee, respectively. The suggested algorithm gives better solutions rather than existing algorithms.

• Journal of Welding and Joining
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• v.29 no.6
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• pp.82-87
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• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.

• Journal of KSNVE
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• v.10 no.1
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• pp.33-40
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• 2000

With the increased requirement for automobile noise, a design fo mufflers with higher performances becomes more important in recent days. For a design of some mufflers, it must satisfy both minimizing back pressure and maximizing sound attenuation in broad range of frequecny. Even for a simple Helmholtz resonator, an important element in a muffler, a resonator design with accurate resonant frequency is difficult if one want to consider standing waves within the cavity. In this paper, the genetic algorithm, one of the optimization technique with high capability of global fittest solution and robust convergence, is applied to the design process of mufflers. Results show that the genetic algorithm can be successfully and efficiently used to find the fittest model for both mufflers and Helmoltz resonators.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1093-1117
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• 2016

Global sensitivity analysis (GSA) has been widely used to investigate the sensitivity of the model output with respect to its input parameters. In this paper a new single-solution search optimization algorithm is developed based on the GSA, and applied to the size optimization of truss structures. In this method the search space of the optimization is determined using the sensitivity indicator of variables. Unlike the common meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach the sensitive variables of solution are iteratively changed more rapidly than the less sensitive ones in the search space. Comparisons of the present results with those of some previous population-based meta-heuristic algorithms demonstrate its capability, especially for decreasing the number of fitness functions evaluations, in solving the presented benchmark problems.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.214-224
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• 2021

We was confirmed that the antler extract increases the expression of marker genes expressed in the process of bone formation, and that the effect on the increase in the expression of the gene is further increased by fermentation of the antler extract. In addition, the mouse model in which menopausal was induced by ovary extraction significantly reduced the movement distance and exercise time of mice compared to the control group. But the decrease was somewhat alleviated by the administration of the antler extract, and completely restored when the fermented antler extract was administered. In the menopause-induced mice, the body weight ratio of heart, liver, and spleen weights increased compared to the control group, but the antler extract and the antler ferment extract restored the body weight ratio of various organ weights to the level of the control group in the menopause-induced mice. Consequently, this has led to mitigating changes in the metabolism affected by menopause.

• Advances in Computational Design
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• v.8 no.1
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• pp.37-59
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• 2023

Squat reinforced concrete (SRC) shear walls are a critical part of the structure for both office/residential buildings and nuclear structures due to their significant role in withstanding seismic loads. Despite this, empirical formulae in current design standards and published studies demonstrate a considerable disparity in predicting SRC wall shear strength. The goal of this research is to develop and evaluate hybrid and ensemble artificial neural network (ANN) models. State-of-the-art population-based algorithms are used in this research for hybrid intelligence algorithms. Six models are developed, including Honey Badger Algorithm (HBA) with ANN (HBA-ANN), Hunger Games Search with ANN (HGS-ANN), fitness-distance balance coyote optimization algorithm (FDB-COA) with ANN (FDB-COA-ANN), Averaging Ensemble (AE) neural network, Snapshot Ensemble (SE) neural network, and Stacked Generalization (SG) ensemble neural network. A total of 434 test results of SRC walls is utilized to train and assess the models. The results reveal that the SG model not only minimizes prediction variance but also produces predictions (with R²= 0.99) that are superior to other models.

• Journal of Fashion Business
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• v.8 no.4
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• pp.22-32
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• 2004

The purpose of this research is to know the pattern of Hanbok Jegory with measuring Jegory and studying manufacturing method of the Jegory used currently. It is a purpose to find constitutional problem caused by the character of the bending somatotype and, to study the standard model of the Jegory for bending somatotyped women in old age, by comparison of this fitness for bending-somatotyped women in old age. The results obtained are as follows; 1. The kinds of measurements considered in manufacturing process are Hwajang Length, Bust girth, and the skirt length. The length of Jegory and width of Neck are also considered. 2. Manufacturers consider somatotype the most important thing when they make Jegory for women in old age. Front length, Back length and Width of the Jegory are considered secondly important. 3. The results of the comparison show that the Standard Hanbok drafting method is not suitable for drafting Jegory for bending somatotyped women in old age. 4. The suitability test for the model designed by the above methods shows that it fits in bending somatotyped women in old age better than standard drafting method. The results show the superiority of the above methods especially in the breast width, the Godae length, and the adaptedness to the body.

• Spatial Information Research
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• v.18 no.5
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• pp.107-117
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• 2010

Taking the East-Hwasung area as the case, this study first builds gridded population data based on the municipal population survey raw data, and then measures, by way of GIS tools, the major urban spatial variables that are thought to influence the composition of the regional population. For the purpose of comparison, the urban models based on the Genetic Algorithm technique and the regression technique are constructed using the same input variables. The findings indicate that the GA output performed better in differentiating the effective variables among the pilot model variables, and predicted as much consistent and meaningful coefficient estimates for the explanatory variables as the regression models. The study results indicate that GA technique could be a very useful and supplementary research tool in understanding the urban phenomena.

• Korea Journal of Hospital Management
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• v.22 no.1
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• pp.21-39
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• 2017

Purpose : This study was intended to investigate the structural relationship among empowerment, self-efficacy, job motivation, autonomy, critical thinking, job-satisfaction, burnout, and self-achievement. In addition, we tested the moderating effect of the career period on the influence of empowerment. Methodology : The structural equation model was used to test the causal relationship between factors, and t-test, ANOVA, descriptive statistics are applied to analyze the research data. Findings : The result of this study shows that the structural model that is the empowerment encourages the self-efficacy, job motivation, autonomy, and critical thinking, also these factors affect the self-achievement through both the job-satisfaction and burnout is acceptable according to the goodness of fitness indices. In addition, we show that the career period moderates the influence of empowerment on the self-efficacy, job-motivation, and autonomy, but not critical thinking. Usually, the shorter the career period is the higher the influence of empowerment is. This moderating effect means that to give proper empowerment to lower position nurses encourage them, and prevent from burnout. Therefore, they feel job-satisfaction and finally self-achievement. Practical Implications : The empowerment helps the nurse to activate self-efficacy, job motivation, autonomy, critical thinking. Hence, these factors decrease burn-out but increase job satisfaction. Finally a sense of self-perfection increase.