• Korean Institute of Interior Design Journal
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• v.20 no.6
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• pp.36-43
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• 2011

The study presupposes that, ever since its modernization, the Korean local government buildings have undergone an evolutionary process of their spatial organizations and the process can be analyzed in terms of increased publicness of architectural space. For the purpose, fifteen examples of local government buildings in Korea are selected and analyzed in terms of their plans converted into spatial diagrams measuring accessibility depth. Within these analytical diagrams, some quantitative measures such as permeability and visual connection, and the number of decision making points that visitors face on the way to their targets. The study analyzes these analytic measures of selected samples which are categorized into three chronological groups in order to search any evolutionary tendency of spatial transformation. The analysis shows that the accessibility of public functions and presumably the publicness of the spatial organization of local government buildings has been increased. The results of the study implies that, to acquire architectural publicness in government buildings, not only the insertion of public programs but also the organization of open spatial structure is significant.

• Wind and Structures
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• v.17 no.2
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• pp.227-244
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• 2013

Non-stationary extreme winds such as thunderstorm downbursts are responsible for many structural damages. This research presents a time domain approach for estimating along-wind load effects on tall buildings using multiple wind speed time history samples, which are simulated from evolutionary power spectra density (EPSD) functions of non-stationary wind fluctuations using the method developed by the authors' earlier research. The influence of transient wind loads on various responses including time-varying mean, root-mean-square value and peak factor is also studied. Furthermore, a simplified model is proposed to describe the non-stationary wind fluctuation as a uniformly modulated process with a modulation function following the time-varying mean. Finally, the probabilistic extreme response and peak factor are quantified based on the up-crossing theory of non-stationary process. As compared to the time domain response analysis using limited samples of wind record, usually one sample, the analysis using multiple samples presented in this study will provide more statistical information of responses. The time domain simulation also facilitates consideration of nonlinearities of structural and wind load characteristics over previous frequency domain analysis.

• Journal of Science and Technology Studies
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• v.3 no.2 s.6
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• pp.61-82
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• 2003

In a new paradigm of competition, firms face a multiple industry in a generation and compete with existing capabilities and resources in a new industry. Firms need to increase dynamic capabilities to adjust to a radical change in terms of technologies for survival and sustainable growth in a new industry. But we lack a clear conceptual model explaining evolutionary process of firms facing a emerging industry with different experiences in a prior industry and where heterogeneity in firms' technological portfolios come from. How we explaining firms' heterogeneity arising in a new industiy? In this article, I suggest hypothesis explaining firms' heterogeneity in a new industry with the concept of existent industry's technological trajectories, available assets, core processes and show the possibility of model to explain the heterogeneity of firms.

• Journal of the military operations research society of Korea
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• v.29 no.2
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• pp.131-147
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• 2003

The complexity of modern weapon systems using the intelligence technology demands that rapid and effective transition from force requirements to deployment and fielding. Thus this paper deals with the integration of development procedure, evolutionary acquisition, integrated test and evaluation, improvement of the requirements decision process, use of commercial products of high quality and low cost, specification deviation, and the effective use of dual use technology. In general, decision­makers, and military field users shall first consider the moving technology rapidly into use. This study is aimed to improve the defence acquisition management directive for timely force integration of weapon system.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.67-80
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• 2000

Symbiotic evolutionary algorithms, also called cooperative coevolutionary algorithms, are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual required first selecting symbiotic partners of the individual. Several partner selection strategies are provided. The goal of this study is to analyze how much partnering strategies can influence the performance of the algorithms. With two types of test-bed problems: the NKC model and the binary string covering problem, extensive experiments are carried out to compare the performance of partnering strategies, using the analysis of variance. The experimental results indicate that there does not exist statistically significant difference in their performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.255-258
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• 2001

This paper is implementation of cellular automata neural network system which is a living creatures' brain using evolving hardware concept. Cellular automata neural network system is based on the development and the evolution, in other words, it is modeled on the ontogeny and phylogeny of natural living things. The proposed system developes each cell's state in neural network by CA. And it regards code of CA rule as individual of genetic algorithm, and evolved by genetic algorithm. In this paper we implement this system using evolving hardware concept Evolving hardware is reconfigurable hardware whose configuration is under the control of an evolutionary algorithm. We design genetic algorithm process for evolutionary algorithm and cells in cellular automata neural network for the construction of reconfigurable system. The effectiveness of the proposed system is verified by applying it to time-series prediction.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.158-166
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• 2003

The paper describes the development and application of advanced evolutionary computing techniques referred to as micro genetic algorithms ($\mu$GA) in the context of engineering design optimization. The basic concept behind $\mu$GA draws from the use of small size of population irrespective of the bit string length in the representation of design variable. Such strategies also demonstrate the faster convergence capability and more savings in computational resource requirements than simple genetic algorithms (SGA). The paper first explores ten-bar truss design problems to see the optimization performance between $\mu$GA and SGA. Subsequently, $\mu$GA is applied to a realistic engineering design problem in the injection molding process optimization.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.239-242
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• 2000

Symbiotic evolutionary algorithms are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual requires first selecting symbiotic partners of the individual. The symbiotic partner effects the change of individual's fitness and search direction. In this study we are to analyze how much partnering strategies can influence the performance of the algorithms. For this goal extensive experiments are carried out to compare the performance of partnering strategies. The NKC model and the binary string covering problem are used as the test-bed problems. The experimental results indicate that there does not exist statistically significant difference in their performance.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.6
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• pp.37-46
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• 2007

In designing the structure, the stress path is the basic data. But the stress path is not standardized to analysis the structure. So the one-dimensional frame element structure model with the triangle irregular network is used to solve the problem. And the refined evolutionary structural optimization(RESO) used in structural topology optimization is applied to this study. Through this process, the search method of the stress path is advanced and the burden of the calculation. is reduced.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.322-324
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• 2005

In this paper, we introduce the advanced Self-Organizing Fuzzy Polynomial Neural Network based on optimized FPN by evolutionary algorithm and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed model gives rise to a structurally and parametrically optimized network through an optimal parameters design available within Fuzzy Polynomial Neuron(FPN) by means of GA. Through the consecutive process of such structural and parametric optimization, an optimized and flexible the proposed model is generated in a dynamic fashion. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.