• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.6
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• pp.478-487
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• 2002

This paper presents a hybrid method to compute the solutions of an optimization Problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The artificial life algorithm has the most important feature called emergence. The emergence is the result of dynamic interaction among the individuals consisting of the system and is not found in an individual. The conventional artificial life algorithm for optimization is a stochastic searching algorithm using the feature of artificial life. Emergent colonies appear at the optimum locations in an artificial ecology. And the locations are the optimum solutions. We combined the feature of random-tabu search method with the conventional algorithm. The feature of random-tabu search method is to divide any given region into sub-regions. The enhanced artificial life algorithm (EALA) not only converge faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. The enhanced artificial life algorithm is applied to the optimum design of high-speed, short journal bearings and its usefulness is verified through an optimization problem.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.400-403
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• 2004

This paper presents an optimum design of journal bearings using a hybrid method to find the solutions of optimization problem. The present hybrid algorithm, namely Enhanced Artificial Life Algorithm(EALA), is a synthesis of an artificial life algorithm(ALA) and the random tabu search(R-tabu) method. EALA is applied to the optimum design of journal bearings supporting simple rotor. The applicability of EALA to optimum design of rotor-bearing system is exemplified through this study.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.193-201
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• 2011

In this study, we consider the evolved interactivity at the Artificial Life Art beyond 'open interactivity' as 'closed relationship' between viewer/participant and artwork by immersive and interactive features of digital media art. In order to consider this evolved interactivity, we survey the theory of artificial life of which result of many studies like biology and computational science. And then we analysed characteristics related artistic context of artificial life at the autonomy and emergent behavior of artificial life. Especially, we research the artworks of interaction with ecologies and of living in outside(not in- silico) among the artworks of officially adopting an artificial life arts in 'VIDA : Art and Artificial Life International Awards'. And we are going to understand the relationship of emotional subjects between viewer/participant and artwork, and a step further to understand the diverse relationship of symbiosis and co-evolution of the technology and human.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.2
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• pp.173-181
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• 2001

This paper presents an artificial life algorithm which is remarkable in the area of engineering for functions optimization. As artificial life organisms have a sensing system, they can find the resource which they want to find and metabolize. And the characteristics of artificial life are emergence and dynamic interaction with environment. In other words, the micro-interaction with each other in the artificial lifes group results in emergent colonization in the whole system. In this paper, therefore, artificial life algorithm by using above characteristics is employed into functions optimization. The optimizing ability and convergent characteristics of this proposed algorithm is verified by using three test functions. The numerical results also show that the proposed algorithm is superior to genetic algorithms and immune algorithms for the multimodal functions.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.698-702
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• 2001

This paper presents a combinatorial method to compute the solutions of optimization problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The hybrid algorithm is not only faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. And the enhanced artificial life algorithm is applied to optimum design of high-speed, short journal bearings and the usefuless is verified through this example.

• The Plant Pathology Journal
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• v.37 no.3
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• pp.299-306
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• 2021

Pollination is an essential process for plants to carry on their generation. Pollination is carried out in various ways depending on the type of plant species. Among them, pollination by insect pollinator accounts for the most common. However, these pollinators have be decreasing in population density due to environmental factors. Therefore, use of artificial pollination is increasing. However, there is a lack of information on microorganisms present in the artificial pollens. We showed the composition of bacteria structure present in the artificial pollens of apple, kiwifruit, peach and pear, and contamination of high-risk pathogens was investigated. Acidovorax spp., Pantoea spp., Erwinia spp., Pseudomonas spp., and Xanthomonas spp., which are classified as potential high-risk pathogens, have been identified in imported pollens. This study presented the pollen-associated bacterial community structure, and the results are expected to be foundation for strengthening biosecurity in orchard industry.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.9
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• pp.85-94
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• 2004

As over 70% of the total life cycle cost (LCC) of a product is committed at the early design stage, designers are in an important position to substantially reduce the LCC of the products they design by giving due to life cycle implications of their design decisions. During early design stages, there may be competing concepts with dramatic differences. In addition, the detailed information is scarce and decisions must be made quickly. Thus, both the overhead in developing parametric LCC models fur a wide range of concepts, and the lack of detailed information make the application of traditional LCC models impractical. A different approach is needed, because a traditional LCC method is to be incorporated in the very early design stages. This paper explores an approximate method for providing the preliminary LCC, Learning algorithms trained to use the known characteristics of existing products might allow the LCC of new products to be approximated quickly during the conceptual design phase without the overhead of defining new LCC models. Artificial neural networks are trained to generalize product attributes and LCC data from pre-existing LCC studies. Then the product designers query the trained artificial model with new high-level product attribute data to quickly obtain an LCC for a new product concept. Foundations fur the learning LCC approach are established, and then an application is provided.

• Journal of Life Science
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• v.4 no.3
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• pp.92-101
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• 1994

With the rapid development of bioorganic chemistry recently, a field of artificial enzymes has a great concern from the industrial point of view. A number of possibilities now exist ofr the construction of artificial enzymes. They must posses two structural entities, a substrate-binding site and a catalytically effective site. It has been found that producing the facility for substrate binding is relatively straightforward but catalytic sites are somewhat more difficult. Therefore, synthetic catalysts do not yet match all the properties of an enzyme, however, the design of catalysts has lead to very powerful effects. This article reviews the existing literature on the modeling of artificial enzymes using cyclodextrin, modified cyclodextrin and crown compounds.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.1034-1037
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• 2002

This paper presents an optimum design of rotor-bearing system using a hybrid method to compute the solutions of optimization problem. The present hybrid algorithm namely Enhanced Artificial Life Algorithm(EALA), is a synthesis of an artificial life algorithm(ALA) and the random tabu search(R-tabu) method. We applied EALA to the optimum design of rotor-shaft system supported by the floating ring journal bearings. we will propose the optimum shape of rotor, position and shape of bearings. Through this study, we investigate the reliability and usefulness of EALA.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.400.1-400
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• 2002

This paper presents an optimum design of rotor-bearing system using a hybrid method to compute the solutions of optimization problem. The present hybrid algorithm, namely Enhanced Artificial Life Algorithm(EALA), is a synthesis of an artificial life algorithm(ALA) and the random tabu search(R-tabu) method. We applied EALA to the optimum design of rotor-shaft system supported by the floating ring journal bearings. (omitted)