• 한국소음진동공학회논문집
• /
• 제12권6호
• /
• pp.478-487
• /
• 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.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2004년도 춘계학술대회논문집
• /
• pp.400-403
• /
• 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.

• 한국콘텐츠학회논문지
• /
• 제11권1호
• /
• pp.193-201
• /
• 2011

본 연구에서는 디지털 미디어아트의 몰입과 상호작용적 특성에 따른 관객과 작품 사이의 '닫힌 관계'로써의 '열린 상호작용성'을 넘어, 인공생명(Artificial Life) 예술에 이르러 더욱 진화된 상호작용성에 관해 고찰한다. 이를 위해 생물학 및 계산과학을 비롯한 다양한 학문의 성과에 따른 인공생명 이론을 살펴보고, 인공생명의 자율성과 창발적 행동을 인공생명 예술적 맥락과 연결되는 특성으로 분석하였다. 특히 인공생명 예술을 공인하는 역할을 하고 있는 'VIDA : Art and Artificial Life International Awards'에서 선정된 예술 작품들 중 환경과 상호작용하는 인공생명 예술 작품과 외부 세계에서 개체로 살아 움직이는 인공생명 예술 작품들을 중심으로 분석하여, 관객과 작품 간의 감성적 주체로써의 관계와 나아가 기술과 인간이 맺는 공생과 공진화의 다양한 층위의 관계성에 대해 이해하고자 하였다.

• 대한기계학회논문집A
• /
• 제25권2호
• /
• pp.173-181
• /
• 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.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2001년도 추계학술대회논문집A
• /
• pp.698-702
• /
• 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
• /
• 제37권3호
• /
• pp.299-306
• /
• 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.

• 한국정밀공학회지
• /
• 제21권9호
• /
• pp.85-94
• /
• 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.

• 생명과학회지
• /
• 제4권3호
• /
• pp.92-101
• /
• 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.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2002년도 추계학술대회논문집
• /
• pp.1034-1037
• /
• 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.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2002년도 추계학술대회논문초록집
• /
• pp.400.1-400
• /
• 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)