• Proceedings of the Korean Environmental Sciences Society Conference
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• 2020.10a
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• pp.201-201
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• 2020

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2020.10a
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• pp.200-200
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• 2020

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.116-123
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• 2019

This study focused on defining concepts such as biology push (biology-based biomimicry) and technology pull (technology problem-based biomimicry) in the multidisciplinary field of ecological imitation and analyzing the status of related research and technology at the domestic and international levels. From an ecological point of view, biomimicry is defined as ecological mimicry in which ideas obtained through classification and investigation of principles of biology and ecology are applied to the concepts of engineering and technology. We also defined the biology push as the ecological imitation based on biological characteristics starting from an ecological viewpoint and technology pull as the ecological imitation based on technical problems starting from technical needs. Although biomimicry studies often focus on the technology development by finding stable and eco-friendly source materials from biological and ecological characteristics, we wanted to emphasize the unlimited potential of research of biomimicry that can begin with an idea based on biological and ecological characteristics. This study presents the need to develop the research and technology further based on the biological and ecological viewpoints that can contribute to future sustainable development.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2020.10a
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• pp.224-224
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• 2020

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.27-29
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• 2007

패턴 인식 문제를 푸는데 있어 특징 선택을 해주는 것은 패턴 인식의 성능 향상을 위해 중요한 과정 중 하나이다. 본 연구에서는 대표적인 생태계 모방 알고리즘 2 가지를 선택하여 특징 선택 문제에 적용하여 보고, 그 성능을 비교 분석하였다. 데이터의 특징을 줄여주는 기능과 패턴 인식 성능의 향상 여부를 중심으로 평가하였으며, 이를 통해 생태계 모방 알고리즘이 특징 선택 문제에 효과적으로 사용될 수 있는지에 대해 논의해보고, 두 방법의 장단점과 특징에 대해 생각해 본다.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.331-340
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• 2008

Feature Selection is one of methods to improve the classification accuracy of data in the field of machine learning. Many feature selection algorithms have been proposed and discussed for years. However, the problem of finding the optimal feature subset from full data still remains to be a difficult problem. Bio-inspired algorithms are well-known evolutionary algorithms based on the principles of behavior of organisms, and very useful methods to find the optimal solution in optimization problems. Bio-inspired algorithms are also used in the field of feature selection problems. So in this paper we proposed new improved bio-inspired algorithms for feature selection. We used well-known bio-inspired algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to find the optimal subset of features that shows the best performance in classification accuracy. In addition, we modified the bio-inspired algorithms considering the prior importance (prior relevance) of each feature. We chose the mRMR method, which can measure the goodness of single feature, to set the prior importance of each feature. We modified the evolution operators of GA and PSO by using the prior importance of each feature. We verified the performance of the proposed methods by experiment with datasets. Feature selection methods using GA and PSO produced better performances in terms of the classification accuracy. The modified method with the prior importance demonstrated improved performances in terms of the evolution speed and the classification accuracy.

• Information and Communications Magazine
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• v.31 no.1
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• pp.53-62
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• 2013

생태계를 구성하고 있는 각 생물체들은 외부에서의 제어 개체 없이 독자적이면서 매우 단순하고 적은 수의 행동 규칙의 준수를 통하여 해당 생태계의 유지, 관리 및 동기화 등의 기능을 수행하고 있음을 관찰 할 수 있다. 이처럼 지구상의 다양한 생물체의 행동 원리를 관찰하고 이를 기반으로 모델링한 알고리듬을 생체모방 알고리듬 (biologically inspired or bio-inspired algorithm)이라 한다. 생체모방 알고리즘은 동종 혹은 이종의 다수의 개체가 존재하고, 주변 환경이 동적으로 변하며, 사용가능한 자원의 제약이 정해져 있을 때, 각 개체들이 분산 및 자율적으로 움직이는 환경에서 안정성, 확장성, 적응성과 같은 특징을 보여주는데, 이는 통신 네트워크 환경 및 서비스 요구사항과 유사성을 갖는다. 본 논문에서는 최근에 발표된 생체모방 알고리즘으로 통신 및 네트워킹 기술로 적용 가능한 Huddling Penguins 알고리즘, Krill Herd알고리즘, Cuckoo 알고리즘에 대해 살펴보고, 관련 프로젝트 및 연구 동향을 정리한다.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.9
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• pp.416-424
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• 2007

The Bio-Inspired system is a computing model that emulates the objects in ecosystem which are evolving themselves and cooperate each other to perform some tasks. Since it could be used to solved the complex problems that have been very difficult to resolve with previous algorithms, there have been a lot of researches to develop an application based on the Bio-Inspired system. However, since this computing model requires the process of evolving and cooperating with a lot of objects and this process takes a lot of times, it has been very hard to develop an application based on this computing model. This paper presents a parallel simulator for a Bio-Inspired system that is designed and implemented with OMNeT++ on PC clusters, and proves its usefulness by showing its simulation performance for a couple of applications. In the proposed parallel simulator, the functions required in the ERS platform for evolving and cooperating between objects (called Ecogent) are mapped onto the functions of OMNeT++, and they are simulated on PC clusters simultaneously to reduce the total simulation time. The simulation results could be monitored with a GUI In realtime, and they are also recorded into DBMS for systematic analyses afterward. This paper shows the usefulness of the proposed system by analyzing its performances for simulating various applications based on Bio-Inspired system on PC clusters with 4 PCs.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.545-549
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• 2007

The Bio-Inspired System focuses on the creation of an effective system model for massive network applications and is being widely developed. However, the system has a problem-difficulty implementing three features in the system, which includes scalability, adaptability and survivability. To solve this problem, we designed an Ecogent as a multiple intelligence agent, and a Bio-platform to address the three features of scalability, adaptability and survivability. The Bio-Inspired System Platform consists of an ERS (Ecogent Runtime Services) Platform and a Bio-Platform. The ERS platform serves the basic functions of mobile agents, such as Registration, Life Cycle, Migration, Communication, Location and Fault Tolerance. The Bio-Platform includes the functions of Evolution Control and Stigmergy Control to address evolution and adaptation.

• Korean Journal of Environmental Biology
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• v.38 no.4
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• pp.554-562
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• 2020

Tremex fuscicornis (Siricidae), known as the xylophagous horntail, and Leucospis japonica (Leucospidae), known as the parasitoid wasp, are wood-boring wasps belonging to the order Hymenoptera. These insects are interesting sources of biological inspiration for the development of drilling mechanisms. To study the biomimicry aspects, the morphological characters of the ovipositor of T. fuscicornis and L. japonica were analyzed using a stereoscopic microscope, a field emission scanning electron microscope, and an optical microscope. There were many differences in the ovipositors between the two species, such as shape, length, surface structure, and arrangement of the teeth. Evenly arranged teeth were developed at the tip of both the dorsal valve and the ventral valve of the ovipositor of T. fuscicornis and looked like a rotating drill bit. In contrast, in L. japonica, the teeth, which looked like a saw, were found only on the ventral valve. Moreover, the tip of the ovipositor of T. fuscicornis was symmetrically divided into four parts, while that of L. japonica was divided into three parts having a 2:1:1 ratio. However, in the case of T. fuscicornis, after the 14th tooth, four parts melded into three parts maintaining a 2:1:1 ratio, and a dovetail joint was found on the horizontal cross-section of the ovipositor that allowed vertical movement for making a hole. These morphological differences of the ovipositor may be due to the insects' lifestyles and phylogenetic distance. Finally, zinc was commonly found at the tip of the ovipositors of both species, a probable result of ecological adaptation created by drilling wood.