• Journal of the Korean Society for Precision Engineering
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• v.21 no.5
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• pp.188-202
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• 2004

This research was designed to investigate biomechanical aspects of the evolution based on the hypothesis of dynamic cooperative interactions between the locomotion pattern and the body shape in the evolution of human bipedal walking The musculoskeletal model used in the computer simulation consisted of 12 rigid segments and 26 muscles. The nervous system was represented by 18 rhythmic pattern generators. The genetic algorithm was employed based on the natural selection theory to represent the evolutionary mechanism. Evolutionary strategy was assumed to minimize the cost function that is weighted sum of the energy consumption, the muscular fatigue and the load on the skeletal system. The simulation results showed that repeated manipulations of the genetic algorithm resulted in the change of body shape and locomotion pattern from those of chimpanzee to those of human. It was suggested that improving locomotive efficiency and the load on the musculoskeletal system are feasible factors driving the evolution of the human body shape and the bipedal locomotion pattern. The hypothetical evolution method employed in this study can be a new powerful tool for investigation of the evolution process.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.487-496
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• 2003

The promoter that plays a very important role in gene expression as a signal part has various binding sites for transcription factors. These binding sites are located on various parts in promoter region and have highly conserved consensus sequence patterns. This paper presents a new method for the consensus pattern search in promoter regions using genetic algorithm, which adopts the assumption of N-occurrence-per-dataset model of MEME algorithm and employs the advantage of Wataru method in determining the pattern length. Our method will be employed by genome researchers who try to predict the promoter region on anonymous DNA sequence and to find out the binding site for a specific transcription factor.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.37-44
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• 2003

In this paper, we investigated the performance of both DNA coding method and Genetic Algorithm(GA) in numeric pattern (from 0 to 9) recognition. The performance of the DNA coding method is compared to the that of the GA. GA searches effectively an optimal solution via the artificial evolution of individual group of binary string using binary coding, while DNA coding method uses four-type bases denoted by Adenine(A), Cytosine(C), Guanine(G) and Thymine(T). To compare the performance of both method, the same genetic operators(crossover and mutation) are applied and the probabilities of crossover and mutation are set the same values. The results show that the DNA coding method has better performance over GA. The reasons for this outstanding performance are multiple candidate solution presentation in one string and variable solution string length.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.59-77
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• 2010

The purpose of this study is to examine the relationship between the smart-phone and the existing service convergence to find out the future direction in convergence pattern in e-business. To analyze the data and to derive the result, the association rules are applied. As a result, the findings are as followings. Firstly, it is observed that the usage patterns of smart-phone and the existing service convergence are very similar. This means that the convergence of smart-phone can be predicted through the usage pattern of the existing users. Secondly, through the analysis on the convergence patterns of smart-phone usages and the existing services, the smart-phone's link to home networking and office equipments can significantly conform to the user's requirements. It is meaningful that this research has newly approached to the future direction of e-business and the future convergence paradigm by analyzing the relationship between the usage patterns of smart-phone users and the existing service convergence.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.219-241
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• 2014

In general, Innovation Systems consists of actors, institution and network. And mutual learning through the innovation capacity is to be increased, which ultimately evolved through innovation that explains the system itself. In this study, Senior Friendly Industry in Korea for 'Innovation systems formation and evolution of the process' a dynamic perspective. The purpose of this paper is to provide suggestions that innovation policy implications for technological innovation in this sector or similar industry like a health industry, environment industry and etc. Study, a new type of formation and the evolution of the innovative system was confirmed. As the Senior Friendly Industry is a new case for innovation studies, our study may provide new research opportunities to the academia.

• Korean Journal of Plant Taxonomy
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• v.42 no.1
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• pp.13-23
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• 2012

The trnL-F region islocated in the large single-copy region of the chloroplast genome. It consists of the trnL gene, the trnL intron, and the trnL-F IGS. Molecular evolution and phylogenetic relationships in Korean Thalictrum L. were investigated using data from the cpDNA trnL-F region. Bayesian and parsimony analyses of the data set with the gap characteristics recovered well-resolved trees that are topologically similar, with clades supported by some indels evolution. Indel events of cpDNA trnL-F in Korean Thalictrum were interpreted as phylogenetically informative characteristics. Sect. Physocarpum (excluding T. osmorhizoides) was an early-diverging group with in the genus and the remaining section formed strongly supported clades. Korean Thalictrum has various evolutionary patterns, such as the spatial distribution of the nucleotide diversity and transversion-type base substitutions in the trnL-F region.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.67-82
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• 2006

We propose the HBEM(Hybrid Behavior Evolution Model) composed of rule classification and evolutionary neural network using rule descriptor and link descriptor for evolutionary behavior of virtual robots. In our model, two levels of the knowledge of behaviors were represented. In the upper level, the representation was improved using rule and link descriptors together. And then in the lower level, behavior knowledge was represented in form of bit string and learned adapting their chromosomes by the genetic operators. A virtual robot was composed by the learned chromosome which had the best fitness. The composed virtual robot perceives the surrounding situations and they were classifying the pattern through rules and processing the result in neural network and behaving. To evaluate our proposed model, we developed HBES(Hybrid Behavior Evolution System) and adapted the problem of gathering food of the virtual robots. In the results of testing our system, the learning time was fewer than the evolution neural network of the condition which was same. And then, to evaluate the effect improving the fitness by the rules we respectively measured the fitness adapted or not about the chromosomes where the learning was completed. In the results of evaluating, if the rules were not adapted the fitness was lowered. It showed that our proposed model was better in the learning performance and more regular than the evolutionary neural network in the behavior evolution of the virtual robots.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.869-871
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• 2003

단백질 부분 구조는 일종의 단백질 패턴으로써 진화적인 성질을 띄고 있다. 본 논문에서는 단백질 간의 열 안정성과 이러한 단백질 부분 구조 간의 관련성에 대해서 알아보고자 한다. 또한 오류 허용 알고리즘 (FT-Apriori)의 성능을 향상시킬 수 있는 효과적인 기법을 제안한다. 이러한 기법을 단백질 부분 구조에 적용시킴으로써 실제 단백질 데이터에서 그 효용성을 일아본다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.706-708
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• 2003

침입탐지 시스템 중 하나인 오용탐지 시스템은 축적된 침입패턴 정보를 이용하기 때문에 새로운 침입에 대하여 새로운 정의가 필요하다. 이러한 문제점을 극복하여 새로운 침입에 대하여 일일이 정의하지 않고 자동으로 새로운 규칙을 생성하도록 하는 것이 좀 더 바람직하다. 본 논문에서는 새로운 규칙을 찾기 위한 방법으로 생물의 진화과정을 모델링한 유전자 알고리즘(GA)을 이용하였다. GA는 계산에 의존한 방법에 비하여 전역적인 해를 구할 때 더 효율적이다. GA를 이용하여 규칙을 자동 생성하고 침입을 탐지할 수 있는 규칙을 찾아가는 방식을 제안하였다. 실험 결과에서는 GA를 이용하여 자동 생성된 규칙으로 40~60%의 탐지율로 침입을 탐지할 수 있다는 것을 확인하였다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1964-1965
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• 2011

본 연구에서는 패턴분류를 위해 기존의 방사형 기저 함수 신경회로망(Radial Basis Funtion Neural Network)과 다항식 신경회로망(Polynomial Neural Network)을 결합한 다중 출력 방사형 기저 함수다항식 신경회로망 (Multi Output Radial Basis Funtion Polynomial Neural Network)의 분류기를 제안한다. 제안된 모델은 PNN을 기본 구조로 하여 1층에 기존의 다항식 노드 대신 다중 출력 형태의 RBFNN을 적용 한다. RBFNN의 은닉층에는 기존의 활성함수가 아닌 fuzzy 클러스터링을 사용하여 입력 데이터의 특성을 고려한 적합도를 사용하였다. PNN은 입력변수의 수와 다항식 차수가 모델의 성능을 결정함으로 최적화가 필요하며 본 논문에서는 Differential Evolution(DE)을 사용하여 모델의 구조 및 파라미터를 최적화시켜 모델의 성능을 향상시켰다. 패턴분류기로써의 제안된 모델을 평가하기 위해 pima 데이터를 이용하였다.