• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.489-502
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• 2015

Sometimes called the Silicon Fen, the Cambridge cluster is well known as the most innovative hi-tech cluster in the world. This paper attempts to explore the evolutionary dynamics of the Cambridge cluster, drawing upon the triple-helix approach. To understand the evolutionary dynamics of the Cambridge cluster, it is important to examine the role and impact of the University of Cambridge, which is conceived as one of the best higher educational institutions in the world. The Cambridge cluster has been evolved on the basis of a strong university-industry relationship. University spin-outs have a long tradition in Cambridge with the history of more than a century, and they have played a critical role in making the cluster more innovative. Business networks and social capital molded for a long time in the region become a foundation for active local spin-out activities. However, since 2000 the central government started steadily to require British universities to be an entrepreneurial university, with the purpose of the reduction of university subsidies. As a result of this, spin-out activities in the Cambridge cluster show a sharp decline, which is a factor of threatening the dynamic evolution of the cluster.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1207-1236
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• 2018

This paper explores the life cycle of innovation cluster, especially focussing on the Korean representative innovation cluster, Daedeok Innopolis. For this purpose, we review theoretically how an innovation cluster has been growing up. In particular, we discuss how a cluster has been formed and activated by governmental innovation policies from an evolutionary perspective. By doing so, the study identifies the typical features of an innovation cluster according to each dimensions of the cluster life cycle. The results of this study are as follows: First, in this study, Daedeok Innopolis has characteristics of latency, emergence, growth, and maturity from evolutionary perspective. Second, the governmental structure of the Daedeok Innopolis is a strong government-led and top-down structure, which has features of inclusiveness and flexibility such as umbrella policy. Third, the Daedeok Innopolis can be seen that adaptive or renewal development, as while, it can be applied fine adjustment the innovation cluster policy towards the recognition of innovation obstacle at each dimensions of the life cycle. Therefore, these discussions expose what kind of policy interventions should be addressed to form and develop the innovation cluster according to the cluster life cycle, as while, the development of adaptive policies during the risk and take-off period. Ultimately, the study provides that a different kind of policy instruments and tools should be implemented according to innovation cluster development and its distinctive characteristic per each dimensions of the cluster life cycle.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.2
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• pp.249-263
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• 2014

Established as the first science park in the world in the late 1950's, the Research Triangle Park(RTP) has not jut grown significantly but also has been successful in the transition from the exogenous development model to the endogenous development model. In this context, this paper attempts to explore the evolutionary path of the RTP by drawing upon the concept of triple-helix spaces of regional innovation. Firstly, the three research universities in the triangle area, as a knowledge space, played a fundamental role for forming the RTP. However, it is difficult to say that the regional universities, as opposed to the Silicon Valley and the Boston area, have had a significant impact on inducing the dynamics of the cluster evolution and the triple helix spaces. Secondly, it can be argued that the North Carolina's Board of Science and Technology, which was formed in 1961 but traced back to the 1950's in its origin, has been a centerpiece of a consensus space that makes a contribution to creating, sustaining and transforming the RTP as a triple-helix-based innovation cluster. Thirdly, there have been a plenty of agents to be an innovation space in the RTP. Particularly, the North Carolina Biotechnology Center(NCBC) and the Microelectronic Center of North Carolina(MCNC) have been the boundary permeable agents to make triple-helix agents interact. Today, the RTP has the triple-helix spaces with the structure that a consensus spaces is centered on out of the three, but all of those are inter-connected and influenced by each other. It can be claimed that the RTP today shows the dynamic structure of cluster evolution in a way in which the existing industry sectors have adapted to the changes in external environment and the new industry sectors have emerged at the same time.

• Journal of the Korean association of regional geographers
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• v.20 no.3
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• pp.256-258
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• 2014

This paper aims at examining the role of university, industry and government, which constitute the triple-helix innovation system in hi-tech cluster, based on the case of the Research Triangle Park, North Carolina, USA. Firstly, the state government has played a catalytic role by building the horizontal governance of triple-helix actors. By doing so, the state government has made it possible for not only growing but also transforming the RTP as an high-tech cluster. Secondly, universities in the triangle area have played to some extent a limited role in sustaining the evolution of cluster. Thirdly, the RTP has long been dominated by a small group of large firms. However, the situation has been changed since 1990s, because new start-ups from universities and local large firms and the technology transfer activities between universities and firms have been increased in the RTP and its surrounding area. Finally, it argues that the continuous evolution of the RTP has been to some or large extent influenced by the transition from the exogenous development model to the endogenous development model.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.89-96
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• 2007

Various classification methods have been developed to reuse components. These classification methods enable the user to access the needed components quickly and easily. Conventional classification approaches include the following problems: a labor-intensive domain analysis effort to build a classification structure, the representation of the inter-component relationships, difficult to maintain as the domain evolves, and applied to a limited domain. In order to solve these problems, this paper describes a composite cluster analysis approach for component classification. The cluster analysis approach is a combination of a hierarchical cluster analysis method, which generates a stable clustering structure automatically, and a non-hierarchical cluster analysis concept, which classifies new components automatically. The clustering information generated from the proposed approach can support the domain analysis process.

• Journal of the Korean association of regional geographers
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• v.18 no.3
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• pp.283-297
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• 2012

This study aims to analyze an evolutionary path and the dynamics of the Seoul Digital Industrial Complex in Korea based on the analysis of cluster life cycles. From the mid 1960s to the late 1990s, the life cycles and their characteristics of the Seoul Digital Industrial Complex (Guro Industrial Park) are examined as emergence-growth-sustainment-decline focused on the number of firms and employees. After the late 1990s, the number of firms and employees increases rapidly and the active actors of the growth and restructuring are transformed to the technology-intensive SMEs and knowledge-based service firms. Knowledge industry centers (apartment-type factories) help evolve into the life cycle of transformation as knowledge-based clusters after the mid 2000s.

• Journal of the Korean Academic Society of Industrial Cluster
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• v.2 no.1
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• pp.1-13
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• 2008

Despite growing recognition of the significance of industrial clusters to regional economic success, there has been only limited attention paid to the effectiveness of cluster policies in old industrial regions. Many of these regions still retain functioning industrial clusters, or have clusters which are adopting new strategies as part of a process of regeneration. This paper argues that the effectiveness of cluster policies in old industrial regions depends upon the extent to which they recognise the evolutionary nature of industrial clusters. It reviews the literature on the transformation of old industrial regions in Europe, and examines how cluster policies have risen to prominence as a policy tool. These strands ate brought together in an exploration of cluster policies in old industrial regions. A brief case study is presented of the evolution of the steel industry supply chain in north east England. The conclusions focus upon the data requirements that form a starting point for informed policy intervention into presses of cluster evolution.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.251-260
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• 2006

Homology searching on the primary structure (i.e., amino acid arrangement) of protein sequences is an essential part in predicting the functions and evolutionary histories of proteins. However, proteins distant in an evolutionary history do not conserve amino acid residue arrangements, while preserving their structures. Therefore, homology searching on proteins' secondary structure is quite important in finding out distant homology. In this manuscript, we propose an indexing scheme for efficient approximate searching on the secondary structure of protein sequences which can be easily implemented in RDBMS. Exploiting the concept of clustering and lookahead, the proposed indexing scheme processes three types of secondary structure queries (i.e., exact match, range match, and wildcard match) very quickly. To evaluate the performance of the proposed method, we conducted extensive experiments using a set of actual protein sequences. CSI was proved to be faster than the existing indexing methods up to 6.3 times in exact match, 3.3 times in range match, and 1.5 times in wildcard match, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.41-44
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• 2003

인공생명 기법의 대표적인 응용분야 중 하나인 창발적인 개체의 생성에서 유전자를 표현하는 방법으로 크게 방향성 그래프와 L-system의 두 가지 방법이 사용되고 있다. 두 가지 방법 모두 각기 좋은 특성이 있지만 L-system은 사용자에 의해 내부적인 파라메터로 정의되기 때문에 전체적인 실제 모양을 구조적으로 정의하기 어렵다 본 논문에서는 이런 단점을 극복하고자 실제 모양을 표현하는데 적절한 구조적 방향성 그래프를 도입하여 개체의 유전자를 구조적으로 표현함으로써 실제 개체와 유사한 모양을 창발적으로 생성하고, 이를 클러스터 대화형 유전자 알고리즘에 적용하여 사용자가 생성하고자 하는 실제 모양의 캐릭터를 자동으로 생성하게 하였다. 실험을 통해 2차원에서의 의자모양과 꽃 모양을 생성함으로써 다양한 구조의 창발적인 캐릭터를 생성할 수 있는 가능성을 제시했다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.204-210
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• 2005

This paper presents online identification algorithm for TSK fuzzy model. The proposed algorithm identify structure of premise part by using distance, and obtain the parameters of the piecewise linear function consisting consequent part by using recursive least square. Only input space was considered in Most researches on structure identification, but input and output space is considered in the proposed algorithm. By doing so, outliers are excluded in clustering effectively. The existing other algorithm has disadvantage that it is sensitive to noise by using data itself as cluster centers. The proposed algorithm is non-sensitive to noise not by using data itself as cluster centers. Model can be obtained through one pass and it is not needed to memorize many data in the proposed algorithm.