• 정보학연구
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• 제8권1호
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• pp.119-124
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• 2005

Learning procedure in the neural network is updating of weights between neurons. Unadequate initial learning coefficient causes excessive iterations of learning process or incorrect learning results and degrades learning efficiency. In this paper, adaptive learning algorithm is proposed to increase the efficient in the learning algorithms of Kohonens Self-Organization Neural networks. The algorithm updates the weights adaptively when learning procedure runs. To prove the efficiency the algorithm is experimented to clustering of the random weight. The result shows improved learning rate about 42~55% ; less iteration counts with correct answer.

• 지식경영연구
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• 제17권3호
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• pp.65-91
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• 2016

Although the success of industrial clusters largely depends on whether clustering firms can achieve economic performance, there has been less attention on investigating factors and conditions contributing to the performance enhancement for clustering small and medium-sized enterprises (SMEs). Along this vein, we adopt the theories of social capital and organizational learning as those success factors for clustering SMEs. This study thus aims at examining what effect social capital accrued in the relationships among actors within clusters has on firm performance of clustering SMEs and what role organizational learning plays in the linkage between social capital and firm performance. For the empirical analysis, we operationalized the variables and their measures to develop questionnaires through the theoretical reviews on literatures. As a sample of 227 clustering SMEs, our collected data was analyzed by hierarchical regression analysis. The results confirmed that a high level of social capital, represented by network, trust, and norm, has positive effect on firm performance of clustering SMEs. We also found that clustering firms presenting high organizational learning, represented by absorptive and transformative capability, achieve better performance than those placing less value on organizational learning. Furthermore the significant relationship between social capital and firm performance is mediated partially through organizational learning. These findings imply not only that the territorial agglomeration of industrial cluster does not guarantee the performance creation of clustering SMEs but that they need to develop social capital among various actors within clusters, facilitating their knowledge diffusion. In order to absorb and mobilize the shared knowledge and information into strategic resources, the firms should improve their capability associated with organizational learning. These expand our understanding on the importance of social capital and organizational learning for the performance enhancement of clustering firms. Differentiating from major studies addressing benefits and advantages of industrial cluster, this study based on the perspective of firm-internal business process contributes to the literature advancement. Strategic and policy implications of this study are discussed in detail.

• 한국산학기술학회논문지
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• 제19권2호
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• pp.370-379
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• 2018

우리나라는 중이온 가속기 건설을 중심으로 과학지식이 사업화로 연결될 수 있도록 하는 지리적 공간으로서의 국제과학비즈니스벨트에 관한 계획을 2009년에 확정하였다. 과학기반 클러스터의 형성 단계에서 국제과학비즈니스벨트의 각 클러스터의 우선 유치업종의 선택은 클러스터의 성격과 발전에 많은 영향을 미칠 수 있다는 점에서 매우 중요하다. 본 연구는 정부에서 제시한 국제과학비즈니스벨트의 과학기반 혁신클러스터의 조성을 위해 유치해야 할 핵심 업종들을 제시하고자 한다. 산업별로 클러스터 형성과정이 상이할 뿐만 아니라, 산업 내 특정 업종이 클러스터의 성장과정에 미치는 영향력이 다르기 때문에 혁신생태계 조성을 위한 앵커 섹터를 파악하는 것이 매우 중요하다. 국제과학비즈니스벨트 내 4개 클러스터의 형성 및 성장을 위한 기업을 분석하기 위해 본 연구는 Swann & Prevezer의 산업 클러스터링(industrial clustering) 모델을 활용하여 분석하였다. 본 연구에서는 기업 관련 자료의 경우 2014년의 제조업 및 서비스업 대상 한국기업혁신조사(ICT 클러스터), 2014년 국내 바이오산업 실태조사(바이오헬스케어 클러스터), 2015 국내 나노융합산업 실태조사(첨단산업 클러스터)에 관한 최신자료를 이용하였다. ICT, 바이오헬스케어, 나노 등 3개 산업군에 대한 클러스터링 분석을 수행한 결과 각 산업군에는 다른 여러 섹터에 속하는 기업들의 지역 내 진입을 유발하는 중심적 역할을 하는 섹터들이 있는 것으로 나타났는데, ICT 산업의 경우 정보통신서비스 섹터, 바이오헬스케어 산업의 경우 바이오공정/기기 섹터, 나노 산업군의 경우 나노전자 섹터가 각각 중심적 역할을 하는 것으로 분석되었다. 분석 결과를 바탕으로 본 연구는 국제과학비즈니스벨트 클러스터를 육성하기 위한 기업 유치 전략과 정책에 대한 시사점을 제시하였다.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1998년도 제13회 하계학술발표회 논문집
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• pp.208-215
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• 1998

Since the advent of conceptual prototype and seminal application, the notion of national systems of innovation(NSI) has drawn an increasing recognition. Although the morphological entanglement is still ubiquitous and the theoretical underpinning is fragile, NSI seems to be the last step toward an increasingly complex and encompassing concept of innovation research. Inevitably, NSI necessitates the comparative analysis in that it normatively attempts to draw best practices. Unfortunately, national profiles are too complex and diverse to derive a unified, concrete representation of the system, posing the problem of defining and modelling NSI for international comparison. This paper aims at providing an inductive taxonomy of NSI based on R&D structure of OECD member economies. Based on the similarity among national profiles, clustering method was applied to identify seven clusters such as (1) enterprise-government funding and enterprise-education performing group, (2) enterprise-government funding and balanced performing group, (3) balanced funding and enterprise-education performing group, (4) balanced funding and performing group, (5) enterprise-dominating group, (6) government-education dominating group and (7) government-education funding and education performing group. This paper by nature is descriptive and exploratory. R&D structure represents a static snapshot of innovative performance since it accounts for only the input side of NSI and thus may not offer convincing explanations of the holistic innovation system. A more detailed and extensive analysis on the economic/technological performance across clusters will shed light on the promising avenue to future research.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.29-36
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• 2022

In deep learning classification tasks, most models frequently assume that all labels are available for the training datasets. As such strategies to learn new concepts from unlabeled datasets are scarce. In fingerprint classification tasks, most of the fingerprint datasets are labelled using the subject/individual and fingerprint datasets labelled with finger type classes are scarce. In this paper, authors have developed approaches of classifying fingerprint images using the majorly known fingerprint classes. Our study provides a flexible method to learn new classes of fingerprints. Our classifier model combines both the clustering technique and use of deep learning to cluster and hence label the fingerprint images into appropriate classes. The K means clustering strategy explores the label uncertainty and high-density regions from unlabeled data to be clustered. Using similarity index, five clusters are created. Deep learning is then used to train a model using a publicly known fingerprint dataset with known finger class types. A prediction technique is then employed to predict the classes of the clusters from the trained model. Our proposed model is better and has less computational costs in learning new classes and hence significantly saving on labelling costs of fingerprint images.

• Fisheries and Aquatic Sciences
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• 제27권1호
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• pp.48-55
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• 2024

The study assessed the utility of mitochondrial DNA for identifying a deceased rorqual discovered off the western coast of India. Both the COI and Cytb genes exhibited remarkable 99-100% similarity with the GenBank sequence of Balaenoptera musculus through a global BLAST search, confirming their affiliation with this species. Inter-species genetic distances for COI and Cytb genes ranged from 6.75% to 9.80% and 7.37% to 10.96% respectively, compared with other Balaenopteridae species. The Bayesian phylogenies constructed based on both COI and Cytb genes demonstrated clear and separate clustering for all Balaenopteridae species, further reaffirming their distinctiveness, while concurrently revealing a cohesive clustering pattern of the generated sequences within the B. musculus clade. Beyond species confirmation, this study provides valuable insights into the presence of live and deceased B. musculus individuals within Indian marine ecosystems. This information holds significant potential for guiding conservation efforts aimed at safeguarding Important Marine Mammal Areas (IMMAs) in India over the long term.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 2005년도 27회 하계학술발표회 논문집
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• pp.116-139
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• 2005

ICT(information and communication technology) has played a pivotal role in the world economy, and the out look for ICT has improved markedly. One of the noticeable characteristics in the ICT sector Is the global rationalization of its technology and service. Specialization on the specific ICT capability is a pressing problem for many countries. Along the line of classical innovation cluster and network studies, this paper suggests a way to find and analyze the role of core technologies on the ICT network First, technology network is constructed by using patent citation data from USPTO. Then, a couple of cluster is generated by K-means clustering technique. Finally, brokerage analysis is applied to manifest the role of principal technologies. The network visualization and some stylized facts on dynamics are briefly given altogether Based on the role and relationship of technologies across clusters, it is expected that this research could contribute to the ICT cluster formation and the vision-making for ICT specialization at the viewpoint of technology Policy.

• Asian Journal of Innovation and Policy
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• 제5권3호
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• pp.293-314
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• 2016

Patent information as a proxy measure of technological capability has been utilized to establish technological strategies of firms. It is important to monitor what competitors' plans for direction on research and development in the initial stage of new industry. Cancer metabolism has been considered as a beacon of hope for cancer research because it is anticipated that the research field will play a central role in developing effective cancer therapies. There is little attention given to understanding the status quo of organizational configurations. By utilizing network analysis, six sub-groups of cancer metabolism were categorized and the relationship between an individual field and participants were analyzed based on cluster and entire network-level. Although the largest drug and biotech companies tried to take an initiative across the whole fields, the differences in technological capabilities between them was discovered. This paper attempts to improve the validity of the suggested procedure and is significant in that it looks at the entire structure of cancer metabolism research from a strategic perspective for the first time.

• 산업클러스터
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• 제1권1호
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• pp.29-46
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• 2007

이 논문은 우리나라 산업 클러스터 형성여건을 파악하고 정책적 함의를 도출하는데 목적이 있다. 이를 위하여 지역혁신사업 추진 주체들을 대상으로 지역의 클러스터 형성수준을 조사한 설문조사 결과를 활용하였다. 그 결과 수도권과 비수도권, 대도시와 중소도시 간에는 클러스터 형성여건과 발전단계가 상이하다. 집적 등 기반조성기 요인들은 양호하나 형성기 요인들인 전략산업별 연구자, 벤처기업과 대기업 관계, 경영, 금융 및 마케팅 등 기업지원기관 및 분리신설기업 등은 취약한 것으로 나타났다. 따라서 발전된 지역과 저 발전된 지역을 구분하고 지역의 여건과 발전단계에 맞는 다양한 사업을 개발하여 추진할 필요가 있다. 수도권과 지방간의 균형발전이 중요한 현 시점에서 지역혁신사업의 입지는 형평성 보다는 효율성, 분산 보다는 집적, 백화점식 보다는 지역의 특화를 고려하여 선정 추진하는 것이 필요하다. 발전된 지역은 지역내 균형발전 방향, 저 발전된 지역은 지역내 선택과 집중 방향으로 추진할 필요가 있다.

• 벤처창업연구
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• 제2권3호
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• pp.103-122
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• 2007

본 연구는 지역발전을 위한 다양한 이론모형들을 살펴보았고, 경쟁적으로 추진되고 있는 각국이 혁신클러스터 육성정책과 성공요인, 대전지역을 중심으로 혁신클러스터 활성화를 위한 정책과제 등을 살펴보았다. 혁클러스터의 활성화를 통해 지역을 발전시키기 위해서는 산업혁신클러스터가 발전할 수 있는 여건의 조성과 체계적이고 지속적인 정부의 지원정책이 중요하다. 세계적으로 성공적이라고 평가받고 있는 미국의 실리콘밸리, 샌디에고의 UCSD, 중국의 중관촌(中關村), 스웨덴의 시스타(Kista), 핀란드의 울루(Oulu) 등은 연구개발, 생산, 지원시스템 외에 이들 요소들을 유기적으로 연결시켜주는 역동성과 해외 클러스터 및 시장과의 긴밀한 네트워크가 발달되어 있다. 그러나 유리한 여건에도 불구하고 대전지역의 벤처산업은 수도권 등에 비하여 활성화되지 못하고 있다. 산업혁신 클러스터가 성공적으로 작동하고 발전하기 위해서는 혁신클러스터와 산업(생산)클러스터, 지원시스템과 인프라 혹은 선도적 대기업 등이 유기적인 네트워크를 구축하여 역동성을 발휘해야 한다. 구체적인 활성화 전력으로는 (1)기업환경 개선과 연구 성과의 사업화, (2)벤처금융지원 강화, (3)첨단기업의 유치와 네트워크 강화, (4)정부의 체계적인 지원과 혁신클러스터 구축 등이 있다.