• The Journal of Information Technology
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• v.8 no.1
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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.

• Knowledge Management Research
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• v.17 no.3
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.370-379
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• 2018

The Korean government announced plans for the International Science Business Belt as a spatial area for promoting the linkage between scientific knowledge and commercialization in 2009. R&D and entrepreneurial activities are essential for the success of the International Science Business Belt. In particular, prioritizing the types of businesses is critical at the cluster establishment stage in that this largely affects the features and development of clusters comprising the International Science Business Belt. This research aims to predict the entry and growth of firms that specialize in four industrial clusters, including Big Science Cluster, Frontier Cluster, ICT Cluster, and Bio-Healthcare Cluster. For this purpose, we employ the Swann & Prevezer's industrial clustering model to identify sectors that affect the establishment and growth of industrial clusters in the International Science Business Belt, focusing on ICT, Bio-Healthcare and Frontier clusters. Data was collected from the 2014 Korean Innovation Survey (KIS) and University Alimi for the ICT cluster, 2014 National Bio Industry Survey and University Alimi for the Bio-Healthcare Cluster, and the 2015 National Nano Convergent Industry Survey and Annual Report of Nano Technology for the Frontier cluster. Empirical results show that the ICT service sector, bio process/equipment sector, and Nano electronic sector promote clustering in other sectors. Based on the analysis results, we discuss several policy implications and strategies that can attract relevant firms for the development of industrial clusters.

• Proceedings of the Technology Innovation Conference
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• 1998.06a
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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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• v.22 no.3
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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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• v.27 no.1
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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.

• Proceedings of the Technology Innovation Conference
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• 2005.06a
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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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• v.5 no.3
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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.

• Journal of the Korean Academic Society of Industrial Cluster
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• v.1 no.1
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• pp.29-46
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• 2007

The purpose of this paper is to analyses current status and issues of cluster formation and extract policy implications. To this end, the questionnaire which surveyed the level of cluster formation were executed targeting the actors of regional innovation projects(RIPs). The results show that the situations and development stage of the cluster formation between capital region and non-capital region, large cities and small and medium sized cites are different. The level of clustering is also satisfactory, which is a requirement for cluster formation at its early stage. However, the capacity for phase II of cluster growth is not sufficient yet in terns of relationships between ventures and large corporations, institutions supporting management, finance and marketing, researchers from each individual sector of strategic industries and spin-off fines. Therefore, RIPs should be promoted with different policy tools for various regions that are devised according to the varying development stage of each region. The location of RIPs should be determined considering efficiency rather than equity, clustering rather than decentralization, and specialization rather than multiple development. In the long term, developed regions should pursue balanced regional development, with underdeveloped regions targeting specialization.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.3
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• pp.103-122
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• 2007

Innovation clusters developed or evolved around a specific region IS the key element of national innovation system and determine national competitiveness. Recognizing the importance of innovation clusters, Korean government has made "Daedeok Special R&D Zone" in 2005. This paper examines the success factors of famous Cluster in advanced countries and China, and proposes the strategy for regional development in Daejeon through boosting Daedeok Innovation Cluster. Although 30.5% of government R&D investment is being concentrated in Daedeok along with 10% of the country's doctorate degree holders, it is lack of increasing revenue by linking corporate R&D with a creative and challenging entrepreneur spirit. The core of the innovation cluster is the integration and mutual networking of the main participants. This paper suggests strategies for developing as a world class innovation cluster, global networking and clustering, venture ecosystem formation, commercialization the knowledge by interacting with market. It also explains the necessity of regional integration for cluster to cluster linkages in the East Asia Region.