• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.16-18
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• 2004

Single system image(SSI) have been the mainstay high-performance computing for many years. SSI requires the integration and aggregation of all types of resources in a cluster to present a single interface to users. In this paper, we describe a cluster computing architecture with the concept of single process space(SPS) where all processes share a uniform process identification scheme. With SPS, a process on any node can create child process on the same or different node or communicate with any other process on a remote node, as if they are on a single node. For this purpose, SPS is built with the support of unique cluster-wide pid, signal forwarding, and remote fork. We propose a novel design of SPS cluster which addresses the scalability and flexibility problem of traditional clusterwidely unique pid implementation by using blocked pid assignment. We have implemented this new design of SPS cluster, and we demonstrate its performance by comparing it to Beowulf distributed process space. Benchmark performance results show that our design of SPS cluster realized both scalability and flexibility that are essential to building SPS cluster.

• Communications of the Korean Mathematical Society
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• v.26 no.1
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• pp.135-149
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• 2011

Using (r, s)-preopen sets [14] and pre-${\omega}_t$-closures [6], a new kind of covering property $P^t_{({\omega}_r,s)}$-closedness is introduced in a bitopological space and several characterizations via filter bases, nets and grills [30] along with various properties of such concept are investigated. Two new types of cluster sets, namely pre-(${\omega}_r$, s)t-${\theta}_f$-cluster sets and (r, s)t-${\theta}_f$-precluster sets of functions and multifunctions between two bitopological spaces are introduced. Several properties of pre-(${\omega}_r$, s)t-${\theta}_f$-cluster sets are investigated and using the degeneracy of such cluster sets, some new characterizations of some separation axioms in topological spaces or in bitopological spaces are obtained. A sufficient condition for $P^t_{({\omega}_r,s)}$-closedness has also been established in terms of pre-(${\omega}_r$, s)t-${\theta}_f$-cluster sets.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.45-52
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• 2012

This paper proposes a new enhancing document clustering method using the important terms of cluster and the wikipedia. The proposed method can well represent the concept of cluster topics by means of selecting the important terms in cluster by the semantic features of NMF. It can solve the problem of "bags of words" to be not considered the meaningful relationships between documents and clusters, which expands the important terms of cluster by using of the synonyms of wikipedia. Also, it can improve the quality of document clustering which uses the expanded cluster important terms to refine the initial cluster by re-clustering. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.425-437
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• 2018

Since the 1990s, clusters defined as a geographic concentration of interconnected companies, research and educational institutions, technology transfer agencies, and other public or semi-public institutions in a particular field have not only been subject to academic research, but have also become goals for various innovation and regional policies. Over the past 20 years Germany at both the Federal and $L{\ddot{a}}nder$ levels has been pursuing various cluster promotion policies and initiatives for upgrading industries' competitiveness and innovations, and some of these measures have been evaluated as successful. This study aims to examine the industrial cluster promotion policy of Germany. For this purpose, the study first outlines the concept of cluster and cluster policy theoretically, and then explores the formation and historical development of cluster polices of the German federal government.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.189-213
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• 2017

This study seeks to critically examine the significance and limits of the cluster adaptive cycle model for analysis of cluster evolution and to propose research issues for future analysis of cluster evolution based on this critical examination. Until the 1980s, research on industrial complexes including clusters was based on a 'static perspective' that focuses on the aspect of economic space at a specific point in time, but the research paradigm has recently shifted to a 'dynamic perspective' focusing on 'evolution' of 'complex adaptive systems'. As a result, the adaptive cycle model has attracted attention as an analysis tool of dynamically evolving clusters. However, the cluster adaptive cycle model has emerged by being appropriately modified and expanded according to the properties of the cluster and its evolution. The cluster adaptive cycle model is a comprehensive analysis framework that identifies the characteristics of cluster evolution in terms of resource accumulation, interdependence, and resilience and classifies cluster evolution paths into six different categories. Nevertheless, there is still a need for further discussion and supplementation in terms of theoretical and empirical research to expand and deepen the model. Therefore, research issues for future analysis of cluster evolution are to specify and elaborate the cluster evolution model, to emphasize the concept of resilience, and to verify the applicability and usefulness of the model through empirical research.

• World Technopolis Review
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• v.6 no.2
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• pp.102-112
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• 2017

In this increasingly globalised and rapidly-changing world, the various challenges that can arise are also increasingly globalised and complex. These may range from economic, environmental, societal or even demographic challenges. Solutions should therefore be applicable world-wide, but they need to be properly adapted to the specifications and needs at the regional and country level. This implies that past models of centralised innovation can be progressively substituted by new approaches based on openness and strategic collaboration between the various players involved. There are various models of openness and collaboration in research, development and innovation creating scientific networks at different levels. This paper is designed in a way to present the concept of smart specialisation and clusters and how they are linked and contribute to the support of Smart Specialisation Strategy in the Asian countries. The following paragraphs describe how smart specialisation is applied and the importance of clusters in developing a S3 strategy. In addition, the status of cluster policies in Asia as well as the steps towards S3 are also presented. The status of cluster policies and their steps towards S3 policies in Asia are described. The approach of China to adopt S3 in their R&I policy is also presented. The scope of this paper, is to demonstrate the policy framework of cluster and S3 policies in the region of Asia and how they are applied. China has been further analysed as a case, since they are more active in applying such policies.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.1
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• pp.52-70
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• 2011

Industrial cluster is basically related to the concept of knowledge management in that innovations are pursued through knowledge sharing and knowledge exchanges in the level of related industries or adjacent regions. Recently, assertions that knowledge management is worth of application in the level of an industry or regional industrial cluster appear in academics and practitioners. This study explores the characteristics and challenges of knowledge management when it is applied in the level of an industrial cluster. Critical concepts and research questions are developed from the review on previous studies and explored through interpretive case studies and in-depth interviews.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.976-990
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• 2020

The k-means algorithm is widely used in academia and industry due to easy and simple implementation, enabling fast learning for complex datasets. However, k-means struggles to classify datasets without prior knowledge of specific domains. We proposed the repulsive k-means (RK-means) algorithm in a previous study to improve the k-means algorithm, using the repulsive force concept, which allows deleting unnecessary cluster centroids. Accordingly, the RK-means enables to classifying of a dataset without domain knowledge. However, three main problems remain. The RK-means algorithm includes a cluster repulsive force offset, for clusters confined in other clusters, which can cause cluster locking; we were unable to prove RK-means provided optimal convergence in the previous study; and RK-means shown better performance only normalize term and weight. Therefore, this paper proposes the advanced RK-means (ARK-means) algorithm to resolve the RK-means problems. We establish an initialization strategy for deploying cluster centroids and define a metric for the ARK-means algorithm. Finally, we redefine the mass and normalize terms to close to the general dataset. We show ARK-means feasibility experimentally using blob and iris datasets. Experiment results verify the proposed ARK-means algorithm provides better performance than k-means, k'-means, and RK-means.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.481-486
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• 2021

Machine learning algorithms adopt criterion function as a key component to measure the quality of their model derived from data. Cluster analysis also uses this function to rate the clustering result. All the criterion functions have in general certain types of favoritism in producing high quality clusters. These clusters are then described by attributes and their values. Category utility and partition utility play an important role in cluster analysis. These are fully analyzed in this research particularly in terms of how they are related to the favoritism in the final results. In this research, several data sets are selected and analyzed to show how different results are induced from these criterion functions.

• Journal of the Chungcheong Mathematical Society
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• v.16 no.2
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• pp.23-30
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• 2003

In this note, we introduce the concept of the modulus of a curve family in $R^n$ and examine some basic properties. And we study the boundary behavior of quasiconformal mappings on a domain $D{\subset}\bar{R}^n$ and present some geometric applications.