• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.485-489
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• 2003

Several clustering methods for spatial data mining have been devised in the literature, but have the following drawback: increase cost due to calculating distance among objects. To solve this problem, we propose a spatial clustering method using regular cells. In this paper, we design and implement file structures, data structures and algorithms to realize the proposed method, also, show experimental results after applying test data to the implemented method.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.29-36
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• 2017

In this paper, we implement a spatial big data analysis prototype based on Spark which is an in-memory system and compares the performance by the spatial split algorithm on this basis. In cluster computing environments, big data is divided into blocks of a certain size order to balance the computing load of big data. Existing research showed that in the case of the Hadoop based spatial big data system, the split method by spatial is more effective than the general sequential split method. Hadoop based spatial data system stores raw data as it is in spatial-divided blocks. However, in the proposed Spark-based spatial analysis system, there is a difference that spatial data is converted into a memory data structure and stored in a spatial block for search efficiency. Therefore, in this paper, we propose an in-memory spatial big data prototype and a spatial split block storage method. Also, we compare the performance of existing spatial split algorithms in the proposed prototype. We presented an appropriate spatial split strategy with the Spark based big data system. In the experiment, we compared the query execution time of the spatial split algorithm, and confirmed that the BSP algorithm shows the best performance.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.83-90
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• 2004

In this paper, we study the CCD(Clustering with Circular Distance) and the COD(Clustering with Obstructed Distance) problems to be considered when objects are being clustered in a circularly search space and a search space with the presence of obstacles. We also propose a now clustering algorithm for clustering efficiently objects that the insertion or the deletion is occurring frequently in multi-dimensional search space. The distance function for solving the CCD and COD Problems is defined in the Proposed clustering algorithm. This algorithm is included a clustering method to create clusters that have a high spatial locality by minimum computation time.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.301-303
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• 2001

본 연구는 저가의 가상현실 시스템을 구현하기 위하여 LAN에 연결된 다수의 PC들로 구성된 가상현실 시스템을 제시한다. 이때, PC들은 고유 기능에 따라 3차원 그래픽을 실시간으로 랜더링 하는 VR 서버, 가상공간의 운영을 위하여 GUI 인터페이스를 지원하는 제어 서버, 상호작용을 위하여 입출력 장치가 연결된 장치 서버로 분류한다. 제안하는 시스템의 핵심 기능은 분산된 서버들을 단일 가상공간에 통합하는 것이다. 우리는 서로 다른 특징을 가지는 서버들을 통합하기 위하여 동기 마스터/슬레이브, 이벤트 관리자, 상호 작용 관리자를 설계하고 이를 구현하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.96-106
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• 2009

Extending the scale of the distributed processing in a single Ethernet cluster is physically restricted by maximum ports per switch. This paper presents an implementation of MPI-based multicluster consisting of multiple Ethernet switches for extending the scale of distributed processing, and a asymptotical analysis for communication overhead through execution-time analysis model. To determine an optimum task partitioning, we analyzed the processing time for various partitioning schemes, and AAP(accumulator array partitioning) scheme was finally chosen to minimize the overall communication overhead. The scope of data partitioned in AAP was modified to fit for incremented nodes, and suitable load balancing algorithm was implemented. We tried to alleviate the communication overhead through exploiting the pipelined broadcast and flat-tree based result gathering, and overlapping of the communication and the computation time. We used the linear pipeline broadcast to reduce the communication overhead in intercluster which is interconnected by a single link. Experimental results shows nearly linear speedup by the proposed parallel distributed GHT implemented on MPI-based Ethernet multicluster with four 100Mbps Ethernet switches and up to 128 nodes of Pentium PC.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.1-20
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• 2024

Regarding the discourse on the correlation between governmental financial support and firm performance, much emphasis has been placed on the role of individual corporate characteristics as well as spatial features. However, there is a notable scarcity of empirical research examining the integrated impact of corporate and cluster characteristics on managerial performance. This study addresses this gap by empirically analyzing the financial and non-financial outcomes resulting from specific allocations of governmental financial support. Additionally, it explores corporate and cluster characteristics predicted to moderate the influence between governmental financial support and firm performance. The analysis employs a two-level hierarchical linear model (HLM) at individual and group levels. The data, reorganized based on business registration numbers at the firm and cluster levels, ultimately utilized panel data from 83,395 firms and 641 clusters. The research findings indicate that governmental financial support demonstrates a positive effect (+) on both sales and patents for firms, suggesting its effectiveness in complementing market failures. Results from the hierarchical linear model analysis show that when combined with human capital capacity, absorptive capacity, and cluster network density, governmental financial support exhibits significant positive effects on sales. This study contributes theoretical and practical insights by analyzing the relationship between governmental financial support and firm performance using a two-level hierarchical linear model. It highlights the role of corporate characteristics such as human capital and absorptive capacity, along with cluster characteristics like cluster network density, in moderating the effects of governmental financial support on firm performance.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.203-209
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• 2016

In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1646-1657
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• 1996

This paper presents a color transformation method based on a uniform color image model. Firstly, color variation factors are grouped into identical (multiplicative) factor and independent(additive) one for the color model, and they are modelled by the Gaussian function. The shape of a color cluster in (R, G, B) feature space is an ellipsoid whose elongated major axis correspond to the direction of mean vector. Secondly, the transformation of a color cluster using the model is studied. A transformation method for three dimensional coordinated is described. The proposed method is applied to artificial and natural color images. By the result of experiments, the elongated major axis of each cluster making up the transformed color image aggress with the direction of its mean vector.

• Journal of Korea Multimedia Society
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• v.10 no.2
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• pp.236-245
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• 2007

Wireless sensor networks consist of numerous nodes equipped with small-sized and limited calculation capacities and storage space as well as low-capacity batteries. Therefore, the key issue is to reduce energy consumption of sensor nodes in sensor network environment. To reduce energy consumption of sensor nodes, consideration must be given to decreasing frequency of messages transmitted by nodes. Also, considering network application, security of sensor networks is also considered important. Therefore, this study proposes a key distribution scheme in dynamic clustering model. The dynamic clustering model used for this scheme is very effective in extending life span of wireless sensor networks. The proposed scheme provides improved security compared to the existing key distribution scheme by applying grid-based key distribution scheme and allocating polynomial s hare to the nodes forming a cluster. Also, comparison was made with the previously proposed grid-based, location-based and cluster-based key distribution schemes to illustrate the advantages of the proposed scheme.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.195-202
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• 2008

In this paper, To improve the effectiveness of security enforcement, the first contribution in this work is that we present a clustered heterogeneous WSN(Wareless Sensor Network) architecture, composed of not only resource constrained sensor nodes, but also a number of more powerful high-end devices acting as cluster heads. Compared to sensor nodes, a high-end cluster head has higher computation capability, larger storage, longer power supply, and longer radio transmission range, and it thus does not suffer from the resource scarceness problem as much as a sensor node does. A distinct feature of our heterogeneous architecture is that cluster heads are equipped with TC(trusted computing) technology, and in particular a TCG(Trusted Computing Group) compliant TPM (Trusted Platform Module) is embedded into each cluster head. According the TCG specifications, TPM is a tamper-resistant, self-contained secure coprocessor, capable of performing cryptographic functions. A TPM attached to a host establishes a trusted computing platform that provides sealed storage, and measures and reports the integrity state of the platform.