• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.923-930
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• 2004

Wireless sensor networks is a core technology of ubiquitous computing which enables the network to aware the different kind of context by integrating exiting wired/wireless infranet with various sensor devices and connecting collected environmental data with applications. However it needs an energy-efficient approach in network layer to maintain the dynamic ad hoc network and to maximize the network lifetime by using energy constrained node. Cluster-based data aggregation and routing are energy-efficient solution judging from architecture of sensor networks and characteristics of data. In this paper. we propose a new distributed clustering algorithm in using distance from the sink. This algorithm shows that it can balance energy dissipation among nodes while minimizing the overhead. We verify that our clustering is more en-ergy-efficient and thus prolongs the network lifetime in comparing our proposed clustering to existing probabilistic clustering for sensor network via simulation.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.17-24
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• 2022

Hierarchical clustering methods have been proposed for more than sixty years and yet are used in various disciplines for relation observation and clustering purposes. In 1965, divisive hierarchical methods were proposed in biological sciences and have been used in various disciplines such as, and anthropology, ecology. Furthermore, recently hierarchical methods are being deployed in economy and energy studies. Unlike most clustering algorithms that require the number of clusters to be specified by the user, hierarchical clustering is well suited for situations where the number of clusters is unknown. This paper presents an overview of the hierarchical clustering algorithm. The dissimilarity measurements that can be utilized in hierarchical clustering algorithms are discussed. Further, the paper highlights the various and recent disciplines where the hierarchical clustering algorithms are employed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.890-893
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• 2008

자율성 및 이동성 갖는 네트워크 구조의 하나인 MANET(Mobile Ad-Hoc Networks)은 각 node들은 그 특성에 따라서 clustering service을 한다. node의 전송과정 중 path access에 대하여 중요성 또한 강조되고 있다. 일반적인 무선 네트워크 상에서의 node들은 clustering을 하게 되는데 그 과정에서 발생되는 여러 가지 문제점을 가지고 전송이 이루어진다. 모든 node들이 송, 수신상의 전송 범위(Beam forming area)가지고 있으며, 이러한 각 node들의 전송범위 내에 전송이 이루어지는 전통적인 전송기술 mechanism을 찾는다. 이러한 전송상황에서의 송신하는 node와 수신된 node간에 발생되고 있는 중복성의 문제점으로 즉, 상호적용에 의한 네트워크 duplicate(overlapping)이 크게 우려가 되고 있다. 이러한 전송상의 전송 범위 중첩, node간의 packet 간섭현상, packet의 중복수신 및 broadcasting의 storming현상이 나타난다. 따라서 본 논문에서는 상황정보의 속성을 이용한 계층적 상호 head node들의 접근된 위치와 연계되는 전송속도, 보존하고 있는 head node들의 에너지 source value, doppler효과를 통한 head node의 이동방향 등 분석한다. 분석된 방법으로 전송상의 계층적 path가 구성된 경험적 path 속성을 통한 네트워크 connectivity 신뢰성을 극대화 할 뿐만 아니라 네트워크의 전송 범위 duplicate을 사전에 줄일 수 있고 전송망의 최적화를 유지할 수 있는 기법의 하나인 상황정보를 이용한 ad hoc network의 ODDMRP(Ontology Doppler effect-based Dynamic Multicast Routing Protocol) clustering 기법을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.853-858
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• 2006

TMHMM(Tied Mixture Hidden Markov Model) is an important approach to reduce the number of free parameters in speech recognition. However, this model suffers from a degradation in recognition accuracy due to its GPDF (Gaussian Probability Density Function) clustering error. This paper proposes a clustering algorithm, called HCNN(Homogeneous Centroid Neural network), to cluster acoustic feature vectors in TMHMM. Moreover, the HCNN uses the heterogeneous distance measure to allocate more code vectors in the heterogeneous areas where probability densities of different states overlap each other. When applied to Korean digit isolated word recognition, the HCNN reduces the error rate by 9.39% over CNN clustering, and 14.63% over the traditional K-means clustering.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.875-880
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• 2005

One of the most important issues in the sensor network with resource-constrained sensor nodes is prolonging the network lifetime by efficiently utilizing the given energy of nodes. The most representative mechanism to achieve a long-lived network is the clustering mechanism. In this paper, we propose a new dynamic-size multi-hop clustering mechanism in which the burden of a node acting as a cluster head(CH) is balanced regardless of the density of nodes in a sensor network by adjusting the size of a cluster based on the information about the communication load and the residual energy of the node and its neighboring nodes. We show that our proposed scheme outperforms other single-hop or fixed-size multi-hop clustering mechanisms by carrying out simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.157-176
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• 2011

An interest-based P2P constructs the peer connections based on similarities for efficient search of resources. A clustering technique using peer similarities as data is an effective approach to group the most relevant peers. However, the separation of groups produced from clustering lowers the scalability of a P2P network. Moreover, the interest-based approach is only concerned with user-level grouping where topology-awareness on the physical network is not considered. This paper proposes an efficient scalable search for the interest-based P2P system. A scalable multi-ring (SMR) based on fuzzy clustering handles the grouping of relevant peers and the proposed scalable search utilizes the SMR for scalability of peer queries. In forming the multi-ring, a minimized route function is used to determine the shortest route to connect peers on the physical network. Performance evaluation showed that the SMR acquired an accurate peer grouping and improved the connectivity rate of the P2P network. Also, the proposed scalable search was efficient in finding more replicated files throughout the peer network compared to other traditional P2P approaches.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3472-3480
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• 2010

The Clustering technology of Energy efficiency wireless sensor network gets the energy efficiency by reducing the number of communication between sensor nodes and sink node. In this paper, First analyzed on the clustering technique of the distributed clustering protocol routing scheme LEACH (Low Energy Adaptive Clustering Hierarchy) and HEED (Hybrid, Energy-Efficient Distributed Clustering Approach), and based on this, new energy-efficient clustering technique is proposed for the cause the maximum delay of dead nodes and to increase the lifetime of the network. In the proposed method, the cluster head is elect the optimal efficiency node based on the residual energy information of each member node and located information between sink node and cluster node, and elected a node in the cluster head since the data transfer process from the data been sent to the sink node to form a network by sending the energy consumption of individual nodes evenly to increase the network's entire life is the purpose of this study. To verify the performance of the proposed method through simulation and compared with existing clustering techniques. As a result, compared to the existing method of the network life cycle is approximately 5-10% improvement could be confirmed.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.909-922
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• 2000

High sped messaging layer for application's feeling of low level network performance is needed by Clustering System based on high speed network fabrics. It should have the mechanism to directly pass messages between network card and application space, and provide flexible affodabilities for many diverse applications. In this paper, CROWN (Clustering Resources On Workstations' Network) which is designed and implemented for multi-purpose clustering system will be introduced briefly, and CLCP(CROWN Lean Communication Primitives)which is the high speed messaging layer for CROWN will be followed. CLCP consists of a firmware for controlling Myrinet card, device drier, and user libraries. CLCP supports various application domains as a result of pooling and interrupt receive mechanism. In case of polling based receive, 8 bytes short message, and no other process, CLCP has 262 micro-second response time between two nodes, and IM bytes large message, it shows 442Mbps bandwidth.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.239-240
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• 2008

본 논문에서는 Subtractive clustering 알고리즘을 이용한 Fuzzy Radial Basis Function Neural Network (FRBFNN)의 규칙 수를 자동적으로 생성하는 방법을 제시한다. FRBFNN은 멤버쉽 함수로써 기존 RBFNN에서 가우시안이나 타원형 형태의 특정 RBF를 사용하는 구조와 달리 Fuzzy C-Means clustering 알고리즘에서 사용하는 거리에 기한 멤버쉽 함수를 사용하여 전반부의 공간 분할 및 활성화 레벨을 결정하는 구조이다. 본 논문에서는 데이터의 밀집도에 기반을 두어 클러스터링을 하는 Subtractive clustering 알고리즘을 사용하여 퍼지 규칙의 수와 같은 의미를 갖는 분할할 입력공간의 수와 분할된 입력공간의 중심값을 동정하며, Least Square Estimator (LSE) 알고리즘을 사용하여 후반부 다항식의 계수를 추정 한다.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.252-254
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• 2007

This paper introduces the method of sequential clustering as a tool for the effective clustering of mass unit electrical systems. The interconnected network system retains information about the location of each line. With this information, this paper aims to carry out initial clustering through the transmission usage rate, compare the results of similarity measures for regional information with similarity measures for regional price, and introduce the technicalities of the clustering method. This transmission usage rate used power flow based on congestion costs and modified similarity measurements using the FCM algorithm. This paper also aims to prove the propriety of the proposed clustering method by comparing it with existing clustering methods that use the similarity measurement system. The proposed algorithm is demonstrated through the IEEE 39-bus RTS.