• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.792-796
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• 2009

Determining the optimal number of cluster is an important issue in research area of data clustering. It is choosing the cluster validity method and finding the cluster number where it optimizes the cluster validity. In this paper, an efficient heuristic for determining optimal number of cluster using clustering balance is proposed. The experimental results using k-means at artificial and real-life data set show that proposed algorithm is excellent in aspect of time efficiency.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.119-125
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• 2011

The part family (PF) formation in a cellular manufacturing has been a key issue for the successful implementation of Group Technology (GT). Basically, a part has two different attributes; i.e., design and manufacturing. The respective similarity in both attributes is often conflicting each other. However, the two attributes should be taken into account appropriately in order for the PF to maximize the benefits of the GT implementation. This paper proposes a clustering algorithm which considers the two attributes simultaneously based on pareto optimal theory. The similarity in each attribute can be represented as two individual objective functions. Then, the resulting two objective functions are properly combined into a pareto fitness function which assigns a single fitness value to each solution based on the two objective functions. A GA is used to find the pareto optimal set of solutions based on the fitness function. A set of hypothetical parts are grouped using the proposed system. The results show that the proposed system is very promising in clustering with multiple objectives.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.507-511
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• 2008

Supporting energy efficiency and load balancing in wireless sensor network is the most important issue in devising the hierarchical routing protocols. Recently, the dual layered clustering scheme with GPS was proposed for the supporting of load balancing for cluster heads but there would be many collided messages in the overlapped area between two layers. Thereby, the purpose of this paper is to reduce the collision rate in the overlapped layer by concisely distinguish them with the same number of nodes in them. For the layer partition, this paper uses an equation $x^2+ y^2{\le}(\frac{R}{\sqrt{2\pi}})^2$ to distinguish layers. By using it, the scheme could efficiently distinguish two layers and gets the balanced number of elements in them. Therefore, the proposed routing scheme could prolong the overall network life cycle about 10% compared to the previous two layered clustering scheme.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.427-429
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• 2005

Energy efficiency is the most challenging issue in wireless sensor network to prolong the life time of the network, as the sensors has to be unattended. Cluster based communication can reduce the traffic on the network and gives the opportunity to other sensors for periodic sleep and thus save energy. Passive clustering (PC) can perform a significant role to minimize the network load as it is less computational and light weight. First declaration wins method of PC without any priority generates severe collision in the network and forms the clusters very dense with large amount of overlapping region. We have proposed several modifications for the existing passive clustering algorithm to prolong the life time of the network with better cluster formation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.64-69
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• 2013

In ubiquitous computing, shared environments adjust themselves so that all users in the environments are satisfied as possible. Inevitably, some of users sacrifice their satisfactions while the shared environments maximize the sum of all users' satisfactions. In our previous work, we have proposed social welfare functions to avoid a situation which some users in the system face the worst setting of environments. In this work, we consider a more direct approach which is a preference based clustering to handle this issue. In this approach, first, we categorize all users into several subgroups in which users have similar tastes to environmental parameters based on their preference information. Second, we assign the subgroups into different time or space of the shared environments. Finally, each shared environments can be adjusted to maximize satisfactions of each subgroup and consequently the optimal of overall system can be achieved. We demonstrate the effectiveness of our approach with a numerical analysis.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.40.3-40.3
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• 2018

This dissertation presents the results on two-dimensional Redshift space distortion (hereafter RSD) analyses of the large-scale structure of the universe using spectroscopic data and on improvement of modeling of the RSD effect. RSD is an effect caused by galaxies' peculiar velocity on their clustering feature in observation along the line of sight and is thus intimately connected to the growth rate of the structure in the universe, from which we can test the origin of cosmic acceleration and Einstein's theory of gravity at cosmic scales in the end. However, there are several challenges in modeling precise and accurate RSD effect, such as non-linearities and the existence of an exotic component, e.g. massive neutrino. As part of endeavors for modeling more precise and accurate galaxy clustering in redshift space, this dissertation includes a series of works for this issue. (More detailed descriptions were omitted.)

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.1-6
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• 2024

Energy efficiency in wireless sensor networks (WSNs) is a critical issue because batteries are used for operation and communication. In terms of scalability, energy efficiency, data integration, and resilience, WSN-cluster-based routing algorithms often outperform routing algorithms without clustering. Low-energy adaptive clustering hierarchy (LEACH) is a cluster-based routing protocol with a high transmission efficiency to the base station. In this paper, we propose an energy consumption model for LEACH and compare it with the existing LEACH, advanced LEACH (ALEACH), and power-efficient gathering in sensor information systems (PEGASIS) algorithms in terms of network lifetime. The energy consumption model comprises energy-sensitive cluster formation and a cluster head selection technique. The setup and steady-state phases of the proposed model are discussed based on the cluster head selection. The simulation results demonstrated that a low-energy-consumption network was introduced, modeled, and validated for LEACH.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.251-260
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• 2008

In internet being a repository of massive information, we easily may not find our desired information, this issue also exists in e-commerce which gets rapid growth. In most of e-commerce sites, the methods furnishing information have been made use of statistical analysis or simple process by category-oriented, but these can't represent diverse correlation among products information and also hardly reflect users' purchasing patterns precisely. In this thesis, we propose more efficient web mining ways for discovering interesting information using effective clustering in e-commerce, which get achieved more suitable relationship among products information using both sequential patterns and association rules in category-independent, and experiments show the efficiency of our proposed methods. And we propose search using effective clustering rapidly.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.475-479
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• 2009

In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Current research activity for the Minimum Energy Multicast (MEM) problem has been focused on devising efficient centralized greedy algorithms for static ad hoc networks. In this paper, we consider mobile ad hoc networks(MANETs) that could provide the reliable monitoring and control of a variety of environments for remote place. Mobility of MANET would require the topology change frequently compared with a static network. To improve the routing protocol in MANET, energy efficient routing protocol would be required as well as considering the mobility would be needed. In this paper, we propose a new method, the CACH(Context-aware Clustering Hierarchy) algorithm, a hybrid and clustering-based protocol that could analyze the link cost from a source node to a destination node. The proposed analysis could help in defining the optimum depth of hierarchy architecture CACH utilize. The proposed CACH could use localized condition to enable adaptation and robustness for dynamic network topology protocol and this provide that our hierarchy to be resilient. As a result, our simulation results would show that CACH could find energy efficient depth of hierarchy of a cluster.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.253-258
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• 2014

In smartphone sensing which monitors various social phenomena of the individuals by using embedded sensors, managing metadata is one of the important issue to process large-scale data, improve the data quality, and share collected data. In this paper, we proposed a document clustering scheme for the large-scale metadata management architecture which is designed as a hybrid back-end consisting of a cluster head and member nodes to reduce the server-side overhead. we also verified that the proposed scheme is more efficient than the distance based clustering scheme in terms of the server-side overhead through simulation results.