• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.39.3-40
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• 2017

Ultra-diffuse galaxies (UDGs) are an unusual galaxy population. They are ghostlike galaxies with fainter surface brightness than normal dwarf galaxies, but they are as large as MW-like galaxies. The key question on UDGs is whether they are 'failed' giant galaxies or 'extended' dwarf galaxies. To answer this question, we study UDGs in massive galaxy clusters. We find an amount of UDGs in deep HST images of three Hubble Frontier Fields clusters, Abell 2744 (z=0.308), Abell S1063 (z=0.347), and Abell 370 (z=0.374). These clusters are the farthest and most massive galaxy clusters in which UDGs have been discovered until now. The color-magnitude relations show that most UDGs have old stellar population with red colors, while a few of them show bluer colors implying the existence of young stars. The stellar masses of UDGs show that they have less massive stellar components than the bright red sequence galaxies. The radial number density profiles of UDGs exhibit a drop in the central region of clusters, suggesting some of them were disrupted by strong gravitational potential. Their spatial distributions are not homogeneous, which implies UDGs are not virialized enough in the clusters. With virial masses of UDGs estimated from the fundamental manifold, most UDGs have M_200 = 10^10 - 10^11 M_Sun indicating that they are dwarf galaxies. However, a few of UDGs more massive than 10^11 M_Sun indicate that they are close to failed giant galaxies.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.455-460
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• 2003

A new cluster validity index is proposed that determines the optimal partition and optimal number of clusters for fuzzy partitions obtained from the fuzzy c-means algorithm. The proposed validity index exploits an overlap measure and a separation measure between clusters. The overlap measure is obtained by computing an inter-cluster overlap. The separation measure is obtained by computing a distance between fuzzy clusters. A good fuzzy partition is expected to have a low degree of overlap and a larger separation distance. Testing of the proposed index and nine previously formulated indexes on well-known data sets showed the superior effectiveness and reliability of the proposed index in comparison to other indexes.

• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.599-621
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• 2011

The role of local economies in pursuing national economic development has expanded with greater influence. So a number of countries have adopted industrial cluster policies for regional and national economic development. Korean government, by the same token, puts emphasis on industrial cluster policies. But the academic studies on the necessities and effects of industrial clusters for Korean shipbuilding industry have been carried out little in Korean due to the lack of empirical studies on Korean industrial clusters. So this study focuses on analysing the industrial clusters in the Busan, Ulsan, Koungnam as southeast area of Korea. To be more specific, this study intends to provide answers to the following question: Are there industrial clusters in the Busan, Ulsan, Koungnam as southeast area of Korea analysed by the Location Quotient(LQ) analysis method? And as a consequence, Shipbuilding industrial clusters of southeast area of Korea were not identified.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.38.2-38.2
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• 2019

S0 galaxies are mostly known to be formed in dense environments from spiral progenitors. Recently, however, a new formation scenario has been suggested that field S0s can be formed from elliptical progenitors. The Sombrero galaxy (M104, NGC 4594) is a massive disk galaxy located in the field environment, and its morphological type has been controversial from Sa to E. Thus, it is an ideal target to test the new scenario. We trace the giant halo of M104 with globular clusters to test this scenario. From the wide images obtained with CFHT/MegaCam, we find a large number of globular clusters in this galaxy. We also confirm their membership by measuring the radial velocities from the spectra obtained with MMT/Hectospec. The color distribution of these globular clusters is bimodal, and blue (metal-poor) globular clusters are more spatially widely spread than red (metal-rich) globular clusters. This indicates that M104 hosts a giant metal-poor halo as well as an inner metal-rich halo. Combining this result with the fact that M104 is unusually massive and brighter than other spiral galaxies, we infer that M104 was indeed a massive elliptical galaxy that had formed a metal-rich halo by gas-rich mergers and a metal-poor halo by gas-poor mergers. In addition, we find young star clusters around the disk of M104, which shows that the disk formed after the spheroidal halos had formed. In conclusion, we suggest that M104 was originally a massive elliptical galaxy and was transformed to a lenticular galaxy by acquiring its disk later.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2352-2360
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• 2011

In this paper, we introduce a comprehensive design methodology of Radial Basis Function Neural Networks (RBFNN) that is based on mechanism of clustering and optimization algorithm. We can divide some clusters based on similarity of input dataset by using clustering algorithm. As a result, the number of clusters is equal to the number of nodes in the hidden layer. Moreover, the centers of each cluster are used into the centers of each receptive field in the hidden layer. In this study, we have applied Fuzzy-C Means(FCM) and K-Means(KM) clustering algorithm, respectively and compared between them. The weight connections of model are expanded into the type of polynomial functions such as linear and quadratic. In this reason, the output of model consists of relation between input and output. In order to get the optimal structure and better performance, Particle Swarm Optimization(PSO) is used. We can obtain optimized parameters such as both the number of clusters and the polynomial order of weights connection through structural optimization as well as the widths of receptive fields through parametric optimization. To evaluate the performance of proposed model, NXT equipment offered by National Instrument(NI) is exploited. The situation awareness system-related intelligent model was built up by the experimental dataset of distance information measured between object and diverse sensor such as sound sensor, light sensor, and ultrasonic sensor of NXT equipment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.8
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• pp.84-97
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• 2012

In wireless sensor networks, cluster structure brings on many advantages such as load balancing, energy saving, and distributed key management, and so on. To transform a physical network into the cluster structure, sensor nodes should invoke a cluster formation protocol. During the protocol operation, if some nodes are compromised and they do not conform to the protocol, an inconsistency of membership in a cluster happen. This splits the cluster and consequently increases the number of clusters and decreases the number of members in the cluster. In this paper, we propose a scheme which well copes with such a problem. First, our scheme generates two hop clusters where hop distance between any two nodes is at most two. Besides, our scheme employs verification of two hop distant nodes to prevent the cluster split induced by compromised nodes. Last, our scheme mainly employs broadcast transmissions to reduce energy consumption of nodes. Simulation results have proven that our scheme reduces the number of clusters and more secure and energy-efficient than other scheme.

• Spatial Information Research
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• v.20 no.6
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• pp.13-21
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• 2012

In this study, homogeneous regions for regional frequency analysis were identified using rainfall data from 61 observation points in Korea. The used data were gathered from 1980 to 2010. Self organizing map and K-means clustering based on Davies-Bouldin Index were used to make clusters showing similar rainfall patterns and to decide the optimum number of the homogeneous regions. The results from this analysis showed that the 61 observation points can be optimally grouped into 6 geographical clusters. Finally, the 61 observations points grouped into 6 clusters were mapped regionally using Thiessen polygon method.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.857-866
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• 2006

Performance of an image retrieval system is usually very low because of the semantic gap between the low level feature and the high level concept in a query image. Semantically relevant images may exhibit very different visual characteristics, and may be scattered in several clusters. In this paper, we propose a content based image rertrieval approach which combines region based image retrieval and a new relevance feedback method using adaptive clustering together. Our main goal is finding semantically related clusters to narrow down the semantic gap. Our method consists of region based clustering processes and cluster-merging process. All segmented regions of relevant images are organized into semantically related hierarchical clusters, and clusters are merged by finding the number of the latent clusters. This method, in the cluster-merging process, applies r: using v principal components instead of classical Hotelling's $T_v^2$ [1] to find the unknown number of clusters and resolve the singularity problem in high dimensions and demonstrate that there is little difference between the performance of $T^2$ and that of $T_v^2$. Experiments have demonstrated that the proposed approach is effective in improving the performance of an image retrieval system.

• Journal of Korea Multimedia Society
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• v.21 no.6
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• pp.667-677
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• 2018

Since sensor networks consist of sensor nodes with limited energy resources, so efficient energy use of sensor nodes is very important in the design of sensor networks. Sensor nodes consume a lot of energy for data transmission. Clustering technique is used to efficiently use energy in data transmission. Recently, mobile sink techniques have been proposed to reduce the energy load concentrated on the cluster header near a sink node. The CMS(Cluster-based Mobile sink) technique minimizes the generation of control messages by creating a data transmission path while creating clusters, and supports the inter-cluster one-hop transmission. But, there is a case where there is no connectivity between neighbor clusters, it causes a problem of having a long hop data transmission path regardless of local distance. In this paper, we propose a SCBC(Strong connection balancing cluster) to support the path of the minimum number of hops. The proposed scheme minimizes the number of hops in the data transmission path and supports efficient use of energy in the cluster header. This also minimizes a number of hops in data transmission paths even when the sink moves and establishes a new path, and it supports the effect of extending the life cycle of the entire sensor network.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.87-99
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• 2008

High Altitude Platform network systems utilize Unmanned Aerial Vehicle as routers for ground node communication. For this purpose, geographical clustering of ground nodes must be required. In this paper, we assume mobile ground nodes over wide area and the clusters composed of ground nodes are identified. UAVs can be positioned at the point of centroid of clusters. The number of UAVs are derived from the area size and the number of ground nodes deployed in that area. From the simulation and application of clustering algorithms, we showed visual clustering results with dynamic variance of number of ground nodes.