• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.34C no.7
• /
• pp.51-60
• /
• 1997

Prototype based methods are commonly used in cluster analysis and the results may be highly dependent on the prototype used. In this paper, we propose a fuzzy clustering method that involves adaptively expanding convex polytopes. Thus, the dependency on the use of prototypes can be eliminated. The proposed method makes it possible to effectively represent an arbitrarily distributed data set without a priori knowledge of the number of clusters in the data set. Specifically, nonlinear membership functions are utilized to determine whether a new cluster is created or which vertex of the cluster should be expanded. For this, the membership function of a new vertex is assigned according to not only a distance measure between an incoming pattern vector and a current vertex, but also the amount how much the current vertex has been modified. Therefore, cluster expansion can be only allowed for one cluster per incoming pattern. Several experimental results are given to show the validity of our mehtod.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.2
• /
• pp.138-143
• /
• 2006

In this paper, we have presented a Sequential Agglomerative Hierarchical Nested (SAHN) algorithm-based data clustering method in fuzzy inference system to achieve optimal performance of fuzzy model. SAHN-based algorithm is used to give possible range of number of clusters with cluster centers for the system identification. The axes of membership functions of this fuzzy model are optimized by using cluster centers obtained from clustering method and the consequence parameters of the fuzzy model are identified by standard least square method. Finally, in this paper, we have observed our model's output performance using the Box and Jenkins's gas furnace data and Sugeno's non-linear process data.

• Journal of The Korean Astronomical Society
• /
• v.46 no.3
• /
• pp.103-123
• /
• 2013

Star clusters are superb astrophysical laboratories containing cospatial and coeval samples of stars with similar chemical composition. We initiate the Sejong Open cluster Survey (SOS) - a project dedicated to providing homogeneous photometry of a large number of open clusters in the SAAO Johnson-Cousins' UBV I system. To achieve our main goal, we pay much attention to the observation of standard stars in order to reproduce the SAAO standard system. Many of our targets are relatively small sparse clusters that escaped previous observations. As clusters are considered building blocks of the Galactic disk, their physical properties such as the initial mass function, the pattern of mass segregation, etc. give valuable information on the formation and evolution of the Galactic disk. The spatial distribution of young open clusters will be used to revise the local spiral arm structure of the Galaxy. In addition, the homogeneous data can also be used to test stellar evolutionary theory, especially concerning rare massive stars. In this paper we present the target selection criteria, the observational strategy for accurate photometry, and the adopted calibrations for data analysis such as color-color relations, zero-age main sequence relations, Sp - MV relations, Sp - $T_{eff}$ relations, Sp - color relations, and $T_{eff}$ - BC relations. Finally we provide some data analysis such as the determination of the reddening law, the membership selection criteria, and distance determination.

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

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.1 no.1
• /
• pp.1-17
• /
• 2007

This paper proposes and analyzes a scalable and an efficient cluster based group key management protocol by introducing identity based infrastructure for secure communication in mobile wireless sensor networks. To ensure scalability and dynamic re-configurability, the system employs a cluster based approach by which group members are separated into clusters and the leaders of clusters securely communicate with each other to agree on a group key in response to changes in membership and member movements. Through analysis we have demonstrated that our protocol has a high probability of being resilient for secure communication among mobile nodes. Finally, it is established that the proposed scheme is efficient for secure positioning in wireless sensor networks.

• Publications of The Korean Astronomical Society
• /
• v.30 no.2
• /
• pp.275-278
• /
• 2015

We studied a cluster family in the northern part of the Carina Nebula (NGC 3372) a group of clusters near NGC 3324 (Tr 15, NGC 3293, Loden 165, Loden 153 and IC 2581). We used data from UCAC4 to determine the cluster's membership and the near infrared CMDs of each cluster. We analyzed the spatial density and elongation as a function of radius for each cluster and found a possible interaction between NGC 3293 and Loden153. However, the shape distortion of NGC 3324 cannot be evaluated because of the inhomogenity in the coverage of UCAC4 in the east part of NGC 3324.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.619-624
• /
• 1998

This paper presents a new clustering algorithm called FCM algorithm for the design of fuzzy controller. FCM is an extended version of FCM(Fuzzy c-Means) algorithm and can estimate the number of clusters automatically and give membership grades $u_{ik}$ suitable for making fuzzy control rules. This paper also shows an example of its application to the line pursuit control of a car.

• Journal of the Korean Data and Information Science Society
• /
• v.17 no.2
• /
• pp.301-309
• /
• 2006

In this paper, we show the improved fuzzy c-means clustering method. To improve, we use the double clustering as principal component analysis from objects which is located on common region of more than two clusters. In addition we use the degree of membership (probability) of fuzzy c-means which is the advantage. From simulation result, we find some improvement of accuracy in data of the probability 0.7 exterior and interior of overlapped area.

• Journal of The Korean Astronomical Society
• /
• v.38 no.4
• /
• pp.423-428
• /
• 2005

The main physical parameters; the cluster center, distance, radius, age, reddening, and visual absorbtion; have been re-estimated and improved for the open cluster NGC 7086. The metal abundance, galactic distances, membership richness, luminosity function, mass function, and the total mass of NGC 7086 have been examined for the first time here using Monet et al. (2003) catalog.

• The Journal of the Korea Contents Association
• /
• v.11 no.4
• /
• pp.74-82
• /
• 2011

To do fuzzy modelling of a nonlinear process needs to analyze the characteristics of input-output of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods. For this, fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the fuzzy rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the clusters are used for identification of fuzzy model and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. In the consequence part of the fuzzy rules fuzzy reasoning is conducted by two types of inferences such as simplified and linear inference. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. And lastly, using gas furnace process which is widely used in nonlinear process we evaluate the performance and the system characteristics.