• Journal of The Korean Astronomical Society
• /
• v.37 no.5
• /
• pp.593-596
• /
• 2004

We introduce a method of identifying evidence of shocks in the X-ray emitting gas in clusters of galaxies. Using information from synthetic observations of simulated clusters, we do a blind search of the synthetic image plane. The locations of likely shocks found using this method closely match those of shocks identified in the simulation hydrodynamic data. Though this method assumes nothing about the geometry of the shocks, the general distribution of shocks as a function of Mach number in the cluster hydrodynamic data can be extracted via this method. Characterization of the cluster shock distribution is critical to understanding production of cosmic rays in clusters and the use of shocks as dynamical tracers.

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.2
• /
• pp.67.3-67.3
• /
• 2021

Shocks are induced in the intracluster medium by mergers of subclusters during the hierarchical structure formation of the universe. Radio relics detected in the outskirts of galaxy clusters have been interpreted as diffuse synchrotron emission from cosmic ray electrons accelerated at such merger shocks. Using a set of cosmological hydrodynamic simulations, we study how the properties of merger-driven shocks depend on the parameters such as the mass ratio and impact parameter of mergers. In particular, we examine the distribution of the Mach number and energetics of shocks associated with synthetic radio relics in simulated merging clusters. In this poster, we will present the preliminary results and the implications.

• The Bulletin of The Korean Astronomical Society
• /
• v.37 no.2
• /
• pp.72.2-72.2
• /
• 2012

We analyzed the properties of shock waves in galaxy clusters, by using the data of simulations for the large-scale structure of the universe with the spatial resolution of up to 25 kpc/h. In a substantial fraction of clusters, we found that strong shocks with Mach number of several or larger exist in outskirts within the virial radius. They are produced by the accretion of warm gas flowing from filaments to clusters, and generate large cosmic-ray fluxes. The cosmic rays advect into cluster cores, but may temporally induce the population inversion, that is, larger population at larger radius, suggested by recent radio and ${\gamma}$-ray observations.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.31 no.3
• /
• pp.41-51
• /
• 2006

Clustering is to group similar objects into clusters. Until now there are a lot of approaches using Self-Organizing feature Maps (SOFMS) But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of c output-layer nodes, if they want to make c clusters. This approach has problems to classify elaboratively. This Paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We un find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. The proposed algorithm was tested on well-known IRIS data and TSPLIB. The results of this computational study demonstrate the superiority of the proposed algorithm.

• 한국전산유체공학회:학술대회논문집
• /
• 2006.10a
• /
• pp.26-27
• /
• 2006

Characteristics of spatial structure of particle clusters are investigated by using the flow field data obtained from three-dimensional numerical simulations. Eulerian/Lagrangian approach with two-way coupling is applied and individual particle-particle collisions are taken into account by using the hard-sphere model. More than 16 million particles are traced in the maximum case. The results show that the cluster is consisted from the multiple-spatial scale components while the low wave-number, hence the large-scale structure, is dominant. Three-dimensional structure reconstructed from the low-pass filtered data enables us to investigate the essential dynamics of particle clusters in detail.

• Fashion & Textile Research Journal
• /
• v.6 no.5
• /
• pp.585-594
• /
• 2004

This study aimed to classify the lifestyles of 1020 college students, and to analyze the effect of the lifestyles on the usages of credit card, price perception, purchasing satisfaction and the number of new clothing. The number of credit cards, total payment of credit cards and the attitude to credit card were different by the 7 clusters of college students, but the frequency of credit card use, the amount of cash service and arrear ages were not different. The perception to the apparel price, purchasing satisfaction, and the degree of clothing purchasing varied according to the lifestyle clusters. For example, 6th cluster being highest in the pursuit of appearance showed the highest amount of credit cards usage significantly and tendency of highest arrearage, and used credit cards mostly in clothing purchase.

• Communications for Statistical Applications and Methods
• /
• v.22 no.6
• /
• pp.625-637
• /
• 2015

We develop a Bayesian clustering procedure based on a Dirichlet process prior with cluster specific random effects. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet process was implemented to calculate posterior probabilities when the number of clusters was unknown. Our approach (unlike its counterparts) provides simultaneous partitioning and parameter estimation with the computation of the classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. We find that the proposed Dirichlet process mixture model with cluster specific random effects detects clusters sensitively by combining vague edges into different clusters. Examples are given to show how these models perform on real data.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.406-409
• /
• 2008

Clustering data streams has an importance over many applications like sensor networks. Existing hierarchical methods follow a semi fuzzy clustering that yields duplicate clusters. In order to solve the problems, we propose an extended online divisive agglomerative clustering on data streams. It builds a tree-like top-down hierarchy of clusters that evolves with data streams using geometric time frame for snapshots. It is an enhancement of the Online Divisive Agglomerative Clustering (ODAC) with a pruning strategy to avoid duplicate clusters. Our main features are providing update time and memory space which is independent of the number of examples on data streams. It can be utilized for clustering sensor data and network monitoring as well as web click streams.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.4
• /
• pp.480-485
• /
• 2003

We Propose a Path planning method to reduce the Inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.18 no.1
• /
• pp.35-42
• /
• 1998

Eleven Italian ryegrass cultivars were examined for their genetic polymorphisms and phylogenetic relationships using randomly amplified polymorphic DNA (RAPD) markers. In RAPD analysis of 34 random primers, 96 of total 162 bands obtained from 16 primers were polymorphic and sizes of polymorphic band ranged between 0.5 and 1.5kb. Number of bands amplified per primer was varied from 3 to 16 and average number was 14.8. Phylogenetic relationship among cultivars based on the RAPD analysis was examined using UPGMA computer program. In pairwise genetic similarity test of 11 Italian ryegrass cultivars, Grazer and Orlando showed highest coefficient of genetic similarity as 0.740, whereas Marshall and Orlando was lowest as 0.438. Eleven Italian ryegrass cultivars were grouped into 3 major clusters and genetic distance of clusters ranged between 0.567 and 0.646, indicating low level of genetic variation.