Using cosmological N-body simulations of critical (SCDM) and open (Ω=0.3, OCDM) cold dark matter models we have identified dark matter halos which are associated with the progenitors of present day bright early–type galaxies. By following their merging history, we show how early–type galaxies that formed within massive halos at redshift ' 3 are now preferentially residing in clusters and groups...

Text summarization system can save the time for user when reading large number of documents. The summary of text summarization system usually composed of meaningful sentence which represent content of text. The relations between keyword usually come from their cooccurrences in document. This study using hierarchical clustering method cluster sentences and apply concept formal analysis to find o...

abstract purpose of this paper: the objectives of this paper are two folds: (1) utilizing hierarchical fuzzy technique for order preference by similarity to ideal solution (topsis) approach to evaluate the most suitable rfid-based systems decision, and (2) to highlight key risks and benefits of radio frequency identification technology in healthcare industry. design/methodology/approach: resear...

The paper proposes a new method to approximate the normalized information distance by a compression method that is particularly suited for image data. The new method is based on a video compressor. The new method is used to compute the distance matrix of all the images in the data sets considered. Moreover, the hierarchical clustering method from the R package is used to cluster the distance ma...

Article history: Received 10 May 2015 Received in revised form 19 January 2016 Accepted 19 January 2016 Available online 3 February 2016 Hundreds of studies have shown that, in people, cognitive abilities overlap yielding anunderlying ‘g’ factor, which explainsmuch of the variance.We assessed individual differences in cognitive abilities in 68 border collies to determine the structure of intell...

Semantic clustering is important to various fields in the modern information society. In this work we applied the Independent Component Analysis method to the extraction of the features of latent concepts. We used verb and object noun information and formulated a concept as a linear combination of verbs. The proposed method is shown to be suitable for our framework and it performs better than a...

A self-organizing framework for object recognition is described. We describe a hierarchical database structure for image retrieval. The SHOSLIF (Self-Organizing Hierarchical Optimal Subspace Learning and Inference Framework) system uses the theories of optimal linear projection for automatic optimal feature derivation and a hierarchical structure to achieve a logarithmic retrieval complexity. A...

The existing methods for clustering of gene expression profile data either require manual inspection and other biological knowledge or require some cut-off value which can not be directly calculated from the given data set. Thus, the problem of systematic and efficient determination of cluster boundaries of clusters in gene expression profile data still remains demanding. In this context, we ha...

Entropy Agglomeration (EA) is a hierarchical clustering algorithm introduced in 2013. Here, we generalize it to define Generalized Entropy Agglomeration (GEA) that can work with multiset blocks and blocks with rational occurrence numbers. We also introduce a numerical categorization procedure to apply GEA to numerical datasets. The software REBUS 2.0 is published with these capabilities: http:/...