Search results for "Correlation"
showing 10 items of 2282 documents
Scalable Clustering by Iterative Partitioning and Point Attractor Representation
2016
Clustering very large datasets while preserving cluster quality remains a challenging data-mining task to date. In this paper, we propose an effective scalable clustering algorithm for large datasets that builds upon the concept of synchronization. Inherited from the powerful concept of synchronization, the proposed algorithm, CIPA (Clustering by Iterative Partitioning and Point Attractor Representations), is capable of handling very large datasets by iteratively partitioning them into thousands of subsets and clustering each subset separately. Using dynamic clustering by synchronization, each subset is then represented by a set of point attractors and outliers. Finally, CIPA identifies the…
Gravitational weighted fuzzy c-means with application on multispectral image segmentation
2014
This paper presents a novel clustering approach based on the classic Fuzzy c-means algorithm. The approach is inspired from the concept of interaction between objects in physics. Each data point is regarded as a particle. A specific weight is associated with each data particle depending on its interaction with other particles. This interaction is induced by attraction forces between pairs of particles and the escape velocity from other particles. Classification experiments using two data sets from UCI repository demonstrate the outperformance of the proposed approach over other clustering algorithms. In addition, results demonstrate the effectiveness of the proposed scheme for segmentation …
A Novel Clustering Algorithm based on a Non-parametric "Anti-Bayesian" Paradigm
2015
The problem of clustering, or unsupervised classification, has been solved by a myriad of techniques, all of which depend, either directly or implicitly, on the Bayesian principle of optimal classification. To be more specific, within a Bayesian paradigm, if one is to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strategy would be to achieve this based on the distance from the corresponding means or central points in the respective distributions. When this principle is applied in clustering, one would assign an unassigned sample into the cluster whose mean is the closest, and this can be done in either a bottom-up or a top-dow…
Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering
2017
Clustering is an unsupervised machine learning and pattern recognition method. In general, in addition to revealing hidden groups of similar observations and clusters, their number needs to be determined. Internal clustering validation indices estimate this number without any external information. The purpose of this article is to evaluate, empirically, characteristics of a representative set of internal clustering validation indices with many datasets. The prototype-based clustering framework includes multiple, classical and robust, statistical estimates of cluster location so that the overall setting of the paper is novel. General observations on the quality of validation indices and on t…
Levels of self-consistency in the GW approximation
2009
We perform $GW$ calculations on atoms and diatomic molecules at different levels of self-consistency and investigate the effects of self-consistency on total energies, ionization potentials and on particle number conservation. We further propose a partially self-consistent $GW$ scheme in which we keep the correlation part of the self-energy fixed within the self-consistency cycle. This approximation is compared to the fully self-consistent $GW$ results and to the $G W_0$ and the $G_0W_0$ approximations. Total energies, ionization potentials and two-electron removal energies obtained with our partially self-consistent $GW$ approximation are in excellent agreement with fully self-consistent $…
Rayleigh and Rice Channels
2011
This chapter contains sections titled: System Theoretical Description of Multipath Channels Formal Description of Rayleigh and Rice Channels Elementary Properties of Rayleigh and Rice Channels Statistical Properties of Rayleigh and Rice Channels Further Reading Appendix 3.A Derivation of the Jakes Power Spectral Density and the Corresponding Autocorrelation Function Appendix 3.B Derivation of the Autocorrelation Function of the Envelope Appendix 3.C Derivation of the Autocovariance Spectrum of the Envelope Under Isotropic Scattering Conditions Appendix 3.D Derivation of the Level‐Crossing Rate of Rice Processes with Different Spectral Shapes of the Underlying Gaussian Random Processes
WT1 isoform expression pattern in acute myeloid leukemia.
2013
WT1 plays a dual role in leukemia development, probably due to an imbalance in the expression of the 4 main WT1 isoforms. We quantify their expression and evaluate them in a series of AML patients. Our data showed a predominant expression of isoform D in AML, although in a lower quantity than in normal CD34+ cells. We found a positive correlation between the total WT1 expression and A, B and C isoforms. The overexpression of WT1 in AML might be due to a relative increase in A, B and C isoforms, together with a relative decrease in isoform D expression.
Disassembly of structurally modified viral nanoparticles: characterization by fluorescence correlation spectroscopy.
2005
Abstract Analysis of the breakdown products of engineered viral particles can give useful information on the particle structure. We used various methods to breakdown both a recombinant enveloped virus and virus-like particles (VLPs) from two non-enveloped viruses and analysed the resulting subunits by fluorescence correlation spectroscopy (FCS). Analysis of the enveloped baculovirus, Autographa californica multicapsid nucleopolyhedrovirus (AcMNPV), displaying the green fluorescent protein (GFP) fused to its envelope protein gp64 was performed in the presence and absence of 5 mM SDS and 25 mM DTT. Without treatment, the viral particle showed a diffusion time of 3.3 ms. In the presence of SDS…
A CI study of the CuCO and CuCO+ complexes
1987
MO CI calculations are carried out using an optimal space of valence virtual MOs obtained by means of a projection technique, as a linear combination of the AOs which are more occupied in the molecular Fock space. Localization of the occupied MOs and nonvalence virtual MOs is also achieved. The overall procedure is proven to be quite advantageous and well suited to obtain potential energy curves which keep the same physical meaning along the range of distances studied. Using a slightly better than double‐zeta quality basis set, a valence CAS‐CI, and selected CI wave function by the CIPSI algorithm have revealed a possible weak van der Waals interaction for the 2Σ+ state of CuCO, which remai…
Large-scale calculations of excitation energies in coupled cluster theory: The singlet excited states of benzene
1996
Algorithms for calculating singlet excitation energies in the coupled cluster singles and doubles (CCSD) model are discussed and an implementation of an atomic-integral direct algorithm is presented. Each excitation energy is calculated at a cost comparable to that of the CCSD ground-state energy. Singlet excitation energies are calculated for benzene using up to 432 basis functions. Basis-set effects of the order of 0.2 eV are observed when the basis is increased from augmented polarized valence double-zeta (aug-cc-pVDZ) to augmented polarized valence triple-zeta (aug-cc-pVTZ) quality. The correlation problem is examined by performing calculations in the hierarchy of coupled cluster models…