Search results for "density [dark matter]"

Spectral clustering with the probabilistic cluster kernel

2015

Abstract This letter introduces a probabilistic cluster kernel for data clustering. The proposed kernel is computed with the composition of dot products between the posterior probabilities obtained via GMM clustering. The kernel is directly learned from the data, is parameter-free, and captures the data manifold structure at different scales. The projections in the kernel space induced by this kernel are useful for general feature extraction purposes and are here exploited in spectral clustering with the canonical k-means. The kernel structure, informative content and optimality are studied. Analysis and performance are illustrated in several real datasets.

Semisupervised kernel orthonormalized partial least squares

2012

This paper presents a semisupervised kernel orthonormalized partial least squares (SS-KOPLS) algorithm for non-linear feature extraction. The proposed method finds projections that minimize the least squares regression error in Hilbert spaces and incorporates the wealth of unlabeled information to deal with small size labeled datasets. The method relies on combining a standard RBF kernel using labeled information, and a generative kernel learned by clustering all available data. The positive definiteness of the kernels is proven, and the structure and information content of the derived kernels is studied. The effectiveness of the proposed method is successfully illustrated in standard UCI d…

Semisupervised Kernel Feature Extraction for Remote Sensing Image Analysis

2014

This paper presents a novel semisupervised kernel partial least squares (KPLS) algorithm for nonlinear feature extraction to tackle both land-cover classification and biophysical parameter retrieval problems. The proposed method finds projections of the original input data that align with the target variable (labels) and incorporates the wealth of unlabeled information to deal with low-sized or underrepresented data sets. The method relies on combining two kernel functions: the standard radial-basis-function kernel based on labeled information and a generative, i.e., probabilistic, kernel directly learned by clustering the data many times and at different scales across the data manifold. Th…

A family of kernel anomaly change detectors

2014

This paper introduces the nonlinear extension of the anomaly change detection algorithms in [1] based on the theory of reproducing kernels. The presented methods generalize their linear counterparts, under both the Gaussian and elliptically-contoured assumptions, and produce both improved detection accuracies and reduced false alarm rates. We study the Gaussianity of the data in Hilbert spaces with kernel dependence estimates, provide low-rank kernel versions to cope with the high computational cost of the methods, and give prescriptions about the selection of the kernel functions and their parameters. We illustrate the performance of the introduced kernel methods in both pervasive and anom…

Semi-Supervised Remote Sensing Image Classification based on Clustering and the Mean Map Kernel

2008

This paper presents a semi-supervised classifier based on the combination of the expectation-maximization (EM) algorithm for Gaussian mixture models (GMM) and the mean map kernel. The proposed method uses the most reliable samples in terms of maximum likelihood to compute a kernel function that accurately reflects the similarity between clusters in the kernel space. The proposed method improves classification accuracy in situations where the available labeled information does not properly describe the classes in the test image.

Influence of M23C6 carbides on the heterogeneous strain development in annealed 420 stainless steel

2020

Understanding the local strain enhancement and lattice distortion resulting from different microstructure features in metal alloys is crucial in many engineering processes. The development of heterogeneous strain not only plays an important role in the work hardening of the material but also in other processes such as recrystallization and damage inheritance and fracture. Isolating the contribution of precipitates to the development of heterogeneous strain can be challenging due to the presence of grain boundaries or other microstructure features that might cause ambiguous interpretation. In this work a statistical analysis of local strains measured by electron back scatter diffraction and …

1992

The molecular packing and spatial correlations of polymers [CH 2 CR(COOR')] n (R= H, Me; R'= (CH 2 ) 11 + NMe 2 (CH 2 ) 3 SO 3 - ; (CH 2 ) 2 + N(Me)[(CH 2 ) 3 SO 3 - ][C 10 H 21 ]) are studied by means of X-ray analysis and conformational calculations. The analysis of the correlation functions and density distribution profiles suggest a double-layered molecular packing which is discussed for the three polymers investigated, with respect to their different chemical structures. Whereas the zwitterionic polymethacrylates studied exhibit liquid-like short-range order, the polyacrylate analog exhibits an ordered double-layered superstructure

Long Range Bond-Bond Correlations in Dense Polymer Solutions

2004

The scaling of the bond-bond correlation function $C(s)$ along linear polymer chains is investigated with respect to the curvilinear distance, $s$, along the flexible chain and the monomer density, $\rho$, via Monte Carlo and molecular dynamics simulations. % Surprisingly, the correlations in dense three dimensional solutions are found to decay with a power law $C(s) \sim s^{-\omega}$ with $\omega=3/2$ and the exponential behavior commonly assumed is clearly ruled out for long chains. % In semidilute solutions, the density dependent scaling of $C(s) \approx g^{-\omega_0} (s/g)^{-\omega}$ with $\omega_0=2-2\nu=0.824$ ($\nu=0.588$ being Flory's exponent) is set by the number of monomers $g(\r…

Effect of conjugated system extension on structural features and electron-density distribution in charge–transfer difluoroborates

2021

A comparative structural study of two related donor–acceptor pyridine-based BF2 complexes, namely, 3-(dimethylamino)-1,1-difluoro-1H-pyrido[1,2-c][1,3,5,2]oxadiazaborinin-9-ium-1-uide, C8H10BF2N3O (1), and 3-{(1E,3E)-4-[4-(dimethylamino)phenyl]buta-1,3-dien-1-yl}-1,1-difluoro-1H-pyrido[1,2-c][1,3,5,2]oxadiazaborinin-9-ium-1-uide, C18H18BF2N3O (2), containing a dimethylamino group and either the shortest (in 1) or the longest (in 2) charge-transfer path known until now in this family of compounds, is presented. Single-crystal X-ray diffraction analysis supported by computational investigations shed more light on these systems, indicating, among other aspects, the predominance of C—H...F cont…

Are there plenty of fish in the sea? How life history traits affect the eco-evolutionary consequences of population oscillations

2022

Understanding fish population oscillations is important for both fundamental population biology and for fisheries science. Much research has focused on the causes of population oscillations, but the eco-evolutionary consequences of population oscillations are unclear. Here, we used an empirically parametrised individual-based simulation model to explore the consequences of oscillations with different amplitudes and wavelengths. We show that oscillations with a wavelength shorter than the maximum lifespan of the fish produce marked differences in the evolutionary trajectories of asymptotic length. Wavelengths longer than the maximum lifespan of the fish, in turn, mainly manifest as ecologica…