Search results for "distributions"
showing 10 items of 214 documents
B-meson hadroproduction in the SACOT-mT scheme
2023
We apply the SACOT-mT general-mass variable flavour number scheme (GM-VFNS) to the inclusive B-meson production in hadronic collisions at next-to-leading order in perturbative Quantum Chromodynamics. In the GM-VFNS approach one matches the fixed-order heavy-quark production cross sections, accurate at low transverse momentum (pT), with the zero-mass cross sections, accurate at high pT. The physics idea of the SACOT-mT scheme is to do this by accounting for the finite momentum transfer required to create a heavy quark-antiquark pair throughout the calculation. We compare our results with the latest LHC data from proton-proton and proton-lead collisions finding a very good agreement within th…
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.
Fuzzy sigmoid kernel for support vector classifiers
2004
This Letter proposes the use of the fuzzy sigmoid function presented in (IEEE Trans. Neural Networks 14(6) (2003) 1576) as non-positive semi-definite kernel in the support vector machines framework. The fuzzy sigmoid kernel allows lower computational cost, and higher rate of positive eigenvalues of the kernel matrix, which alleviates current limitations of the sigmoid kernel.
Feature extraction from remote sensing data using Kernel Orthonormalized PLS
2007
This paper presents the study of a sparse kernel-based method for non-linear feature extraction in the context of remote sensing classification and regression problems. The so-called kernel orthonormalized PLS algorithm with reduced complexity (rKOPLS) has two core parts: (i) a kernel version of OPLS (called KOPLS), and (ii) a sparse (reduced) approximation for large scale data sets, which ultimately leads to rKOPLS. The method demonstrates good capabilities in terms of expressive power of the extracted features and scalability.
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.
A particle based simulation model for glacier dynamics
2013
This publication is contribution number 22 of the Nordic Centre of Excellence SVALI, “Stability and Variations of Arctic Land Ice”, funded by the Nordic Top-level Research Initiative (TRI). The work has been supported by the SVALI project through the University of Lapland, Arctic Centre, and through the University Centre in Svalbard. Funding was also provided by the Conoco-Phillips and Lunding High North Research Program (CRIOS: Calving Rates and Impact on Society). A particle-based computer simulation model was developed for investigating the dynamics of glaciers. In the model, large ice bodies are made of discrete elastic particles which are bound together by massless elastic beams. These…
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 …
Transverse energy production and charged-particle multiplicity at midrapidity in various systems from √sNN = 7.7 to 200 GeV
2016
Measurements of midrapidity charged-particle multiplicity distributions, dNch/dη, and midrapidity transverseenergy distributions, dET /dη, are presented for a variety of collision systems and energies. Included are distributions for Au + Au collisions at √sNN = 200, 130, 62.4, 39, 27, 19.6, 14.5, and 7.7 GeV, Cu + Cu collisions at √sNN = 200 and 62.4 GeV, Cu + Au collisions at √sNN = 200 GeV, U + U collisions at √sNN = 193 GeV, d + Au collisions at √sNN = 200 GeV, 3 He + Au collisions at √sNN = 200 GeV, and p + p collisions at √sNN = 200 GeV. Centrality-dependent distributions at midrapidity are presented in terms of the number of nucleon participants, Npart, and the number of constituent q…