Search results for "Matrices"
showing 10 items of 155 documents
Longitudinal Associations of Fitness, Motor Competence, and Adiposity with Cognition
2019
Purpose: The purpose of this study was to investigate the longitudinal associations of cardiorespiratory fitness (CRF), motor competence (MC), and body fat percentage (BF%) with cognition in children. Methods: Altogether, 371 children (188 boys and 183 girls) 6–9 yr of age at baseline participated in this 2-yr follow-up study. We assessed CRF by maximal cycle ergometer test, computed the MC score from the z-scores of the 50-m shuttle run, static balance, and box and block test results, measured BF% by dual-energy x-ray absorptiometry, and assessed cognition using the Raven’s Coloured Progressive Matrices (RCPM) score. The associations were studied by linear regression analysis and repeated-…
Algorithms for {K, s+1}-potent matrix constructions
2013
In this paper, we deal with {K, s + 1}-potent matrices. These matrices generalize all the following classes of matrices: k-potent matrices, periodic matrices, idempotent matrices, involutory matrices, centrosymmetric matrices, mirrorsymmetric matrices, circulant matrices, among others. Several applications of these classes of matrices can be found in the literature. We develop algorithms in order to compute {K, s + 1}-potent matrices and {K, s + 1}-potent linear combinations of {K, s + 1}-potent matrices. In addition, some examples are presented in order to show the numerical performance of the method. (C) 2012 Elsevier B.V. All rights reserved.
Implementation of eco-sustainable biocomposite materials reinforced by optimized agave fibers
2018
Abstract Although several works have recently been published in literature about biocomposites, i.e. about composites with polymeric matrix reinforced by natural fibers, only a few articles have been devoted to the implementation of high performance biocomposites for structural and semi-structural applications. The present study aims to give a contribution by considering biocomposites obtained by using an eco-friendly partially bio-based epoxy (green epoxy) and sisal (agave sisalana fibers) obtained by a proper optimization process. Through a systematic experimental analysis, three different types of biocomposites obtained with a suitable manufacturing process, such as random short fiber bi…
How to simulate normal data sets with the desired correlation structure
2010
The Cholesky decomposition is a widely used method to draw samples from multivariate normal distribution with non-singular covariance matrices. In this work we introduce a simple method by using singular value decomposition (SVD) to simulate multivariate normal data even if the covariance matrix is singular, which is often the case in chemometric problems. The covariance matrix can be specified by the user or can be generated by specifying a subset of the eigenvalues. The latter can be an advantage for simulating data sets with a particular latent structure. This can be useful for testing the performance of chemometric methods with data sets matching the theoretical conditions for their app…
A fast 3D dual boundary element method based on hierarchical matrices
2008
AbstractIn this paper a fast solver for three-dimensional BEM and DBEM is developed. The technique is based on the use of hierarchical matrices for the representation of the collocation matrix and uses a preconditioned GMRES for the solution of the algebraic system of equations. The preconditioner is built exploiting the hierarchical arithmetic and taking full advantage of the hierarchical format. Special algorithms are developed to deal with crack problems within the context of DBEM. The structure of DBEM matrices has been efficiently exploited and it has been demonstrated that, since the cracks form only small parts of the whole structure, the use of hierarchical matrices can be particula…
The varieties of bifocal Grassmann tensors
2022
AbstractGrassmann tensors arise from classical problems of scene reconstruction in computer vision. In particular, bifocal Grassmann tensors, related to a pair of projections from a projective space onto view spaces of varying dimensions, generalize the classical notion of fundamental matrices. In this paper, we study in full generality the variety of bifocal Grassmann tensors focusing on its birational geometry. To carry out this analysis, every object of multi-view geometry is described both from an algebraic and geometric point of view, e.g., the duality between the view spaces, and the space of rays is explicitly described via polarity. Next, we deal with the moduli of bifocal Grassmann…
Controlled Release of Metformin Hydrochloride from Core-Shell Nanofibers with Fish Sarcoplasmic Protein
2019
Ficai, Anton/0000-0002-1777-0525; Karademir, Betul/0000-0003-1762-0284 WOS:000503463400074 PubMed ID: 31658758 Background and Objectives: A coaxial electrospinning technique was used to produce core/shell nanofibers of a polylactic acid (PLA) as a shell and a polyvinyl alcohol (PVA) containing metformin hydrochloride (MH) as a core. Materials and Methods: Fish sarcoplasmic protein (FSP) was extracted from fresh bonito and incorporated into nanofiber at various concentrations to investigate the influence on properties of the coaxial nanofibers. The morphology, chemical structure and thermal properties of the nanofibers were studied. Results: The results show that uniform and bead-free struct…
OnMLM: An Online Formulation for the Minimal Learning Machine
2019
Minimal Learning Machine (MLM) is a nonlinear learning algorithm designed to work on both classification and regression tasks. In its original formulation, MLM builds a linear mapping between distance matrices in the input and output spaces using the Ordinary Least Squares (OLS) algorithm. Although the OLS algorithm is a very efficient choice, when it comes to applications in big data and streams of data, online learning is more scalable and thus applicable. In that regard, our objective of this work is to propose an online version of the MLM. The Online Minimal Learning Machine (OnMLM), a new MLM-based formulation capable of online and incremental learning. The achievements of OnMLM in our…
T-patterns in the study of movement and behavioral disorders
2020
Aim of the present review is to offer an outline of the application of T-pattern analysis (TPA) in the study of neurological disorders characterized by anomalies of movement and, more in general, of behavior. TPA is a multivariate technique to detect real time patterns of behavior on the basis of statistically significant constraints among the events in sequence. TPA is particularly suitable to analyse the structure of behavior. The application of TPA to study movement and behavioral disorders is able to offer, with a high level of detail, hidden characteristics of behavior otherwise impossible to detect. For its intrinsic features, TPA is completely different not only from quantitative eva…
Evolution of worldwide stock markets, correlation structure and correlation based graphs
2011
We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period Jan 1996 - Jul 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term timescale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the non diagonal elements of the correlation matrix, corre…