Simulations of incompressible fluid flows by a least squares finite element method

In this work simulations of incompressible fluid flows have been done by a Least Squares Finite Element Method (LSFEM) using velocity-pressure-vorticity and velocity-pressure-stress formulations, named u-p-ω) and u-p-τ formulations respectively. These formulations are preferred because the resulting equations are partial differential equations of first order, which is convenient for implementation by LSFEM. The main purposes of this work are the numerical computation of laminar, transitional and turbulent fluid flows through the application of large eddy simulation (LES) methodology using the LSFEM. The Navier-Stokes equations in u-p-ω and u-p-τ formulations are filtered and the eddy viscosity model of Smagorinsky is used for modeling the sub-grid-scale stresses. Some benchmark problems are solved for validate the numerical code and the preliminary results are presented and compared with available results from the literature. Copyright © 2005 by ABCM.

Mitigating systematic errors for single frequency GPS receivers employing a penalized least squares methodology

Among the positioning systems that compose GNSS (Global Navigation Satellite System), GPS has the capability of providing low, medium and high precision positioning data. However, GPS observables may be subject to many different types of errors. These systematic errors can degrade the accuracy of the positioning provided by GPS. These errors are mainly related to GPS satellite orbits, multipath, and atmospheric effects. In order to mitigate these errors, a semiparametric model and the penalized least squares technique were employed in this study. This is similar to changing the stochastical model, in which error functions are incorporated and the results are similar to those in which the functional model is changed instead. Using this method, it was shown that ambiguities and the estimation of station coordinates were more reliable and accurate than when employing a conventional least squares methodology.

At least two indigenous species of the Bemisia tabaci complex are present in Brazil

Bemisia tabaci is one of the most important global agricultural insect pests, being a vector of emerging plant viruses such as begomoviruses and criniviruses that cause serious problems in many countries. Although knowledge of the genetic diversity of B. tabaci populations is important for controlling this pest and understanding viral epidemics, limited information is available on this pest in Brazil. A survey was conducted in different locations of São Paulo and Mato Grosso states, and the phylogenetic relationships of B. tabaci individuals from 43 populations sampled from different hosts were analysed based on partial mitochondrial cytochrome oxidase 1 gene (mtCOI) sequences. According to the recently proposed classification of the B. tabaci complex, which employs the 3.5% mtCOI sequence divergence threshold for species demarcation, most of the specimens collected were found to belong to the Middle East-Asia Minor 1 species, which includes the invasive populations of the commonly known B biotype, within the Africa/Middle East/Asia Minor high-level group. Three specimens collected from Solanun gilo and Ipomoea sp. were grouped together and could be classified in the New World species that includes the commonly known A biotype. However, six specimens collected from Euphorbia heterophylla, Xanthium cavanillesii and Glycine maxima could not be classified into any of the 28 previously proposed species, although according to the 11% mtCOI sequence divergence threshold, they belong to the New World high-level group. These specimens were classified into a new recently proposed species named New World 2 that includes populations from Argentina. Middle East-Asia Minor 1, New World and New World 2 were differentiated by RFLP analysis of the mtCOI gene using TaqI enzyme. Taq I analysis in silico also differentiates these from Mediterranean species, thus making this method a convenient tool to determine population dynamics, especially critical for monitoring the presence of this exotic pest in Brazil. © 2012 Blackwell Verlag, GmbH.

A brief look at the least-squares approach as a classifier applied to restricted-vocabulary speech recognition

In this letter, a speech recognition algorithm based on the least-squares method is presented. Particularly, the intention is to exemplify how such a traditional numerical technique can be applied to solve a signal processing problem that is usually treated by using more elaborated formulations.