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Waldmann J.,Brazilian Technological Institute of Aeronautics | Da Silva R.I.G.,INSPER Institute Ensino e Pesquisa | Chagas R.A.J.,National Institute for Space Research
Information Sciences | Year: 2016

Fusion of inertial and vision sensors is an effective aid to inertial navigation systems (INS) during GPS outage. Optical flow-aided inertial navigation circumvents feature tracking, landmark mapping, and state vector augmentation typical of simultaneous localization and mapping (SLAM). This paper focuses on the observability analysis of INS errors from implicit measurements of the optical flow subspace constraint, and derives how observable and unobservable directions are affected by the motion of a camera rigidly coupled to an inertial measurement unit (IMU). Straight motion and piecewise constant (PWC) attitude segments yield the random constant IMU errors observable. The unobservable directions are the three-dimensional (3D) position error, the velocity error along the ground velocity, and the combination of angular misalignment about the local vertical and the velocity error along the horizontal direction orthogonal to the ground velocity. The velocity error along the ground velocity becomes observable with horizontal maneuvering. A Monte Carlo simulation validates the observability analysis, and reveals the feasibility of IMU calibration and the mitigation of navigation error growth with the aid of the optical flow subspace constraint compared with the unaided INS. © 2015 Elsevier Inc. Source

Caetano M.A.L.,INSPER Institute Ensino e Pesquisa | Gherardi D.F.M.,National Institute for Space Research | Yoneyama T.,Brazilian Technological Institute of Aeronautics
Ecological Modelling | Year: 2011

The Brazilian government has already acknowledged the importance of investing in the development and application of technologies to reduce or prevent CO 2 emissions resulting from human activities in the Legal Brazilian Amazon (BA). The BA corresponds to a total area of 5×10 6km 2 from which 4×10 6km 2 was originally covered by the rain forest. One way to interfere with the net balance of greenhouse gases (GHG) emissions is to increase the forest area to sequester CO 2 from the atmosphere. The single most important cause of depletion of the rain forest is cattle ranching. In this work, we present an effective policy to reduce the net balance of CO 2 emissions using optimal control theory to obtain a compromising partition of investments in reforestation and promotion of clear technology to achieve a CO 2 emission target for 2020. The simulation indicates that a CO 2 emission target for 2020 of 376 million tonnes requires an estimated forest area by 2020 of 3,708,000km 2, demanding a reforestation of 454,037km 2. Even though the regional economic growth can foster the necessary political environment for the commitment with optimal emission targets, the reduction of 38.9% of carbon emissions until 2020 proposed by Brazilian government seems too ambitious. © 2011 Elsevier B.V. Source

Venezuela M.K.,INSPER Institute Ensino e Pesquisa | Sandoval M.C.,University of Sao Paulo | Botter D.A.,University of Sao Paulo
Computational Statistics and Data Analysis | Year: 2011

Local influence diagnostics based on estimating equations as the role of a gradient vector derived from any fit function are developed for repeated measures regression analysis. Our proposal generalizes tools used in other studies (Cook, 1986; Cadigan and Farrell, 2002), considering herein local influence diagnostics for a statistical model where estimation involves an estimating equation in which all observations are not necessarily independent of each other. Moreover, the measures of local influence are illustrated with some simulated data sets to assess influential observations. Applications using real data are presented. © 2010 Published by Elsevier B.V. Source

Giannetti E.,INSPER Institute Ensino e Pesquisa
Dementia e Neuropsychologia | Year: 2011

Modern science has undermined belief in countless imaginary causalities. What is the nature of the relation between mind and brain? Philosophers have debated the issue for millennia, but it is only in the last twenty years that empirical evidence has begun to uncover some of the secrets of this ancient riddle. This lecture explores the possibility that advances in neuroscience will undermine and subvert our intuitive, mentalist understanding of the mind-body relationship. Recent findings in neuroscience seem to support the notions that (i) mental events are a subclass of neurophysiological events, and (ii) they are devoid of causal efficacy upon the workings of the brain. If physicalism is true then the belief in the causal potency of conscious thoughts and free will are bound to join company with countless other imaginary causalities exploded by the progress of science. Source

Sandoval Jr. L.,INSPER Institute Ensino e Pesquisa
Physica A: Statistical Mechanics and its Applications | Year: 2014

Financial markets worldwide do not have the same working hours. As a consequence, the study of correlation or causality between financial market indices becomes dependent on whether we should use all indices on the same day or lagged indices in computations of correlation matrices. The answer this article proposes is that we should consider both, by representing original and lagged indices in the same network. We then obtain a better understanding of how indices that operate on different hours relate to each other. We use a diverse range of 79 stock market indices from around the world and study their correlation structure, the eigenvalues and eigenvectors of their correlations under different time periods and volatility, as well as the differences between the working hours of the stock exchanges in order to analyze the possible time zone effects and suggest ways to remove them. We also analyze the enlarged correlation matrix obtained from original and lagged indices and examine a network structure derived from it, thus showing connections between lagged and original indices that could not be well represented before. © 2014 Elsevier B.V. All rights reserved. Source

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