São José dos Campos, Brazil
São José dos Campos, Brazil

Time filter

Source Type

Grzybowski J.M.V.,Federal University of Fronteira Sul | Macau E.E.N.,National Institute for Space Research | Yoneyama T.,Aeronautics Institute of Technology
Physica D: Nonlinear Phenomena | Year: 2017

This paper presents a self-contained framework for the stability assessment of isochronal synchronization in networks of chaotic and limit-cycle oscillators. The results were based on the Lyapunov–Krasovskii theorem and they establish a sufficient condition for local synchronization stability of as a function of the system and network parameters. With this in mind, a network of mutually delay-coupled oscillators subject to direct self-coupling is considered and then the resulting error equations are block-diagonalized for the purpose of studying their stability. These error equations are evaluated by means of analytical stability results derived from the Lyapunov–Krasovskii theorem. The proposed approach is shown to be a feasible option for the investigation of local stability of isochronal synchronization for a variety of oscillators coupled through linear functions of the state variables under a given undirected graph structure. This ultimately permits the systematic identification of stability regions within the high-dimensionality of the network parameter space. Examples of applications of the results to a number of networks of delay-coupled chaotic and limit-cycle oscillators are provided, such as Lorenz, Rössler, Cubic Chua's circuit, Van der Pol oscillator and the Hindmarsh–Rose neuron. © 2017 Elsevier B.V.


Silva F.O.,Federal University of Lavras | Hemerly E.M.,Aeronautics Institute of Technology | Leite Filho W.C.,National Institute for Space Research
Sensors (Switzerland) | Year: 2017

This paper presents the second part of a study aiming at the error state selection in Kalman filters applied to the stationary self-alignment and calibration (SSAC) problem of strapdown inertial navigation systems (SINS). The observability properties of the system are systematically investigated, and the number of unobservable modes is established. Through the analytical manipulation of the full SINS error model, the unobservable modes of the system are determined, and the SSAC error states (except the velocity errors) are proven to be individually unobservable. The estimability of the system is determined through the examination of the major diagonal terms of the covariance matrix and their eigenvalues/eigenvectors. Filter order reduction based on observability analysis is shown to be inadequate, and several misconceptions regarding SSAC observability and estimability deficiencies are removed. As the main contributions of this paper, we demonstrate that, except for the position errors, all error states can be minimally estimated in the SSAC problem and, hence, should not be removed from the filter. Corroborating the conclusions of the first part of this study, a 12-state Kalman filter is found to be the optimal error state selection for SSAC purposes. Results from simulated and experimental tests support the outlined conclusions. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.


Muniz F.,Aeronautics Institute of Technology | Maximo M.R.O.A.,Aeronautics Institute of Technology | Ribeiro C.H.C.,Aeronautics Institute of Technology
Proceedings - 13th Latin American Robotics Symposium and 4th Brazilian Symposium on Robotics, LARS/SBR 2016 | Year: 2016

Motion control for a high degrees of freedom humanoid robot is one the hardest problems in Mobile Robotics. Researchers have been very successful in designing walking motions using reduced order mathematical models based on the ZMP approach. However, this approach is unable to design very dynamic motions, such as movements to get up and long distance kicks. In these cases, keyframe movements have proven to be a successful technique. Therefore, this paper presents a system that allows a parallel approach for optimizing keyframe movements for the Robocup 3D Soccer Simulation League. Moreover, optimization results obtained using this system are shown to validate it. © 2016 IEEE.


Bendinelli W.E.,Aeronautics Institute of Technology | Bettini H.F.A.J.,Aeronautics Institute of Technology | Bettini H.F.A.J.,University of Sao Paulo | Oliveira A.V.M.,Aeronautics Institute of Technology
Transportation Research Part A: Policy and Practice | Year: 2016

This paper develops an econometric model of flight delays to investigate the influence of competition and dominance on the incentives of carriers to maintain on-time performance. We consider both the route and the airport levels to inspect the local and global effects of competition, with a unifying framework to test the hypotheses of 1. airport congestion internalization and 2. the market competition-quality relationship in a single econometric model. In particular, we examine the impacts of the entry of low cost carriers (LCC) on the flight delays of incumbent full service carriers in the Brazilian airline industry. The main results indicate a highly significant effect of airport congestion self-internalization in parallel with route-level quality competition. Additionally, the potential competition caused by LCC presence provokes a global effect that suggests the existence of non-price spillovers of the LCC entry to non-entered routes. © 2016 Elsevier Ltd.


Rolim P.S.W.,Aeronautics Institute of Technology | Bettini H.F.A.J.,University of Sao Paulo | Oliveira A.V.M.,Aeronautics Institute of Technology
Journal of Air Transport Management | Year: 2016

This paper develops an empirical model of passenger demand for routes of airports subject to either imminent or recent privatization. We investigate whether the privatization process produces a sequential impact over traffic. By employing a regression-based event methodology and controlling for fixed effects, price endogeneity and sample selection, we perform an econometric analysis of pre-privatization and post-privatization dynamic patterns of demand to infer the demand consequences of the major change in airport governance. We examine recent Brazilian airport privatization experience as a case. The main results suggest that privatization produced an overall increase in airline demand and that the airport notably recognized with the greatest demand potential and with the largest market penetration of a fast-growing low cost newcomer had the highest estimated ceteris paribus effect of privatization on demand. © 2016 Elsevier Ltd.


Madeira Jr. A.G.,Aeronautics Institute of Technology | Cardoso Jr. M.M.,Aeronautics Institute of Technology | Belderrain M.C.N.,Aeronautics Institute of Technology | Correia A.R.,Transportation Institute | Schwanz S.H.,Aeronautics Institute of Technology
International Journal of Production Economics | Year: 2012

Port services are key elements of a country's economy. They provide the necessary infrastructure for the development of industry, business and international trade. In this case, evaluating and improving their performance is essential to achieve international competitiveness. This paper presents a model for obtaining the performance of container terminals based on a multicriteria methodology. Factor analysis was used to reduce the number of criteria and ensure independence among them. The model has proved to be satisfactory in the ordering of container terminals considering the available data on major Brazilian ports from 2006 to 2009, according to the decision maker's values. The proposed method can develop applied models in the port area for any sector in order to evaluate performance. The results and the methodology are useful in supporting port authorities in providing incentives to achieve improvements in efficiency. © 2012 Elsevier B.V. All rights reserved.


Oliveira A.V.M.,Aeronautics Institute of Technology | Lohmann G.,Griffith University | Costa T.G.,Virtus BR Partners
Journal of Transport Geography | Year: 2016

This paper empirically investigates the main drivers of airline network concentration in an air transport market subject to rapid growth. We consider the Brazilian air transport industry of the 2000s, in which network concentration rapidly increased and was followed by a period of massive flight delays and cancelations, which resulted in the "big blackout" of 2006-2007. We develop an econometric model of network concentration, accounting for demand, cost and competition variables that may affect the propensity of carriers to concentrate flights and passenger connections on a few airports of a network. The main focus of the paper is on the relation between networks leading to the problems of the blackout episode. We investigate the dynamic pattern of the evolution of concentration before and after the abnormal period of operations and find that concentration began to rise at least six quarters before, and persisted at a high level until two quarters after the blackout - and then plunged steeply toward the end of the decade. We believe that our analysis contributes to an improved understanding of the behavior of air transport systems subject to network concentration and congestion. With respect to methodology, we suggest and employ the use of alternative measures of network concentration to check the robustness and validity of our results. © 2015 Elsevier Ltd.


Eliott F.M.,Aeronautics Institute of Technology | Ribeiro C.H.C.,Aeronautics Institute of Technology
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) | Year: 2015

Human behavior can be analysed through a moral perspective when considering strategies for cooperation in evolutionary games. Presuming a multiagent task performed by self-centered agents, artificial moral behavior could bring about the emergence of cooperation as a consequence of the computational model itself. Herein we present results from our MultiA computational architecture, derived from a biologically inspired model and projected to simulate moral behavior through an Empathy module. Our testbed is a multiagent game previously defined in the literature such that the lack of cooperation may cause a cascading failure effect ("bankruptcy") that impacts on the global network topology via local neighborhood interactions. Starting with sensorial information originated from the environment, MultiA transforms it into basic and social artificial emotions and feelings. Then its own emotions are employed to estimate the current state of other agents through an Empathy module. Finally, the artificial feelings of MultiA provide a measure (called well-being) of its performance in response to the environment. Through that measure and reinforcement learning techniques, MultiA learns a mapping from emotions to actions. Results indicate that strategies relied upon simulation of moral behavior may indeed help to decrease the internal reward from selfish selection of actions, thus favoring cooperation as an emergent property of multiagent systems. © Springer International Publishing Switzerland 2015.


Santos R.S.,Aeronautics Institute of Technology | Malheiros S.M.F.,Federal University of São Paulo | Cavalheiro S.,Federal University of São Paulo | de Oliveira J.M.P.,Aeronautics Institute of Technology
Computer Methods and Programs in Biomedicine | Year: 2013

Cancer is the leading cause of death in economically developed countries and the second leading cause of death in developing countries. Malignant brain neoplasms are among the most devastating and incurable forms of cancer, and their treatment may be excessively complex and costly. Public health decision makers require significant amounts of analytical information to manage public treatment programs for these patients. Data mining, a technology that is used to produce analytically useful information, has been employed successfully with medical data. However, the large-scale adoption of this technique has been limited thus far because it is difficult to use, especially for non-expert users. One way to facilitate data mining by non-expert users is to automate the process. Our aim is to present an automated data mining system that allows public health decision makers to access analytical information regarding brain tumors. The emphasis in this study is the use of ontology in an automated data mining process. The non-experts who tried the system obtained useful information about the treatment of brain tumors. These results suggest that future work should be conducted in this area. © 2012 Elsevier Ireland Ltd.


Sternberg E.M.A.,Aeronautics Institute of Technology | Rodrigues N.A.S.,Aeronautics Institute of Technology | Amorim J.,Aeronautics Institute of Technology
Applied Physics B: Lasers and Optics | Year: 2016

In this work, we suggest a method for electron impact width parameter calculation based on Stark broadening of emission lines of a laser-ablated plasma plume. First, electron density and temperature must be evaluated by means of the Saha–Boltzmann plot method for neutral and ionized species of the plasma. The method was applied for laser-ablated molybdenum plasma plume. For molybdenum plasma electron temperature, which varies around 10,000 K, and electron density, which reaches values around 1018 cm−3, and considering that total measured line broadening was due experimental and Stark broadening mainly, electron impact width parameter of molybdenum emission lines was determined as (0.01 ± 0.02) nm. Intending to validate the presented method, it was analyzed the laser-ablated aluminum plasma plume and the obtained results were in agreement with the predicted on the literature. © 2016, Springer-Verlag Berlin Heidelberg.

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