Towards forecasting and mitigating ionospheric scintillation effects on GNSS

The effect of the ionosphere on the signals of Global Navigation Satellite Systems (GNSS), such as the Global Positionig System (GPS) and the proposed European Galileo, is dependent on the ionospheric electron density, given by its Total Electron Content (TEC). Ionospheric time-varying density irregularities may cause scintillations, which are fluctuations in phase and amplitude of the signals. Scintillations occur more often at equatorial and high latitudes. They can degrade navigation and positioning accuracy and may cause loss of signal tracking, disrupting safety-critical applications, such as marine navigation and civil aviation. This paper addresses the results of initial research carried out on two fronts that are relevant to GNSS users if they are to counter ionospheric scintillations, i.e. forecasting and mitigating their effects. On the forecasting front, the dynamics of scintillation occurrence were analysed during the severe ionospheric storm that took place on the evening of 30 October 2003, using data from a network of GPS Ionospheric Scintillation and TEC Monitor (GISTM) receivers set up in Northern Europe. Previous results [1] indicated that GPS scintillations in that region can originate from ionospheric plasma structures from the American sector. In this paper we describe experiments that enabled confirmation of those findings. On the mitigation front we used the variance of the output error of the GPS receiver DLL (Delay Locked Loop) to modify the least squares stochastic model applied by an ordinary receiver to compute position. This error was modelled according to [2], as a function of the S4 amplitude scintillation index measured by the GISTM receivers. An improvement of up to 21% in relative positioning accuracy was achieved with this technnique.

Generating VRS data using atmospheric models: How far can we go?

Nowadays, with the expansion of the reference stations networks, several positioning techniques have been developed and/or improved. Among them, the VRS (Virtual Reference Station) concept has been very used. In this paper the goal is to generate VRS data in a modified technique. In the proposed methodology the DD (double difference) ambiguities are not computed. The network correction terms are obtained using only atmospheric (ionospheric and tropospheric) models. In order to carry out the experiments it was used data of five reference stations from the GPS Active Network of West of São Paulo State and an extra station. To evaluate the VRS data quality it was used three different strategies: PPP (Precise Point Positioning) and Relative Positioning in static and kinematic modes, and DGPS (Differential GPS). Furthermore, the VRS data were generated in the position of a real reference station. The results provided by the VRS data agree quite well with those of the real file data.

Otimização da distância de extração de madeira com forwarder

The activities and management operations of wood harvesting do not have good computational tools available to help the forest technicians with the task of cost reduction. In many cases, machines of high investment are used in wood harvesting without adequate operation planning; consequently, the cost per hour of these machines, which is high, could be reduced. Using technological resources such as the Geographic Information Systems (GIS) integrated with the Global Positioning System (GPS), which are the basis of precision harvesting. In this research, a technological tool capable of calculating and optimizing the average skidding distance of the forwarder was developed. It was used in stands of different sizes and formats through mathematical techniques and available functionalities in the Geographic Information System GRASS. The developed tool, called optimized model, divides the stand in small parts in relation to shorter skidding distances. The main variable considered was the alignment of plantation. The model was tested in eucalypt stands located in the State of São Paulo. Sixteen stands were randomly selected: eight with a rectangular polygon form, and eight with irregular polygon form. The main variables were collected in these stands. Results showed that the optimized model developed, is efficient and flexible. It was possible to divide the stands in small parts resulting in smaller skidding medium distances. The stands with irregular form had shorter skidding medium distances than the rectangular stands.

Virtual simulator for mobile robots navigation systems

This paper presents the virtual environment implementation for project simulation and conception of supervision and control systems for mobile robots, that are capable to operate and adapting in different environments and conditions. This virtual system has as purpose to facilitate the development of embedded architecture systems, emphasizing the implementation of tools that allow the simulation of the kinematic conditions, dynamic and control, with real time monitoring of all important system points. For this, an open control architecture is proposal, integrating the two main techniques of robotic control implementation in the hardware level: systems microprocessors and reconfigurable hardware devices. The implemented simulator system is composed of a trajectory generating module, a kinematic and dynamic simulator module and of a analysis module of results and errors. All the kinematic and dynamic results shown during the simulation can be evaluated and visualized in graphs and tables formats, in the results analysis module, allowing an improvement in the system, minimizing the errors with the necessary adjustments optimization. For controller implementation in the embedded system, it uses the rapid prototyping, that is the technology that allows, in set with the virtual simulation environment, the development of a controller project for mobile robots. The validation and tests had been accomplish with nonholonomics mobile robots models with diferencial transmission. © 2008 IEEE.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Mobile Robot navigation modelling, control and applications

This work presents and discusses the main topics involved on the design of a mobile robot system and focus on the control and navigation systems for autonomous mobile robots. Introduces the main aspects of the Robot design, which is a holistic vision about all the steps of the development process of an autonomous mobile robot; discusses the problems addressed to the conceptualization of the mobile robot physical structure and its relation to the world. Presents the dynamic and control analysis for navigation robots with kinematic and dynamic model and, for final, presents applications for a robotic platform of Automation, Simulation, Control and Supervision of Mobile Robots Navigation, with studies of dynamic and kinematic modelling, control algorithms, mechanisms for mapping and localization, trajectory planning and the platform simulator. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.

Indices of body fat distribution for assessment of lipodysthrophy in people living with HIV/AIDS

Background: Metabolic and morphological changes associated with excessive abdominal fat, after the introduction of Antiretroviral Therapy, increase the risk of cardiovascular disease in people living with HIV/AIDS(PLWHA). Accurate methods for body composition analysis are expensive and the use of anthropometric indices is an alternative. However the investigations about this subject in PLWHA are rare, making this research very important for clinical purpose and to advance scientific knowledge. The aim of this study is to correlate results of anthropometric indices of evaluation of body fat distribution with the results obtained by Dual-energy X-Ray Absorptiometry(DEXA) , in people living with HIV/AIDS. Methods. The sample was of 67 PLWHA(39 male and 28 female), aged 43.6+7.9 years. Body mass index, conicity index, waist/hip ratio, waist/height ratio and waist/thigh were calculated. Separated by sex, each index/ratio was plotted in a scatter chart with linear regression fit and their respective Pearson correlation coefficients. Analyses were performed using Prism statistical program and significance was set at 5%. Results: The waist/height ratio presented the highest correlation coefficient, for both male (r=0.80, p<0.001) and female (r=0.87, p <001), while the lowest were in the waist/thigh also for both: male group (r=0.58, p<0.001) and female group (r=0.03, p=0.86). The other indices also showed significant positive correlation with DEXA. Conclusion: Anthropometric indices, especially waist/height ratio may be a good alternative way to be used for evaluating the distribution of fat in the abdominal region of adults living with HIV/ADIS. © 2012 Segatto et al.; licensee BioMed Central Ltd.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Gestantes vivendo com HIV/AIDS: Características antropométricas e peso ao nascer dos seus recém-nascidos

PURPOSE: To describe the anthropometric and pregnancy characteristics of women with HIV/AIDS, assisted by the Brazilian National Health System and the birth weight of their newborns. METHODS: The participants were women assisted at public STD/AIDS clinics of the Municipal Health system of São Paulo. The anthropometric characteristics were evaluated by trained nutritionists and other information was obtained from the medical records. For comparison of the survey data to those of the general population, secondary maternal and pregnancy data were obtained from live birth certificates through the Live Birth Information System. Continuous variables were summarized as mean and standard deviation or as the 25th, 50th and 75th percentiles and minimum and maximum values. The other variables are presented as percentages. Means were compared by the Student's t-test or Kruskal-Wallis test depending on the fulfillment of assumptions, with the decision based on the p value. RESULTS: We found the presence of inadequate maternal nutrition according to triceps skinfold (60.9%). The BMI/gestational age showed the presence of underweight (18.5%) and overweight or obesity (40%). There was no association between disease status (HIV or AIDS) and weight, height, and lean or fat mass. Mean newborn birth weight was lower than the value for the general population without infection or disease. The results of this study indicate the need to develop adapted curves to allow a more accurate nutritional assessment of this population group.

Evolução de pacientes com AIDS pós cART: Evolução clínica e laboratorial de pacientes com AIDS após 48 semanas de tratamento antirretroviral

Combination Antiretroviral Therapy (cART) aims to inhibit viral replication, delay immunodeficiency progression and improve survival in AIDS patients. The objective of this study was to compare two different schemes of cART, based on plasma viral load (VL) and CD4+ T lymphocyte count, during 48 weeks of treatment. For this purpose, 472 medical charts of a Specialized Outpatient Service were reviewed from 1998 to 2005. Out of these, 58 AIDS patients who had received a triple drug scheme as the initial treatment were included in the study and two groups were formed: Group 1 (G1): 47 individuals treated with two nucleoside reverse-transcriptase inhibitors (NRTI) and one non-nucleoside reverse-transcriptase inhibitor; Group 2 (G2): 11 patients treated with two NRTI and one protease inhibitor. In G1 and G2, 53.2% and 81.8% respectively were patients with an AIDS-defining disease. The T CD4+ lymphocyte count increased progressively up until the 24th week of treatment in all patients, while VL became undetectable in 68.1% of G1 and in 63.6% of G2. The study concluded that the evolutions of laboratory tests were similar in the two treatment groups and that both presented a favorable clinical evolution.

Prevalência e fatores associados á verrugas anogenitais em homens portadores de HIV/AIDS atendidos em serviço especializado

Pós-graduação em Doenças Tropicais - FMB

Atividade física e lipodistrofia em portadores de HIV/AIDS submetidos à terapia anti-retroviral

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)