974 resultados para Dados Espaciais


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The objective of this thesis is proposes a method for a mobile robot to build a hybrid map of an indoor, semi-structured environment. The topological part of this map deals with spatial relationships among rooms and corridors. It is a topology-based map, where the edges of the graph are rooms or corridors, and each link between two distinct edges represents a door. The metric part of the map consists in a set of parameters. These parameters describe a geometric figure which adapts to the free space of the local environment. This figure is calculated by a set of points which sample the boundaries of the local free space. These points are obtained with range sensors and with knowledge about the robot s pose. A method based on generalized Hough transform is applied to this set of points in order to obtain the geomtric figure. The building of the hybrid map is an incremental procedure. It is accomplished while the robot explores the environment. Each room is associated with a metric local map and, consequently, with an edge of the topo-logical map. During the mapping procedure, the robot may use recent metric information of the environment to improve its global or relative pose

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This graduate thesis proposes a model to asynchronously replicate heterogeneous databases. This model singularly combines -in a systematic way and in a single project -different concepts, techniques and paradigms related to the areas of database replication and management of heterogeneous databases. One of the main advantages of the replication is to allow applications to continue to process information, during time intervals when they are off the network and to trigger the database synchronization, as soon as the network connection is reestablished. Therefore, the model introduces a communication and update protocol that takes in consideration the environment of asynchronous characteristics used. As part of the work, a tool was developed in Java language, based on the model s premises in order to process, test, simulate and validate the proposed model

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In recent decades, changes have been occurring in the telecommunications industry, allied to competition driven by the policies of privatization and concessions, have fomented the world market irrefutably causing the emergence of a new reality. The reflections in Brazil have become evident due to the appearance of significant growth rates, getting in 2012 to provide a net operating income of 128 billion dollars, placing the country among the five major powers in the world in mobile communications. In this context, an issue of increasing importance to the financial health of companies is their ability to retain their customers, as well as turn them into loyal customers. The appearance of infidelity from customer operators has been generating monthly rates shutdowns about two to four percent per month accounting for business management one of its biggest challenges, since capturing a new customer has meant an expenditure greater than five times to retention. For this purpose, models have been developed by means of structural equation modeling to identify the relationships between the various determinants of customer loyalty in the context of services. The original contribution of this thesis is to develop a model for loyalty from the identification of relationships between determinants of satisfaction (latent variables) and the inclusion of attributes that determine the perceptions of service quality for the mobile communications industry, such as quality, satisfaction, value, trust, expectation and loyalty. It is a qualitative research which will be conducted with customers of operators through simple random sampling technique, using structured questionnaires. As a result, the proposed model and statistical evaluations should enable operators to conclude that customer loyalty is directly influenced by technical and operational quality of the services offered, as well as provide a satisfaction index for the mobile communication segment

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This work presents simulation results of an identification platform compatible with the INPE Brazilian Data Collection System, modeled with SystemC-AMS. SystemC-AMS that is a library of C++ classes dedicated to the simulation of heterogeneous systems, offering a powerful resource to describe models in digital, analog and RF domains, as well as mechanical and optic. The designed model was divided in four parts. The first block takes into account the satellite s orbit, necessary to correctly model the propagation channel, including Doppler effect, attenuation and thermal noise. The identification block detects the satellite presence. It is composed by low noise amplifier, band pass filter, power detector and logic comparator. The controller block is responsible for enabling the RF transmitter when the presence of the satellite is detected. The controller was modeled as a Petri net, due to the asynchronous nature of the system. The fourth block is the RF transmitter unit, which performs the modulation of the information in BPSK ±60o. This block is composed by oscillator, mixer, adder and amplifier. The whole system was simulated simultaneously. The results are being used to specify system components and to elaborate testbenchs for design verification

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We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

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Global Positioning System, or simply GPS, it is a radionavigation system developed by United States for military applications, but it becames very useful for civilian using. In the last decades Brazil has developed sounding rockets and today many projects to build micro and nanosatellites has appeared. This kind of vehicles named spacecrafts or high dynamic vehicles, can use GPS for its autonome location and trajectories controls. Despite of a huge number of GPS receivers available for civilian applications, they cannot used in high dynamic vehicles due environmental issues (vibrations, temperatures, etc.) or imposed dynamic working limits. Only a few nations have the technology to build GPS receivers for spacecrafts or high dynamic vehicles is available and they imposes rules who difficult the access to this receivers. This project intends to build a GPS receiver, to install them in a payload of a sounding rocket and data collecting to verify its correct operation when at the flight conditions. The inner software to this receiver was available in source code and it was tested in a software development platform named GPS Architect. Many organizations cooperated to support this project: AEB, UFRN, IAE, INPE e CLBI. After many phases: defining working conditions, choice and searching electronic, the making of the printed boards, assembling and assembling tests; the receiver was installed in a VS30 sounding rocket launched at Centro de Lançamento da Barreira do Inferno in Natal/RN. Despite of the fact the locations data from the receiver were collected only the first 70 seconds of flight, this data confirms the correct operation of the receiver by the comparison between its positioning data and the the trajectory data from CLBI s tracking radar named ADOUR

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In this work, we propose a Geographical Information System that can be used as a tool for the treatment and study of problems related with environmental and city management issues. It is based on the Scalable Vector Graphics (SVG) standard for Web development of graphics. The project uses the concept of remate and real-time mar creation by database access through instructions executed by browsers on the Internet. As a way of proving the system effectiveness, we present two study cases;.the first on a region named Maracajaú Coral Reefs, located in Rio Grande do Norte coast, and the second in the Switzerland Northeast in which we intended to promote the substitution of MapServer by the system proposed here. We also show some results that demonstrate the larger geographical data capability achieved by the use of the standardized codes and open source tools, such as Extensible Markup Language (XML), Document Object Model (DOM), script languages ECMAScript/ JavaScript, Hypertext Preprocessor (PHP) and PostgreSQL and its extension, PostGIS

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O presente trabalho teve por objetivo avaliar quantitativamente as informações obtidas por diferentes tipos de fotografias. Os estudos basearam-se em fotografias pancromáticas, coloridas e infravermelhas coloridas de uma área teste localizada no município de Campinas - SP. A cobertura fotográfica denominada Missão 96 resultou da colaboração científica entre INPE - Instituto de Pesquisas Espaciais, NASA - National Aeronautics and Space Administration e IAC - Instituto Agronômico do Estado de São Paulo. A rede de drenagem foi o elemento de comparação tendo sido estudados dois parâmetros: número de segmentos de rios e comprimentos de rios. A rede de drenagem foi estudada em monoscopia e em estereoscopia, onde as medições foram efetuadas em amostras circulares de 10 km² (parcelas), sendo que o delineamento experimental foi o de parcelas inteiramente casualizadas. Os dados obtidos foram utilizados para avaliar a eficiência de cada tipo de fotografia, para; os parâmetros considerados. Para as condições estudadas, obteve-se as seguintes conclusões principais: a) a fotografia infravermelha forneceu maior número de informações comparativamente às fotografias pancromáticas e coloridas, as quais ofereceram resultados semelhantes; b) os resultados obtidos pela análise monoscópica da fotografia infravermelha foram semelhantes aos resultados obtidos pela análise estereoscópica da fotografia pancromática, o que pode facilitar bastante o processo fotointerpretativo.

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Digital signal processing (DSP) aims to extract specific information from digital signals. Digital signals are, by definition, physical quantities represented by a sequence of discrete values and from these sequences it is possible to extract and analyze the desired information. The unevenly sampled data can not be properly analyzed using standard techniques of digital signal processing. This work aimed to adapt a technique of DSP, the multiresolution analysis, to analyze unevenly smapled data, to aid the studies in the CoRoT laboratory at UFRN. The process is based on re-indexing the wavelet transform to handle unevenly sampled data properly. The was efective presenting satisfactory results

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Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

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The last years have presented an increase in the acceptance and adoption of the parallel processing, as much for scientific computation of high performance as for applications of general intention. This acceptance has been favored mainly for the development of environments with massive parallel processing (MPP - Massively Parallel Processing) and of the distributed computation. A common point between distributed systems and MPPs architectures is the notion of message exchange, that allows the communication between processes. An environment of message exchange consists basically of a communication library that, acting as an extension of the programming languages that allow to the elaboration of applications parallel, such as C, C++ and Fortran. In the development of applications parallel, a basic aspect is on to the analysis of performance of the same ones. Several can be the metric ones used in this analysis: time of execution, efficiency in the use of the processing elements, scalability of the application with respect to the increase in the number of processors or to the increase of the instance of the treat problem. The establishment of models or mechanisms that allow this analysis can be a task sufficiently complicated considering parameters and involved degrees of freedom in the implementation of the parallel application. An joined alternative has been the use of collection tools and visualization of performance data, that allow the user to identify to points of strangulation and sources of inefficiency in an application. For an efficient visualization one becomes necessary to identify and to collect given relative to the execution of the application, stage this called instrumentation. In this work it is presented, initially, a study of the main techniques used in the collection of the performance data, and after that a detailed analysis of the main available tools is made that can be used in architectures parallel of the type to cluster Beowulf with Linux on X86 platform being used libraries of communication based in applications MPI - Message Passing Interface, such as LAM and MPICH. This analysis is validated on applications parallel bars that deal with the problems of the training of neural nets of the type perceptrons using retro-propagation. The gotten conclusions show to the potentiality and easinesses of the analyzed tools.

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Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The control of industrial processes has become increasingly complex due to variety of factory devices, quality requirement and market competition. Such complexity requires a large amount of data to be treated by the three levels of process control: field devices, control systems and management softwares. To use data effectively in each one of these levels is extremely important to industry. Many of today s industrial computer systems consist of distributed software systems written in a wide variety of programming languages and developed for specific platforms, so, even more companies apply a significant investment to maintain or even re-write their systems for different platforms. Furthermore, it is rare that a software system works in complete isolation. In industrial automation is common that, software had to interact with other systems on different machines and even written in different languages. Thus, interoperability is not just a long-term challenge, but also a current context requirement of industrial software production. This work aims to propose a middleware solution for communication over web service and presents an user case applying the solution developed to an integrated system for industrial data capture , allowing such data to be available simplified and platformindependent across the network

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Low voltage solar panels increase the reliability of solar panels due to reduction of in series associations the configurations of photovoltaic cells. The low voltage generation requires DCDC converters devices with high efficiency, enabling raise and regulate the output voltage. This study analyzes the performance of a photovoltaic panel of Solarex, MSX model 77, configured to generate an open circuit voltage of 10.5 V, with load voltage of 8.5 V, with short circuit current of 9 A and a power of 77 W. The solar panel was assembled in the isolated photovoltaic system configuration, with and without energy storage as an interface with a DCDC converter, Booster topology. The converter was designed and fabricated using SMD (Surface Mounted Devices) technology IC (integrated circuit) that regulates its output voltage at 14.2 V, with an efficiency of 87% and providing the load a maximum power of 20.88 W. The system was installed and instrumented for measurement and acquisition of the following data: luminosities, average global radiation (data of INPE Instituto Nacional de Pesquisas Espaciais), solar panel and environment temperatures, solar panel and DC-DC converter output voltages, panel, inverter, and battery charge output currents. The photovoltaic system was initially tested in the laboratory (simulating its functioning in ideal conditions of operation) and then subjected to testing in real field conditions. The panel inclination angle was set at 5.5°, consistent with the latitude of Natal city. Factors such as climatic conditions (simultaneous variations of temperature, solar luminosities and ra diation on the panel), values of load resistance, lower limit of the maximum power required by the load (20.88 W) were predominant factors that panel does not operate with energy efficiency levels greater than 5 to 6%. The average converter efficiency designed in the field test reached 95%