150 resultados para Engenharia de Telecomunicações e Redes
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This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process
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On this paper, it is made a comparative analysis among a controller fuzzy coupled to a PID neural adjusted by an AGwith several traditional control techniques, all of them applied in a system of tanks (I model of 2nd order non lineal). With the objective of making possible the techniques involved in the comparative analysis and to validate the control to be compared, simulations were accomplished of some control techniques (conventional PID adjusted by GA, Neural PID (PIDN) adjusted by GA, Fuzzy PI, two Fuzzy attached to a PID Neural adjusted by GA and Fuzzy MISO (3 inputs) attached to a PIDN adjusted by GA) to have some comparative effects with the considered controller. After doing, all the tests, some control structures were elected from all the tested techniques on the simulating stage (conventional PID adjusted by GA, Fuzzy PI, two Fuzzy attached to a PIDN adjusted by GA and Fuzzy MISO (3 inputs) attached to a PIDN adjusted by GA), to be implemented at the real system of tanks. These two kinds of operation, both the simulated and the real, were very important to achieve a solid basement in order to establish the comparisons and the possible validations show by the results
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The increasing of the number of attacks in the computer networks has been treated with the increment of the resources that are applied directly in the active routers equip-ments of these networks. In this context, the firewalls had been consolidated as essential elements in the input and output control process of packets in a network. With the advent of intrusion detectors systems (IDS), efforts have been done in the direction to incorporate packets filtering based in standards of traditional firewalls. This integration incorporates the IDS functions (as filtering based on signatures, until then a passive element) with the already existing functions in firewall. In opposite of the efficiency due this incorporation in the blockage of signature known attacks, the filtering in the application level provokes a natural retard in the analyzed packets, and it can reduce the machine performance to filter the others packets because of machine resources demand by this level of filtering. This work presents models of treatment for this problem based in the packets re-routing for analysis by a sub-network with specific filterings. The suggestion of implementa- tion of this model aims reducing the performance problem and opening a space for the consolidation of scenes where others not conventional filtering solutions (spam blockage, P2P traffic control/blockage, etc.) can be inserted in the filtering sub-network, without inplying in overload of the main firewall in a corporative network
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The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm
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The greater part of monitoring onshore Oil and Gas environment currently are based on wireless solutions. However, these solutions have a technological configuration that are out-of-date, mainly because analog radios and inefficient communication topologies are used. On the other hand, solutions based in digital radios can provide more efficient solutions related to energy consumption, security and fault tolerance. Thus, this paper evaluated if the Wireless Sensor Network, communication technology based on digital radios, are adequate to monitoring Oil and Gas onshore wells. Percent of packets transmitted with successful, energy consumption, communication delay and routing techniques applied to a mesh topology will be used as metrics to validate the proposal in the different routing techniques through network simulation tool NS-2
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The characteristic properties of the fractal geometry have shown to be very useful for the construction of filters, frequency selective surfaces, synchronized circuits and antennas, enabling optimized solutions in many different commercial uses at microwaves frequency band. The fractal geometry is included in the technology of the microwave communication systems due to some interesting properties to the fabrication of compact devices, with higher performance in terms of bandwidth, as well as multiband behavior. This work describes the design, fabrication and measurement procedures for the Koch quasi-fractal monopoles, with 1 and 2 iteration levels, in order to investigate the bandwidth behavior of planar antennas, from the use of quasi-fractal elements printed on their rectangular patches. The electromagnetic effect produced by the variation of the fractal iterations and the miniaturization of the structures is analyzed. Moreover, a parametric study is performed to verify the bandwidth behavior, not only at the return loss but also in terms of SWR. Experimental results were obtained through the accomplishment of measurements with the aid of a vetorial network analyzer and compared to simulations performed using the Ansoft HFSS software. Finally, some proposals for future works are presented
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The objective of the present work is develop a model to simulate electrical energy networks in transient and stead states, using the software ATP (Alternative Transient Program), able to be a way to join two distinct themes, present in classical methodology planning networks: short circuit analysis and load flow theory. Beyond that, using a tool for relay simulation, this paper intend to use the new developed model to investigate the influence of transient phenomenon in operation of protection relays, and calibrate the enterprise's protections relays. For testing the model, some relays, actually, installed at COSERN were used
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In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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In this dissertation new models of propagation path loss predictions are proposed by from techniques of optimization recent and measures of power levels for the urban and suburban areas of Natal, city of Brazilian northeast. These new proposed models are: (i) a statistical model that was implemented based in the addition of second-order statistics for the power and the altimetry of the relief in model of linear losses; (ii) a artificial neural networks model used the training of the algorithm backpropagation, in order to get the equation of propagation losses; (iii) a model based on the technique of the random walker, that considers the random of the absorption and the chaos of the environment and than its unknown parameters for the equation of propagation losses are determined through of a neural network. The digitalization of the relief for the urban and suburban areas of Natal were carried through of the development of specific computational programs and had been used available maps in the Statistics and Geography Brazilian Institute. The validations of the proposed propagation models had been carried through comparisons with measures and propagation classic models, and numerical good agreements were observed. These new considered models could be applied to any urban and suburban scenes with characteristic similar architectural to the city of Natal
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This work proposes the development of an intelligent system for analysis of digital mammograms, capable to detect and to classify masses and microcalcifications. The digital mammograms will be pre-processed through techniques of digital processing of images with the purpose of adapting the image to the detection system and automatic classification of the existent calcifications in the suckles. The model adopted for the detection and classification of the mammograms uses the neural network of Kohonen by the algorithm Self Organization Map - SOM. The algorithm of Vector quantization, Kmeans it is also used with the same purpose of the SOM. An analysis of the performance of the two algorithms in the automatic classification of digital mammograms is developed. The developed system will aid the radiologist in the diagnosis and accompaniment of the development of abnormalities
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abstract
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The main purpose of this dissertation, consists of the study and analysis of the PBG (Photonic Band Gap )..tecnology incorporated in optical fiber structures. So, we'l1 present a complete PBG structure theory, and folowing this, we'l1 present also a chapter for convencional optical fiber, due to the need to construct the base theory of them, and latter a more complete work about photonic crystal fiber. Finaly, we'l1 show the results of the signals , dispersion, and obtained curves under the right dimensions according to the required signals, for convencional optical and photonic crystal fiber. Knowing that PBG crystals with low losses act as perfect mirrors for forbidden frequences and knowing that the persence of structures of PBG as substrates, brings some desirable characteristics such as spontaneous emition supression and superficial waves. We' 11 show according to these characteristics its applications in telecomunication. Therefore, the enphasis of this work is to show that the optical fibers are the only practible thing to integrate the enormous quantity of data and video at intemet' s market, developing, manipulating, changing, and multiplexing the optical fibers chanels in an area where we expect that the photonic crystals has an important hole, since the photonic crystals can be projected and made to avoid losses in the bands of certain wavelength which permits the increase in efficiency ofthe optical components projected with crystals. A sequence of this work would be the utilisation of the PBG structures in the new system of optical network without fiber developed by Bell laboratories of the lucent tecnology, last year using light rays for transmiting information through the air. The new system of optical networks without fiber will permit sending the data of 15 cd-rooms in less then one second, what represents 65 times more information than those transmitted through the actual radio frequences
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ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error
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In the two last decades of the past century, following the consolidation of the Internet as the world-wide computer network, applications generating more robust data flows started to appear. The increasing use of videoconferencing stimulated the creation of a new form of point-to-multipoint transmission called IP Multicast. All companies working in the area of software and the hardware development for network videoconferencing have adjusted their products as well as developed new solutionsfor the use of multicast. However the configuration of such different solutions is not easy done, moreover when changes in the operational system are also requirede. Besides, the existing free tools have limited functions, and the current comercial solutions are heavily dependent on specific platforms. Along with the maturity of IP Multicast technology and with its inclusion in all the current operational systems, the object-oriented programming languages had developed classes able to handle multicast traflic. So, with the help of Java APIs for network, data bases and hipertext, it became possible to the develop an Integrated Environment able to handle multicast traffic, which is the major objective of this work. This document describes the implementation of the above mentioned environment, which provides many functions to use and manage multicast traffic, functions which existed only in a limited way and just in few tools, normally the comercial ones. This environment is useful to different kinds of users, so that it can be used by common users, who want to join multimedia Internet sessions, as well as more advenced users such engineers and network administrators who may need to monitor and handle multicast traffic