993 resultados para Novas redes de acesso


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The main objective of work is to show procedures to implement intelligent control strategies. This strategies are based on fuzzy scheduling of PID controllers, by using only standard function blocks of this technology. Then, the standardization of Foundation Fieldbus is kept. It was developed an environment to do the necessary tests, it validates the propose. This environment is hybrid, it has a real module (the fieldbus) and a simulated module (the process), although the control signals and measurement are real. Then, it is possible to develop controllers projects. In this work, a fuzzy supervisor was developed to schedule a network of PID controller for a non-linear plant. Analyzing its performance results to the control and regulation problem

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This work aims to investigate the behavior of fractal elements in planar microstrip structures. In particular, microstrip antennas and frequency selective surfaces (FSSs) had changed its conventional elements to fractal shapes. For microstrip antennas, was used as the radiating element of Minkowski fractal. The feeding method used was microstrip line. Some prototypes were built and the analysis revealed the possibility of miniaturization of structures, besides the multiband behavior, provided by the fractal element. In particular, the Minkowski fractal antenna level 3 was used to exploit the multiband feature, enabling simultaneous operation of two commercial tracks (Wi-Fi and WiMAX) regulated by ANATEL. After, we investigated the effect of switches that have been placed on the at the pre-fractal edges of radiating element. For the FSSs, the fractal used to elements of FSSs was Dürer s pentagon. Some prototypes were built and measured. The results showed a multiband behavior of the structure provided by fractal geometry. Then, a parametric analysis allowed the analysis of the variation of periodicity on the electromagnetic behavior of FSS, and its bandwidth and quality factor. For numerical and experimental characterization of the structures discussed was used, respectively, the commercial software Ansoft DesignerTM and a vector network analyzer, Agilent N5230A model

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The use of wireless sensor and actuator networks in industry has been increasing past few years, bringing multiple benefits compared to wired systems, like network flexibility and manageability. Such networks consists of a possibly large number of small and autonomous sensor and actuator devices with wireless communication capabilities. The data collected by sensors are sent directly or through intermediary nodes along the network to a base station called sink node. The data routing in this environment is an essential matter since it is strictly bounded to the energy efficiency, thus the network lifetime. This work investigates the application of a routing technique based on Reinforcement Learning s Q-Learning algorithm to a wireless sensor network by using an NS-2 simulated environment. Several metrics like energy consumption, data packet delivery rates and delays are used to validate de proposal comparing it with another solutions existing in the literature

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New versions of SCTP protocol allow the implementation of handover procedures in the transport layer, as well as the supply of a partially reliable communication service. A communication architecture is proposed herein, integrating SCTP with the session initiation protocol, SIP, besides additional protocols. This architecture is intended to handle voice applications over IP networks with mobility requirements. User localization procedures are specified in the application layer as well, using SIP, as an alternative mean to the mechanisms used by traditional protocols, that support mobility in the network layer. The SDL formal specification language is used to specify the operation of a control module, which coordinates the operation of the system component protocols. This formal specification is intended to prevent ambiguities and inconsistencies in the definition of this module, assisting in the correct implementation of the elements of this architecture

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The Ethernet technology dominates the market of computer local networks. However, it was not been established as technology for industrial automation set, where the requirements demand determinism and real-time performance. Many solutions have been proposed to solve the problem of non-determinism, which are based mainly on TDMA (Time Division Multiple Access), Token Passing and Master-Slave. This work of research carries through measured of performance that allows to compare the behavior of the Ethernet nets when submitted with the transmissions of data on protocols UDP and RAW Ethernet, as well as, on three different types of Ethernet technologies. The objective is to identify to the alternative amongst the protocols and analyzed Ethernet technologies that offer to a more satisfactory support the nets of the industrial automation and distributed real-time application

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A serious problem that affects an oil refinery s processing units is the deposition of solid particles or the fouling on the equipments. These residues are naturally present on the oil or are by-products of chemical reactions during its transport. A fouled heat exchanger loses its capacity to adequately heat the oil, needing to be shut down periodically for cleaning. Previous knowledge of the best period to shut down the exchanger may improve the energetic and production efficiency of the plant. In this work we develop a system to predict the fouling on a heat exchanger from the Potiguar Clara Camarão Refinery, based on data collected in a partnership with Petrobras. Recurrent Neural Networks are used to predict the heat exchanger s flow in future time. This variable is the main indicator of fouling, because its value decreases gradually as the deposits on the tubes reduce their diameter. The prediction could be used to tell when the flow will have decreased under an acceptable value, indicating when the exchanger shutdown for cleaning will be needed

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Complex network analysis is a powerful tool into research of complex systems like brain networks. This work aims to describe the topological changes in neural functional connectivity networks of neocortex and hippocampus during slow-wave sleep (SWS) in animals submited to a novel experience exposure. Slow-wave sleep is an important sleep stage where occurs reverberations of electrical activities patterns of wakeness, playing a fundamental role in memory consolidation. Although its importance there s a lack of studies that characterize the topological dynamical of functional connectivity networks during that sleep stage. There s no studies that describe the topological modifications that novel exposure leads to this networks. We have observed that several topological properties have been modified after novel exposure and this modification remains for a long time. Major part of this changes in topological properties by novel exposure are related to fault tolerance

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Bayesian networks are powerful tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This thesis compare three of most used score metrics. The K-2 algorithm and two pattern benchmarks, ASIA and ALARM, were used to carry out the comparison. Results show that score metrics with hyperparameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures for both metrics (Heckerman-Geiger and modified MDL). Heckerman-Geiger Bayesian score metric works better than MDL with large datasets and MDL works better than Heckerman-Geiger with small datasets. The modified MDL gives similar results to Heckerman-Geiger for large datasets and close results to MDL for small datasets with stronger tendency to select simpler network structures

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This work has as main objective the application of Artificial Neural Networks, ANN, in the resolution of problems of RF /microwaves devices, as for example the prediction of the frequency response of some structures in an interest region. Artificial Neural Networks, are presently a alternative to the current methods of analysis of microwaves structures. Therefore they are capable to learn, and the more important to generalize the acquired knowledge, from any type of available data, keeping the precision of the original technique and adding the low computational cost of the neural models. For this reason, artificial neural networks are being increasily used for modeling microwaves devices. Multilayer Perceptron and Radial Base Functions models are used in this work. The advantages/disadvantages of these models and the referring algorithms of training of each one are described. Microwave planar devices, as Frequency Selective Surfaces and microstrip antennas, are in evidence due the increasing necessities of filtering and separation of eletromagnetic waves and the miniaturization of RF devices. Therefore, it is of fundamental importance the study of the structural parameters of these devices in a fast and accurate way. The presented results, show to the capacities of the neural techniques for modeling both Frequency Selective Surfaces and antennas

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The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed

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One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

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Expanded Bed Adsorption (EBA) is an integrative process that combines concepts of chromatography and fluidization of solids. The many parameters involved and their synergistic effects complicate the optimization of the process. Fortunately, some mathematical tools have been developed in order to guide the investigation of the EBA system. In this work the application of experimental design, phenomenological modeling and artificial neural networks (ANN) in understanding chitosanases adsorption on ion exchange resin Streamline® DEAE have been investigated. The strain Paenibacillus ehimensis NRRL B-23118 was used for chitosanase production. EBA experiments were carried out using a column of 2.6 cm inner diameter with 30.0 cm in height that was coupled to a peristaltic pump. At the bottom of the column there was a distributor of glass beads having a height of 3.0 cm. Assays for residence time distribution (RTD) revelead a high degree of mixing, however, the Richardson-Zaki coefficients showed that the column was on the threshold of stability. Isotherm models fitted the adsorption equilibrium data in the presence of lyotropic salts. The results of experiment design indicated that the ionic strength and superficial velocity are important to the recovery and purity of chitosanases. The molecular mass of the two chitosanases were approximately 23 kDa and 52 kDa as estimated by SDS-PAGE. The phenomenological modeling was aimed to describe the operations in batch and column chromatography. The simulations were performed in Microsoft Visual Studio. The kinetic rate constant model set to kinetic curves efficiently under conditions of initial enzyme activity 0.232, 0.142 e 0.079 UA/mL. The simulated breakthrough curves showed some differences with experimental data, especially regarding the slope. Sensitivity tests of the model on the surface velocity, axial dispersion and initial concentration showed agreement with the literature. The neural network was constructed in MATLAB and Neural Network Toolbox. The cross-validation was used to improve the ability of generalization. The parameters of ANN were improved to obtain the settings 6-6 (enzyme activity) and 9-6 (total protein), as well as tansig transfer function and Levenberg-Marquardt training algorithm. The neural Carlos Eduardo de Araújo Padilha dezembro/2013 9 networks simulations, including all the steps of cycle, showed good agreement with experimental data, with a correlation coefficient of approximately 0.974. The effects of input variables on profiles of the stages of loading, washing and elution were consistent with the literature

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The diesel combustion form sulfur oxides that can be discharged into the atmosphere as particulates and primary pollutants, SO2and SO3, causing great damage to the environment and to human health. These products can be transformed into acids in the combustion chamber, causing damage to the engines. The worldwide concern with a clean and healthy environment has led to more restrictive laws and regulations regulating the emission levels of pollutants in the air, establishing sulfur levels increasingly low on fuels. The conventional methods for sulfur removal from diesel are expensive and do not produce a zero-level sulfur fuel. This work aims to develop new methods of removing sulfur from commercial diesel using surfactants and microemulsion systems. Its main purpose is to create new technologies and add economic viability to the process. First, a preliminary study using as extracting agent a Winsor I microemulsion system with dodecyl ammonium chloride (DDACl) and nonyl phenol ethoxylated (RNX95) as surfactant was performed to choose the surfactant. The RNX95 was chosen to be used as surfactant in microemulsioned systems for adsorbent surface modification and as an extracting agent in liquid-liquid extraction. Vermiculite was evaluated as adsorbent. The microemulsion systems applied for vermiculite surface modification were composed by RNX95 (surfactant), n-butanol (cosurfactant), n-hexane (oil phase), and different aqueous phases, including: distilled water (aqueous phase),20ppm CaCl2solution, and 1500ppm CaCl2solution. Batch and column adsorption tests were carried out to estimate the ability of vermiculite to adsorb sulfur from diesel. It was used in the experiments a commercial diesel fuel with 1,233ppm initial sulfur concentration. The batch experiments were performed according to a factorial design (23). Two experimental sets were accomplished: the first one applying 1:2 vermiculite to diesel ratio and the second one using 1:5 vermiculite to diesel ratio. It was evaluated the effects of temperature (25°C and 60°C), concentration of CaCl2in the aqueous phase (20ppm and 1500ppm), and vermiculite granule size (65 and 100 mesh). The experimental response was the ability of vermiculite to adsorb sulfur. The best results for both 1:5 and 1:2 ratios were obtained using 60°C, 1500ppm CaCl2solution, and 65 mesh. The best adsorption capacities for 1:5 ratio and for 1:2 ratio were 4.24 mg sulfur/g adsorbent and 2.87 mg sulfur/g adsorbent, respectively. It was verified that the most significant factor was the concentration of the CaCl2 solution. Liquid-liquid extraction experiments were performed in two and six steps using the same surfactant to diesel ratio. It was obtained 46.8% sulfur removal in two-step experiment and 73.15% in six-step one. An alternative study, for comparison purposes, was made using bentonite and diatomite asadsorbents. The batch experiments were done using microemulsion systems with the same aqueous phases evaluated in vermiculite study and also 20ppm and 1500 ppm BaCl2 solutions. For bentonite, the best adsorption capacity was 7.53mg sulfur/g adsorbent with distilled water as aqueous phase of the microemulsion system and for diatomite the best result was 17.04 mg sulfur/g adsorbent using a 20ppm CaCl2solution. The accomplishment of this study allowed us to conclude that, among the alternatives tested, the adsorption process using adsorbents modified by microemulsion systems was considered the best process for sulfur removal from diesel fuel. The optimization and scale upof the process constitutes a viable alternative to achieve the needs of the market

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La disertación, desarrollada en el Programa de PostGraduación en Enseñanza de las Ciencias Naturales y de la Matemática de la UFRN, estudia las necesidades formativas de licenciandos en Química sobre el uso de las nuevas tecnologías de la información y de las comunicaciones (NTIC), en especial, las relacionadas con la utilización de programas computacionales para la enseñanza de la química. En la actual sociedad del conocimiento, se torna imperativo la eclosión de nuevas formas de aprender y de enseñar, que requieren de nuevas concepciones del trabajo pedagógico. En ese sentido, se exige de los profesores el desarrollo de nuevas habilidades y competencias. El presente trabajo está comprometido con la búsqueda de elementos que puedan nortear los procesos formativos de profesores de química con el objetivo de contribuir con una mejor preparación de la formación inicial, tomando en cuenta sus necesidades de formación. Fue utilizado el cuestionario como instrumento de investigación para diagnosticar y caracterizar las necesidades fomativas, buscando establecer correlaciones entre diferentes variables que cacarterizan el estudio, con el fin de establecer semenazas y discrepancias entre las habilidades docentes en estudio y las necesidades formativas. Los analises de los datos tomo elementos de la estadistica descriptivo e inferencial, con analises multivariados, lo que posibilitó identificar las necesidades formativas. Los resultados muestran ue de forma general los licenciandos evaluan como de bajo, el grado de desarrollo de las habilidades para enseñar usando las NTIC, así como manifiestan sentir necesidades formativas en todas las habilidades referentes a esa esfera del trabajo docente

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This work discuss about the transformation of public space, based on the recent challenges imposed by communication practices that are renewed and recopying of the sociocultural contexts of everyday life. The study presents theoretical and empirical reports of regional political blogs. In this issue, it looks for understand the political participation in the Internet space, examining the reconfigurations that accompany social relations and new forms of interaction that are merged in the media scene. The ambience of the study limits comments of readers in two political blogs in Rio Grande do Norte, Território Livre, and Thaisa Galvão. The observation concerns about the democratic participation of citizens in matters of collective interest, during the 2010 election. The analysis update the debate on democratic discussion and conversation everyday, trying to grasp changes in social practices in virtual platforms. From this perspective, the work restores some conceptual notions that involve the public places, identifying the changes that appear in the virtual and traditional spheres, with the emergence of new places of conversations, from the Internet usage. Are also compared to similarities and differences between the two elements of the analysis. It is possible, therefore, the communication process of the two discursive spaces with ideas from the public sphere, trying to analyze the duality between public, private, and political participation in these virtual places