772 resultados para Engenharia de Telecomunicações e Redes


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Wireless sensor networks are reality nowadays. The growing necessity of connectivity between existing industrial plant equipments pushes the research and development of several technologies. The IEEE 802.15.4 LR-WPAN comes as a low-cost and powersaving viable solution, which are important concerns while making decisions on remote sensoring projects. This study intends to propose a wireless communication system which makes possible the monitoring of analogic and/or digital variables (i. e., the pressure studied) involved on the artificial methods for oil and gas lifting. The main issues are: To develop a software based on SMAC Standard in order to create a wireless network to monitoring analogic and/or digital variables; To evaluate the communication link based on the number of lost packets tested in different environments (indoor and outdoor) and To propose an instrumentation system consisting of wireless devices

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Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

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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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This work describes the development of a nonlinear control strategy for an electro-hydraulic actuated system. The system to be controlled is represented by a third order ordinary differential equation subject to a dead-zone input. The control strategy is based on a nonlinear control scheme, combined with an artificial intelligence algorithm, namely, the method of feedback linearization and an artificial neural network. It is shown that, when such a hard nonlinearity and modeling inaccuracies are considered, the nonlinear technique alone is not enough to ensure a good performance of the controller. Therefore, a compensation strategy based on artificial neural networks, which have been notoriously used in systems that require the simulation of the process of human inference, is used. The multilayer perceptron network and the radial basis functions network as well are adopted and mathematically implemented within the control law. On this basis, the compensation ability considering both networks is compared. Furthermore, the application of new intelligent control strategies for nonlinear and uncertain mechanical systems are proposed, showing that the combination of a nonlinear control methodology and artificial neural networks improves the overall control system performance. Numerical results are presented to demonstrate the efficacy of the proposed control system

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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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In Brazil, between the late nineteenth and early decades of the twentieth, polytechnic engineers assumed an important role in discussing the establishment of a modern country. The problem of drought in northeastern Brazil gave the professionals performance, within an interventional process more mounts, the conception plans and measures for the purposeful integration of the territory afflicted. With the foundation of Inspetoria de Obras Contra as Secas (IOCS), in 1909, the actions to combat drought and would be institutionalized, them, studies performed out by technical and scientific committees would be systematically applied in the Brazilian Northeast. So, This work was central objective understand the historical process inplantation of a whole infrastructure of modern character by professional technical and their consequences within the Northeast Geographic space, in specific, in the municipality of Acari in the State of Rio Grande do Norte, in the first half of the twentieth century. The politics of the government, through technical education and scientific engineers polytechnics, would emphasize, during the twentieth century, the building of dams, and irrigation canals, wells, railways, highways, between other elements, that would soon transform the physical space-northeast, specifically, the territory acariense. These works began to contribute to the setting of man backcountry their land, promote the regular practice of agriculture even in periods of drought and, the integration, especially, economic of territory acariense the other producing regions of Rio Grande do Norte and the Northeast as well as promoting the modification of the landscape of the world backcountry. These actions functioned as elements of modernity and progress that transformed the space by favoring by favoring the formation of urban networks (urban) in this space

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The field of Wireless Sensor and Actuator Networks (WSAN) is fast increasing and has attracted the interest of both the research community and the industry because of several factors, such as the applicability of such networks in different application domains (aviation, civil engineering, medicine, and others). Moreover, advances in wireless communication and the reduction of hardware components size also contributed for a fast spread of these networks. However, there are still several challenges and open issues that need to be tackled in order to achieve the full potential of WSAN usage. The development of WSAN systems is one of the most relevant of these challenges considering the number of variables involved in this process. Currently, a broad range of WSAN platforms and low level programming languages are available to build WSAN systems. Thus, developers need to deal with details of different sensor platforms and low-level programming abstractions of sensor operational systems on one hand, and they also need to have specific (high level) knowledge about the distinct application domains, on the other hand. Therefore, in order to decouple the handling of these two different levels of knowledge, making easier the development process of WSAN systems, we propose LWiSSy (Domain Language for Wireless Sensor and Actuator Networks Systems), a domain specific language (DSL) for WSAN. The use of DSLs raises the abstraction level during the programming of systems and modularizes the system building in several steps. Thus, LWiSSy allows the domain experts to directly contribute in the development of WSANs without having knowledge on low level sensor platforms, and network experts to program sensor nodes to meet application requirements without having specific knowledge on the application domain. Additionally, LWiSSy enables the system decomposition in different levels of abstraction according to structural and behavioral features and granularities (network, node group and single node level programming)

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Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.

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O surgimento de novas tecnologias e serviços vem impondo mudanças substanciais ao tradicional sistema de telecomunicações. Múltiplas possibilidades de evolução do sistema fazem da etapa de planejamento um procedimento não só desejável como necessário, principalmente num ambiente de competitividade. A utilização de metodologias abrangentes e flexíveis que possam auxiliar no processo de decisão, fundadas em modelos de otimização, parece um caminho inevitável. Este artigo propõe um modelo de programação linear inteiro misto para ajudar no planejamento estratégico de sistemas de telecomunicações, e em particular da rede de acesso. Os principais componentes de custo e receita são identificados e o modelo é desenvolvido para determinar a configuração da rede (serviços, tecnologias, etc) que maximize a receita esperada pelo operador do sistema. O conceito de números fuzzy é adotado para avaliar o risco técnico-econômico em situações de imprecisão nos dados de demanda. Resultados de experimentos computacionais são apresentados e discutidos.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Elétrica - FEIS

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)