849 resultados para Inteligência artificial - Engenharia de Aplicações
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This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables
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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 using of supervision systems has become more and more essential in accessing, managing and obtaining data of industrial processes, because of constant and frequent developments in industrial automation. These supervisory systems (SCADA) have been widely used in many industrial environments to store process data and to control the processes in accordance with some adopted strategy. The SCADA s control hardware is the set of equipments that execute this work. The SCADA s supervision software accesses process data through the control hardware and shows them to the users. Currently, many industrial systems adopt supervision softwares developed by the same manufacturer of the control hardware. Usually, these softwares cannot be used with other equipments made by distinct manufacturers. This work proposes an approach for developing supervisory systems able to access process information through different control hardwares. An architecture for supervisory systems is first defined, in order to guarantee efficiency in communication and data exchange. Then, the architecture is applied in a supervisory system to monitor oil wells that use distinct control hardwares. The implementation was modeled and verified by using the formal method of the Petri networks. Finally, experimental results are presented to demonstrate the applicability of the proposed solution
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Artificial neural networks are usually applied to solve complex problems. In problems with more complexity, by increasing the number of layers and neurons, it is possible to achieve greater functional efficiency. Nevertheless, this leads to a greater computational effort. The response time is an important factor in the decision to use neural networks in some systems. Many argue that the computational cost is higher in the training period. However, this phase is held only once. Once the network trained, it is necessary to use the existing computational resources efficiently. In the multicore era, the problem boils down to efficient use of all available processing cores. However, it is necessary to consider the overhead of parallel computing. In this sense, this paper proposes a modular structure that proved to be more suitable for parallel implementations. It is proposed to parallelize the feedforward process of an RNA-type MLP, implemented with OpenMP on a shared memory computer architecture. The research consistes on testing and analizing execution times. Speedup, efficiency and parallel scalability are analyzed. In the proposed approach, by reducing the number of connections between remote neurons, the response time of the network decreases and, consequently, so does the total execution time. The time required for communication and synchronization is directly linked to the number of remote neurons in the network, and so it is necessary to investigate which one is the best distribution of remote connections
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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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A modelagem de processos industriais tem auxiliado na produção e minimização de custos, permitindo a previsão dos comportamentos futuros do sistema, supervisão de processos e projeto de controladores. Ao observar os benefícios proporcionados pela modelagem, objetiva-se primeiramente, nesta dissertação, apresentar uma metodologia de identificação de modelos não-lineares com estrutura NARX, a partir da implementação de algoritmos combinados de detecção de estrutura e estimação de parâmetros. Inicialmente, será ressaltada a importância da identificação de sistemas na otimização de processos industriais, especificamente a escolha do modelo para representar adequadamente as dinâmicas do sistema. Em seguida, será apresentada uma breve revisão das etapas que compõem a identificação de sistemas. Na sequência, serão apresentados os métodos fundamentais para detecção de estrutura (Modificado Gram- Schmidt) e estimação de parâmetros (Método dos Mínimos Quadrados e Método dos Mínimos Quadrados Estendido) de modelos. No trabalho será também realizada, através dos algoritmos implementados, a identificação de dois processos industriais distintos representados por uma planta de nível didática, que possibilita o controle de nível e vazão, e uma planta de processamento primário de petróleo simulada, que tem como objetivo representar um tratamento primário do petróleo que ocorre em plataformas petrolíferas. A dissertação é finalizada com uma avaliação dos desempenhos dos modelos obtidos, quando comparados com o sistema. A partir desta avaliação, será possível observar se os modelos identificados são capazes de representar as características estáticas e dinâmicas dos sistemas apresentados nesta dissertação
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Quadrotors aircraft are composed by four propellers mounted on four engines on a cross or x disposition, and, in this structure, the engines on the same arm spin in the same direction and the other arm in the opposite direction. By rotating each helix generates vertical upward thrust. The control is done by varying the rotational speed of each motor. Among the advantages of this type of vehicle can cite the mechanical simplicity of construction, the high degree of maneuverability and the ability to have vertical takeoffs and landings. The modeling and control of quadrirrotores have been a challenge due to problems such as nonlinearity and coupling between variables. Several strategies have been developed to control this type of vehicle, from the classical control to modern. There are air surveillance applications where a camera is fixed on the vehicle to point forward, where it is desired that the quadrotor moves at a fixed altitude toward the target also pointing forward, which imposes an artificial constraint motion, because it is not desired that it moves laterally, but only forwards or backwards and around its axes . This restriction is similar to the naturally existing on robots powered by wheels with differential drive, which also can not move laterally, due to the friction of the wheels. Therefore, a position control strategy similar to that used in this type of robot could be adapted for aerial robots like quadrotor. This dissertation presents and discusses some strategies for the control of position and orientation of quadrotors found in the literature and proposes a strategy based on dynamic control of mobile robots with differential drive, called the variable reference control. The validity of the proposed strategy is demonstrated through computer simulations
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Thermal insulation is used to protect the heated or cooled surfaces by the low thermal conductivity materials. The rigid ricin polyurethane foams (PURM) are used for thermal insulation and depend on the type and concentration of blowing agent. Obtaining PURM occurs by the use of polyol, silicone, catalyst and blowing agent are pre -mixed, reacting with the isocyanate. The glass is reusable, returnable and recyclable heat insulating material, whose time of heat dissipation determines the degree of relaxation of its structure; and viscosity determines the conditions for fusion, operating temperatures, annealing, etc. The production of PURM composites with waste glass powder (PV) represents economical and renewable actions of manufacturing of thermal insulating materials. Based on these aspects, the study aimed to produce and characterize the PURM composites with PV, whose the mass percentages were 5, 10, 20, 30, 40 and 50 wt%. PURM was obtained commercially, while the PV was recycled from the tailings of the stoning process of a glassmaking; when the refining process was applied to obtain micrometer particles. The PURM + PV composites were studied taking into account the standard sample of pure PURM and the influence of the percentage of PV in this PURM matrix. The results of the chemical, physical and morphological characterization were discussed taking into account the difference in the microstructural morphology of the PURM+PV composites and the pure PURM, as well the results of the physicochemical, mechanical e thermophysical tests by values obtained of density, hardness, compressive strength, specific heat, thermal conductivity and diffusivity. In general, the structure of pure PURM showed large, elongated and regular pores, while PURM+PV composites showed irregular, small and rounded pores with shapeless cells. This may have contributed to reducing their mechanical strength, especially for PURM - PV50. The hardness and density were found to have a proportional relationship with the PV content on PURM matrix. The specific heat, thermal diffusivity and thermal conductivity showed proportional relationship to each other. So, this has been realized that the increasing the PV content on PURM matrix resulted in the rise of diffusivity and thermal conductivity and the decrease of the specific heat. However, the values obtained by the PURM composites were similar the values of pure PURM, mainly the PURM-PV5 and PURM-PV10. Therefore, these composites can be applied like thermal insulator; furthermore, their use could reduce the production costs and to preserve the environment
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Research for better performance materials in biomedical applications are constants. Thus recent studies aimed at the development of new techniques for modification of surfaces. The low pressure plasma has been highlighted for its versatility and for being environmentally friendly, achieving good results in the modification of physic chemical properties of materials. However, it is requires an expensive vacuum system and cannot able to generate superficial changes in specific regions. Furthermore, it is limits their use in polymeric materials and sensitive terms due to high process temperatures. Therefore, new techniques capable of generating cold plasma at atmospheric pressure (APPJ) were created. In order to perform surface treatments on biomaterials in specific regions was built a prototype capable of generating a cold plasma jet. The prototype plasma generator consists of a high voltage source, a support arm, sample port and a nozzle through which the ionized argon. The device was formed to a dielectric tube and two electrodes. This work was varied some parameters such as position between electrodes, voltage and electrical frequency to verify the behavior of glow discharges. The disc of titanium was polished and there was a surface modification. The power consumed, length, intensity and surface modifications of titanium were analyzed. The energy consumed during the discharges was observed by the Lissajous figure method. To check the length of the jets was realized with Image Pro Plus software. The modifications of the titanium surfaces were observed by optical microscopy (OM ) and atomic force microscopy (AFM ). The study showed that variations of the parameters such as voltage, frequency and geometric position between the electrodes influence the formation of the plasma jet. It was concluded that the plasma jet near room temperature and atmospheric pressure was able to cause modifications in titanium surface
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Currently, studies in the area of polymeric microcapsules and nanocapsules and controlled release are considerably advanced. This work aims the study and development of microcapsules and nanocapsules from Chitosan/MDI, using a new technique of interfacial polycondensation combined to spontaneous emulsification, for encapsulation of BZ-3. It was firstly elaborated an experimental design of 23 of the particle in white without the presence of BZ-3 and Miglyol, where the variables were the concentrations of MDI, chitosan and solvent. Starting from the data supplied by the experimental design was chosen the experiment with smaller particle diameter and only added like this BZ-3 and Miglyol. The suspension containing concentrations of 6.25 mg/mL, 12.5 mg/mL, 18.75 mg/mL, 25 mg/mL of BZ-3 were prepared, nevertheless, during the storage time, these formulations presented drug precipitates in the suspensions of 18.75 mg/mL and 25 mg/mL of BZ-3. This apparition of precipitate was attributed to the diffusion of BZ-3 for the aqueous phase without any encapsulation, suggesting so the use of the smaller concentrations of the BZ-3. The suspension containing 6.25mg/mL of BZ3 presented average size of 1.47μm, zeta potential of 61 mV, pH 5.64 and this sample showed an amount of BZ-3 and drug entrapment of 100 %. The suspension containing 12.5mg/mL of BZ-3 presented average size of 1.76μm, zeta potential of 47.4 mV, pH 5.71 and this sample showed an amount of BZ-3 and drug entrapment of 100 %. Then, showing such important characteristics, these two formulations were chosen for futher continuity to the study. These formulations were also characterized by the morphology, FTIR, stability for Turbiscan, DSC and a study of controlled release of the BZ-3 was elaborated in different receiving means
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Rare earth elements have recently been involved in a range of advanced technologies like microelectronics, membranes for catalytic conversion and applications in gas sensors. In the family of rare earth elements like cerium can play a key role in such industrial applications. However, the high cost of these materials and the control and efficiencies associated processes required for its use in advanced technologies, are a permanent obstacle to its industrial development. In present study was proposed the creation of phases based on rare earth elements that can be used because of its thermal behavior, ionic conduction and catalytic properties. This way were studied two types of structure (ABO3 and A2B2O7), the basis of rare earths, observing their transport properties of ionic and electronic, as well as their catalytic applications in the treatment of methane. For the process of obtaining the first structure, a new synthesis method based on the use of EDTA citrate mixture was used to develop a precursor, which undergone heat treatment at 950 ° C resulted in the development of submicron phase BaCeO3 powders. The catalytic activity of perovskite begins at 450 ° C to achieve complete conversion at 675 ° C, where at this temperature, the catalytic efficiency of the phase is maximum. The evolution of conductivity with temperature for the perovskite phase revealed a series of electrical changes strongly correlated with structural transitions known in the literature. Finally, we can establish a real correlation between the high catalytic activity observed around the temperature of 650 ° C and increasing the oxygen ionic conductivity. For the second structure, showed clearly that it is possible, through chemical processes optimized to separate the rare earth elements and synthesize a pyrochlore phase TR2Ce2O7 particular formula. This "extracted phase" can be obtained directly at low cost, based on complex systems made of natural minerals and tailings, such as monazite. Moreover, this method is applied to matters of "no cost", which is the case of waste, making a preparation method of phases useful for high technology applications
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Smart card applications represent a growing market. Usually this kind of application manipulate and store critical information that requires some level of security, such as financial or confidential information. The quality and trustworthiness of smart card software can be improved through a rigorous development process that embraces formal techniques of software engineering. In this work we propose the BSmart method, a specialization of the B formal method dedicated to the development of smart card Java Card applications. The method describes how a Java Card application can be generated from a B refinement process of its formal abstract specification. The development is supported by a set of tools, which automates the generation of some required refinements and the translation to Java Card client (host) and server (applet) applications. With respect to verification, the method development process was formalized and verified in the B method, using the Atelier B tool [Cle12a]. We emphasize that the Java Card application is translated from the last stage of refinement, named implementation. This translation process was specified in ASF+SDF [BKV08], describing the grammar of both languages (SDF) and the code transformations through rewrite rules (ASF). This specification was an important support during the translator development and contributes to the tool documentation. We also emphasize the KitSmart library [Dut06, San12], an essential component of BSmart, containing models of all 93 classes/interfaces of Java Card API 2:2:2, of Java/Java Card data types and machines that can be useful for the specifier, but are not part of the standard Java Card library. In other to validate the method, its tool support and the KitSmart, we developed an electronic passport application following the BSmart method. We believe that the results reached in this work contribute to Java Card development, allowing the generation of complete (client and server components), and less subject to errors, Java Card applications.
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The development of smart card applications requires a high level of reliability. Formal methods provide means for this reliability to be achieved. The BSmart method and tool contribute to the development of smart card applications with the support of the B method, generating Java Card code from B specifications. For the development with BSmart to be effectively rigorous without overloading the user it is important to have a library of reusable components built in B. The goal of KitSmart is to provide this support. A first research about the composition of this library was a graduation work from Universidade Federal do Rio Grande do Norte, made by Thiago Dutra in 2006. This first version of the kit resulted in a specification of Java Card primitive types byte, short and boolean in B and the creation of reusable components for application development. This work provides an improvement of KitSmart with the addition of API Java Card specification made in B and a guide for the creation of new components. The API Java Card in B, besides being available to be used for development of applications, is also useful as a documentation of each API class. The reusable components correspond to modules to manipulate specific structures, such as date and time. These structures are not available for B or Java Card. These components for Java Card are generated from specifications formally verified in B. The guide contains quick reference on how to specify some structures and how some situations were adapted from object-orientation to the B Method. This work was evaluated through a case study made through the BSmart tool, that makes use of the KitSmart library. In this case study, it is possible to see the contribution of the components in a B specification. This kit should be useful for B method users and Java Card application developers
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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.