Desenvolvimento de antenas de microfita com aberturas nos patches condutores através do método da segmentação

Microstrip antennas are widely used in modern telecommunication systems. This is particularly due to the great variety of geometries and because they are easily built and integrated to other high frequency devices and circuits. This work presents a study of the properties of the microstrip antenna with an aperture impressed in the conducting patch. Besides, the analysis is performed for isotropic and anisotropic dielectric substrates. The Multiport Network Model MNM is used in combination with the Segmentation Method and the Greens function technique in the analysis of the considered microstrip antenna geometries. The numerical analysis is performed by using the boundary value problem solution, by considering separately the impedance matrix of the structure segments. The analysis for the complete structure is implemented by choosing properly the number and location of the neighboor element ports. The numerial analysis is performed for the following antenna geometries: resonant cavity, microstrip rectangular patch antenna, and microstrip rectangular patch antenna with aperture. The analysis is firstly developed for microstrip antennas on isotropic substrates, and then extended to the case of microstrip antennas on anisotropic substrates by using a Mapping Method. The experimental work is described and related to the development of several prototypes of rectangular microstrip patch antennas wtih and without rectangular apertures. A good agreement was observed between the simulated and measured results. Thereafter, a good agreement was also observed between the results of this work and those shown in literature for microstrip antennas on isotropic substrates. Furthermore, results are proposed for rectangular microstrip patch antennas wtih rectangular apertures in the conducting patch

A Mismatch-Based Model for Memory Reconsolidation and Extinction in Attractor Networks

OSAN, R. , TORT, A. B. L. , AMARAL, O. B. . A mismatch-based model for memory reconsolidation and extinction in attractor networks. Plos One, v. 6, p. e23113, 2011.

A Mismatch-Based Model for Memory Reconsolidation and Extinction in Attractor Networks

OSAN, R. , TORT, A. B. L. , AMARAL, O. B. . A mismatch-based model for memory reconsolidation and extinction in attractor networks. Plos One, v. 6, p. e23113, 2011.

Modelagem e medições de ondas de rádio para predição de perda de propagação em ambientes urbanos

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

Estudo Comparativo de Métricas de Pontuação para Aprendizagem Estrutural de Redes Bayesianas

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

Degradação fotoquímica de hidrocarbonetos da gasolina em efluentes aquosos

Photo-oxidation processes of toxic organic compounds have been widely studied. This work seeks the application of the photo-Fenton process for the degradation of hydrocarbons in water. The gasoline found in the refinery, without additives and alcohol, was used as the model pollutant. The effects of the concentration of the following substances have been properly evaluated: hydrogen peroxide (100-200 mM), iron ions (0.5-1 mM) and sodium chloride (200 2000 ppm). The experiments were accomplished in reactor with UV lamp and in a falling film solar reactor. The photo-oxidation process was monitored by measurements of the absorption spectra, total organic carbon (TOC) and chemical oxygen demand (COD). Experimental results demonstrated that the photo-Fenton process is feasible for the treatment of wastewaters containing aliphatic hydrocarbons, inclusive in the presence of salts. These conditions are similar to the water produced by the petroleum fields, generated in the extraction and production of petroleum. A neural network model of process correlated well the observed data for the photooxidation process of hydrocarbons

Contribuições ao estudo das redes complexas: modelo de qualidade

In this work we analyse the implications of using a power law distribution of vertice's quality in the growth dynamics of a network studied by Bianconi anel Barabási. In particular, we start studying the random networks which characterize or are related to some real situations, for instance the tide movement. In this context of complex networks, we investigate several real networks, as well as we define some important concepts in the network studies. Furthermore, we present the first scale-free network model, which was proposed by Barabási et al., and a modified model studied by Bianconi and Barabási, where now the preferential attachment incorporates the different ability (fitness) of the nodes to compete for links. At the end, our results, discussions and conclusions are presented

Abordagem dirigida a modelos para redes de sensores sem fio

Research on Wireless Sensor Networks (WSN) has evolved, with potential applications in several domains. However, the building of WSN applications is hampered by the need of programming in low-level abstractions provided by sensor OS and of specific knowledge about each application domain and each sensor platform. We propose a MDA approach do develop WSN applications. This approach allows domain experts to directly contribute in the developing of applications without needing low level knowledge on WSN platforms and, at the same time, it allows network experts to program WSN nodes to met application requirements without specific knowledge on the application domain. Our approach also promotes the reuse of the developed software artifacts, allowing an application model to be reused across different sensor platforms and a platform model to be reused for different applications

Dinâmica e estrutura de redes complexas no modelo de afinidade

In this work we elaborate and discuss a Complex Network model which presents connectivity scale free probability distribution (power-law degree distribution). In order to do that, we modify the rule of the preferential attachment of the Bianconi-Barabasi model, including a factor which represents the similarity of the sites. The term that corresponds to this similarity is called the affinity, and is obtained by the modulus of the difference between the fitness (or quality) of the sites. This variation in the preferential attachment generates very interesting results, by instance the time evolution of the connectivity, which follows a power-law distribution ki / ( t t0 )fi, where fi indicates the rate to the site gain connections. Certainly this depends on the affinity with other sites. Besides, we will show by numerical simulations results for the average path length and for the clustering coefficient