923 resultados para Convergence And Extension
Resumo:
Uranium-lead zircon ages between 660 and 640 Ma, obtained from a series of calc-alkaline orthogneisses and plutons in southeast Brazil's Central Mantiqueira Province, suggest that a significant period of magmatism occurred in this region prior to the collisional assembly of West Gondwana (presently constrained in the region between ca. 625 and 580 Ma). While the nature of this earlier magmatism is presently unclear, some preliminary Sm-Nd data suggest that these magmas were not solely derived from the Paleoproterozoic lithosphere, but appear to represent hybrid products of Paleoproterozoic and Neoproterozoic sources. As such hybrid mixtures have been most commonly observed in continental are settings, it is possible that the 660 to 640 Ma magmatism represents are magmatism that resulted from subduction of Neoproterozoic oceanic crust during early precollisional convergence and closure of a branch of either the Adamastor or Goianides oceans.
Resumo:
This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.
Resumo:
Nowadays there is great interest in structural damage detection in systems using nondestructive tests. Once the failure is detected, as for instance a crack, it is possible to take providences. There are several different approaches that can be used to obtain information about the existence, location and extension of the fault in the system by non-destructive tests. Among these methodologies, one can mention different optimization techniques, as for instance classical methods, genetic algorithms, neural networks, etc. Most of these techniques, which are based on element-byelement adjustments of a finite element (FE) model, take advantage of the dynamic behavior of the model. However, in practical situations, usually, is almost impossible to obtain an accuracy model. In this paper, it is proposed an experimental technique for damage location. This technique is based on H: norm to obtain the damage location. The dynamic properties of the structure were identified using experimental data by eigensystem realization algorithm (ERA). The experimental test was carried out in a beam structure through varying the mass of an element. For the output signal was used a piezoelectric sensor. The signal of input of sine form was generated through SignalCalc® software.
Resumo:
The structure of Brazil's National Health System (SUS) is being firmed up through programs adding a new element to its multi-professional healthcare teams: Community Healthcare Agents. This study examines psycho-social factors that are significant for the construction of this identity, from the standpoint of these Community Healthcare Agents, using the hermeneutic phenomenology of Paul Ricoeur as its reference methodology. The subjects of this survey were seven Community Healthcare Agents who were asked during interviews (with informed consent and after approval by the Research Ethics Committee) to: 'Tell me about your experience as Community Healthcare Agent'. The analysis of their replies indicated the following topics: previous experience; capacity-building for the job; bonding; building up expertise; gratifying experience; feelings of power(lessness); communications; daily work routines, personal growth; criticisms of the institution; user-agent experiences; and insertion into the social reality. The overall analysis disclosed the phenomenon through the convergence and divergence of the grouping of these topics, viewed from the standpoint of these Community Healthcare Agents and the psycho-social aspects constructing their identity.
Resumo:
It was purposed the use of electromyography (EMG) to evaluate the activation of the agonists and antagonists muscles of spastic patients, to test the viability in the development of an instrument that given quantitative data of the patient spasticity. 30 hemiplegic and 15 normal volunteers had been submitted to the EMG of flexor and extensor carpi ulnaris muscles during the flexion and extension movements of the wrist. The individuals with less severe spasticity (mAS (modified Ashworth Scale) ringing 0 to 3 degree), had presented deficit in the activation of the flexor muscles in plegic side in relation to the non plegic side and that the individuals seriously compromised by the spasticity (mAS = 4 degree) present deficit of reciprocal inhibition. One evidenced is that the non plegic member does not present a similar neuro-motor comportment when compared to the normal member. The surface electromyography is a practical clinical instrument to evaluate the patient with spasticity and the hemiplegic patient needs to be evaluated on both sides (deficient and no deficient) because the no compromised side do not show a normality standard.
Resumo:
Fraud detection in energy systems by illegal consumers is the most actively pursued study in non-technical losses by electric power companies. Commonly used supervised pattern recognition techniques, such as Artificial Neural Networks and Support Vector Machines have been applied for automatic commercial frauds identification, however they suffer from slow convergence and high computational burden. We introduced here the Optimum-Path Forest classifier for a fast non-technical losses recognition, which has been demonstrated to be superior than neural networks and similar to Support Vector Machines, but much faster. Comparisons among these classifiers are also presented. © 2009 IEEE.
Resumo:
Includes bibliography
Resumo:
In this work we analyze the convergence of solutions of the Poisson equation with Neumann boundary conditions in a two-dimensional thin domain with highly oscillatory behavior. We consider the case where the height of the domain, amplitude and period of the oscillations are all of the same order, and given by a small parameter e > 0. Using an appropriate corrector approach, we show strong convergence and give error estimates when we replace the original solutions by the first-order expansion through the Multiple-Scale Method.
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Pós-graduação em Agronomia (Ciência do Solo) - FCAV
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)