77 resultados para Engineering, Electronics and Electrical|Artificial Intelligence
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Ce(0.8)SM(0.2)O(1.9) and CeO(2) nanomaterials were prepared by a solution technique to produce an ultrafine particulate material with high sinterability. In this work, the structural characteristics, the photoluminescent behavior and the ionic conductivity of the synthesized materials are focused. The thermally decomposed material consists of less than 10 nm in diameter nanoparticles. The Raman spectrum of pure CeO(2) consists of a single triple degenerate F(2g) model characteristic of the fluorite-like structure. The full width at half maximum of this band decreases linearly with increasing calcination temperature. The photoluminescence spectra show a broadened emission band assigned to the ligand-to-metal charge-transfer states O -> Ce(4+). The emission spectra of the Ce(0.8)Sm(0.2)O(1.9) specimens present narrow bands arising from the 4G(5/2) -> (6)H(J) transitions (J = 5/2, 7/2, 9/2 and 11/2) of Sm(3+) ion due to the efficient energy transfer from the O -> Ce(4+) transitions to the emitter 4G(5/2) level. The ionic conductivity of sintered specimens shows a significant dependence on density. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
The aim of this study is to analyze the effect of neuromuscular electrical stimulation (NMES) on myoelectrical activity and on joint torque during isometric plantar flexion contraction. Ten healthy young adult subjects participate in this study. The electrodes for NMES are placed along posterior thigh along ciatic nerve trajectory. It is measured the myoelectrical activity and the isometric torque generated by ankle plantar flexion with an isokinetic dynamometer. The conditions of isometric contractions are maximum isometric voluntary contraction (MIVC), NMES, and association of both (MIVC+NMES). The results show lower torque during NMES and larger SOL activity compare to the others. Besides, in order to keep the same objective task (to produce the same level of torque), neuromuscular adaptations are necessary on the common drive.
Resumo:
In order to assess the influence of the colostrum period on pH and, electrical conductivity, we collected 418 milk samples from 127 Jersey cows. The samples were collected from healthy udders that did not present any bacterial growth in the microbiological examination. They were divided into eight groups as follows < 1/2 day; 1/2 and 1 degrees day; 2 degrees day; 3 degrees day; 4 degrees and 5 degrees day; 6 degrees and 7 degrees day; 8 degrees to 15 degrees day; 16 degrees to 30 degrees days of lactation. The samples were collected before milking and the following analyses were conducted: pH, electrical conductivity. In the first 24 hours of lactation, there was an reduction in electrical conductivity value, associated with an increase in pH value. We observed that transition of secretion from colostrum to milk, occurs during the first week of lactation; from 6(rd) day of lactation for pH value and 3(th) day for electrical conductivity value. We recommend the use the following figures as normal ranges for the first 24 hours of lactation (colostrum period): pH <= 6,51 and electrical conductivity <= 6,33 mS/cm; while for the interval between 2(nd) and 7(th) days of lactation (transition from colostrum to milk) we suggest the use of the values as normal ranges: pH <= 6,66 and electrical conductivity <= 5,93 mS/cm.
Resumo:
Bi(4-x)La(x)Ti(3)O(12) (BLT) ceramics were prepared and studied in this work in terms of La(3+)-modified microstructure and phase development as well as electrical response. According to the results processed from X-ray diffraction and electrical measurements, the solubility limit (XL) of La(3+) into the Bi(4)Ti(3)O(12) (BIT) matrix was here found to locate slightly above x = 1.5. Further, La(3+) had the effect of reducing the material grain size, while changing its morphology from the plate-like form, typical of BIT ceramics, to a spherical-like one. The electrical results presented and discussed here also include the behavior of the temperature of the ferroelectric-paraelectric phase transition as well as the normal or diffuse and/or relaxor nature of this transition depending on the La(3+) content. (c) 2008 Elsevier Ltd. All fights reserved.
Resumo:
Nb(3)Sn is one of the most used superconducting materials for applications in high magnetic fields. The improvement of the critical current densities (J(c)) is important, and must be analyzed together with the optimization of the flux pinning acting in the material. For Nb(3)Sn, it is known that the grain boundaries are the most effective pinning centers. However, the introduction of artificial pinning centers (APCs) with different superconducting properties has been proved to be beneficial for J(c). As these APCs are normally in the nanometric-scale, the conventional heat treatment profiles used for Nb(3)Sn wires cannot be directly applied, leading to excessive grain growth and/or increase of the APCs cross sections. In this work, the heat treatment profiles for Nb(3)Sn superconductor wires with Cu(Sn) artificial pinning centers in nanometric-scale were analyzed in an attempt to improve J(c) . It is described a methodology to optimize the heat treatment profiles in respect to diffusion, reaction and formation of the superconducting phases. Microstructural, transport and magnetic characterization were performed in an attempt to find the pinning mechanisms acting in the samples. It was concluded that the maximum current densities were found when normal phases (due to the introduction of the APCs) are acting as main pinning centers in the global behavior of the Nb(3)Sn superconducting wire.
Resumo:
This paper contains a new proposal for the definition of the fundamental operation of query under the Adaptive Formalism, one capable of locating functional nuclei from descriptions of their semantics. To demonstrate the method`s applicability, an implementation of the query procedure constrained to a specific class of devices is shown, and its asymptotic computational complexity is discussed.
Resumo:
The paper presents the development of a mechanical actuator using a shape memory alloy with a cooling system based on the thermoelectric effect (Seebeck-Peltier effect). Such a method has the advantage of reduced weight and requires a simpler control strategy as compared to other forced cooling systems. A complete mathematical model of the actuator was derived, and an experimental prototype was implemented. Several experiments are used to validate the model and to identify all parameters. A robust and nonlinear controller, based on sliding-mode theory, was derived and implemented. Experiments were used to evaluate the actuator closed-loop performance, stability, and robustness properties. The results showed that the proposed cooling system and controller are able to improve the dynamic response of the actuator. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.
Resumo:
Systems of distributed artificial intelligence can be powerful tools in a wide variety of practical applications. Its most surprising characteristic, the emergent behavior, is also the most answerable for the difficulty in. projecting these systems. This work proposes a tool capable to beget individual strategies for the elements of a multi-agent system and thereof providing to the group means on obtaining wanted results, working in a coordinated and cooperative manner as well. As an application example, a problem was taken as a basis where a predators` group must catch a prey in a three-dimensional continuous ambient. A synthesis of system strategies was implemented of which internal mechanism involves the integration between simulators by Particle Swarm Optimization algorithm (PSO), a Swarm Intelligence technique. The system had been tested in several simulation settings and it was capable to synthesize automatically successful hunting strategies, substantiating that the developed tool can provide, as long as it works with well-elaborated patterns, satisfactory solutions for problems of complex nature, of difficult resolution starting from analytical approaches. (c) 2007 Elsevier Ltd. All rights reserved.
Resumo:
The classical approach for acoustic imaging consists of beamforming, and produces the source distribution of interest convolved with the array point spread function. This convolution smears the image of interest, significantly reducing its effective resolution. Deconvolution methods have been proposed to enhance acoustic images and have produced significant improvements. Other proposals involve covariance fitting techniques, which avoid deconvolution altogether. However, in their traditional presentation, these enhanced reconstruction methods have very high computational costs, mostly because they have no means of efficiently transforming back and forth between a hypothetical image and the measured data. In this paper, we propose the Kronecker Array Transform ( KAT), a fast separable transform for array imaging applications. Under the assumption of a separable array, it enables the acceleration of imaging techniques by several orders of magnitude with respect to the fastest previously available methods, and enables the use of state-of-the-art regularized least-squares solvers. Using the KAT, one can reconstruct images with higher resolutions than was previously possible and use more accurate reconstruction techniques, opening new and exciting possibilities for acoustic imaging.
Resumo:
We consider brightness/contrast-invariant and rotation-discriminating template matching that searches an image to analyze A for a query image Q We propose to use the complex coefficients of the discrete Fourier transform of the radial projections to compute new rotation-invariant local features. These coefficients can be efficiently obtained via FFT. We classify templates in ""stable"" and ""unstable"" ones and argue that any local feature-based template matching may fail to find unstable templates. We extract several stable sub-templates of Q and find them in A by comparing the features. The matchings of the sub-templates are combined using the Hough transform. As the features of A are computed only once, the algorithm can find quickly many different sub-templates in A, and it is Suitable for finding many query images in A, multi-scale searching and partial occlusion-robust template matching. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
In Part I [""Fast Transforms for Acoustic Imaging-Part I: Theory,"" IEEE TRANSACTIONS ON IMAGE PROCESSING], we introduced the Kronecker array transform (KAT), a fast transform for imaging with separable arrays. Given a source distribution, the KAT produces the spectral matrix which would be measured by a separable sensor array. In Part II, we establish connections between the KAT, beamforming and 2-D convolutions, and show how these results can be used to accelerate classical and state of the art array imaging algorithms. We also propose using the KAT to accelerate general purpose regularized least-squares solvers. Using this approach, we avoid ill-conditioned deconvolution steps and obtain more accurate reconstructions than previously possible, while maintaining low computational costs. We also show how the KAT performs when imaging near-field source distributions, and illustrate the trade-off between accuracy and computational complexity. Finally, we show that separable designs can deliver accuracy competitive with multi-arm logarithmic spiral geometries, while having the computational advantages of the KAT.
Resumo:
SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.
Resumo:
For many learning tasks the duration of the data collection can be greater than the time scale for changes of the underlying data distribution. The question we ask is how to include the information that data are aging. Ad hoc methods to achieve this include the use of validity windows that prevent the learning machine from making inferences based on old data. This introduces the problem of how to define the size of validity windows. In this brief, a new adaptive Bayesian inspired algorithm is presented for learning drifting concepts. It uses the analogy of validity windows in an adaptive Bayesian way to incorporate changes in the data distribution over time. We apply a theoretical approach based on information geometry to the classification problem and measure its performance in simulations. The uncertainty about the appropriate size of the memory windows is dealt with in a Bayesian manner by integrating over the distribution of the adaptive window size. Thus, the posterior distribution of the weights may develop algebraic tails. The learning algorithm results from tracking the mean and variance of the posterior distribution of the weights. It was found that the algebraic tails of this posterior distribution give the learning algorithm the ability to cope with an evolving environment by permitting the escape from local traps.
Resumo:
In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.