119 resultados para Aerial application
Resumo:
New results on the theory of constrained systems are applied to characterize the generators of Noethers symmetry transformations. As a byproduct, an algorithm to construct gauge transformations in Hamiltonian formalism is derived. This is illustrated with two relevant examples.
Resumo:
A Lagrangian treatment of the quantization of first class Hamiltonian systems with constraints and Hamiltonian linear and quadratic in the momenta, respectively, is performed. The first reduce and then quantize and the first quantize and then reduce (Diracs) methods are compared. A source of ambiguities in this latter approach is pointed out and its relevance on issues concerning self-consistency and equivalence with the first reduce method is emphasized. One of the main results is the relation between the propagator obtained la Dirac and the propagator in the full space. As an application of the formalism developed, quantization on coset spaces of compact Lie groups is presented. In this case it is shown that a natural selection of a Dirac quantization allows for full self-consistency and equivalence. Finally, the specific case of the propagator on a two-dimensional sphere S2 viewed as the coset space SU(2)/U(1) is worked out. 1995 American Institute of Physics.
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We have analyzed a two-dimensional lattice-gas model of cylindrical molecules which can exhibit four possible orientations. The Hamiltonian of the model contains positional and orientational energy interaction terms. The ground state of the model has been investigated on the basis of Karl¿s theorem. Monte Carlo simulation results have confirmed the predicted ground state. The model is able to reproduce, with appropriate values of the Hamiltonian parameters, both, a smectic-nematic-like transition and a nematic-isotropic-like transition. We have also analyzed the phase diagram of the system by mean-field techniques and Monte Carlo simulations. Mean-field calculations agree well qualitatively with Monte Carlo results but overestimate transition temperatures.
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One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.
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A method for characterizing the microroughness of samples in optical coating technology is developed. Measurements over different spatial-frequency ranges are composed into a single power spectral density (PSD) covering a large bandwidth. This is followed by the extraction of characteristic parameters through fitting of the PSD to a suitable combination of theoretical models. The method allows us to combine microroughness measurements performed with different techniques, and the fitting procedure can be adapted to any behavior of a combined PSD. The method has been applied to a set of ion-beam-sputtered fluoride vacuum-UV coatings with increasing number of alternative low- and high-index layers. Conclusions about roughness development and microstructural growth are drawn.
Resumo:
We communicate a detailed study of the epitaxial growth of CeO2 on MgO. The key feature of the growth is the dependence of the in¿plane orientation of the CeO2 epitaxial layer on the MgO surface morphology. Atomic force microscopic (AFM) measurements, x¿ray analyses, as well as high¿resolution transmission electron microscopy (HRTEM) investigations reveal that on rough substrates a cube¿on¿cube growth of CeO2 on MgO occurs while on smooth substrates the CeO2 unit cell is rotated around the surface normal by 45° with respect to the MgO unit cell when the deposition rate is low (~0.3 Å/s) during the first stages of growth. This growth mechanism can be used for a defined fabrication of 45° grain boundaries in the CeO2 layer by controlling the surface roughness of the MgO substrate. This report demonstrates that these 45° grain boundaries may be used to fabricate YBa2Cu3O7¿x Josephson junctions.
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The design of appropriate multifractal analysis algorithms, able to correctly characterize the scaling properties of multifractal systems from experimental, discretized data, is a major challenge in the study of such scale invariant systems. In the recent years, a growing interest for the application of the microcanonical formalism has taken place, as it allows a precise localization of the fractal components as well as a statistical characterization of the system. In this paper, we deal with the specific problems arising when systems that are strictly monofractal are analyzed using some standard microcanonical multifractal methods. We discuss the adaptations of these methods needed to give an appropriate treatment of monofractal systems.
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We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.
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Background Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations. Method We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure. Results We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis. Conclusion CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.
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In this paper we deal with the identification of dependencies between time series of equity returns. Marginal distribution functions are assumed to be known, and a bivariate chi-square test of fit is applied in a fully parametric copula approach. Several families of copulas are fitted and compared with Spanish stock market data. The results show that the t-copula generally outperforms other dependence structures, and highlight the difficulty in adjusting a significant number of bivariate data series
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A novel and simple procedure for concentrating adenoviruses from seawater samples is described. The technique entails the adsorption of viruses to pre-flocculated skimmed milk proteins, allowing the flocs to sediment by gravity, and dissolving the separated sediment in phosphate buffer. Concentrated virus may be detected by PCR techniques following nucleic acid extraction. The method requires no specialized equipment other than that usually available in routine public health laboratories, and due to its straightforwardness it allows the processing of a larger number of water samples simultaneously. The usefulness of the method was demonstrated in concentration of virus in multiple seawater samples during a survey of adenoviruses in coastal waters.
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Estrone is a powerful growth-inducing hormone that is present in milk, mainly in the form of fatty acid esters, at concentrations that promote growth in experimental animals. We present here a method useful for the measurement of this natural hormone in foods and applied it to several common dairy products. Samples were frozen, finely powdered, and lyophilized then extracted with trichloromethane/methanol; the dry extract was saponified with potassium hydroxide. The free estrone evolved was extracted with ethyl acetate and was used for the estimation of total estrone content through radioimmunoassay. Application of the method to dairy products showed high relative levels of total estrone (essentially acyl-estrone) in milk, in the range of 1 ¿M, which were halved in skimmed milk. Free estrone levels were much lower, in the nanomolar range. A large proportion of estrone esters was present in all other dairy products, fairly correlated with their fat content. The amount of estrone carried by milk is well within the range, where its intake may exert a physiological response in the sucklings for which it is provided. These growth-inducing and energy expenditure-lowering effects may affect humans ingesting significant amounts of dairy products.