Signal classification of submerged aquatic vegetation based on the hemispherical-conical reflectance factor spectrum shape in the yellow and red regions

The water column overlying the submerged aquatic vegetation (SAV) canopy presents difficulties when using remote sensing images for mapping such vegetation. Inherent and apparent water optical properties and its optically active components, which are commonly present in natural waters, in addition to the water column height over the canopy, and plant characteristics are some of the factors that affect the signal from SAV mainly due to its strong energy absorption in the near-infrared. By considering these interferences, a hypothesis was developed that the vegetation signal is better conserved and less absorbed by the water column in certain intervals of the visible region of the spectrum; as a consequence, it is possible to distinguish the SAV signal. To distinguish the signal from SAV, two types of classification approaches were selected. Both of these methods consider the hemispherical-conical reflectance factor (HCRF) spectrum shape, although one type was supervised and the other one was not. The first method adopts cluster analysis and uses the parameters of the band (absorption, asymmetry, height and width) obtained by continuum removal as the input of the classification. The spectral angle mapper (SAM) was adopted as the supervised classification approach. Both approaches tested different wavelength intervals in the visible and near-infrared spectra. It was demonstrated that the 585 to 685-nm interval, corresponding to the green, yellow and red wavelength bands, offered the best results in both classification approaches. However, SAM classification showed better results relative to cluster analysis and correctly separated all spectral curves with or without SAV. Based on this research, it can be concluded that it is possible to discriminate areas with and without SAV using remote sensing. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Local electronic structure, optical bandgap and photoluminescence (PL) properties of Ba(Zr0.75Ti0.25)O3 powders

Ba(Zr0.75Ti0.25)O3 (BZT-75/25) powders were synthesized by the polymeric precursor method. Samples were structurally characterized by X-ray diffraction (XRD), Rietveld refinement, X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) techniques. Their electronic structures were evaluated by first-principle quantum mechanical calculations based on density functional theory at the B3LYP level. Their optical properties were investigated by ultraviolet-visible (UV-Vis) spectroscopy and photoluminescence (PL) measurements at room temperature. XRD patterns and Rietveld refinement data indicate that the samples have a cubic structure. XANES spectra confirm the presence of pyramidal [TiO5] clusters and octahedral [TiO6] clusters in the disordered BZT-75/25 powders. EXAFS spectra indicate distortion of Ti-O and Ti-O-Ti bonds the first and second coordination shells, respectively. UV-Vis absorption spectra confirm the presence of different optical bandgap values and the band structure indicates an indirect bandgap for this material. The density of states demonstrates that intermediate energy levels occur between the valence band (VB) and the conduction band (CB). These electronic levels are due to the predominance of 4d orbitals of Zr atoms in relation to 3d orbitals of Ti atoms in the CB, while the VB is dominated by 2p orbitals related to O atoms. There was good correlation between the experimental and theoretical optical bandgap values. When excited at 482 nm at room temperature, BZT-75/25 powder treated at 500 C for 2 h exhibited broad and intense PL emission with a maximum at 578 nm in the yellow region. © 2013 Elsevier Ltd. All rights reserved.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.

A critical analysis of the ubiquity of linear local-regional richness relationships

Synthesis Despite theoretical criticisms, the ubiquity of linear relationships between local and regional species richness has long been used to justify it as a valid framework to conclude that local communities are not saturated with species. However, we reanalyzed published studies with a new unbiased method and found no prevalence of linear relationships and more than 40% of misclassifications, including textbook examples. We thus conclude that the prevailing argument in favor of associating a valid ecological interpretation to local-regional species richness plots, its ubiquity, is not sustained, and that ecologists could use for instance metacommunity theory to make inference on the strength of local and regional processes. Identifying the relative importance of regional and local processes to local species diversity is a central issue to many questions in basic and applied ecology. One widely-used method is to plot local species richness against its regional richness to infer whether regional or local processes determine local diversity. However, this method increases the tendency to find regional prevalence as suggested by a recent simulation. We reanalyzed studies in the literature with an unbiased method and found no prevalence of either regional or local processes. In addition, almost 40% of the studies and 50% of the ecology textbook examples using the traditional method were misclassified. Our findings reinforce the need of alternative, novel tools identified by for instance metacommunity theory to go beyond the studies of local-regional relationships in the ecological literature that focus on the interdependence of regional and local processes.© 2013 The Authors. Oikos © 2013 Nordic Society Oikos.

Automatic segmentation and classification of human intestinal parasites from microscopy images

Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

Local order of Pb1-xLaxZr0.40Ti 0.60O3 ferroelectric ceramic materials probed by X-ray absorption and Raman spectroscopies

This paper reports on the structural characterization of Pb 1-xLaxZr0.40Ti0.60O3 (PLZT) ferroelectric ceramic compositions prepared by the conventional solid state reaction method. X-ray absorption spectroscopy (XAS) and Raman spectroscopy were used to probe the local structure of PLZT samples that exhibits a normal and relaxor ferroelectric behavior. From the Zr K-edge and Pb LIII-edge EXAFS spectra, a considerable dissymmetry of Zr and Pb sites was observed in all samples, including those showing a long-range order cubic symmetry and a relaxor behavior. The Raman spectroscopy results confirmed the existence of a local disorder in all PLZT samples through the observation of Raman active vibrational modes. The variation in the intensity of the E(TO 3) mode in the PLZT relaxor samples indicates that the process of correlation between nanodomains stabilizes at temperatures lower than T m. © 2013 Elsevier B.V. All rights reserved.

A interface entre uma Unidade de internação infantil em Pronto Socorro de Hospital Universitário, com o Sistema de Saúde local e regional

Pós-graduação em Pediatria - FMB

Avaliação da degradação do meio físico por áreas de empréstimo utilizando geoindicadores e sistema de informações geográficas - área de expansão urbana de Ilha Solteira (SP)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Gerenciamento integrado de rede local com software livre

Pós-graduação em Engenharia Elétrica - FEIS

Photoluminescence properties of CaTiO3:Eu3+ nanophosphor obtained by the polymeric precursor method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Insight into the Effects of Fe Addition on the Local Structure and Electronic Properties of SrTiO3

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Validation of an HPLC Method for the Determination of Dibucaine Encapsulated in Solid Lipid Nanoparticles and Nanostructured Lipid Carriers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A local-global scheme for tracking crack path in three-dimensional solids

This paper aims to contribute to the three-dimensional generalization of numerical prediction of crack propagation through the formulation of finite elements with embedded discontinuities. The analysis of crack propagation in two-dimensional problems yields lines of discontinuity that can be tracked in a relatively simple way through the sequential construction of straight line segments oriented according to the direction of failure within each finite element in the solid. In three-dimensional analysis, the construction of the discontinuity path is more complex because it requires the creation of plane surfaces within each element, which must be continuous between the elements. In the method proposed by Chaves (2003) the crack is determined by solving a problem analogous to the heat conduction problem, established from local failure orientations, based on the stress state of the mechanical problem. To minimize the computational effort, in this paper a new strategy is proposed whereby the analysis for tracking the discontinuity path is restricted to the domain formed by some elements near the crack surface that develops along the loading process. The proposed methodology is validated by performing three-dimensional analyses of basic problems of experimental fractures and comparing their results with those reported in the literature.

Pruning methods to MLP neural networks considering proportional apparent error rate for classification problems with unbalanced data

This article deals with classification problems involving unequal probabilities in each class and discusses metrics to systems that use multilayer perceptrons neural networks (MLP) for the task of classifying new patterns. In addition we propose three new pruning methods that were compared to other seven existing methods in the literature for MLP networks. All pruning algorithms presented in this paper have been modified by the authors to do pruning of neurons, in order to produce fully connected MLP networks but being small in its intermediary layer. Experiments were carried out involving the E. coli unbalanced classification problem and ten pruning methods. The proposed methods had obtained good results, actually, better results than another pruning methods previously defined at the MLP neural network area. (C) 2014 Elsevier Ltd. All rights reserved.