Zirconia foams prepared by integration of the sol-gel method and dual soft template techniques

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Combined characterisation of GOME and TOMS total ozone measurements from space using ground-based observations from the NDSC

Several years of total ozone measured from space by the ERS-2 GOME, the Earth Probe TOMS, and the ADEOS TOMS, are compared with high-quality ground-based observations associated with the Network for the Detection of Stratospheric Change (NDSC), over an extended latitude range and a variety of geophysical conditions. The comparisons with each spaceborne sensor are combined altogether for investigating their respective solar zenith angle (SZA) dependence, dispersion, and difference of sensitivity. The space- and ground-based data are found to agree within a few percent on average. However, the analysis highlights for both GOME and TOMS several sources of discrepancies: (i) a SZA dependence with TOMS beyond 80° SZA; (ii) a seasonal SZA dependence with GOME beyond 70° SZA; (iii) a difference of sensitivity with GOME at high latitudes; (iv) a difference of sensitivity to low ozone values between satellite and SAOZ sensors around the southern tropics; (v) a north/south difference of TOMS with the ground-based observations; and (vi) internal inconsistencies in GOME total ozone. © 2001 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

Morphological routine proposal to extraction of highways in digital images of high resolution

This research proposes to apply techniques of Mathematics Morphology to extract highways in digital images of high resolution, targeting the upgrade of cartographic products. Remote Sensing data and Mathematical Morphological techniques were integrated in the process of extraction. Mathematical Morphology's objective is to improve and extract the relevant information of the visual image. In order to test the proposed approach some morphological operators related to preprocess, were applied to the original images. Routines were implemented in the MATLAB environment. Results indicated good performances by the implemented operators. The integration of the technologies aimed to implement the semiautomatic extraction of highways with the purpose to use them in processes of cartographic updating.

Proposal of a dedicated telemetry device for real-time and remote measurements

This work aims to demonstrate an application of telemetry for monitoring process variables. The authors developed the prototype of a dedicated device capable of multiplexing, encoding and transmitting real-time data signals via amplitude-shift keying modulation to remotely located device(s). The prototype development is described in details, enabling the reproduction of the proposed telemetry system for a three-phase motor as well as for other devices. Furthermore, the proposed device has an easy implementation by using of accessible components and low cost, also presenting a tutorial and educational purpose. © 2011 IEEE.

Chlorophyll a spatial inference using artificial neural network from multispectral images and in situ measurements

Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.

Soft-chemical synthesis, characterization and humidity sensing behavior of WO3/TiO2 nanopowders

Tungsten oxide/titania (WO3/TiO2) nanopowders were synthesized by the polymeric precursor method which varied the WO3 content between 0 and 10 mol%. The powders were thermally treated in a conventional furnace and their structural, microstructural and electric properties were evaluated by X-ray diffraction (XRD), Raman spectrometry, N 2 physisorption, NH3 chemisorption, temperature-programmed reduction (TPR), X-ray absorption near-edge spectroscopy (XANES) in situ XANES and extended X-ray absorption fine structure spectroscopy (EXAFS) and transmission electron microscopy (TEM). XRD and Raman spectrometry confirmed the homogeneous distribution of an amorphous WO3 phase in the TiO 2 matrix which stabilized the anatase phase through the generation of [TiO5·V0] or [TiO5·V 0] complex sites. Conventional TPR-H2 (temperature programmed reduction) along with XANES TPR-H2 and XANES TPR-EtOH showed that WO3/TiO2 sample reduction occurs through the formation of these complex clusters. Moreover, the addition of WO3 promoted an increase in the surface acidity of doped samples as revealed by NH3 chemisorption. The WO3/TiO2 bulk-ceramic samples were further used to estimate their potential application in a humidity sensor in the range of 15-85% relative humidity. Probable reasons that lead to the different humidity sensor responses of samples were given based on the structural and surface characterizations. Correlation between the sensing performance of the sensor and its structural features are also discussed. Although all samples responded as a humidity sensor, the W2T sample (2 mol% added WO3) excelled for sensitivity due to the increase in acid sites, optimum mean pore size and pore size distribution. © 2013 Elsevier B.V.

An investigation into the influence of zinc precursor on the microstructural, photoluminescence, and gas-sensing properties of ZnO nanoparticles

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Inverse Modeling of GPS Multipath for Snow Depth Estimation-Part I: Formulation and Simulations

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Inverse Modeling of GPS Multipath for Snow Depth Estimation-Part II: Application and Validation

GPS multipath reflectometry (GPS-MR) is a technique that uses geodetic quality GPS receivers to estimate snow depth. The accuracy and precision of GPS-MR retrievals are evaluated at three different sites: grasslands, alpine, and forested. The assessment yields a correlation of 0.98 and an rms error of 6-8 cm for observed snow depths of up to 2.5 m. GPS-MR underestimates in situ snow depth by 10%-15% at these three sites, although the validation methods do not measure the same footprint as GPS-MR.

Taxonomic review of the species of Mugil (Teleostei: Perciformes: Mugilidae) from the Atlantic South Caribbean and South America, with integration of morphological, cytogenetic and molecular data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)