31 resultados para sand filter
Resumo:
This paper presents an analysis of a reconfigurable patch filter based on a triple-mode circular patch resonator with four radial slots. The analysis has been carried out thanks to the development of a new theoretical approach of the tunable patch filter based on the coupling matrix. The coefficients of the coupling matrix related to the tunable behavior have been identified and some rules for their evolution have been derived. For a proof-of-concept, a bandpass filter has been designed with a continuous tunability obtained with varactors connected across the slots. State-of-the-art results have been obtained, with a frequency tuning range of 27% from 1.95 to 2.43 GHz and a change in fractional bandwidth from 8.5% to 31.5% for the respective frequencies. In the entire tuning range, the return loss is better than 10 dB and the maximum insertion loss is 2 dB. Due to the newly developed coupling matrix, measurements, simulations, and theory showed great agreement.
Resumo:
This article presents a triple-mode bandpass filter using a modified circular patch resonator. Etched slots in the resonator split the TM(1, 1, 0)(z) degenerate fundamental modes and also perturb the TM(2, 1, 0)(z) mode, approximating their resonant frequencies to form a third-order bandpass filter. A 2.42 GHz centered filter was designed and fabricated. Experimental results showed a fractional bandwidth of 29%, return loss better than 16 dB, insertion loss of 0.5 dB, and good second harmonic band rejection. The filter exhibited a size reduction of 51% compared with a filter using an unperturbed circular patch resonator at the same frequency. (C) 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 178-182, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23950
Resumo:
In this work, we present the simulation, fabrication and characterization of a tunable Bragg filter employing amorphous dielectric films deposited by plasma enhanced chemical vapor deposition technique on a crystalline silicon substrate. The optical device was built using conventional microelectronic processes and consisted of fifteen periodic intervals of Si3N4 layers separated by air with appropriated thickness and lengths to produce transmittance attenuation peaks in the visible region. For this, previous simulations were realized based in the optical parameters of the dielectric film, which were extracted from ellipsometry and profilometry techniques. For the characterization of the optical interferential filter, a 633 nm monochromatic light was injected on the filter, and then the transmitted output light was collected and conducted to a detector through an optical waveguide made also of amorphous dielectric layers. Afterwards, the optical filter was mounted on a Peltier thermoelectric device in order to control the temperature of the optical device. When the temperature of filter changes, a refractive index variation is originated in the dielectric film due to the thermo-optic effect, producing a shift of attenuation peak, which can be well predicted by numerical simulations. This characteristic allows this device to be used as a thermo-optic sensor. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.
Resumo:
The use of the Boltzmann transform function, lambda(theta), to solve the Richards equation when the diffusivity, D, is a function of only soil water content,., is now commonplace in the literature. Nevertheless, a new analytic solution of the Boltzmann transform lambda(h) as a function of matric potential for horizontal water infiltration into a sand was derived without invoking the concept or use of D(theta). The derivation assumes that a similarity exists between the soil water retention function and the Boltzmann transform lambda(theta). The solution successfully described soil water content profiles experimentally measured for different infiltration times into a homogeneous sand and agrees with those presented by Philip in 1955 and 1957. The applicability of this solution for all soils remains open, but it is anticipated to hold for soils whose air-filled pore-size distribution before wetting is sufficiently narrow to yield a sharp increase of water content at the wetting front during infiltration. It also improves and provides a versatile alternative to the well-known analysis pioneered by Green and Ampt in 1911.
Resumo:
A rapid DNA extraction was used for T. cruzi detection in triatomines dry fecal spots collected on filter paper and analyzed by PCR. Fifty T infestans were fed on experimentally infected Balb/C mice with high T. cruzi parasitemia and divided into five groups of len triatomines, and 100 triatomines were infected with lower parasitemia and divided into five groups of 20 triatomines, One dry fecal spot was analyzed per group on days 1, 2, 3, 4 and 5 post feeding. Amplification targeted T. cruzi TCZ sequence and resulted positive from day 4 after bugs feeding in the two models (high and lower parasitemia). The rapid DNA isolation and PCR proposed are suitable for detection of T. cruzi DNA in in filter paper and should be considered in field research.
Resumo:
An increase in cutaneous and visceral leishmaniasis cases has been reported in recent years in the state of Mato Grosso do Sul, Brazil, and little is known to date about their etiological agents. An investigation into natural Leishmania infection of sand flies captured in this state between December 2003 and August 2004 was carried out. Mini-exon sequences were used as targets to identify Leishmania, and an RFLP technique was employed for those identified as belonging to the Viannia subgenus. Calculation of the minimal infection rate (MR) revealed that 1.6% of sand flies captured in the forest, peridomicile and intradomicile were positive. Six species were found to be infected by Leishmania (V.) braziliensis. Interestingly, two of the six species. Lutzomyia longipalpis and Nyssomyia whitmani, were captured in anthropic environments. The findings of this study constitute a useful tool for planning control measures against this disease in the State of Mato Grosso do Sul. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
A particle filter method is presented for the discrete-time filtering problem with nonlinear ItA ` stochastic ordinary differential equations (SODE) with additive noise supposed to be analytically integrable as a function of the underlying vector-Wiener process and time. The Diffusion Kernel Filter is arrived at by a parametrization of small noise-driven state fluctuations within branches of prediction and a local use of this parametrization in the Bootstrap Filter. The method applies for small noise and short prediction steps. With explicit numerical integrators, the operations count in the Diffusion Kernel Filter is shown to be smaller than in the Bootstrap Filter whenever the initial state for the prediction step has sufficiently few moments. The established parametrization is a dual-formula for the analysis of sensitivity to gaussian-initial perturbations and the analysis of sensitivity to noise-perturbations, in deterministic models, showing in particular how the stability of a deterministic dynamics is modeled by noise on short times and how the diffusion matrix of an SODE should be modeled (i.e. defined) for a gaussian-initial deterministic problem to be cast into an SODE problem. From it, a novel definition of prediction may be proposed that coincides with the deterministic path within the branch of prediction whose information entropy at the end of the prediction step is closest to the average information entropy over all branches. Tests are made with the Lorenz-63 equations, showing good results both for the filter and the definition of prediction.
Resumo:
Analysis of the phylogenetic relationships among trypanosomes from vertebrates and invertebrates disclosed a new lineage of trypanosomes circulating among anurans and sand flies that share the same ecotopes in Brazilian Amazonia. This assemblage of closely related trypanosomes was determined by comparing whole SSU rDNA sequences of anuran trypanosomes from the Brazilian biomes of Amazonia, the Pantanal, and the Atlantic Forest and from Europe, North America, and Africa, and from trypanosomes of sand flies from Amazonia. Phylogenetic trees based on maximum likelihood and parsimony corroborated the positioning of all new anuran trypanosomes in the aquatic clade but did not support the monophyly of anuran trypanosomes. However, all analyses always supported four major clades (An01-04) of anuran trypanosomes. Clade An04 is composed of trypanosomes from exotic anurans. Isolates in clades An01 and An02 were from Brazilian frogs and toads captured in the three biomes studied, Amazonia, the Pantanal and the Atlantic Forest. Clade An01 contains mostly isolates from Hylidae whereas clade An02 comprises mostly isolates from Bufonidae; and clade An03 contains trypanosomes from sand flies and anurans of Bufonidae, Leptodactylidae, and Leiuperidae exclusively from Amazonia. To our knowledge, this is the first study describing morphological and growth features, and molecular phylogenetic affiliation of trypanosomes from anurans and phlebotomines, incriminating these flies as invertebrate hosts and probably also as important vectors of Amazonian terrestrial anuran trypanosomes.
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Sand fly populations of different ecological niches in the Amaraji endemic American Cutaneous Leishmaniasis (ACL) focus of the Pernambuco Atlantic Forest region of northeastern Brazil were monitored spatiotemporally. Lutzomyia whitmani was dominant in all niches but occurred in smaller numbers in forested locations. L. whitmani was significantly less seasonal than the other species, being present throughout the year while other species were more abundant between February and April. These results suggest that L. whitmani may potentially be the principal vector of ACL in the region, even though the sand fly fauna was diverse: 88% were L.whitmani and 12% belonged to 11 other species. Two other species, L. complexa (1.3%) and L. migonei (0.8%), considered to be ACL vectors in other regions, were also present. This detailed picture of the sand fly population`s abundance and spatiotemporal distribution provides a basis for future modeling studies of forecasting sand fly activity patterns and ACL occurence.
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This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.
Resumo:
Localization and Mapping are two of the most important capabilities for autonomous mobile robots and have been receiving considerable attention from the scientific computing community over the last 10 years. One of the most efficient methods to address these problems is based on the use of the Extended Kalman Filter (EKF). The EKF simultaneously estimates a model of the environment (map) and the position of the robot based on odometric and exteroceptive sensor information. As this algorithm demands a considerable amount of computation, it is usually executed on high end PCs coupled to the robot. In this work we present an FPGA-based architecture for the EKF algorithm that is capable of processing two-dimensional maps containing up to 1.8 k features at real time (14 Hz), a three-fold improvement over a Pentium M 1.6 GHz, and a 13-fold improvement over an ARM920T 200 MHz. The proposed architecture also consumes only 1.3% of the Pentium and 12.3% of the ARM energy per feature.
Resumo:
The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.
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This paper proposes a novel way to combine different observation models in a particle filter framework. This, so called, auto-adjustable observation model, enhance the particle filter accuracy when the tracked objects overlap without infringing a great runtime penalty to the whole tracking system. The approach has been tested under two important real world situations related to animal behavior: mice and larvae tracking. The proposal was compared to some state-of-art approaches and the results show, under the datasets tested, that a good trade-off between accuracy and runtime can be achieved using an auto-adjustable observation model. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
In this paper, the relationship between the filter coefficients and the scaling and wavelet functions of the Discrete Wavelet Transform is presented and exemplified from a practical point-of-view. The explanations complement the wavelet theory, that is well documented in the literature, being important for researchers who work with this tool for time-frequency analysis. (c) 2011 Elsevier Ltd. All rights reserved.