64 resultados para Abrupt edges removal


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High-Tc superconducting thin films can be deposited and processed by pulsed and CW lasers, and a respectable materials technology for the Y-Ba-Cu-O superconductor is rapidly emerging. The pulsed laser deposition technique is simple because it produces films with compositions nearly identical to those of the target pellets. A larger variety of substrates can be used, compared to other deposition technologies, because of the relatively low temperature requirements. The laser deposition mechanism has been investigated. As-deposited superconducting films, epitaxial films with smooth surfaces, and multilayer structures with abrupt interfaces have been produced. The electrical transport properties can be changed locally using a focused argon-ion laser by modifying the oxygen stoichiometry. This laser writing can be erased by room-temperature exposure to an oxygen plasma. Other laser patterning methods such as material removal, melt-quench, and direct pattern transfer are being developed.

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A commercial acrylic fiber with 92% (w/w) acrylonitrile content was partially hydrolyzed converting a fraction of the nitrile (-CN) groups to carboxylic acid (-COOH) groups, to coat the fiber with polyethylenimine (PEI) resin, which was then crosslinked with glutaraldehyde and further quaternized with ethyl chloroacetate to produce a novel strong-base anionic exchanger in the form of fiber. Designated as PAN(QPEI.XG)(Cl-), the fibrous sorbent was compared with a commercial bead-form resin Amberlite IRA-458(Cl-) in respect of sorption capacity, selectivity, and kinetics for removal of silver thiosulfate complexes from aqueous solutions. Though the saturation level of [Ag(S2O3)(2)](3-) on PAN(QPEI.XG)(Cl-) is considerably less than that on IRA-458(Cl-), the gel-coated fibrous sorbent exhibits, as compared to the bead-form sorbent, a significantly higher sorption selectivity for the silver thiosulfate complex in the presence of excess of other anions Such as S2O32-, SO42-, and Cl-, and a remarkably faster rate of both sorption and stripping. The initial uptake of the sorbate by the fibrous sorbent is nearly instantaneous, reaching up to similar to 80% of the saturation capacity within 10 s, as compared to only similar to 12% on the bead-form sorbent. The high initial rate of uptake fits a shell-core kinetic model for sorption on fiber of cylindrical geometry. With 4M HCl, the stripping of the sorbed silver complex from the fibrous sorbent is clean and nearly instantaneous, while, in contrast, a much slower rate of stripping on the bead-form sorbent leads to its fouling due to a slow decomposition of the silver thiosulfate complex in the acidic medium.

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The utility of rice husk as an adsorbent for metal ions such as iron, zinc and copper from acid mine water was assessed. The adsorption isotherms exhibited Langmuirian behavior and were endothermic in nature. The free energy values for adsorption of the chosen metal ions onto rice husk were found to be highly negative attesting to favorable interaction. Over 99% Fe3+, 98% of Fe2+ and Zn2+ and 95% Cu2+ uptake was achieved from acid mine water, with a concomitant increase in the pH value by two units using rice husk. The remediation studies carried out on acid mine water and simulated acid mine water pretreated with rice husk indicated successful growth of Desulfotomaculum nigrificans (D. nigrificans). The amount of sulphate bioreduction in acid mine water at an initial pH of 5.3 was enhanced by D. nigrificans from 21% to 40% in the presence of rice husk filtrate supplemented with carbon and nitrogen. In simulated acid mine water with fortified husk filtrate, the sulphate reduction was even more extensive, with an enhancement to 73%. Concurrently, almost 90% Fe2+, 89% Zn2+ and 75% Cu2+ bioremoval was attained from simulated acid mine water. Metal adsorption by rice husk was confirmed in desorption experiments in which almost complete removal of metal ions from the rice husk was achieved after two elutions using 1 M HCl. The possible mechanisms of metal ion adsorption onto rice husk and sulphate reduction using D. nigrificans are discussed.

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The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

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In this paper, we propose a systolic architecture for hidden-surface removal. Systolic architecture is a kind of parallel architecture best known for its easy VLSI implementability. After discussing the design details of the architecture, we present the results of the simulation experiments conducted in order to evaluate the performance of the architecture.

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The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

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X-ray absorption spectra at the oxygen K edge using the total yield technique are reported for YBa2Cu3O6.9 and YBa2Cu2.7Fe0.3O6.9. A comparison of the two spectra reveals that the mobile holes in YBa2Cu3O7-δ are removed and localized on Fe doping. Fe thus enters the lattice primarily in the formally trivalent oxidation state.

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Removal of impurity elements from hot metal is essential in basic oxygen steelmaking. Oxidation of phosphorus from hot metal has been studied by several authors since the early days of steelmaking. Influence of different parameters on the distribution of phosphorus, seen during the recent work of the authors, differs somewhat from that reported earlier. On the other hand, removal of sulphur during steelmaking has drawn much less attention. This may be due to the magnitude of desulphurisation in oxygen steelmaking being relatively low and desulphurisation during hot metal pre-treatment or in the ladle furnace offering better commercial viability Further, it is normally accepted that sulphur is removed to steelmaking slag in the form of sulphide only However, recent investigations have indicated that a significant amount of sulphur removed during basic oxygen steelmaking can exist in the form of sulphate in the slag under oxidising conditions. The distribution of sulphur during steelmaking becomes more important in the event of carry-over of sulphur-rich blast-furnace slag, which increases sulphur load in the BOF. The chemical nature of sulphur in this slag undergoes a gradual transition from sulphide to sulphate as the oxidative refining progresses.

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The potential to remove chromium(VI) from aqueous solutions through biosorption using coffee husk was investigated. The effects of pH, contact time, initial concentration and adsorbent dosage on the adsorption of Cr(VI) were studied. The data obeyed Langmuir and Freundlich adsorption isotherms. The Langmuir adsorption capacity was found to be 44.95 mg/g. The Freundlich constants K-f and n were 1.027 mg/g (litre/mg)(n)] and 1.493, respectively. Desorption studies indicated the removal of 60% of the hexavalent chromium. Infrared spectral studies revealed the presence of functional groups, such as hydroxyl and carboxyl groups, on the surface of the biomass, which facilitates biosorption of Cr(VI).

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A detailed experimental and simulation study has been carried out in the present work to understand drop breakup in regions around the edge of the Rushton turbine in agitated vessels. The effect of impeller speed, impeller size, interfacial tension, and the viscosities of the two phases is studied on drop breakup through their effect on dmax, the size of the largest drop in the system, and the whole size distribution. The measurements were carried out using Galai particle size analyser and optical microscope. Experimental analysis shows that the dmax, maximum stable drop diameter varies with impeller tip velocity to the power -1. The variation of dmax with interfacial tension is studied using different surfactants. The effect of viscosity ratio, achieved by changing the dispersed phase viscosity, on dmax is captured. For the same dmax values obtained from two different dispersed phases show that the wider drop size distribution is observed for higher dispersed phase viscosity.

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With the advent of VLSI it has become possible to map parallel algorithms for compute-bound problems directly on silicon. Systolic architecture is very good candidate for VLSI implementation because of its regular and simple design, and regular communication pattern. In this paper, a systolic algorithm and corresponding systolic architecture, a linear systolic array, for the scanline-based hidden surface removal problem in three-dimensional computer graphics have been proposed. The algorithm is based on the concept of sample spans or intervals. The worst case time taken by the algorithm is O(n), n being the number of segments in a scanline. The time taken by the algorithm for a given scene depends on the scene itself, and on an average considerable improvement over the worst case behaviour is expected. A pipeline scheme for handling the I/O process has also been proposed which is suitable for VLSI implementation of the algorithm.

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In a number of applications of computerized tomography, the ultimate goal is to detect and characterize objects within a cross section. Detection of edges of different contrast regions yields the required information. The problem of detecting edges from projection data is addressed. It is shown that the class of linear edge detection operators used on images can be used for detection of edges directly from projection data. This not only reduces the computational burden but also avoids the difficulties of postprocessing a reconstructed image. This is accomplished by a convolution backprojection operation. For example, with the Marr-Hildreth edge detection operator, the filtering function that is to be used on the projection data is the Radon transform of the Laplacian of the 2-D Gaussian function which is combined with the reconstruction filter. Simulation results showing the efficacy of the proposed method and a comparison with edges detected from the reconstructed image are presented