99 resultados para intra-day volume


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We analyze the dynamics of desorption of a polymer molecule which is pulled at one of its ends with force f, trying to desorb it. We assume a monomer to desorb when the pulling force on it exceeds a critical value f(c). We formulate an equation for the average position of the n-th monomer, which takes into account excluded-volume interaction through the blob-picture of a polymer under external constraints. The approach leads to a diffusion equation with a p-Laplacian for the propagation of the stretching along the chain. This has to be solved subject to a moving boundary condition. Interestingly, within this approach, the problem can be solved exactly in the trumpet, stem-flower and stem regimes. In the trumpet regime, we get tau = tau(0)n(d)(2), where n(d) is the number of monomers that have desorbed at the time tau. tau(0) is known only numerically, but for f close to f(c), it is found to be tau(0) similar to f(c)/(f(2/3) - f(c)(2/3)) If one used simple Rouse dynamics, this result would change to tau similar to f(c)n(d)(2)/(f - f(c)). In the other regimes too, one can find exact solution, and interestingly, in all regimes tau similar to n(d)(2). Copyright (C) EPLA, 2011

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In this paper, we present a new speech enhancement approach, that is based on exploiting the intra-frame dependency of discrete cosine transform (DCT) domain coefficients. It can be noted that the existing enhancement techniques treat the transformdomain coefficients independently. Instead of this traditional approach of independently processing the scalars, we split the DCT domain noisy speech vector into sub-vectors and each sub-vector is enhanced independently. Through this sub-vector based approach, the higher dimensional enhancement advantage, viz. non-linear dependency, is exploited. In the developed method, each clean speech sub-vector is modeled using a Gaussian mixture (GM) density. We show that the proposed Gaussian mixture model (GMM) based DCT domain method, using sub-vector processing approach, provides better performance than the conventional approach of enhancing the transform domain scalar components independently. Performance improvement over the recently proposed GMM based time domain approach is also shown.

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We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

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We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

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Web services are now a key ingredient of software services offered by software enterprises. Many standardized web services are now available as commodity offerings from web service providers. An important problem for a web service requester is the web service composition problem which involves selecting the right mix of web service offerings to execute an end-to-end business process. Web service offerings are now available in bundled form as composite web services and more recently, volume discounts are also on offer, based on the number of executions of web services requested. In this paper, we develop efficient algorithms for the web service composition problem in the presence of composite web service offerings and volume discounts. We model this problem as a combinatorial auction with volume discounts. We first develop efficient polynomial time algorithms when the end-to-end service involves a linear workflow of web services. Next we develop efficient polynomial time algorithms when the end-to-end service involves a tree workflow of web services.

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The paper brings out the role of calcium carbonate (CaCO3) on the volume change behaviour of natural black cotton soil with 1N sulfuric acid (H2SO4) as pore fluid. Natural black cotton soil contained predominantly montmorillonite [Ca0.2(Al,Mg)2Si4 O10 (OH)2 .4H2O] along with other minerals such as amesite [(Mg Fe)2 Al (Si Al)2 O5 (OH)4], kalsilite [KAlSiO4] and quartz [SiO2]. The calcitic soil, reacted with H2SO4 during consolidation testing, showed the presence of the new mineral yavapaiite [K Fe(SO4)2]. Consequently, the carbonate soil treated with 1N H2SO4 led to higher swell at seating load and more compression upon loading than the soil with no carbonate. The swelling increased with increase in the amount of carbonate present in the soil.

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This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.

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Nuclear electro-magnetic pulse (NEMP) simulators which are used in the simulation of transient electromagnetic fields due to a high altitude nuclear detonation are generally excited with a double exponential high voltage pulse. This results in a current distribution on the wires of the simulator and hence a transient electric field in the working volume of the simulator where the test object is kept. It is found that for the simulator under study, the current distribution is non-uniform and so is the field distribution along the width of the simulator in the working volume. To make the current distribution uniform, several methods have been suggested and the results of these methods are analyzed and suitable conclusions are arrived at from those results.

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The tie lines delineating ion-exchange equilibria between FeCr2O4FeAl2O4 spinel solid solution and Cr2O3Al2O3 solid solution with corundum structure have been determined at 1373 K by electron microprobe and EDAX point count analysis of oxide phases equilibrated with metallic iron. Activities in the spinel solid solution are derived from the tie lines and the thermodynamic data on Cr2O3Al2O3 solid solution available in the literature. The oxygen potentials corresponding to the tie-line composition of oxide phases in equilibrium with metallic iron were measured using solid oxide galvanic cells with CaOZrO2 and Y2O3ThO2 electrolytes. These electrochemical measurements also yield activities in the spinel solid solution, in good agreement with those obtained from tie lines. The activity-composition relationship in the spinel solid solution is analysed in terms of the intra-crystalline ion exchange between the tetrahedral and octahedral sites of the spinel structures. The ion exchange is governed by site-preference energies of the cations and the entropy of cations mixing on each site.

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Objective: To study the antihyperlipidemic effect of Cedrus deodara (C. deodara) against monosodium glutamate (MSG) induced obesity in neonatal rats. Materials and Methods: The studies were carried out on newborn neonatal rats and were injected intraperitoneally with 2 mg/g of MSG on the 2(nd) and 4(th) postnatal days and 4 mg/g on 6(th), 8(th) and 10(th) postnatal days. Ethanolic extract (EE) and acetone extract (AE) of C. deodara was administered in a dose of 100 and 200 mg/kg, p.o./day at the age of 65 days. On day 60 of treatment, body weight, locomotor activity, body temperature, and various biochemical parameters like serum glucose, total cholesterol, triglyceride, and organs weights were recorded. Results: There was a significant reduction in body weight, organs and increased body temperature, locomotor activity after treatment with extracts. C. deodara decreased serum glucose, total cholesterol and triglyceride, low density lipoprotein (LDL) and very low density lipoprotein (VLDL) levels and increased high density lipoprotein (HDL) significantly has compared to MSG-control rats. Conclusion: C. deodara extracts exhibited antihyperlipidemic effect and it possesses anti-obesity properties in MSG induced obese rats.

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Objective: This study was undertaken to evaluate the neuroprotective activity of Wedelia calendulacea against cerebral ischemia/reperfusion induced oxidative stress in the rats. Materials and Methods: The global cerebral ischemia was induced in male albino Wistar rats by occluding the bilateral carotid arteries for 30 min followed by 1 h and 4 h reperfusion. At various times of reperfusion, the histopathological changes and the levels of malondialdehyde (MDA), glutathione peroxidase (GPx), glutathione reductase (GR), glutathione-s-transferase (GST), and hydrogen peroxide (H(2)O(2)) activity and brain water content were measured. Results: The ischemic changes were preceded by increase in concentration of MDA, hydrogen peroxide and followed by decreased GPx, GR, and GST activity. Treatment with W. calendulacea significantly attenuated ischemia-induced oxidative stress. W. calendulacea administration markedly reversed and restored to near normal level in the groups pre-treated with methanolic extract (250 and 500 mg/kg, given orally in single and double dose/day for 10 days) in dose-dependent way. Similarly, W. calendulacea reversed the brain water content in the ischemia reperfusion animals. The neurodegenaration also conformed by the histopathological changes in the cerebral-ischemic animals. Conclusion: The findings from the present investigation reveal that W. calendulacea protects neurons from global cerebral-ischemic injury in rat by attenuating oxidative stress.

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A technique is proposed for classifying respiratory volume waveforms(RVW) into normal and abnormal categories of respiratory pathways. The proposed method transforms the temporal sequence into frequency domain by using an orthogonal transform, namely discrete cosine transform (DCT) and the transformed signal is pole-zero modelled. A Bayes classifier using model pole angles as the feature vector performed satisfactorily when a limited number of RVWs recorded under deep and rapid (DR) manoeuvre are classified.