98 resultados para Maximum modulus princple


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Electromagnetic Articulography (EMA) technique is used to record the kinematics of different articulators while one speaks. EMA data often contains missing segments due to sensor failure. In this work, we propose a maximum a-posteriori (MAP) estimation with continuity constraint to recover the missing samples in the articulatory trajectories recorded using EMA. In this approach, we combine the benefits of statistical MAP estimation as well as the temporal continuity of the articulatory trajectories. Experiments on articulatory corpus using different missing segment durations show that the proposed continuity constraint results in a 30% reduction in average root mean squared error in estimation over statistical estimation of missing segments without any continuity constraint.

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In this paper the effects of crystallographic texture and microstructure on the elastic modulus of different grades of steel have been collected from the available literature and put in one place. It is expected that this will help researchers in their understanding of both the fundamental and the practical aspects of the different grades of steel used for various purposes.

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The work presented in this paper involves the stochastic finite element analysis of composite-epoxy adhesive lap joints using Monte Carlo simulation. A set of composite adhesive lap joints were prepared and loaded till failure to obtain their strength. The peel and shear strain in the bond line region at different levels of load were obtained using digital image correlation (DIC). The corresponding stresses were computed assuming a plane strain condition. The finite element model was verified by comparing the numerical and experimental stresses. The stresses exhibited a similar behavior and a good correlation was obtained. Further, the finite element model was used to perform the stochastic analysis using Monte Carlo simulation. The parameters influencing stress distribution were provided as a random input variable and the resulting probabilistic variation of maximum peel and shear stresses were studied. It was found that the adhesive modulus and bond line thickness had significant influence on the maximum stress variation. While the adherend thickness had a major influence, the effect of variation in longitudinal and shear modulus on the stresses was found to be little. (C) 2014 Elsevier Ltd. All rights reserved.

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Modulus variation of NiTi shape memory alloy has been investigated at microstructural level through nano dynamical mechanical analysis and compared with bulk experimental measurements. The differences between the modulus values at the macro and micro level as well as within the micro level are discussed and the corresponding variations have been explained based on the crystal structure, orientation and misorientation. The experimental results confirm a higher modulus value for the martensite phase that is in agreement with the theoretical predictions. (C) 2015 Elsevier B. V. All rights reserved.

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This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

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In this study, branched poly(ethyleneimine), BPEI, was synthesized from carboxylic acid terminated multi-walled carbon nanotubes (c-MWNTs) and characterized using FTIR, TEM and TGA. The BPEI was then chemically grafted onto MWNTs to enhance the interfacial adhesion with the epoxy matrix. The epoxy composites with c-MWNTs and the BPEI-g-MWNTs were prepared using a sonication and mechanical stirring method, followed by curing at 100 degrees C and post-curing at 120 degrees C. The dynamic mechanical thermal analysis showed an impressive 49% increment in the storage elastic modulus in the composites. In addition, the nanoindentation on the composites exhibited significant improvement in the hardness and decrease in the plasticity index in the presence of the BPEI-g-MWNTs. Thus, epoxy composites with BPEI-g-MWNTs can be further explored as self-healing materials.

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An iterative image reconstruction technique employing B-Spline potential function in a Bayesian framework is proposed for fluorescence microscopy images. B-splines are piecewise polynomials with smooth transition, compact support and are the shortest polynomial splines. Incorporation of the B-spline potential function in the maximum-a-posteriori reconstruction technique resulted in improved contrast, enhanced resolution and substantial background reduction. The proposed technique is validated on simulated data as well as on the images acquired from fluorescence microscopes (widefield, confocal laser scanning fluorescence and super-resolution 4Pi microscopy). A comparative study of the proposed technique with the state-of-art maximum likelihood (ML) and maximum-a-posteriori (MAP) with quadratic potential function shows its superiority over the others. B-Spline MAP technique can find applications in several imaging modalities of fluorescence microscopy like selective plane illumination microscopy, localization microscopy and STED. (C) 2015 Author(s).

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We propose an algorithmic technique for accelerating maximum likelihood (ML) algorithm for image reconstruction in fluorescence microscopy. This is made possible by integrating Biggs-Andrews (BA) method with ML approach. The results on widefield, confocal, and super-resolution 4Pi microscopy reveal substantial improvement in the speed of 3D image reconstruction (the number of iterations has reduced by approximately one-half). Moreover, the quality of reconstruction obtained using accelerated ML closely resembles with nonaccelerated ML method. The proposed technique is a step closer to realize real-time reconstruction in 3D fluorescence microscopy. Microsc. Res. Tech. 78:331-335, 2015. (c) 2015 Wiley Periodicals, Inc.

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Probable maximum precipitation (PMP) is a theoretical concept that is widely used by hydrologists to arrive at estimates for probable maximum flood (PMF) that find use in planning, design and risk assessment of high-hazard hydrological structures such as flood control dams upstream of populated areas. The PMP represents the greatest depth of precipitation for a given duration that is meteorologically possible for a watershed or an area at a particular time of year, with no allowance made for long-term climatic trends. Various methods are in use for estimation of PMP over a target location corresponding to different durations. Moisture maximization method and Hershfield method are two widely used methods. The former method maximizes the observed storms assuming that the atmospheric moisture would rise up to a very high value estimated based on the maximum daily dew point temperature. On the other hand, the latter method is a statistical method based on a general frequency equation given by Chow. The present study provides one-day PMP estimates and PMP maps for Mahanadi river basin based on the aforementioned methods. There is a need for such estimates and maps, as the river basin is prone to frequent floods. Utility of the constructed PMP maps in computing PMP for various catchments in the river basin is demonstrated. The PMP estimates can eventually be used to arrive at PMF estimates for those catchments. (C) 2015 The Authors. Published by Elsevier B.V.

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The main objective of the paper is to develop a new method to estimate the maximum magnitude (M (max)) considering the regional rupture character. The proposed method has been explained in detail and examined for both intraplate and active regions. Seismotectonic data has been collected for both the regions, and seismic study area (SSA) map was generated for radii of 150, 300, and 500 km. The regional rupture character was established by considering percentage fault rupture (PFR), which is the ratio of subsurface rupture length (RLD) to total fault length (TFL). PFR is used to arrive RLD and is further used for the estimation of maximum magnitude for each seismic source. Maximum magnitude for both the regions was estimated and compared with the existing methods for determining M (max) values. The proposed method gives similar M (max) value irrespective of SSA radius and seismicity. Further seismicity parameters such as magnitude of completeness (M (c) ), ``a'' and ``aEuro parts per thousand b `` parameters and maximum observed magnitude (M (max) (obs) ) were determined for each SSA and used to estimate M (max) by considering all the existing methods. It is observed from the study that existing deterministic and probabilistic M (max) estimation methods are sensitive to SSA radius, M (c) , a and b parameters and M (max) (obs) values. However, M (max) determined from the proposed method is a function of rupture character instead of the seismicity parameters. It was also observed that intraplate region has less PFR when compared to active seismic region.

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We use Floquet theory to study the maximum value of the stroboscopic group velocity in a one-dimensional tight-binding model subjected to an on-site staggered potential varying sinusoidally in time. The results obtained by numerically diagonalizing the Floquet operator are analyzed using a variety of analytical schemes. In the low-frequency limit we use adiabatic theory, while in the high-frequency limit the Magnus expansion of the Floquet Hamiltonian turns out to be appropriate. When the magnitude of the staggered potential is much greater or much less than the hopping, we use degenerate Floquet perturbation theory; we find that dynamical localization occurs in the former case when the maximum group velocity vanishes. Finally, starting from an ``engineered'' initial state where the particles (taken to be hard-core bosons) are localized in one part of the chain, we demonstrate that the existence of a maximum stroboscopic group velocity manifests in a light-cone-like spreading of the particles in real space.

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This paper reports on the effect of multiwall carbon nanotubes (CNTs) without and with chemical functionalization on the mechanical properties of Bisphenol E cyanate ester resin (BECy) based carbon fibre reinforced plastic (CFRP) laminated composites. BECy with its low viscosity, low moisture uptake and superior mechanical properties is selected for its application in CFRP laminates through the cost-effective Vacuum Assisted Resin Transfer Moulding (VARTM) process. However, unlike CNT-epoxy-CFRP composites, processing and performance issues such as dispersion of CNTs, chemical bonding with resin, functionalization effects, effects on mechanical properties, etc. for BECy-CNT-CFRP composite system are not well reported. The objective of this study is to improve the mechanical properties of BECy resin with small additions of CNTs and functionalized CNTs in CFRP laminates. CNTs and fCNTs are infused into BECy using ultrasonication and standard mixing methods. Improvements in Young's modulus and strength in tension, compression, shear, flexure and interlaminar shear strength are analysed. It is observed that addition of 0.5wt% CNTs effected for maximum mechanical properties of the resin and 1wt% CNTs for the mechanical properties of CNT-CFRP nanocomposite. Further, improvements obtained with fCNTs are marginal. Dispersion behaviour and effect of CNTs/fCNTs in load transfer corroborated with SEM pictures are presented. The enhanced mechanical properties realized in VARTM processing of BECy-CFRP laminate indicate clear advantage of CNT based modification of the process.

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Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.

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Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

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Transition metal atom (Co) substituted synthetic tetrahedrite compounds Cu12-xCoxSb4S13 (x = 0, 0.5, 1.0, 1.5, 2.0) were prepared by solid state synthesis. X-Ray Diffraction (XRD) patterns revealed tetrahedrite as the main phase, whereas for the compounds with x = 0, 0.5 a trace of impurity phase Cu3SbS4 was observed. The surface morphology showed a large grain size with low porosity, which indicated appropriate compaction for the hot pressed samples. The phase purity, as monitored by Electron Probe Micro Analysis (EPMA) is in good agreement with the XRD data. The elemental composition for all the compounds almost matched with the nominal composition. The X-ray Photoelectron Spectroscopy (XPS) data showed that Cu existed in both +1 and +2 states, while Sb exhibited +3 oxidation states. Elastic modulus and hardness showed a systematic variation with increasing Co content. The electrical resistivity and Seebeck coefficient increased with increase in the doping content due to the decrease in the number of carriers caused by the substitution of Co2+ on the Cu1+ site. The positive Seebeck coefficient for all samples indicates that the dominant carriers are holes. A combined effect of resistivity and Seebeck coefficient leads to the maximum power factor of 1.76 mW m(-1) K-2 at 673 K for Cu11.5Co0.5Sb4S13. This could be due to the optimization in the carrier concentration by the partial substitution of Co2+ on both the Cu1+ as well as Cu2+ site at the same doping levels, which is also supported by the XPS data. The total thermal conductivity systematically decreased with increase of doping content as it is mainly influenced by the decrease of carrier thermal conductivity. The maximum thermoelectric figure of merit zT = 0.98 was obtained at 673 K for Cu11.5Co0.5Sb4S13. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.