956 resultados para Automatic method


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Time-frequency analysis of various simulated and experimental signals due to elastic wave scattering from damage are performed using wavelet transform (WT) and Hilbert-Huang transform (HHT) and their performances are compared in context of quantifying the damages. Spectral finite element method is employed for numerical simulation of wave scattering. An analytical study is carried out to study the effects of higher-order damage parameters on the reflected wave from a damage. Based on this study, error bounds are computed for the signals in the spectral and also on the time-frequency domains. It is shown how such an error bound can provide all estimate of error in the modelling of wave propagation in structure with damage. Measures of damage based on WT and HHT is derived to quantify the damage information hidden in the signal. The aim of this study is to obtain detailed insights into the problem of (1) identifying localised damages (2) dispersion of multifrequency non-stationary signals after they interact with various types of damage and (3) quantifying the damages. Sensitivity analysis of the signal due to scattered wave based on time-frequency representation helps to correlate the variation of damage index measures with respect to the damage parameters like damage size and material degradation factors.

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Arc discharge between graphite electrodes under a relatively high pressure of hydrogen yields graphene flakes generally containing 2-4 layers in the inner wall region of the arc chamber. The graphene flakes so obtained have been characterized by X-ray diffraction, atomic force microscopy, transmission electron microscopy, and Raman spectroscopy. The method is eminently suited to dope graphene with boron and nitrogen by carrying out arc discharge in the presence of diborane and pyridine respectively.

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In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

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It is shown that prop-2-ynyl esters are useful protecting groups for carboxylic acids and that they are selectively deprotected in the presence of other esters on treatment with tetrathiomolybdate under mild conditions.

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A gyrostabiliser control system and method for stabilising marine vessel motion based on precession information only. The control system employs an Automatic Gain Control (AGC) precession controller (60). This system operates with a gain factor that is always being gradually minimized so as to let the gyro flywheel (12) develop as much precession as possible - the higher the precession, the higher the roll stabilising moment. This continuous gain change provides adaptation to changes in sea state and sailing conditions. The system effectively predicts the likelihood of maximum precession being reached. Should this event be detected, then the gain is rapidly increased so as to provide a breaking precession torque. Once the event has passed, the system again attempts to gradually decrease the gain.

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This paper presents a novel three-dimensional hybrid smoothed finite element method (H-SFEM) for solid mechanics problems. In 3D H-SFEM, the strain field is assumed to be the weighted average between compatible strains from the finite element method (FEM) and smoothed strains from the node-based smoothed FEM with a parameter α equipped into H-SFEM. By adjusting α, the upper and lower bound solutions in the strain energy norm and eigenfrequencies can always be obtained. The optimized α value in 3D H-SFEM using a tetrahedron mesh possesses a close-to-exact stiffness of the continuous system, and produces ultra-accurate solutions in terms of displacement, strain energy and eigenfrequencies in the linear and nonlinear problems. The novel domain-based selective scheme is proposed leading to a combined selective H-SFEM model that is immune from volumetric locking and hence works well for nearly incompressible materials. The proposed 3D H-SFEM is an innovative and unique numerical method with its distinct features, which has great potential in the successful application for solid mechanics problems.

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In this paper an attempt has been made to evaluate the spatial variability of the depth of weathered and engineering bedrock in Bangalore, south India using Multichannel Analysis of Surface Wave (MASW) survey. One-dimensional MASW survey has been carried out at 58 locations and shear-wave velocities are measured. Using velocity profiles, the depth of weathered rock and engineering rock surface levels has been determined. Based on the literature, shear-wave velocity of 330 ± 30 m/s for weathered rock or soft rock and 760 ± 60 m/s for engineering rock or hard rock has been considered. Depths corresponding to these velocity ranges are evaluated with respect to ground contour levels and top surface levels have been mapped with an interpolation technique using natural neighborhood. The depth of weathered rock varies from 1 m to about 21 m. In 58 testing locations, only 42 locations reached the depths which have a shear-wave velocity of more than 760 ± 60 m/s. The depth of engineering rock is evaluated from these data and it varies from 1 m to about 50 m. Further, these rock depths have been compared with a subsurface profile obtained from a two-dimensional (2-D) MASW survey at 20 locations and a few selected available bore logs from the deep geotechnical boreholes.

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Neural data are inevitably contaminated by noise. When such noisy data are subjected to statistical analysis, misleading conclusions can be reached. Here we attempt to address this problem by applying a state-space smoothing method, based on the combined use of the Kalman filter theory and the Expectation–Maximization algorithm, to denoise two datasets of local field potentials recorded from monkeys performing a visuomotor task. For the first dataset, it was found that the analysis of the high gamma band (60–90 Hz) neural activity in the prefrontal cortex is highly susceptible to the effect of noise, and denoising leads to markedly improved results that were physiologically interpretable. For the second dataset, Granger causality between primary motor and primary somatosensory cortices was not consistent across two monkeys and the effect of noise was suspected. After denoising, the discrepancy between the two subjects was significantly reduced.

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Quantifying the stiffness properties of soft tissues is essential for the diagnosis of many cardiovascular diseases such as atherosclerosis. In these pathologies it is widely agreed that the arterial wall stiffness is an indicator of vulnerability. The present paper focuses on the carotid artery and proposes a new inversion methodology for deriving the stiffness properties of the wall from cine-MRI (magnetic resonance imaging) data. We address this problem by setting-up a cost function defined as the distance between the modeled pixel signals and the measured ones. Minimizing this cost function yields the unknown stiffness properties of both the arterial wall and the surrounding tissues. The sensitivity of the identified properties to various sources of uncertainty is studied. Validation of the method is performed on a rubber phantom. The elastic modulus identified using the developed methodology lies within a mean error of 9.6%. It is then applied to two young healthy subjects as a proof of practical feasibility, with identified values of 625 kPa and 587 kPa for one of the carotid of each subject.

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Rupture of atherosclerotic plaque is a major cause of mortality. Plaque stress analysis, based on patient-specific multisequence in vivo MRI, can provide critical information for the understanding of plaque rupture and could eventually lead to plaque rupture prediction. However, the direct link between stress and plaque rupture is not fully understood. In the present study, the plaque from a patient who recently experienced a transient ischaemic attack (TIA) was studied using a fluid-structure interaction method to quantify stress distribution in the plaque region based on in vivo MR images. The results showed that wall shear stress is generally low in the artery with a slight increase at the plaque throat owing to minor luminal narrowing. The oscillatory shear index is much higher in the proximal part of the plaque. Both local wall stress concentrations and the relative stress variation distribution during a cardiac cycle indicate that the actual plaque rupture site is collocated with the highest rupture risk region in the studied patient.

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The mechanical properties of arterial walls have long been recognized to play an essential role in the development and progression of cardiovascular disease (CVD). Early detection of variations in the elastic modulus of arteries would help in monitoring patients at high cardiovascular risk stratifying them according to risk. An in vivo, non-invasive, high resolution MR-phase-contrast based method for the estimation of the time-dependent elastic modulus of healthy arteries was developed, validated in vitro by means of a thin walled silicon rubber tube integrated into an existing MR-compatible flow simulator and used on healthy volunteers. A comparison of the elastic modulus of the silicon tube measured from the MRI-based technique with direct measurements confirmed the method's capability. The repeatability of the method was assessed. Viscoelastic and inertial effects characterizing the dynamic response of arteries in vivo emerged from the comparison of the pressure waveform and the area variation curve over a period. For all the volunteers who took part in the study the elastic modulus was found to be in the range 50-250 kPa, to increase during the rising part of the cycle, and to decrease with decreasing pressure during the downstroke of systole and subsequent diastole.

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Direct precipitation of fine powders of lead zirconate titanate (PZT) in the complete range of solid solution, is investigated under hydrothermal conditions, starting from lead oxide and titania/zirconia mixed gels. The perovskite phase is formed in the temperature range of 165 – 340°C. Sequence of the hydrothermal reactions is studied by identifying the intermediate phases. The initial formation of PbO: TiO2 solid solution is followed by the reaction of the same with the remaining mixed gels giving rise to X-ray amorphous PZT phase. Further, through crystallite growth, the X-ray crystalline PZT is formed. This method can be extended for the preparation of PLZT powder as well. The resulting powders are sinterable to high density ceramics.

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The quality of ultrasound computed tomography imaging is primarily determined by the accuracy of ultrasound transit time measurement. A major problem in analysis is the overlap of signals making it difficult to detect the correct transit time. The current standard is to apply a matched-filtering approach to the input and output signals. This study compares the matched-filtering technique with active set deconvolution to derive a transit time spectrum from a coded excitation chirp signal and the measured output signal. The ultrasound wave travels in a direct and a reflected path to the receiver, resulting in an overlap in the recorded output signal. The matched-filtering and deconvolution techniques were applied to determine the transit times associated with the two signal paths. Both techniques were able to detect the two different transit times; while matched-filtering has a better accuracy (0.13 μs vs. 0.18 μs standard deviation), deconvolution has a 3.5 times improved side-lobe to main-lobe ratio. A higher side-lobe suppression is important to further improve image fidelity. These results suggest that a future combination of both techniques would provide improved signal detection and hence improved image fidelity.

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A modified method has been developed for the deposition of transparent semiconducting thin films of tin oxide, involving the chemical vapour phase oxidation of tin iodide. These films show sheet resistances greater than 100 Ω/□ and an average optical transmission in the visible range exceeding 80%. The method avoids uncontrolled contamination, resulting in better reproducibility of the films. The films showed direct and indirect transitions and the possibility of an indirect forbidden transition. X-ray diffraction studies reveal that the films are polycrystalline. The low mobility values of the films have been attributed to the grain boundary scattering effect.

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The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.