940 resultados para noise level


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This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation sigma of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum sigma also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum sigma depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. (C) 2012 Elsevier B.V. All rights reserved.

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In this paper, a new three-phase, five-level inverter topology with a single-dc source is presented. The proposed topology is obtained by cascading a three-level flying capacitor inverter with a flying H-bridge power cell in each phase. This topology has redundant switching states for generating different pole voltages. By selecting appropriate switching states, the capacitor voltages can be balanced instantaneously (as compared to the fundamental) in any direction of the current, irrespective of the load power factor. Another important feature of this topology is that if any H-bridge fails, it can be bypassed and the configuration can still operate as a three-level inverter at its full power rating. This feature improves the reliability of the circuit. A 3-kW induction motor is run with the proposed topology for the full modulation range. The effectiveness of the capacitor balancing algorithm is tested for the full range of speed and during the sudden acceleration of the motor.

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In this work, we propose an approach for reducing radiated noise from `light' fluid-loaded structures, such as, for example, vibrating structures in air. In this approach, we optimize the structure so as to minimize the dynamic compliance (defined as the input power) of the structure. We show that minimizing the dynamic compliance results in substantial reductions in the radiated sound power from the structure. The main advantage of this approach is that the redesign to minimize the dynamic compliance moves the natural frequencies of the structure away from the driving frequency thereby reducing the vibration levels of the structure, which in turn results in a reduction in the radiated sound power as an indirect benefit. Thus, the need for an acoustic and the associated sensitivity analysis is completely bypassed (although, in this work, we do carry out an acoustic analysis to demonstrate the reduction in sound power levels), making the strategy efficient compared to existing strategies in the literature which try to minimize some measure of noise directly. We show the effectiveness of the proposed approach by means of several examples involving both topology and stiffener optimization, for vibrating beam, plate and shell-type structures.

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We show that it is possible to change from a subnatural electromagnetically induced transparency (EIT) feature to a subnatural electromagnetically induced absorption (EIA) feature in a (degenerate) three-level. system. The change is effected by turning on a second control beam counter-propagating with respect to the first beam. We observe this change in the D-2 line of Rb in a room temperature vapor cell. The observations are supported by density-matrix analysis of the complete sublevel structure including the effect of Doppler averaging, but can be understood qualitatively as arising due to the formation of N-type systems with the two control beams. Since many of the applications of EIT and EIA rely on the anomalous dispersion near the resonances, this introduces a new ability to control the sign of the dispersion. Copyright (C) EPLA, 2012

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In the recent past, there have been enormous efforts to understand effect of drugs on human body. Prior to understand the effect of drugs on human body most of the experiments are carried out on cells or model organisms. Here we present our study on the effect of chemotherapeutic drugs on cancer cells and the acetaminophen (APAP) induced hepatotoxicity in mouse model. Histone deacetylase inhibitors (HDIs) have attracted attention as potential drug molecules for the treatment of cancer. These are the chemotherapeutic drugs which have indirect mechanistic action against cancer cells via acting against histone deacetylases (HDAC). It has been known that different HDAC enzymes are over-expressed in various types of cancers for example; HDAC1 is over expressed in prostate, gastric and breast carcinomas. Therefore, in order to optimise chemotherapy, it is important to determine the efficacy of various classes of HDAC inhibitor drugs against variety of over-expressed HDAC enzymes. In the present study, FTIR microspectroscopy has been employed to predict the acetylation and propionylation brought in by HDIs. The liver plays an important role in cellular metabolism and is highly susceptible to drug toxicity. APAP which is an analgesic and antipyretic drug is extensively used for therapeutic purposes and has become the most common cause of acute liver failure (ALF). In the current study, we have focused to understand APAP induced hepatotoxicity using FTIR microspectroscopy. In the IR spectrum the bands corresponding to glycogen, ester group and were found to be suitable markers to predict liver injury at early time point (0.5hr) due to APAP both in tissue and serum in comparison to standard biochemical assays. Our studies show the potential of FTIR spectroscopy as a rapid, sensitive and non invasive detection technique for future clinical diagnosis.

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Purpose: To optimize the data-collection strategy for diffuse optical tomography and to obtain a set of independent measurements among the total measurements using the model based data-resolution matrix characteristics. Methods: The data-resolution matrix is computed based on the sensitivity matrix and the regularization scheme used in the reconstruction procedure by matching the predicted data with the actual one. The diagonal values of data-resolution matrix show the importance of a particular measurement and the magnitude of off-diagonal entries shows the dependence among measurements. Based on the closeness of diagonal value magnitude to off-diagonal entries, the independent measurements choice is made. The reconstruction results obtained using all measurements were compared to the ones obtained using only independent measurements in both numerical and experimental phantom cases. The traditional singular value analysis was also performed to compare the results obtained using the proposed method. Results: The results indicate that choosing only independent measurements based on data-resolution matrix characteristics for the image reconstruction does not compromise the reconstructed image quality significantly, in turn reduces the data-collection time associated with the procedure. When the same number of measurements (equivalent to independent ones) are chosen at random, the reconstruction results were having poor quality with major boundary artifacts. The number of independent measurements obtained using data-resolution matrix analysis is much higher compared to that obtained using the singular value analysis. Conclusions: The data-resolution matrix analysis is able to provide the high level of optimization needed for effective data-collection in diffuse optical imaging. The analysis itself is independent of noise characteristics in the data, resulting in an universal framework to characterize and optimize a given data-collection strategy. (C) 2012 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4736820]

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Voltage source inverters (VSIs) supply nonsinusoidal voltages to induction motor drives, leading to line current distortion and torque pulsation. Conventional space vector pulsewidth modulation (PWM) techniques are widely used in VSIs on the account of good waveform quality and high dc bus utilization. In a conventional space vector PWM technique, the switching sequence begins with one zero state and ends with the other zero state in a subcycle. Some novel switching sequences have been proposed, which employ only one zero state but apply one of the two active states twice in a subcycle. One pair of such special switching sequences has recently been shown to reduce the pulsating torque considerably. In this paper, the conventional and special switching sequences are compared experimentally in terms of acoustic noise. In the low-and medium-speed ranges, the special switching sequence is seen to reduce the amplitude of the tonal component of noise at the switching frequency considerably and is also found to result in spread spectrum.

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We investigate the impact of the Indian Ocean Dipole (IOD) and El Nino and the Southern Oscillation (ENSO) on sea level variations in the North Indian Ocean during 1957-2008. Using tide-gauge and altimeter data, we show that IOD and ENSO leave characteristic signatures in the sea level anomalies (SLAs) in the Bay of Bengal. During a positive IOD event, negative SLAs are observed during April-December, with the SLAs decreasing continuously to a peak during September-November. During El Nino, negative SLAs are observed twice (April-December and November-July), with a relaxation between the two peaks. SLA signatures during negative IOD and La Nina events are much weaker. We use a linear, continuously stratified model of the Indian Ocean to simulate their sea level patterns of IOD and ENSO events. We then separate solutions into parts that correspond to specific processes: coastal alongshore winds, remote forcing from the equator via reflected Rossby waves, and direct forcing by interior winds within the bay. During pure IOD events, the SLAs are forced both from the equator and by direct wind forcing. During ENSO events, they are primarily equatorially forced, with only a minor contribution from direct wind forcing. Using a lead/lag covariance analysis between the Nino-3.4 SST index and Indian Ocean wind stress, we derive a composite wind field for a typical El Nino event: the resulting solution has two negative SLA peaks. The IOD and ENSO signatures are not evident off the west coast of India.

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Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change ``signal'' in the hydrological observations, above the natural internal climate variability ``noise'' shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.

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In space application the precision level measurement of cryogenic liquids in the storage tanks is done using triple redundant capacitance level sensor, for control and safety point of view. The linearity of each sensor element depends upon the cylindricity and concentricity of the internal and external electrodes. The complexity of calibrating all sensors together has been addressed by two step calibration methodology which has been developed and used for the calibration of six capacitance sensors. All calibrations are done using Liquid Nitrogen (LN2) as a cryogenic fluid. In the first step of calibration, one of the elements of Liquid Hydrogen (LH2) level sensor is calibrated using 700mm eleven point discrete diode array. Four wire method has been used for the diode array. Thus a linearity curve for a single element of LH2 is obtained. In second step of calibration, using the equation thus obtained for the above sensor, it is considered as a reference for calibrating remaining elements of the same LH2 sensor and other level sensor (either Liquid Oxygen (LOX) or LH2). The elimination of stray capacitance for the capacitance level probes has been attempted. The automatic data logging of capacitance values through GPIB is done using LabVIEW 8.5.

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This study proposes an inverter circuit topology capable of generating multilevel dodecagonal (12-sided polygon) voltage space vectors by the cascaded connection of two-level and three-level inverters. By the proper selection of DC-link voltages and resultant switching states for the inverters, voltage space vectors whose tips lie on three concentric dodecagons, are obtained. A rectifier circuit for the inverter is also proposed, which significantly improves the power factor. The topology offers advantages such as the complete elimination of the fifth and seventh harmonics in phase voltages and an extension of the linear modulation range. In this study, a simple method for the calculation of pulse width modulation timing was presented along with extensive simulation and experimental results in order to validate the proposed concept.

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A new hybrid five-level inverter topology with common-mode voltage (CMV) elimination for induction motor drive is proposed in this paper. This topology has only one dc source, and different voltage levels are generated by using this voltage source along with floating capacitors charged to asymmetrical voltage levels. The pulsewidth modulation (PWM) scheme employed in this topology balances the capacitor voltages at the required levels at any power factor and modulation index while eliminating the CMV. This inverter has good fault-tolerant capability as it can be operated in three-or two-level mode with CMV elimination, in case of any failure in the H-bridges. More voltage levels with CMV elimination can be realized from this topology but only in a limited range of modulation index and power factor. Extensive simulation is done to validate the PWM technique for CMV elimination and balancing of the capacitor voltages. The experimental verification of the proposed inverter-fed induction motor is carried out in the linear modulation and overmodulation regions. The steady-state and transient operations of the drive are verified. The dynamics of the capacitor voltage balancing is also tested. The experimental results demonstrate that the proposed topology can be considered for industrial drive applications.

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The classical approach to A/D conversion has been uniform sampling and we get perfect reconstruction for bandlimited signals by satisfying the Nyquist Sampling Theorem. We propose a non-uniform sampling scheme based on level crossing (LC) time information. We show stable reconstruction of bandpass signals with correct scale factor and hence a unique reconstruction from only the non-uniform time information. For reconstruction from the level crossings we make use of the sparse reconstruction based optimization by constraining the bandpass signal to be sparse in its frequency content. While overdetermined system of equations is resorted to in the literature we use an undetermined approach along with sparse reconstruction formulation. We could get a reconstruction SNR > 20dB and perfect support recovery with probability close to 1, in noise-less case and with lower probability in the noisy case. Random picking of LC from different levels over the same limited signal duration and for the same length of information, is seen to be advantageous for reconstruction.

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Intrinsically disordered proteins, IDPs, are proteins that lack a rigid 3D structure under physiological conditions, at least in vitro. Despite the lack of structure, IDPs play important roles in biological processes and transition from disorder to order upon binding to their targets. With multiple conformational states and rapid conformational dynamics, they engage in myriad and often ``promiscuous'' interactions. These stochastic interactions between IDPs and their partners, defined here as conformational noise, is an inherent characteristic of IDP interactions. The collective effect of conformational noise is an ensemble of protein network configurations, from which the most suitable can be explored in response to perturbations, conferring protein networks with remarkable flexibility and resilience. Moreover, the ubiquitous presence of IDPs as transcriptional factors and, more generally, as hubs in protein networks, is indicative of their role in propagation of transcriptional (genetic) noise. As effectors of transcriptional and conformational noise, IDPs rewire protein networks and unmask latent interactions in response to perturbations. Thus, noise-driven activation of latent pathways could underlie state-switching events such as cellular transformation in cancer. To test this hypothesis, we created a model of a protein network with the topological characteristics of a cancer protein network and tested its response to a perturbation in presence of IDP hubs and conformational noise. Because numerous IDPs are found to be epigenetic modifiers and chromatin remodelers, we hypothesize that they could further channel noise into stable, heritable genotypic changes.

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