A risk-estimation-based formulation for speech enhancement and its relation to Wiener filtering

The goal of speech enhancement algorithms is to provide an estimate of clean speech starting from noisy observations. The often-employed cost function is the mean square error (MSE). However, the MSE can never be computed in practice. Therefore, it becomes necessary to find practical alternatives to the MSE. In image denoising problems, the cost function (also referred to as risk) is often replaced by an unbiased estimator. Motivated by this approach, we reformulate the problem of speech enhancement from the perspective of risk minimization. Some recent contributions in risk estimation have employed Stein's unbiased risk estimator (SURE) together with a parametric denoising function, which is a linear expansion of threshold/bases (LET). We show that the first-order case of SURE-LET results in a Wiener-filter type solution if the denoising function is made frequency-dependent. We also provide enhancement results obtained with both techniques and characterize the improvement by means of local as well as global SNR calculations.

Accelerated multistress aging of polymer nanocomposites and its condition monitoring

In recent years, the time dependant maintenance of expensive high voltage power equipments is getting replaced by condition based maintenance so as to detect apriori an impending failure of the equipment. For condition based maintenance, most monitoring systems concentrate on the electrical quantities such as measurement and evaluation of partial discharges, tan delta, tip-up test, dielectric strength, insulation resistance, polarization and depolarization current. However, in the case of equipments being developed with novel nanodielectric insulating materials, the variation in these parameters before an impending failure is not available. Hence in this work, accelerated electrothermal aging studies have been conducted on unfilled epoxy as well as epoxy nanocomposite samples of 5 wt% filler loading, and the tan d values were continuously monitored to obtain the condition of the samples under study. It was observed that those samples whose tan d increased at a rapid rate failed first.

Acoustic emission techniques for NDE & structural health monitoring of advanced composite materials

Structural Health Monitoring (SHM) is an effective extension of NDE to reduce down time and cost of Inspection of structural components. On – line monitoring is an essential part of SHM. Acoustic Emission Techniques have most of the desirable requirements of an effective SHM tool. With the kind of advancement seen in the last couple of decades in the field of electronics, computers and signal processing technologies it can only be more helpful in obtaining better and meaningful quantitative results which can further enhance the potential of AET for the purpose. Advanced Composite materials owing to their specific high performance characteristics are finding a wide range of engineering applications. Testing and Evaluation of this category of materials and SHM of composite structures have been very challenging problems due to the very nature of these materials. Mechanical behaviour of fiber composite materials under different loading conditions is complex and involves different types of failure mechanisms. This is where the potential of AET can be exploited effectively. This paper presents an over view of some relevant studies where AET has been utilised to test, evaluate and monitor health of composite structures.

Channel estimation relying on the minimum bit-error-ratio criterion for BPSK and QPSK signals

The authors consider the channel estimation problem in the context of a linear equaliser designed for a frequency selective channel, which relies on the minimum bit-error-ratio (MBER) optimisation framework. Previous literature has shown that the MBER-based signal detection may outperform its minimum-mean-square-error (MMSE) counterpart in the bit-error-ratio performance sense. In this study, they develop a framework for channel estimation by first discretising the parameter space and then posing it as a detection problem. Explicitly, the MBER cost function (CF) is derived and its performance studied, when transmitting binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals. It is demonstrated that the MBER based CF aided scheme is capable of outperforming existing MMSE, least square-based solutions.

Robust Reentry Guidance of a Reusable Launch Vehicle Using Model Predictive Static Programming

A robust suboptimal reentry guidance scheme is presented for a reusable launch vehicle using the recently developed, computationally efficient model predictive static programming. The formulation uses the nonlinear vehicle dynamics with a spherical and rotating Earth, hard constraints for desired terminal conditions, and an innovative cost function having several components with associated weighting factors that can account for path and control constraints in a soft constraint manner, thereby leading to smooth solutions of the guidance parameters. The proposed guidance essentially shapes the trajectory of the vehicle by computing the necessary angle of attack and bank angle that the vehicle should execute. The path constraints are the structural load constraint, thermal load constraint, bounds on the angle of attack, and bounds on the bank angle. In addition, the terminal constraints include the three-dimensional position and velocity vector components at the end of the reentry. Whereas the angle-of-attack command is generated directly, the bank angle command is generated by first generating the required heading angle history and then using it in a dynamic inversion loop considering the heading angle dynamics. Such a two-loop synthesis of bank angle leads to better management of the vehicle trajectory and avoids mathematical complexity as well. Moreover, all bank angle maneuvers have been confined to the middle of the trajectory and the vehicle ends the reentry segment with near-zero bank angle, which is quite desirable. It has also been demonstrated that the proposed guidance has sufficient robustness for state perturbations as well as parametric uncertainties in the model.

Optical Flow based on Approximate Nearest Neighbor Field

In this work, we propose an algorithm for optical flow estimation using Approximate Nearest Neighbor Fields (ANNF). Proposed optical flow estimation algorithm consists of two steps, flow initialization using ANNF maps and cost filtering. Flow initialization is done by computing the ANNF map using FeatureMatch between two consecutive frames. The ANNF map obtained represents a noisy optical flow, which is refined by making use of superpixels. The best flow associated with each superpixel is computed by optimizing a cost function. The proposed approach is evaluated on Middlebury and MPI-Sintel optical flow dataset and is found to be comparable with the state of the art methods for optical flow estimation.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Accelerating Information Diffusion in Social Networks Under the Susceptible-Infected-Susceptible Epidemic Model

Standard Susceptible-Infected-Susceptible (SIS) epidemic models assume that a message spreads from the infected to the susceptible nodes due to only susceptible-infected epidemic contact. We modify the standard SIS epidemic model to include direct recruitment of susceptible individuals to the infected class at a constant rate (independent of epidemic contacts), to accelerate information spreading in a social network. Such recruitment can be carried out by placing advertisements in the media. We provide a closed form analytical solution for system evolution in the proposed model and use it to study campaigning in two different scenarios. In the first, the net cost function is a linear combination of the reward due to extent of information diffusion and the cost due to application of control. In the second, the campaign budget is fixed. Results reveal the effectiveness of the proposed system in accelerating and improving the extent of information diffusion. Our work is useful for devising effective strategies for product marketing and political/social-awareness/crowd-funding campaigns that target individuals in a social network.

Sampling Period Selection of Control Application Connected to FlexRay Bus

Flexray is a high speed communication protocol designed for distributive control in automotive control applications. Control performance not only depends on the control algorithm but also on the scheduling constraints in communication. A balance between the control performance and communication constraints must required for the choice of the sampling rates of the control loops in a node. In this paper, an optimum sampling period of control loops to minimize the cost function, satisfying the scheduling constraints is obtained. An algorithm to obtain the delay in service of each task in a node of the control loop in the hyper period has been also developed. (C) 2015 The Authors. Published by Elsevier B.V.

Thermalization of Green functions and quasinormal modes

We develop a new method to study the thermalization of time dependent retarded Green function in conformal field theories holographically dual to thin shell AdS Vaidya space times. The method relies on using the information of all time derivatives of the Green function at the shell and then evolving it for later times. The time derivatives of the Green function at the shell is given in terms of a recursion formula. Using this method we obtain analytic results for short time thermalization of the Green function. We show that the late time behaviour of the Green function is determined by the first quasinormal mode. We then implement the method numerically. As applications of this method we study the thermalization of the retarded time dependent Green function corresponding to a minimally coupled scalar in the AdS 3 and AdS 5 thin Vaidya shells. We see that as expected the late time behaviour is determined by the first quasinormal mode. We apply the method to study the late time behaviour of the shear vector mode in AdS 5 Vaidya shell. At small momentum the corresponding time dependent Green function is expected to relax to equilibrium by the shear hydrodynamic mode. Using this we obtain the universal ratio of the shear viscosity to entropy density from a time dependent process.

IMAGE DENOISING IN MULTIPLICATIVE NOISE

We address the problem of denoising images corrupted by multiplicative noise. The noise is assumed to follow a Gamma distribution. Compared with additive noise distortion, the effect of multiplicative noise on the visual quality of images is quite severe. We consider the mean-square error (MSE) cost function and derive an expression for an unbiased estimate of the MSE. The resulting multiplicative noise unbiased risk estimator is referred to as MURE. The denoising operation is performed in the wavelet domain by considering the image-domain MURE. The parameters of the denoising function (typically, a shrinkage of wavelet coefficients) are optimized for by minimizing MURE. We show that MURE is accurate and close to the oracle MSE. This makes MURE-based image denoising reliable and on par with oracle-MSE-based estimates. Analogous to the other popular risk estimation approaches developed for additive, Poisson, and chi-squared noise degradations, the proposed approach does not assume any prior on the underlying noise-free image. We report denoising results for various noise levels and show that the quality of denoising obtained is on par with the oracle result and better than that obtained using some state-of-the-art denoisers.

Monte-Carlo simulation of surface crack growth rate for offshore structural steel E36-Z35

The Monte- Carlo method is used to simulate the surface fatigue crack growth rate for offshore structural steel E36-Z35, and to determine the distributions and relevance of the parameters in the Paris equation. By this method, the time and cost of fatigue crack propagation testing can be reduced. The application of the method is demonstrated by use of four sets of fatigue crack propagation data for offshore structural steel E36-Z35. A comparison of the test data with the theoretical prediction for surface crack growth rate shows the application of the simulation method to the fatigue crack propagation tests is successful.

Dispersion rheology of carbon nanotubes in a polymer matrix

We report on rheological properties of a dispersion of multiwalled carbon nanotubes in a viscous polymer matrix. Particular attention is paid to the process of nanotubes mixing and dispersion, which we monitor by the rheological signature of the composite. The response of the composite as a function of the dispersion mixing time and conditions indicates that a critical mixing time t* needs to be exceeded to achieve satisfactory dispersion of aggregates, this time being a function of nanotube concentration and the mixing shear stress. At shorter times of shear mixing t< t*, we find a number of nonequilibrium features characteristic of colloidal glass and jamming of clusters. A thoroughly dispersed nanocomposite, at t> t*, has several universal rheological features; at nanotube concentration above a characteristic value nc ∼2-3 wt. % the effective elastic gel network is formed, while the low-concentration composite remains a viscous liquid. We use this rheological approach to determine the effects of aging and reaggregation. © 2006 The American Physical Society.

El abastecimiento de agua corriente en la ciudad de Córdoba (1900-1910) : continuidad y cambio en la gestión

Resumen: Desde un punto de vista general el agua es definida en la actualidad como un recurso natural no renovable en cantidad, recuperable en calidad y con posibilidad de nuevo uso (re-uso) en continua mutación dentro del ciclo hidrológico. A la vez posee las categorías de bien común como elemento esencial para la vida humana y que como tal no tiene precio, y de recurso hídrico con dimensión económica como insumo, que supone un valor mensurable. Los recursos hídricos y su gestión forman parte de la administración pública, como pueden serlo la energía o la salud. La organización adecuada de un servicio, y las formas institucionales a través de las que se presta, varían de acuerdo a las épocas, los costes tecnológicos, los de distribución, organización y regulación, resultando un aspecto importante del análisis la implementación y funcionamiento del servicio público. Atendiendo a estos aspectos teóricos, este trabajo continua con la problemática del abastecimiento de agua corriente en la ciudad de Córdoba, ahora en la primera década del siglo XX, manteniendo el supuesto de que las dificultades para el abastecimiento de agua obedecen a razones de orden natural, a dificultades económicas y a enfrentamientos políticos, en el marco de un Estado que aún posee limitaciones de índole institucional y administrativo, por lo cual intervendrán el gobierno provincial y Nacional para la concreción de las obras de salubridad, en una ciudad y un país enrolados en el proceso de modernización impulsado por el deseo de adecuación al modelo de vida europeo. Seguimos analizando las fuentes inéditas del Archivo Histórico Municipal de Córdoba, fuentes oficiales editas, publicaciones periódicas y bibliografía tanto general como específica.

Nonlinear dynamics of atomic force microscopy with intermittent contact

When the atomic force microscopy (AFM) in tapping mode is in intermittent contact with a soft substrate, the contact time can be a significant portion of a cycle, resulting in invalidity of the impact oscillator model, where the contact time is assumed to be infinitely small. Furthermore, we demonstrate that the AFM intermittent contact with soft substrate can induce the motion of higher modes in the AFM dynamic response. Traditional ways of modeling AFM (one degree of freedom (DOF) system or single mode analysis) are shown to have serious mistakes when applied to this kind of problem. A more reasonable displacement criterion on contact is proposed, where the contact time is a function of the mechanical properties of AFM and substrate, driving frequencies/amplitude, initial conditions, etc. Multi-modal analysis is presented and mode coupling is also shown. (c) 2006 Published by Elsevier Ltd.