Efficient calculation of sensor utility and sensor removal in wireless sensor networks for adaptive signal estimation and beamforming

Wireless sensor networks are often deployed over a large area of interest and therefore the quality of the sensor signals may vary significantly across the different sensors. In this case, it is useful to have a measure for the importance or the so-called "utility" of each sensor, e.g., for sensor subset selection, resource allocation or topology selection. In this paper, we consider the efficient calculation of sensor utility measures for four different signal estimation or beamforming algorithms in an adaptive context. We use the definition of sensor utility as the increase in cost (e.g., mean-squared error) when the sensor is removed from the estimation procedure. Since each possible sensor removal corresponds to a new estimation problem (involving less sensors), calculating the sensor utilities would require a continuous updating of different signal estimators (where is the number of sensors), increasing computational complexity and memory usage by a factor. However, we derive formulas to efficiently calculate all sensor utilities with hardly any increase in memory usage and computational complexity compared to the signal estimation algorithm already in place. When applied in adaptive signal estimation algorithms, this allows for on-line tracking of all the sensor utilities at almost no additional cost. Furthermore, we derive efficient formulas for sensor removal, i.e., for updating the signal estimator coefficients when a sensor is removed, e.g., due to a failure in the wireless link or when its utility is too low. We provide a complexity evaluation of the derived formulas, and demonstrate the significant reduction in computational complexity compared to straightforward implementations

Utility based cross-layer collaboration for speech enhancement in wireless acoustic sensor networks

A wireless acoustic sensor network is considered that is used to estimate a desired speech signal that has been corrupted by noise. The application layer of the WASN derives an optimal filter in a linear MMSE sense. A utility function is then used in conjunction with the MMSE estimate in order to evaluate the most significant signal components from each node in the system. The utility values are used as a cross-layer link between the application layer and the network layer so the nodes transmit the signal components that are deemed most relevant to the estimate while adhering to the power constraints of the system. The simulation results show that a high signal-to-error and signal-to-noise ratio is still achievable while transmitting a subset of signal components

More than pretty images – Towards confidence bounds on segmentation thresholds

International audienceWe present an approach to assess the uncertainty associated to classifying voxels into different material phases. The approach consists in a spectral deconvolution of the grey-level histogram using a Gaussian mixture approach, followed by an iterative classification procedure based on the occurrence frequency. As phase attributions become increasingly more uncertain as iterations proceed, confidence bounds on the final segmentation are naturally obtained

Deformation and damage due to drying-induced salt crystallization in porous limestone

ACLInternational audienceThis paper presents a computational model coupling heat, water and salt ion transport, salt crystallization, deformation and damage in porous materials. We focus on crystallization-induced damage. The theory of poromechanics is employed to relate stress, induced by crystallization processes or hygro-thermal origin, to the material's mechanical response. A non-local formulation is developed to describe the crystallization kinetics. The model performance is illustrated by simulating the damage caused by sodium chloride crystallization in a porous limestone. The results are compared with experimental observations based on neutron and X-ray imaging. The simulation results suggest that the crystallization kinetics in porous materials have to be accurately understood in order to be able to control salt damage. The results show that the effective stress caused by salt crystallization depends not only on the crystallization pressure but also on the amount of salt crystals, which is determined by the spreading of crystals in the porous material and the crystallization kinetics. © 2013 Elsevier Ltd

Permeability estimation using vortex-based method and synthetic samples from X-ray micro-CT

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X-ray spectrum estimation from transmission measurements: preliminary results

International audienceIn this study, we propose a method to estimate the polychromatic X-ray spectrum of a microtomograph by measuring transmissions through a series of phantoms with known composition and thickness. An initially lognormal spectrum is iteratively optimized in order to obtain the best fit for all measurements. The validity of the estimated X-ray spectrum is verified based on an independent phantom

Experimental and numerical cross-validation of flow in real porous media. Part 1: Experimental framework

International audienceIn this study, we present the design of a purpose-built test cell, capable of closely mimicking boundary conditions which can be routinely imposed in fluid flow simulators. The test cell permits conducting systematic studies on the influence of unresolved pore-scale wall-roughness and pore space morphology on the hydraulic conductivity: it is therefore an ideal instrument for the generation of validation datasets for the next generation numerical flow models

3D Visualization of biofilms in porous media without using a contrast agent

International audienceIn this study, the challenge is to characterize biofilm growth in a natural aquifer, identified as a potential future location for storing biogas. More precisely, we want to evaluate the impact of biofilm growth on the porosity by means of high-resolution X-ray computed tomography without using artificial contrast agents as these substances could affect the phenomenon of interest

Energy aware greedy subset s election for speech enhancement in wireless acoustic sensor networks

Publication in the conference proceedings of EUSIPCO, Bucharest, Romania, 201