Signal subspace approach in localization of sound source in shallow water

A new algorithm based on signal subspace approach is proposed for localizing a sound source in shallow water. In the first instance we assumed an ideal channel with plane parallel boundaries and known reflection properties. The sound source is assumed to emit a broadband stationary stochastic signal. The algorithm takes into account the spatial distribution of all images and reflection characteristics of the sea bottom. It is shown that both range and depth of a source can be measured accurately with the help of a vertical array of sensors. For good results the number of sensors should be greater than the number of significant images; however, localization is possible even with a smaller array but at the cost of higher side lobes. Next, we allowed the channel to be stochastically perturbed; this resulted in random phase errors in the reflection coefficients. The most singular effect of the phase errors is to introduce into the spectral matrix an extra term which may be looked upon as a signal generated coloured noise. It is shown through computer simulations that the signal peak height is reduced considerably as a consequence of random phase errors.

Composite MR image reconstruction and unaliasing for general trajectories using neural networks

In rapid parallel magnetic resonance imaging, the problem of image reconstruction is challenging. Here, a novel image reconstruction technique for data acquired along any general trajectory in neural network framework, called ``Composite Reconstruction And Unaliasing using Neural Networks'' (CRAUNN), is proposed. CRAUNN is based on the observation that the nature of aliasing remains unchanged whether the undersampled acquisition contains only low frequencies or includes high frequencies too. Here, the transformation needed to reconstruct the alias-free image from the aliased coil images is learnt, using acquisitions consisting of densely sampled low frequencies. Neural networks are made use of as machine learning tools to learn the transformation, in order to obtain the desired alias-free image for actual acquisitions containing sparsely sampled low as well as high frequencies. CRAUNN operates in the image domain and does not require explicit coil sensitivity estimation. It is also independent of the sampling trajectory used, and could be applied to arbitrary trajectories as well. As a pilot trial, the technique is first applied to Cartesian trajectory-sampled data. Experiments performed using radial and spiral trajectories on real and synthetic data, illustrate the performance of the method. The reconstruction errors depend on the acceleration factor as well as the sampling trajectory. It is found that higher acceleration factors can be obtained when radial trajectories are used. Comparisons against existing techniques are presented. CRAUNN has been found to perform on par with the state-of-the-art techniques. Acceleration factors of up to 4, 6 and 4 are achieved in Cartesian, radial and spiral cases, respectively. (C) 2010 Elsevier Inc. All rights reserved.

Interaction of flux tubes with sound waves

The Landau damping of sound waves in a plasma consisting of ensemble of magnetic flux tubes is discussed. It is shown that sound waves cannot be Landau damped in general but under certain restricted conditions on plasma parameters the possibility of absorption of these waves can exist. The possibility of radiative damping of the acoustic waves along the magnetic filaments is also discussed. It appears that the most plausible mechanism of damping of sound waves in a plasma consisting of magnetic filaments can be due to scattering of a sound wave by the filaments.

Crumpling and second sound in lyotropic lamellar phases

We study relative concentration fluctuations in two component lamellar smectic liquid crystals consisting of surfactant layers of width w separated by a background fluid and show that these fluctuations are dominated by crumpling fluctuations of the surfactant layers when (w/l)2

Analysis of reflection characteristics of a normal incidence plane wave on resonant sound absorbers: A finite element approach

Resonant sound absorbers are used widely as anechoic coatings in underwater applications. In this paper a finite element scheme based on the Galerkin technique is used to analyze the reflection characteristics of the resonant absorber when insonified by a normal incidence plane wave. A waveguide theory coupled with an impedance matching condition in the fluid is used to model the problem. It is shown in this paper that the fluid medium encompassing the absorber can be modeled as an elastic medium with equivalent Lamé constants. Quarter symmetry conditions within the periodic unit cell are exploited. The finite element results are compared with analytical results, and with results published elsewhere in the literature. It is shown in the process that meshing of the fluid domain can be obviated if the transmission coefficients or reflection coefficients only are desired as is often the case. Finally, some design curves for thin resonant absorbers with water closure are presented in this paper.

A Parallel Progressive Refinement Image Rendering Algorithm on a Scalable Multithreaded VLSI Processor Array

In this paper we develop a multithreaded VLSI processor linear array architecture to render complex environments based on the radiosity approach. The processing elements are identical and multithreaded. They work in Single Program Multiple Data (SPMD) mode. A new algorithm to do the radiosity computations based on the progressive refinement approach[2] is proposed. Simulation results indicate that the architecture is latency tolerant and scalable. It is shown that a linear array of 128 uni-threaded processing elements sustains a throughput close to 0.4 million patches/sec.

Biomass gasification: Environmentally sound technology for decentralized power generation, a case study from India

This study aims at understanding the need for decentralized power generation systems and to explore the potential, feasibility and environmental implications of biomass gasifier-based electricity generation systems for village electrification. Electricity needs of villages are in the range of 5–20 kW depending on the size of the village. Decentralized power generation systems are desirable for low load village situations as the cost of power transmission lines is reduced and transmission and distribution losses are minimised. A biomass gasifier-based electricity generation system is one of the feasible options; the technology is readily available and has already been field tested. To meet the lighting and stationary power needs of 500,000 villages in India the land required is only 16 Mha compared to over 100 Mha of degraded land available for tree planting. In fact all the 95 Mt of woody biomass required for gasification could be obtained through biomass conservation programmes such as biogas and improved cook stoves. Thus dedication of land for energy plantations may not be required. A shift to a biomass gasifier-based power generation system leads to local benefits such as village self reliance, local employment and skill generation and promotion of in situ plant diversity plus global benefits like no net CO2 emission (as sustainable biomass harvests are possible) and a reduction in CO2 emissions (when used to substitute thermal power and diesel in irrigation pump sets).

Dual-DSP system for signal and image processing

The design of a dual-DSP microprocessor system and its application for parallel FFT and two-dimensional convolution are explained. The system is based on a master-salve configuration. Two ADSP-2101s are configured as slave processors and a PC/AT serves as the master. The master serves as a control processor to transfer the program code and data to the DSPs. The system architecture and the algorithms for the two applications, viz. FFT and two-dimensional convolutions, are discussed.

Normal mode sound propagation in an ocean with random narrow-band surface waves

Normal mode sound propagation in an isovelocity ocean with random narrow-band surface waves is considered, assuming the root-mean-square wave height to be small compared to the acoustic wavelength. Nonresonant interaction among the normal modes is studied straightforward perturbation technique. The more interesting case of resonant interaction is investigated using the method of multiple scales to obtain a pair of stochastic coupled amplitude equations which are solved using the Peano-Baker expansion technique. Equations for the spatial evolution of the first and second moments of the mode amplitudes are also derived and solved. It is shown that, irrespective of the initial conditions, the mean values of the mode amplitudes tend to zero asymptotically with increasing range, the mean-square amplitudes tend towards a state of equipartition of energy, and the total energy of the modes is conserved.

Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units

Diffuse optical tomographic image reconstruction uses advanced numerical models that are computationally costly to be implemented in the real time. The graphics processing units (GPUs) offer desktop massive parallelization that can accelerate these computations. An open-source GPU-accelerated linear algebra library package is used to compute the most intensive matrix-matrix calculations and matrix decompositions that are used in solving the system of linear equations. These open-source functions were integrated into the existing frequency-domain diffuse optical image reconstruction algorithms to evaluate the acceleration capability of the GPUs (NVIDIA Tesla C 1060) with increasing reconstruction problem sizes. These studies indicate that single precision computations are sufficient for diffuse optical tomographic image reconstruction. The acceleration per iteration can be up to 40, using GPUs compared to traditional CPUs in case of three-dimensional reconstruction, where the reconstruction problem is more underdetermined, making the GPUs more attractive in the clinical settings. The current limitation of these GPUs in the available onboard memory (4 GB) that restricts the reconstruction of a large set of optical parameters, more than 13, 377. (C) 2010 Society of Photo-Optical Instrumentation Engineers. DOI: 10.1117/1.3506216]

Fracture Properties of Concrete-Concrete Interfaces Using Digital Image Correlation

The mode I and mode II fracture toughness and the critical strain energy release rate for different concrete-concrete jointed interfaces are experimentally determined using the Digital Image Correlation technique. Concrete beams having different compressive strength materials on either side of a centrally placed vertical interface are prepared and tested under three-point bending in a closed loop servo-controlled testing machine under crack mouth opening displacement control. Digital images are captured before loading (undeformed state) and at different instances of loading. These images are analyzed using correlation techniques to compute the surface displacements, strain components, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It is seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.

Ground state geometric distortions Image distal substituent effects in determining the β-facial selectivity in 7-norbornenones

The X-ray structure of Image and MNDO optimized geometries of related 7-norbornenone derivatives show a clear tilt of the carbonyl bridge away from the C=C double bond. The preferred reduction from the more hindered face of the diester reveals the electron/electrostatic origin of π - facial selectivity in these systems. X-ray structure and MNDO calculations reveal the dominance of electronic effects in determining the π-facial selectivity in 4a.

Accelerated gradient based diffuse optical tomographic image reconstruction

Purpose: Fast reconstruction of interior optical parameter distribution using a new approach called Broyden-based model iterative image reconstruction (BMOBIIR) and adjoint Broyden-based MOBIIR (ABMOBIIR) of a tissue and a tissue mimicking phantom from boundary measurement data in diffuse optical tomography (DOT). Methods: DOT is a nonlinear and ill-posed inverse problem. Newton-based MOBIIR algorithm, which is generally used, requires repeated evaluation of the Jacobian which consumes bulk of the computation time for reconstruction. In this study, we propose a Broyden approach-based accelerated scheme for Jacobian computation and it is combined with conjugate gradient scheme (CGS) for fast reconstruction. The method makes explicit use of secant and adjoint information that can be obtained from forward solution of the diffusion equation. This approach reduces the computational time many fold by approximating the system Jacobian successively through low-rank updates. Results: Simulation studies have been carried out with single as well as multiple inhomogeneities. Algorithms are validated using an experimental study carried out on a pork tissue with fat acting as an inhomogeneity. The results obtained through the proposed BMOBIIR and ABMOBIIR approaches are compared with those of Newton-based MOBIIR algorithm. The mean squared error and execution time are used as metrics for comparing the results of reconstruction. Conclusions: We have shown through experimental and simulation studies that Broyden-based MOBIIR and adjoint Broyden-based methods are capable of reconstructing single as well as multiple inhomogeneities in tissue and a tissue-mimicking phantom. Broyden MOBIIR and adjoint Broyden MOBIIR methods are computationally simple and they result in much faster implementations because they avoid direct evaluation of Jacobian. The image reconstructions have been carried out with different initial values using Newton, Broyden, and adjoint Broyden approaches. These algorithms work well when the initial guess is close to the true solution. However, when initial guess is far away from true solution, Newton-based MOBIIR gives better reconstructed images. The proposed methods are found to be stable with noisy measurement data. (C) 2011 American Association of Physicists in Medicine. DOI: 10.1118/1.3531572]

A Non-contact measurement technique to measure micro surface stress and obtain deformation profiles of the order of 1nm in Micro-cantilever based structures by single image Optical Diffraction method

A new method based on analysis of a single diffraction pattern is proposed to measure deflections in micro-cantilever (MC) based sensor probes, achieving typical deflection resolutions of 1nm and surface stress changes of 50 mu N/m. The proposed method employs a double MC structure where the deflection of one of the micro-cantilevers relative to the other due to surface stress changes results in a linear shift of intensity maxima of the Fraunhofer diffraction pattern of the transilluminated MC. Measurement of such shifts in the intensity maxima of a particular order along the length of the structure can be done to an accuracy of 0.01mm leading to the proposed sensitivity of deflection measurement in a typical microcantilever. This method can overcome the fundamental measurement sensitivity limit set by diffraction and pointing stability of laser beam in the widely used Optical Beam Deflection method (OBDM).