A novel way to treat refractory waste: Sonication followed by wet oxidation (SONIWO)

The effectiveness of the hybrid system sonication followed by wet oxidation (SONIWO) to treat otherwise refractory waste has been demonstrated. In such a hybrid system homogeneous CuSO₄ catalyst was found to be very efficient.     

A ROBUST MART ALGORITHM FOR TOMOGRAPHIC APPLICATIONS

The present work is concerned with the development of a robust reconstruction algorithm for applications involving tomography. In an earlier study it was shown that among the ART family of algorithms, the multiplicative algebraic reconstruction algorithm (MART) was the most appropriate for tomographic reconstruction [1]. In the present work, the MART algorithm has been extended so that (a) its performance is now acceptable over a wider range of relaxation factors, (b) the time requirement for convergence to a solution is lower, and (c) its performance is less sensitive to noise in the projection data. Applications considered for evaluating the proposed algorithms are (1) a circular region with holes, (2) a three-dimensional temperature field in a differentially heated fluid layer, and (3) experimental data recorded in a differentially heated fluid layer using an interferometer. The proposed algorithms are seen to be an improvement over those presently available, for all three examples considered.     

Analysis and characterization of photo-plethysmographic signal

Qualitative assessment of the overall clinical status of the subject and characterization of complex cardiovascular dynamics from digital blood volume pulsations measured noninvasively using a photo-plethysmographic device is addressed. A novel concept is employed to detect the dominant nonsinusoidal periodicity embedded in the data series and to extract the associated periodic component. The detection and the extraction of periodic component is performed with moving window to accommodate the variations of the physiological oscillations. The covariance matrix formed by the gradually varying pattern is used as a simple measure of qualitative assessment. Further, the characterization of the underlying system in the light of nonlinear dynamical analysis is also presented. The stable subjects are shown to behave as a low-dimensional system whereas the diseased subjects exhibit comparatively high dimensional activity.     

On the Decomposition of Large Communication Networks for Hierarchical Control Implementation

In the implementation of hierarchical schemes for the adaptive control of large communication networks, decomposition of the overall network into node clusters and assignment of a supervisor for each cluster are of central importance. A formulation of the decomposition problem as a mathematical optimization problem is given and an algorithm for solution is presented.     

Performance of iterative tomographic algorithms applied to non-destructive evaluation with limited data

Iterative tomographic algorithms have been applied to the reconstruction of a two-dimensional object with internal defects from its projections. Nine distinct algorithms with varying numbers of projections and projection angles have been considered. Each projection of the solid object is interpreted as a path integral of the light-sensitive property of the object in the appropriate direction. The integrals are evaluated numerically and are assumed to represent exact data. Errors in reconstruction are defined as the statistics of difference between original and reconstructed objects and are used to compare one algorithm with respect to another. The algorithms used in this work can be classified broadly into three groups, namely the additive algebraic reconstruction technique (ART), the multiplicative algebraic reconstruction technique (MART) and the maximization reconstruction technique (MRT). Additive ART shows a systematic convergence with respect to the number of projections and the value of the relaxation parameter. MART algorithms produce less error at convergence compared to additive ART but converge only at small values of the relaxation parameter. The MRT algorithm shows an intermediate performance when compared to ART and MART. An increasing noise level in the projection data increases the error in the reconstructed field. The maximum and RMS errors are highest in ART and lowest in MART for given projection data. Increasing noise levels in the projection data decrease the convergence rates. For all algorithms, a 20% noise level is seen as an upper limit, beyond which the reconstructed field is barely recognizable.