Efficient QR Decomposition Using Low Complexity Column-wise Givens Rotation (CGR)

QR decomposition (QRD) is a widely used Numerical Linear Algebra (NLA) kernel with applications ranging from SONAR beamforming to wireless MIMO receivers. In this paper, we propose a novel Givens Rotation (GR) based QRD (GR QRD) where we reduce the computational complexity of GR and exploit higher degree of parallelism. This low complexity Column-wise GR (CGR) can annihilate multiple elements of a column of a matrix simultaneously. The algorithm is first realized on a Two-Dimensional (2 D) systolic array and then implemented on REDEFINE which is a Coarse Grained run-time Reconfigurable Architecture (CGRA). We benchmark the proposed implementation against state-of-the-art implementations to report better throughput, convergence and scalability.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Thermal conductivity of beta-FeSi2/Si endogenous composites formed by the eutectoid decomposition of alpha-Fe2Si5

Thermoelectric properties of semiconducting beta-FeSi2 containing a homogeneous distribution of Si secondary phase have been studied. The synthesis was carried out using arc melting followed by the densification by uniaxial hot pressing. Endogenous beta-FeSi2/Si composites were produced by the eutectoid decomposition of high-temperature alpha-Fe2Si5 phase. The aging heat treatments have been carried out at various temperatures below the equilibrium eutectoid temperature for various durations in order to tune the size of the eutectoid product. Thermal properties of the samples were studied in the temperature range of 100-350 A degrees C. The microstructural investigations support the fact that the finest microstructure generated through the eutectoid decomposition of the alpha-Fe2Si5 metastable phase is responsible of the phonon scattering. The results suggest an opportunity to produce bulk iron silicide alloys with reduced thermal conductivity in order to enhance its thermoelectric performance.

An Alternating l(p) - l(2) Projections Algorithm (ALPA) for Speech Modeling using Sparsity Constraints

We address the problem of separating a speech signal into its excitation and vocal-tract filter components, which falls within the framework of blind deconvolution. Typically, the excitation in case of voiced speech is assumed to be sparse and the vocal-tract filter stable. We develop an alternating l(p) - l(2) projections algorithm (ALPA) to perform deconvolution taking into account these constraints. The algorithm is iterative, and alternates between two solution spaces. The initialization is based on the standard linear prediction decomposition of a speech signal into an autoregressive filter and prediction residue. In every iteration, a sparse excitation is estimated by optimizing an l(p)-norm-based cost and the vocal-tract filter is derived as a solution to a standard least-squares minimization problem. We validate the algorithm on voiced segments of natural speech signals and show applications to epoch estimation. We also present comparisons with state-of-the-art techniques and show that ALPA gives a sparser impulse-like excitation, where the impulses directly denote the epochs or instants of significant excitation.

Iridium-decorated multiwall carbon nanotubes and its catalytic activity with Shell 405 in hydrazine decomposition

Iridium-functionalized multiwalled carbon nanotubes (Ir-MWNT) are the future catalyst support material for hydrazine fuel decomposition. The present work demonstrates decoration of iridium particle on iron-encapsulated multiwalled carbon nanotubes (MWNT) by wet impregnation method in the absence of any stabilizer. Electron microscopy studies reveal the coated iridium particle size in the range of 5-10 nm. Elemental analysis by energy dispersive X-ray diffraction confirms 21 wt% of Ir coated over MWNT. X-ray photoelectron spectroscopy (XPS) shows 4f(5/2) and 4f(7/2) lines of iridium and confirms the metallic nature. The catalytic activity of Ir-MWNT/Shell 405 combination is performed in 1 N hydrazine micro-thrusters. The thruster performance shows increase in chamber pressure and decrease in chamber temperature when compared to Shell 405 alone. This enhanced performance is due to high thermal conducting nature of MWNTs and the presence of Ir active sites over MWNTs.

Prediction of electronically nonadiabatic decomposition mechanisms of isolated gas phase nitrogen-rich energetic salt: Guanidium-triazolate

Electronically nonadiabatic decomposition pathways of guanidium triazolate are explored theoretically. Nonadiabatically coupled potential energy surfaces are explored at the complete active space self-consistent field (CASSCF) level of theory. For better estimation of energies complete active space second order perturbation theories (CASPT2 and CASMP2) are also employed. Density functional theory (DFT) with B3LYP functional and MP2 level of theory are used to explore subsequent ground state decomposition pathways. In comparison with all possible stable decomposition products (such as, N-2, NH3, HNC, HCN, NH2CN and CH3NC), only NH3 (with NH2CN) and N-2 are predicted to be energetically most accessible initial decomposition products. Furthermore, different conical intersections between the S-1 and S-0 surfaces, which are computed at the CASSCF(14,10)/6-31G(d) level of theory, are found to play an essential role in the excited state deactivation process of guanidium triazolate. This is the first report on the electronically nonadiabatic decomposition mechanisms of isolated guanidium triazolate salt. (C) 2015 Elsevier B.V. All rights reserved.

A survey on compressed domain video analysis techniques

Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

A Perspective on Computer Assisted Assessment Techniques for Short Free-Text Answers

Computer Assisted Assessment (CAA) has been existing for several years now. While some forms of CAA do not require sophisticated text understanding (e.g., multiple choice questions), there are also student answers that consist of free text and require analysis of text in the answer. Research towards the latter till date has concentrated on two main sub-tasks: (i) grading of essays, which is done mainly by checking the style, correctness of grammar, and coherence of the essay and (ii) assessment of short free-text answers. In this paper, we present a structured view of relevant research in automated assessment techniques for short free-text answers. We review papers spanning the last 15 years of research with emphasis on recent papers. Our main objectives are two folds. First we present the survey in a structured way by segregating information on dataset, problem formulation, techniques, and evaluation measures. Second we present a discussion on some of the potential future directions in this domain which we hope would be helpful for researchers.

Structural, Optical, and Piezoelectric Response of Lead-Free Ba0.95Mg0.05Zr0.1Ti0.9O3 Nanocrystalline Powder

Nanocrystalline powders of Ba1-xMgxZr0.1Ti0.9O3 (x = 0.025-0.1) were synthesized via citrate assisted sol-gel method. Interestingly, the one with x = 0.05 in the system Ba1-xMgxZr0.1Ti0.9O3 exhibited fairly good piezoelectric response aside from the other physical properties. The phase and structural confirmation of synthesized powder was established by X-ray powder diffraction (XRD) and Raman Spectroscopic techniques. Two distinct Raman bands i.e., 303 and 723 cm(-1) characteristic of tetragonal phase were observed. Thermogravimetric analysis (TGA) was performed to evaluate the phase decomposition of the as-synthesized Ba0.95Mg0.05Zr0.1Ti0.9O3 sample as a function of temperature. The average crystallite size associated with Ba0.95Mg0.05Zr0.1Ti0.9O3 was calculated using Scherrer formula based on the XRD data and was found to be 25 nm. However, Scanning and Transmission Electron Microscopy studies revealed the average crystallite size to be in the range of 30-40 nm, respectively. Kubelka-Munk function was employed to determine the optical band gap of these nanocrystallites. A piezoelectric response of 26 pm/V was observed for Ba0.95Mg0.05Zr0.1Ti0.9O3 nanocrystal by Piezoresponse Force Microscopy (PFM) technique. Photoluminescence (PL) study carried out on these nanocrystals exhibited a blue emission (470 nm) at room temperature.

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(sigma(2)) operations per pixel, where sigma is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary sigma (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the so-called Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.