Epoch extraction based on integrated linear prediction residual using plosion index

Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

Linear and nonlinear optical studies on 3,6-bis (2 pyridyl) pyridazine

3,6-Bis (2 pyridyl) pyridazine has been synthesized and characterized by NMR, XRD and elemental analyses. The vibrational studies were carried out by using FTIR and Raman spectroscopy and the modes of vibrations were analysed and compared with the theoretically calculated values. The nonlinear optical property of the title compound was examined by Kurtz-Perry method and Hyper Raleigh scattering with the fundamental wavelength of 1064nm. This compound possesses less SHG efficiency but large first hyperpolarizability. (C) 2013 Elsevier GmbH. All rights reserved.

Effects of initial height on the steady-state persistence probability of linear growth models

The effects of the initial height on the temporal persistence probability of steady-state height fluctuations in up-down symmetric linear models of surface growth are investigated. We study the (1 + 1)-dimensional Family model and the (1 + 1)-and (2 + 1)-dimensional larger curvature (LC) model. Both the Family and LC models have up-down symmetry, so the positive and negative persistence probabilities in the steady state, averaged over all values of the initial height h(0), are equal to each other. However, these two probabilities are not equal if one considers a fixed nonzero value of h(0). Plots of the positive persistence probability for negative initial height versus time exhibit power-law behavior if the magnitude of the initial height is larger than the interface width at saturation. By symmetry, the negative persistence probability for positive initial height also exhibits the same behavior. The persistence exponent that describes this power-law decay decreases as the magnitude of the initial height is increased. The dependence of the persistence probability on the initial height, the system size, and the discrete sampling time is found to exhibit scaling behavior.

Solvent-induced changes on the polarity of the triplet excited state of 2-chlorothioxanthone: From time-resolved absorption and resonance Raman spectroscopies

Solvent polarity has been known to influence the triplet state structure and reactivity. Here, we present our experimental and theoretical study on the effect of solvent on the lowest triplet excited state structure of 2-chlorothioxanthone (CTX). Time-resolved absorption (TA) spectroscopy has been employed to understand the triplet state electronic structure; whereas solvent-induced structural changes have been studied using time-resolved resonance Raman (TR3) spectroscopy. Both the DFT and TD-DFT calculations have been performed in the solution phase employing self-consistent reaction field implicit solvation model to support the experimental data. It has been observed that CO stretching frequencies of the excited triplet state are sensitive to the solvent polarity and increase with the increase in the solvent polarity. Both TA and TR3 studies reveal that specific solvent effect (H-bonding) is more pronounced in comparison to the nonspecific solvent effect. (C) 2013 Elsevier B.V. All rights reserved.

Role of Crystal Field in Mixed Alkali Metal Effect: Electron Paramagnetic Resonance Study of Mixed Alkali Metal Oxyfluoro Vanadate Glasses

The mixed alkali metal effect is a long-standing problem in glasses. Electron paramagnetic resonance (EPR) is used by several researchers to study the mixed alkali metal effect, but a detailed analysis of the nearest neighbor environment of the glass former using spin-Hamiltonian parameters was elusive. In this study we have prepared a series of vanadate glasses having general formula (mol %) 40 V2O5-30BaF(2)-(30 - x)LiF-xRbF with x = 5, 10, 15, 20, 25, and 30. Spin-Hamiltonian parameters of V4+ ions were extracted by simulating and fitting to the experimental spectra using EasySpin. From the analysis of these parameters it is observed that the replacement of lithium ions by rubidium ions follows a ``preferential substitution model''. Using this proposed model, we were able to account for the observed variation in the ratio of the g parameter, which goes through a maximum. This reflects an asymmetric to symmetric changeover of. the alkali metal ion environment around the vanadium site. Further, this model also accounts for the variation in oxidation state of vanadium ion, which was confirmed from the variation in signal intensity of EPR spectra.

Synthesis, Characterization, and Nuclear Magnetic Resonance Study of Chitosan-Coated Mn1-xZnxFe2O4 Nanocrystals

Ultra-fine crystallites of Mn1-xZnxFe2O4 series (0 <= x <= 1) were synthesized through wet chemical co- precipitation method followed by calcination at 200 degrees C for 4 hours. Formation of ferrites was confirmed by X-ray diffraction, TEM selected area diffraction (SAD) and Fourier Transform Infra-red Spectroscopy (FTIR). Nanocrystallites of different compositions in the series were coated with biocompatible chitosan in order to investigate their possible application as contrast agent for magnetic resonance imaging (MRI). Chitosan coating examined by FTIR, revealed a strong bonding of chitosan molecules to the surface of the ferrite nanocrystallites. Spin-spin, tau(2) relaxivities of nuclear spins of hydrogen protons of the solutions for different ferrites were measured from concentration dependence of relaxation time by nuclear magnetic resonance (NMR). All the compositions of Mn1-xZnxFe2O4 series possess higher values of tau(2) relaxivity thus making them suitable as contrast agents for tau(2) weighted imaging by MRI.

Nonlinear and linear autopilot performance comparison of tactical flight vehicle

n this paper, three-axis autopilot of a tactical flight vehicle has been designed for surface to air application. Both nonlinear and linear design synthesis and analysis have been carried out pertaining to present flight vehicle. Lateral autopilot performance has been compared by tracking lateral acceleration components along yaw and pitch plane at higher angles of attack in presence of side force and aerodynamic nonlinearity. The nonlinear lateral autopilot design is based on dynamic inversion and time scale separation principle. The linear lateral autopilot design is based on three-loop topology. Roll autopilot robustness performance has been enhanced against unmodeled roll disturbances by backstepping technique. Complete performance comparison results of both nonlinear and linear controller based on six degrees of freedom simulation along with stability and robustness studies with respect to plant parameter variation have been discussed in the paper.

Large-MIMO Receiver based on Linear Regression of MMSE Residual

Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs quite well: at a bit error rate (BER) of 10(-3), the SNR gain over MMSE receiver is about 7 dB for a 16 x 16 system; for a 64 x 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.

Synthesis, structural and thermoluminescence properties of YAlO3:Dy3+ nanophosphors

Thermoluminescence properties of YAlO3:Dy3+ nanophosphor prepared by a low temperature solution combustion (SC) method using oxalyl dihydrazide as a fuel were studied and the results were compared to bulk phosphor prepared by solid state (SS) synthesis. Powder X-ray diffraction patterns confirm the orthorhombic phase of SC and SS methods. Rietveld refinement was used to estimate the cell parameters of undoped and Dy3+ doped YAlO3. Scanning electron micrographs reveal dumbbell shape particles. Electron paramagnetic resonance spectra of YAlO3:Dy3+ nanophosphors were studied at 293 K, 77 K and 10 K. Thermoluminescence responses of SC and SS prepared phosphor were studied using gamma irradiation in the dose range 0.1-6 kGy at a warming rate of 1 degrees C s (1) at room temperature (RT). The optimized concentrations of Dy3+ ions in YAlO3 was found to be 3 mol%. The trapping parameters (i. e. activation energy, frequency factor, order of kinetic) of all the individual peaks of the glow curves have been analysed by using Chen's method. The low fading and linear response in the wide range (0.1-1 kGy) suggests the possibility of usage of SC prepared phosphor in dosimeter applications. (C) 2013 Elsevier B. V. All rights reserved.

Co-registration of speech production datasets from electromagnetic articulography and real-time magnetic resonance imaging

This paper describes a spatio-temporal registration approach for speech articulation data obtained from electromagnetic articulography (EMA) and real-time Magnetic Resonance Imaging (rtMRI). This is motivated by the potential for combining the complementary advantages of both types of data. The registration method is validated on EMA and rtMRI datasets obtained at different times, but using the same stimuli. The aligned corpus offers the advantages of high temporal resolution (from EMA) and a complete mid-sagittal view (from rtMRI). The co-registration also yields optimum placement of EMA sensors as articulatory landmarks on the magnetic resonance images, thus providing richer spatio-temporal information about articulatory dynamics. (C) 2014 Acoustical Society of America

Large linear magnetoresistance in a GaAs/AlGaAs heterostructure

We report non-saturating linear magnetoresistance (MR) in a two-dimensional electron system (2DES) at a GaAs/AlGaAs heterointerface in the strongly insulating regime. We achieve this by driving the gate voltage below the pinch-off point of the device and operating it in the non-equilibrium regime with high source-drain bias. Remarkably, the magnitude of MR is as large as 500% per Tesla with respect to resistance at zero magnetic field, thus dwarfing most non-magnetic materials which exhibit this linearity. Its primary advantage over most other materials is that both linearity and the enormous magnitude are retained over a broad temperature range (0.3 K to 10 K), thus making it an attractive candidate for cryogenic sensor applications.

A fast NMR method for resonance assignments: application to metabolomics

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled (C-12) or C-13-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D C-13, H-1] HSQC-TOCSY, (2) 2D H-1-H-1 TOCSY and (3) 2D C-13-H-1 HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D C-13, H-1] HSQC-TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete H-1 and C-13 assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.

Large-Scale Elastic Net Regularized Linear Classification SVMs and Logistic Regression

Elastic Net Regularizers have shown much promise in designing sparse classifiers for linear classification. In this work, we propose an alternating optimization approach to solve the dual problems of elastic net regularized linear classification Support Vector Machines (SVMs) and logistic regression (LR). One of the sub-problems turns out to be a simple projection. The other sub-problem can be solved using dual coordinate descent methods developed for non-sparse L2-regularized linear SVMs and LR, without altering their iteration complexity and convergence properties. Experiments on very large datasets indicate that the proposed dual coordinate descent - projection (DCD-P) methods are fast and achieve comparable generalization performance after the first pass through the data, with extremely sparse models.