On Computing Amplitude, Phase, and Frequency Modulations Using a Vector Interpretation of the Analytic Signal

The amplitude-modulation (AM) and phase-modulation (PM) of an amplitude-modulated frequency-modulated (AM-FM) signal are defined as the modulus and phase angle, respectively, of the analytic signal (AS). The FM is defined as the derivative of the PM. However, this standard definition results in a PM with jump discontinuities in cases when the AM index exceeds unity, resulting in an FM that contains impulses. We propose a new approach to define smooth AM, PM, and FM for the AS, where the PM is computed as the solution to an optimization problem based on a vector interpretation of the AS. Our approach is directly linked to the fractional Hilbert transform (FrHT) and leads to an eigenvalue problem. The resulting PM and AM are shown to be smooth, and in particular, the AM turns out to be bipolar. We show an equivalence of the eigenvalue formulation to the square of the AS, and arrive at a simple method to compute the smooth PM. Some examples on synthesized and real signals are provided to validate the theoretical calculations.

On the unramified principal series of GL(3) over non-archimedean local fields

Let F be a non-archimedean local field and let O be its ring of integers. We give a complete description of the irreducible constituents of the restriction of the unramified principal series representations of GL(3)(F) to GL(3)(O). (C) 2013 Elsevier Inc. All rights reserved.

Support vector clustering-based direct coherency identification of generators in a multi-machine power system

This study investigates the application of support vector clustering (SVC) for the direct identification of coherent synchronous generators in large interconnected multi-machine power systems. The clustering is based on coherency measure, which indicates the degree of coherency between any pair of generators. The proposed SVC algorithm processes the coherency measure matrix that is formulated using the generator rotor measurements to cluster the coherent generators. The proposed approach is demonstrated on IEEE 10 generator 39-bus system and an equivalent 35 generators, 246-bus system of practical Indian southern grid. The effect of number of data samples and fault locations are also examined for determining the accuracy of the proposed approach. An extended comparison with other clustering techniques is also included, to show the effectiveness of the proposed approach in grouping the data into coherent groups of generators. This effectiveness of the coherent clusters obtained with the proposed approach is compared in terms of a set of clustering validity indicators and in terms of statistical assessment that is based on the coherency degree of a generator pair.

Detecting symmetry in scalar fields using augmented extremum graphs

Visualizing symmetric patterns in the data often helps the domain scientists make important observations and gain insights about the underlying experiment. Detecting symmetry in scalar fields is a nascent area of research and existing methods that detect symmetry are either not robust in the presence of noise or computationally costly. We propose a data structure called the augmented extremum graph and use it to design a novel symmetry detection method based on robust estimation of distances. The augmented extremum graph captures both topological and geometric information of the scalar field and enables robust and computationally efficient detection of symmetry. We apply the proposed method to detect symmetries in cryo-electron microscopy datasets and the experiments demonstrate that the algorithm is capable of detecting symmetry even in the presence of significant noise. We describe novel applications that use the detected symmetry to enhance visualization of scalar field data and facilitate their exploration.

A Quick-Simulation Tool for Induction Motor Drives Controlled Using Advanced Space-Vector-Based PWM Techniques

Space-vector-based pulse width modulation (PWM) for a voltage source inverter (VSI) offers flexibility in terms of different switching sequences. Numerical simulation is helpful to assess the performance of a PWM method before actual implementation. A quick-simulation tool to simulate a variety of space-vector-based PWM strategies for a two-level VSI-fed squirrel cage induction motor drive is presented. The simulator is developed using C and Python programming languages, and has a graphical user interface (GUI) also. The prime focus being PWM strategies, the simulator developed is 40 times faster than MATLAB in terms of the actual time taken for a simulation. Simulation and experimental results are presented on a 5-hp ac motor drive.

Efficient Dendrimer-DNA Complexation and Gene Delivery Vector Properties of Nitrogen-Core Poly(propyl ether imine) Dendrimer in Mammalian Cells

Dendrimers as vectors for gene delivery were established, primarily by utilizing few prominent dendrimer types so far. We report herein studies of DNA complexation efficacies and gene delivery vector properties of a nitrogen-core poly(propyl ether imine) (PETIM) dendrimer, constituted with 22 tertiary amine internal branches and 24 primary amines at the periphery. The interaction of the dendrimer with pEGFPDNA was evaluated through UV-vis, circular dichroism (CD) spectral studies, ethidium bromide fluorescence emission quenching, thermal melting, and gel retardation assays, from which most changes to DNA structure during complexation was found to occur at a weight ratio of dendrimer:DNA similar to 2:1. The zeta potential measurements further confirmed this stoichiometry at electroneutrality. The structure of a DNA oligomer upon dendrimer complexation was simulated through molecular modeling and the simulation showed that the dendrimer enfolded DNA oligomer along both major and minor grooves, without causing DNA deformation, in 1:1 and 2:1 dendrimer-to-DNA complexes. Atomic force microscopy (AFM) studies on dendrimer-pEGFP DNA complex showed an increase in the average z-height as a result of dendrimers decorating the DNA, without causing a distortion of the DNA structure. Cytotoxicity studies involving five different mammalian cell lines, using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide] (MTT) assay, reveal the dendrimer toxicity profile (IC50) values of similar to 400-1000 mu g mL(-1), depending on the cell line tested. Quantitative estimation, using luciferase assay, showed that the gene transfection was at least 100 times higher when compared to poly(ethylene imine) branched polymer, having similar number of cationic sites as the dendrimer. The present study establishes the physicochemical behavior of new nitrogen-core PETIM dendrimer-DNA complexes, their lower toxicities, and efficient gene delivery vector properties.

A Novel Design Method for SOGI-PLL for Minimum Settling Time and Low Unit Vector Distortion

Phase-locked loops (PLLs) are necessary in grid connected systems to obtain information about the frequency, amplitude and phase of the grid voltage. In stationary reference frame control, the unit vectors of PLLs are used for reference generation. It is important that the PLL performance is not affected significantly when grid voltage undergoes amplitude and frequency variations. In this paper, a novel design for the popular single-phase PLL topology, namely the second-order generalized integrator (SOGI) based PLL is proposed which achieves minimum settling time during grid voltage amplitude and frequency variations. The proposed design achieves a settling time of less than 27.7 ms. This design also ensures that the unit vectors generated by this PLL have a steady state THD of less than 1% during frequency variations of the grid voltage. The design of the SOGI-PLL based on the theoretical analysis is validated by experimental results.

A New Voltage Stability Index based on the Tangent Vector of the Power Flow Jacobian

This paper presents a new voltage stability index based on the tangent vector of the power flow jacobian. This index is capable of providing the relative vulnerability information of the system buses from the point of view of voltage collapse. In an effort to compare this index with a similar index, the popular voltage stability index L is studied and it is shown through system studies that the L index is not a very consistent indicator of the voltage collapse point of the system but is only a reasonable indicator of the vulnerability of the system buses to voltage collapse. We also show that the new index can be used in the voltage stability analysis of radial systems which is not possible with the L index. This is a significant result of this investigation since there is a lot of contemporary interest in distributed generation and microgrids which are by and large radial in nature. Simulation results considering several test systems are provided to validate the results and the computational needs of the proposed scheme is assessed in comparison with other schemes

Scalable sequential alternating proximal methods for sparse structural SVMs and CRFs

Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.

Magnetic field induced delocalization in multi-wall carbon nanotube-polystyrene composite at high fields

In well dispersed multi-wall carbon nanotube-polystyrene composite of 15 wt%, with room temperature conductivity of similar to 5 S/cm and resistivity ratio R-2K/R-200K] of similar to 1.4, the temperature dependence of conductivity follows a power-law behavior. The conductivity increases with magnetic field for a wide range of temperature (2-200 K), and power-law fits to conductivity data show that localization length (xi) increases with magnetic field, resulting in a large negative magnetoresistance (MR). At 50T, the negative MR at 8 K is similar to 13% and it shows a maximum at 90K (similar to 25%). This unusually large negative MR indicates that the field is delocalizing the charge carriers even at higher temperatures, apart from the smaller weak localization contribution at T < 20 K. This field-induced delocalization mechanism of MR can provide insight into the intra and inter tube transport. (C) 2013 Elsevier Ltd. All rights reserved.

EVOLUTION OF DEFORMATION FIELDS IN PLOUGHING OF SAND

This paper reports on an experimental study on the ploughing or orthogonal cutting in sand. Plane strain cutting or ploughing experiments were carried out on model Ottawa sand while being imaged at high resolution. The images obtained were further processed using image analysis and the evolution of the velocity and deformation fields were obtained from these analysis. The deformation fields show the presence of a clear shear zone in which the sand accrues deformation. A net change in the direction of the velocity of the sand is also clearly visible. The effective depth of cut of the sand also increases with continuous cutting as the sand reposes on itself. This deformation mechanics at the incipient stages of cutting is similar to that observed in metal cutting.

Space-Vector-Based Hybrid Pulsewidth Modulation Techniques for a Three-Level Inverter

Novel switching sequences have been proposed recently for a neutral-point-clamped three-level inverter, controlled effectively as an equivalent two-level inverter. It is shown that the four novel sequences can be grouped into two pairs of sequences. Using each pair of sequences, a hybrid pulsewidth modulation (PWM) technique is proposed, which deploys the two sequences in appropriate spatial regions to reduce the current ripple. Further, a third hybrid PWM technique is proposed which uses all the five sequences (including the conventional sequence) in appropriate spatial regions. Each proposed hybrid PWM is shown, both analytically and experimentally, to outperform its constituent PWM methods in terms of harmonic distortion. In particular, the third proposed hybrid PWM reduces the total harmonic distortion considerably at low- and high-speed ranges of a constant volts-per-hertz induction motor drive, compared to centered space vector PWM.

A Nearly Constant Switching Frequency Current Error Space Vector Based Hysteresis Controller for an IM Drive with 12-sided Polygonal Voltage Space Vectors

In this paper, a current error space vector (CESV) based hysteresis controller for a 12-sided polygonal voltage space vector inverter fed induction motor (IM) drive is proposed, for the first time. An open-end winding configuration is used for the induction motor. The proposed controller uses parabolic boundary with generalized vector selection logic for all sectors. The drive scheme is first studied with a space vector based PWM (SVPWM) control and from this the current error space phasor boundary is obtained. This current error space phasor boundary is approximated with four parabolas and then the system is run with space phasor based hysteresis PWM controller by limiting the CESV within the parabolic boundary. The proposed controller has increased modulation range, absence of 5th and 7th order harmonics for the entire modulation range, nearly constant switching frequency, fast dynamic response with smooth transition to the over modulation region and a simple controller implementation.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Signal tracking approach for phase estimation in digital holographic interferometry

In this research work, we introduce a novel approach for phase estimation from noisy reconstructed interference fields in digital holographic interferometry using an unscented Kalman filter. Unlike conventionally used unwrapping algorithms and piecewise polynomial approximation approaches, this paper proposes, for the first time to the best of our knowledge, a signal tracking approach for phase estimation. The state space model derived in this approach is inspired from the Taylor series expansion of the phase function as the process model, and polar to Cartesian conversion as the measurement model. We have characterized our approach by simulations and validated the performance on experimental data (holograms) recorded under various practical conditions. Our study reveals that the proposed approach, when compared with various phase estimation methods available in the literature, outperforms at lower SNR values (i.e., especially in the range 0-20 dB). It is demonstrated with experimental data as well that the proposed approach is a better choice for estimating rapidly varying phase with high dynamic range and noise. (C) 2014 Optical Society of America