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.

Electronic structure of Nd1-xYxMnO3 from Mn K edge absorption spectroscopy and DFT methods

The electronic structure of Nd1-xYxMnO3 (x-0-0.5) is studied using x-ray absorption near-edge structure (XANES) spectroscopy at the Mn K-edge along with the DFT-based LSDA+U and real space cluster calculations. The main edge of the spectra does not show any variation with doping. The pre-edge shows two distinct features which appear well-separated with doping. The intensity of the pre-edge decreases with doping. The theoretical XANES were calculated using real space multiple scattering methods which reproduces the entire experimental spectra at the main edge as well as the pre-edge. Density functional theory calculations are used to obtain the Mn 4p, Mn 3d and O 2p density of states. For x=0, the site-projected density of states at 1.7 eV above Fermi energy shows a singular peak of unoccupied e(g) (spin-up) states which is hybridized Mn 4p and O 2p states. For x=0.5, this feature develops at a higher energy and is highly delocalized and overlaps with the 3d spin-down states which changes the pre-edge intensity. The Mn 4p DOS for both compositions, show considerable difference between the individual p(x), p(y) and p(z)), states. For x=0.5, there is a considerable change in the 4p orbital polarization suggesting changes in the Jahn-Teller effect with doping. (C) 2013 Elsevier Ltd. All rights reserved.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential.

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data.

A Communication-Theoretic Framework for 2-DMR Channel Modeling: Performance Evaluation of Coding and Signal Processing Methods

We develop a communication theoretic framework for modeling 2-D magnetic recording channels. Using the model, we define the signal-to-noise ratio (SNR) for the channel considering several physical parameters, such as the channel bit density, code rate, bit aspect ratio, and noise parameters. We analyze the problem of optimizing the bit aspect ratio for maximizing SNR. The read channel architecture comprises a novel 2-D joint self-iterating equalizer and detection system with noise prediction capability. We evaluate the system performance based on our channel model through simulations. The coded performance with the 2-D equalizer detector indicates similar to 5.5 dB of SNR gain over uncoded data.

Error analysis of discontinuous Galerkin methods for the Stokes problem under minimal regularity

In this article, we analyse several discontinuous Galerkin (DG) methods for the Stokes problem under minimal regularity on the solution. We assume that the velocity u belongs to H-0(1)(Omega)](d) and the pressure p is an element of L-0(2)(Omega). First, we analyse standard DG methods assuming that the right-hand side f belongs to H-1(Omega) boolean AND L-1(Omega)](d). A DG method that is well defined for f belonging to H-1(Omega)](d) is then investigated. The methods under study include stabilized DG methods using equal-order spaces and inf-sup stable ones where the pressure space is one polynomial degree less than the velocity space.

CONVERGENCE ANALYSIS OF THE LOWEST ORDER WEAKLY PENALIZED ADAPTIVE DISCONTINUOUS GALERKIN METHODS

In this article, we prove convergence of the weakly penalized adaptive discontinuous Galerkin methods. Unlike other works, we derive the contraction property for various discontinuous Galerkin methods only assuming the stabilizing parameters are large enough to stabilize the method. A central idea in the analysis is to construct an auxiliary solution from the discontinuous Galerkin solution by a simple post processing. Based on the auxiliary solution, we define the adaptive algorithm which guides to the convergence of adaptive discontinuous Galerkin methods.

Linear filtering methods for fixed rate quantisation with noisy symmetric error channels

This study considers linear filtering methods for minimising the end-to-end average distortion of a fixed-rate source quantisation system. For the source encoder, both scalar and vector quantisation are considered. The codebook index output by the encoder is sent over a noisy discrete memoryless channel whose statistics could be unknown at the transmitter. At the receiver, the code vector corresponding to the received index is passed through a linear receive filter, whose output is an estimate of the source instantiation. Under this setup, an approximate expression for the average weighted mean-square error (WMSE) between the source instantiation and the reconstructed vector at the receiver is derived using high-resolution quantisation theory. Also, a closed-form expression for the linear receive filter that minimises the approximate average WMSE is derived. The generality of framework developed is further demonstrated by theoretically analysing the performance of other adaptation techniques that can be employed when the channel statistics are available at the transmitter also, such as joint transmit-receive linear filtering and codebook scaling. Monte Carlo simulation results validate the theoretical expressions, and illustrate the improvement in the average distortion that can be obtained using linear filtering techniques.

A Harmonic Suppression Scheme for Open-End Winding Split-Phase IM Drive Using Capacitive Filters for the Full Speed Range

Voltage source inverter (VSI)-fed six-phase induction motor (IM) drives have high 6n +/- 1, n = odd-order harmonic currents. This is because these currents, driven by the corresponding harmonic voltages in the inverter output, are limited only by the stator leakage impedance, as these harmonics are absent in the back electromotive force of the motor. To suppress the harmonic currents, either bulky inductive harmonic filters or complex pulsewidth modulation (PWM) techniques have to be used. This paper proposes a harmonic elimination scheme using switched capacitor filters for a VSI-fed split-phase IM drive. Two 3-phase inverters fed from capacitors are used on the open-end side of the motor to suppress 6n +/- 1, n = odd-order harmonics. A PWM scheme that can suppress the harmonics as well as balance the capacitor voltage is also proposed. The capacitor fed inverters are switched so that the fundamental voltage is not affected, and the fundamental power is always drawn from the main inverters. The proposed scheme is verified with a detailed experimental study. The effectiveness of the scheme is demonstrated by comparing the results with those obtained by disabling the capacitor fed inverters.

Electrothermally tunable MEMS filters

MEMS resonators have potential application in the area of frequency selective devices (e.g., gyroscopes, mass sensors, etc.). In this paper, design of electro thermally tunable resonators is presented. SOIMUMPs process is used to fabricate resonators with springs (beams) and a central mass. When voltage is applied, due to joule heating, temperature of the conducting beams goes up. This results in increase of electrical resistance due to mobility degradation. Due to increase in the temperature, springs start softening and therefore the fundamental frequency decreases. So for a given structure, one can modify the original fundamental frequency by changing the applied voltage. Coupled thermal effects result in non-uniform heating. It is observed from measurements and simulations that some parts of the beam become very hot and therefore soften more. Consequently, at higher voltages, the structure (equivalent to a single resonator) behaves like coupled resonators and exhibits peak splitting. In this mode, the given resonator can be used as a band rejection filter. This process is reversible and repeatable. For the designed structure, it is experimentally shown that by varying the voltage from 1 to 16V, the resonant frequency could be changed by 28%.

Incipient straining in severe plastic deformation methods

Knowledge of the plasticity associated with the incipient stage of chip formation is useful toward developing an understanding of the deformation field underlying severe plastic deformation processes. The transition from a transient state of straining to a steady state was investigated in plane strain machining of a model material system-copper. Characterization of the evolution to a steady-state deformation field was made by image correlation, hardness mapping, load analysis, and microstructure characterization. Empirical relationships relating the deformation heterogeneity and the process parameters were found and explained by the corresponding effects on shear plane geometry. The results are potentially useful to facilitate a framework for process design of large strain deformation configurations, wherein transient deformation fields prevail. These implications are considered in the present study to quantify the efficiency of processing methods for bulk ultrafine-grained metals by large strain extrusion machining and equal channel angular pressing.

Modelling of transient heat conduction with diffuse interface methods

We present a survey on different numerical interpolation schemes used for two-phase transient heat conduction problems in the context of interface capturing phase-field methods. Examples are general transport problems in the context of diffuse interface methods with a non-equal heat conductivity in normal and tangential directions to the interface. We extend the tonsorial approach recently published by Nicoli M et al (2011 Phys. Rev. E 84 1-6) to the general three-dimensional (3D) transient evolution equations. Validations for one-dimensional, two-dimensional and 3D transient test cases are provided, and the results are in good agreement with analytical and numerical reference solutions.

Advances in Image Reconstruction Methods for Real-Time Magnetic Resonance Thermometry

Magnetic Resonance Imaging (MRI) has been widely used in cancer treatment planning, which takes the advantage of high-resolution and high-contrast provided by it. The raw data collected in the MRI can also be used to obtain the temperature maps and has been explored for performing MR thermometry. This review article describes the methods that are used in performing MR thermometry, with an emphasis on reconstruction methods that are useful to obtain these temperature maps in real-time for large region of interest. This article also proposes a prior-image constrained reconstruction method for temperature reconstruction in MR thermometry, and a systematic comparison using ex-vivo tissue experiments with state of the art reconstruction method is presented.

Application of Qualitative Imaging Methods to Electrical Performance-Aware Package Board Design

Package-board co-design plays a crucial role in determining the performance of high-speed systems. Although there exist several commercial solutions for electromagnetic analysis and verification, lack of Computer Aided Design (CAD) tools for SI aware design and synthesis lead to longer design cycles and non-optimal package-board interconnect geometries. In this work, the functional similarities between package-board design and radio-frequency (RF) imaging are explored. Consequently, qualitative methods common to the imaging community, like Tikhonov Regularization (TR) and Landweber method are applied to solve multi-objective, multi-variable package design problems. In addition, a new hierarchical iterative piecewise linear algorithm is developed as a wrapper over LBP for an efficient solution in the design space.

Graded IR Filters: Distinguishing Between Single and Multipoint NO2 center dot center dot center dot I Halogen Bonded Supramolecular Synthons (P, Q, and R Synthons)

The NO2 center dot center dot center dot I supramolecular synthon is a halogen bonded recognition pattern that is present in the crystal structures of many compounds that contain these functional groups. These synthons have been previously distinguished as P, Q, and R types using topological and geometrical criteria. A five step IR spectroscopic sequence is proposed here to distinguish between these synthon types in solid samples. Sets of known compounds that contain the P, Q, and R synthons are first taken to develop IR spectroscopic identifiers for them. The identifiers are then used to create graded IR filters that sieve the synthons. These filters contain signatures of the individual NO2 center dot center dot center dot I synthons and may be applied to distinguish between P, Q, and R synthon varieties. They are also useful to identify synthons that are of a borderline character, synthons in disordered structures wherein the crystal structure in itself is not sufficient to distinguish synthon types, and in the identification of the NO2 center dot center dot center dot I synthons in compounds with unknown crystal structures. This study establishes clear differences for the three different geometries P, Q, and Rand in the chemical differences in the intermolecular interactions contained in the synthons. Our IR method can be conveniently employed when single crystals are not readily available also in high throughput analysis. It is possible that such identification may also be adopted as an input for crystal structure prediction analysis of compounds with unknown crystal structures.