Spectral Zero-Crossings: Localization Properties and Applications

We present an analysis of the rate of sign changes in the discrete Fourier spectrum of a sequence. The sign changes of either the real or imaginary parts of the spectrum are considered, and the rate of sign changes is termed as the spectral zero-crossing rate (SZCR). We show that SZCR carries information pertaining to the locations of transients within the temporal observation window. We show duality with temporal zero-crossing rate analysis by expressing the spectrum of a signal as a sum of sinusoids with random phases. This extension leads to spectral-domain iterative filtering approaches to stabilize the spectral zero-crossing rate and to improve upon the location estimates. The localization properties are compared with group-delay-based localization metrics in a stylized signal setting well-known in speech processing literature. We show applications to epoch estimation in voiced speech signals using the SZCR on the integrated linear prediction residue. The performance of the SZCR-based epoch localization technique is competitive with the state-of-the-art epoch estimation techniques that are based on average pitch period.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Outer Bounds on the Secrecy Rate of the 2-User Symmetric Deterministic Interference Channel with Transmitter Cooperation

This paper derives outer bounds for the 2-user symmetric linear deterministic interference channel (SLDIC) with limited-rate transmitter cooperation and perfect secrecy constraints at the receivers. Five outer bounds are derived, under different assumptions of providing side information to receivers and partitioning the encoded message/output depending on the relative strength of the signal and the interference. The usefulness of these outer bounds is shown by comparing the bounds with the inner bound on the achievable secrecy rate derived by the authors in a previous work. Also, the outer bounds help to establish that sharing random bits through the cooperative link can achieve the optimal rate in the very high interference regime.

Dynamics of Glass Forming Liquids with Randomly Pinned Particles

It is frequently assumed that in the limit of vanishing cooling rate, the glass transition phenomenon becomes a thermodynamic transition at a temperature T-K. However, with any finite cooling rate, the system falls out of equilibrium at temperatures near T-g(> T-K), implying that the very existence of the putative thermodynamic phase transition at T-K can be questioned. Recent studies of systems with randomly pinned particles have hinted that the thermodynamic glass transition may be observed for liquids with randomly pinned particles. This expectation is based on the results of approximate calculations that suggest that the thermodynamic glass transition temperature increases with increasing concentration of pinned particles and it may be possible to equilibrate the system at temperatures near the increased transition temperature. We test the validity of this prediction through extensive molecular dynamics simulations of two model glass-forming liquids in the presence of random pinning. We find that extrapolated thermodynamic transition temperature T-K does not show any sign of increasing with increasing pinning concentration. The main effect of pinning is found to be a rapid decrease in the kinetic fragility of the system with increasing pin concentration. Implications of these observations for current theories of the glass transition are discussed.

Correlation Between Decay Rate and Amplitude of Solar Cycles as Revealed from Observations and Dynamo Theory

Using different proxies of solar activity, we have studied the following features of the solar cycle: i) The linear correlation between the amplitude of cycle and its decay rate, ii) the linear correlation between the amplitude of cycle and the decay rate of cycle , and iii) the anti-correlation between the amplitude of cycle and the period of cycle . Features ii) and iii) are very useful because they provide precursors for future cycles. We have reproduced these features using a flux-transport dynamo model with stochastic fluctuations in the Babcock-Leighton effect and in the meridional circulation. Only when we introduce fluctuations in meridional circulation, are we able to reproduce different observed features of the solar cycle. We discuss the possible reasons for these correlations.

Outer Bounds on the Sum Rate of the K-User MIMO Gaussian Interference Channel

This paper derives outer bounds on the sum rate of the K-user MIMO Gaussian interference channel (GIC). Three outer bounds are derived, under different assumptions of cooperation and providing side information to receivers. The novelty in the derivation lies in the careful selection of side information, which results in the cancellation of the negative differential entropy terms containing signal components, leading to a tractable outer bound. The overall outer bound is obtained by taking the minimum of the three outer bounds. The derived bounds are simplified for the MIMO Gaussian symmetric IC to obtain outer bounds on the generalized degrees of freedom (GDOF). The relative performance of the bounds yields insight into the performance limits of multiuser MIMO GICs and the relative merits of different schemes for interference management. These insights are confirmed by establishing the optimality of the bounds in specific cases using an inner bound on the GDOF derived by the authors in a previous work. It is also shown that many of the existing results on the GDOF of the GIC can be obtained as special cases of the bounds, e. g., by setting K = 2 or the number of antennas at each user to 1.

Prediction of Fatigue Life in Plain Concrete Using Entropy Production

An energy approach within the framework of thermodynamics is used to model the fatigue process in plain concrete. Fatigue crack growth is an irreversible process associated with an irreversible entropy gain. A closed-form expression for entropy generated during fatigue in terms of energy dissipated is derived using principles of dimensional analysis and self-similarity. An increase in compliance is considered as a measure of damage accumulated during fatigue. The entropy at final fatigue failure is shown to be independent of loading and geometry and is proposed as a material property. A relationship between energy dissipated and number of cycles of fatigue loading is obtained. (C) 2015 American Society of Civil Engineers.

Origin of nonlinearity and plausible turbulence by hydromagnetic transient growth in accretion disks: Faster growth rate than magnetorotational instability

We investigate the evolution of hydromagnetic perturbations in a small section of accretion disks. It is known that molecular viscosity is negligible in accretion disks. Hence, it has been argued that a mechanism, known as magnetorotational instability (MRI), is responsible for transporting matter in the presence of a weak magnetic field. However, there are some shortcomings, which question the effectiveness of MRI. Now the question arises, whether other hydromagnetic effects, e.g., transient growth (TG), can play an important role in bringing nonlinearity into the system, even at weak magnetic fields. In addition, it should be determined whether MRI or TG is primarily responsible for revealing nonlinearity in order to make the flow turbulent. Our results prove explicitly that the flows with a high Reynolds number (Re), which is the case for realistic astrophysical accretion disks, exhibit nonlinearity via TG of perturbation modes faster than that by modes producing MRI. For a fixed wave vector, MRI dominates over transient effects only at low Re, lower than the value expected to be in astrophysical accretion disks, and low magnetic fields. This calls into serious question the (overall) persuasiveness of MRI in astrophysical accretion disks.

Modeling of Effect of Nucleation Rate and Electrodes' Resistance on Discharge Characteristics of Lead-Acid Batteries

Classical models are not successful in describing discharge characteristics of a lead-acid battery when the current density is varied over a wide range. A model is developed in this work to overcome this lacuna by introducing into the standard models two mechanisms that have not been used earlier. Lead sulfate particles nucleate and grow on active materials of electrodes during discharge, resulting in coverage of active area. Increasing rate of discharge builds supersaturation of lead sulfate rapidly, and causes increased extents of nucleation and coverage. Electrodes behave almost like an insulator due to deposition of lead sulfate when active materials are converted to a critical extent, and this can stop discharge process. Influence of this mechanism is also rate dependent. The new model developed is tested against data on polarization behavior, and capacity drawn as a function of current. The model successfully predicts both polarization curves and Peukert behavior. The model is used to predict charge that can be drawn at a current after partial discharge at a different current. Model suggests that altering nucleation behavior can be useful in enhancing capacity available for discharge. (C) 2015 The Electrochemical Society.

Generalized Partial Response Equalization and Data-Dependent Noise Predictive Signal Detection Over Media Models for TDMR

Two-dimensional magnetic recording (2-D TDMR) is an emerging technology that aims to achieve areal densities as high as 10 Tb/in(2) using sophisticated 2-D signal-processing algorithms. High areal densities are achieved by reducing the size of a bit to the order of the size of magnetic grains, resulting in severe 2-D intersymbol interference (ISI). Jitter noise due to irregular grain positions on the magnetic medium is more pronounced at these areal densities. Therefore, a viable read-channel architecture for TDMR requires 2-D signal-detection algorithms that can mitigate 2-D ISI and combat noise comprising jitter and electronic components. Partial response maximum likelihood (PRML) detection scheme allows controlled ISI as seen by the detector. With the controlled and reduced span of 2-D ISI, the PRML scheme overcomes practical difficulties such as Nyquist rate signaling required for full response 2-D equalization. As in the case of 1-D magnetic recording, jitter noise can be handled using a data-dependent noise-prediction (DDNP) filter bank within a 2-D signal-detection engine. The contributions of this paper are threefold: 1) we empirically study the jitter noise characteristics in TDMR as a function of grain density using a Voronoi-based granular media model; 2) we develop a 2-D DDNP algorithm to handle the media noise seen in TDMR; and 3) we also develop techniques to design 2-D separable and nonseparable targets for generalized partial response equalization for TDMR. This can be used along with a 2-D signal-detection algorithm. The DDNP algorithm is observed to give a 2.5 dB gain in SNR over uncoded data compared with the noise predictive maximum likelihood detection for the same choice of channel model parameters to achieve a channel bit density of 1.3 Tb/in(2) with media grain center-to-center distance of 10 nm. The DDNP algorithm is observed to give similar to 10% gain in areal density near 5 grains/bit. The proposed signal-processing framework can broadly scale to various TDMR realizations and areal density points.

Probabilistic Prediction based Scheduling for Delay Sensitive Traffic in Internet of Things

This paper proposes a probabilistic prediction based approach for providing Quality of Service (QoS) to delay sensitive traffic for Internet of Things (IoT). A joint packet scheduling and dynamic bandwidth allocation scheme is proposed to provide service differentiation and preferential treatment to delay sensitive traffic. The scheduler focuses on reducing the waiting time of high priority delay sensitive services in the queue and simultaneously keeping the waiting time of other services within tolerable limits. The scheme uses the difference in probability of average queue length of high priority packets at previous cycle and current cycle to determine the probability of average weight required in the current cycle. This offers optimized bandwidth allocation to all the services by avoiding distribution of excess resources for high priority services and yet guaranteeing the services for it. The performance of the algorithm is investigated using MPEG-4 traffic traces under different system loading. The results show the improved performance with respect to waiting time for scheduling high priority packets and simultaneously keeping tolerable limits for waiting time and packet loss for other services. Crown Copyright (C) 2015 Published by Elsevier B.V.

A Zero-Crossing Rate Property of Power Complementary Analysis Filterbank Outputs

We establish zero-crossing rate (ZCR) relations between the input and the subbands of a maximally decimated M-channel power complementary analysis filterbank when the input is a stationary Gaussian process. The ZCR at lag is defined as the number of sign changes between the samples of a sequence and its 1-sample shifted version, normalized by the sequence length. We derive the relationship between the ZCR of the Gaussian process at lags that are integer multiples of Al and the subband ZCRs. Based on this result, we propose a robust iterative autocorrelation estimator for a signal consisting of a sum of sinusoids of fixed amplitudes and uniformly distributed random phases. Simulation results show that the performance of the proposed estimator is better than the sample autocorrelation over the SNR range of -6 to 15 dB. Validation on a segment of a trumpet signal showed similar performance gains.

PREDICTION OF TRANSITIONAL AND SEPARATED BOUNDARY LAYERS IN A COMPRESSOR CASCADE

Numerical simulations were performed of experiments from a cascade of stator blades at three low Reynolds numbers representative of flight conditions. Solutions were assessed by comparing blade surface pressures, velocity and turbulence intensity along blade normals at several stations along the suction surface and in the wake. At Re = 210,000 and 380,000 the laminar boundary layer over the suction surface separates and reattaches with significant turbulence fluctuations. A new 3-equation transition model, the k-k(L)-omega model, was used to simulate this flow. Predicted locations of the separation bubble, and profiles of velocity and turbulence fluctuations on blade-normal lines at various stations along the blade were found to be quite close to measurements. Suction surface pressure distributions were not as close at the lower Re. The solution with the standard k-omega SST model showed significant differences in all quantities. At Re = 640,000 transition occurs earlier and it is a turbulent boundary layer that separates near the trailing edge. The solution with the Reynolds stress model was found to be quite close to the experiment in the separated region also, unlike the k-omega SST solution. Three-dimensional computations were performed at Re = 380,000 and 640,000. In both cases there were no significant differences between the midspan solution from 3D computations and the 2D solutions. However, the 3D solutions exhibited flow features observed in the experiments the nearly 2D structure of the flow over most of the span at 380,000 and the spanwise growth of corner vortices from the endwall at 640,000.

An automatic algorithm for mixed mode crack growth rate based on drop potential method

A new automatic algorithm for the assessment of mixed mode crack growth rate characteristics is presented based on the concept of an equivalent crack. The residual ligament size approach is introduced to implementation this algorithm for identifying the crack tip position on a curved path with respect to the drop potential signal. The automatic algorithm accounting for the curvilinear crack trajectory and employing an electrical potential difference was calibrated with respect to the optical measurements for the growing crack under cyclic mixed mode loading conditions. The effectiveness of the proposed algorithm is confirmed by fatigue tests performed on ST3 steel compact tension-shear specimens in the full range of mode mixities from pure mode Ito pure mode II. (C) 2015 Elsevier Ltd. All rights reserved.