Physical Layer Data Fusion Via Distributed Co-Phasing With General Signal Constellations

This paper studies a pilot-assisted physical layer data fusion technique known as Distributed Co-Phasing (DCP). In this two-phase scheme, the sensors first estimate the channel to the fusion center (FC) using pilots sent by the latter; and then they simultaneously transmit their common data by pre-rotating them by the estimated channel phase, thereby achieving physical layer data fusion. First, by analyzing the symmetric mutual information of the system, it is shown that the use of higher order constellations (HOC) can improve the throughput of DCP compared to the binary signaling considered heretofore. Using an HOC in the DCP setting requires the estimation of the composite DCP channel at the FC for data decoding. To this end, two blind algorithms are proposed: 1) power method, and 2) modified K-means algorithm. The latter algorithm is shown to be computationally efficient and converges significantly faster than the conventional K-means algorithm. Analytical expressions for the probability of error are derived, and it is found that even at moderate to low SNRs, the modified K-means algorithm achieves a probability of error comparable to that achievable with a perfect channel estimate at the FC, while requiring no pilot symbols to be transmitted from the sensor nodes. Also, the problem of signal corruption due to imperfect DCP is investigated, and constellation shaping to minimize the probability of signal corruption is proposed and analyzed. The analysis is validated, and the promising performance of DCP for energy-efficient physical layer data fusion is illustrated, using Monte Carlo simulations.

An Unbiased Risk Estimator for Multiplicative Noise - Application to 1-D Signal Denoising

The effect of multiplicative noise on a signal when compared with that of additive noise is very large. In this paper, we address the problem of suppressing multiplicative noise in one-dimensional signals. To deal with signals that are corrupted with multiplicative noise, we propose a denoising algorithm based on minimization of an unbiased estimator (MURE) of meansquare error (MSE). We derive an expression for an unbiased estimate of the MSE. The proposed denoising is carried out in wavelet domain (soft thresholding) by considering time-domain MURE. The parameters of thresholding function are obtained by minimizing the unbiased estimator MURE. We show that the parameters for optimal MURE are very close to the optimal parameters considering the oracle MSE. Experiments show that the SNR improvement for the proposed denoising algorithm is competitive with a state-of-the-art method.

A modified auxiliary excitation signal for achieving unidirectional ion ejection in quadrupole ion trap mass spectrometers operating in the resonance ejection mode

This paper proposes a technique to cause unidirectional ion ejection in a quadrupole ion trap mass spectrometer operated in the resonance ejection mode. In this technique a modified auxiliary dipolar excitation signal is applied to the endcap electrodes. This modified signal is a linear combination of two signals. The first signal is the nominal dipolar excitation signal which is applied across the endcap electrodes and the second signal is the second harmonic of the first signal, the amplitude of the second harmonic being larger than that of the fundamental. We have investigated the effect of the following parameters on achieving unidirectional ion ejection: primary signal amplitude, ratio of amplitude of second harmonic to that of primary signal amplitude, different operating points, different scan rates, different mass to charge ratios and different damping constants. In all these simulations unidirectional ejection of destabilized ions has been successfully achieved. (C) 2015 Elsevier B.V. All rights reserved.

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.

Mixed norm estimates for the Riesz transforms on the Heisenberg group

In this paper we prove weighted mixed norm estimates for Riesz transforms on the Heisenberg group and Riesz transforms associated to the special Hermite operator. From these results vector-valued inequalities for sequences of Riesz transforms associated to generalised Grushin operators and Laguerre operators are deduced.

Multiple Spectral Peak Tracking for Heart Rate Monitoring from Photoplethysmography Signal During Intensive Physical Exercise

We propose a multiple initialization based spectral peak tracking (MISPT) technique for heart rate monitoring from photoplethysmography (PPG) signal. MISPT is applied on the PPG signal after removing the motion artifact using an adaptive noise cancellation filter. MISPT yields several estimates of the heart rate trajectory from the spectrogram of the denoised PPG signal which are finally combined using a novel measure called trajectory strength. Multiple initializations help in correcting erroneous heart rate trajectories unlike the typical SPT which uses only single initialization. Experiments on the PPG data from 12 subjects recorded during intensive physical exercise show that the MISPT based heart rate monitoring indeed yields a better heart rate estimate compared to the SPT with single initialization. On the 12 datasets MISPT results in an average absolute error of 1.11 BPM which is lower than 1.28 BPM obtained by the state-of-the-art online heart rate monitoring algorithm.

Ultra-small sulphur nanoparticles configured inside a flexible organic mixed conducting network as a cathode for lithium-sulphur batteries

The major challenges in Li-S batteries are the formation of soluble polysulphides during the reversible conversion of S-8 <-> Li2S, large changes in sulphur particle volume during lithiation and extremely poor charge transport in sulphur. We demonstrate here a novel and simple strategy to overcome these challenges towards practical realization of a stable high performance Li-S battery. For the first time, a strategy is developed which does away with the necessity of pre-fabricated high surface area hollow-structured adsorbates and also multiple nontrivial synthesis steps related to sulphur loading inside such adsorbates. A lithiated polyethylene glycol (PEG) based surfactant tethered on ultra-small sulphur nanoparticles and wrapped up with polyaniline (PAni) (abbreviated as S-MIEC) is demonstrated here as an exceptional cathode for Li-S batteries. The PEG and PAni network around the sulphur nanoparticles serves as an efficient flexible trap for sulphur and polysulphides and also provides distinct pathways for electrons (through PAni) and ions (through PEG) during battery operation. Contrary to the cathodes demonstrated based on various carbon-sulphur composites, the mixed conducting S-MIEC showed an extremely high loading of 75%. The S-MIEC exhibited a stable capacity of nearly 900 mA h g(-1) at the end of 100 cycles at a 1C current rate.

Effect of Channel Confinement on Mixed Convective Flow Past an Equilateral Triangular Cylinder

The present work investigates the mixed convective flow and heat transfer characteristics past a triangular cylinder placed symmetrically in a vertical channel. At a representative Reynolds number, Re = 100, simulations are carried out for the blockage ratios beta = 1/3; 1/4; and 1/6. Effect of aiding and opposing buoyancy is brought about by varying the Richardson number in the range -1.0 <= Ri <= 1.0. At a blockage ratio of 1/3, suppression of vortex shedding is found at Ri = 1, whereas von Karman vortex street is seen both at beta = 1/4 and 1/6, respectively. This is the first time that such behavior of blockage ratio past a triangular cylinder in the present flow configuration is reported. Drag coefficient increases progressively with increasing Ri and a slightly higher value is noticed at beta = 1/3. For all b, heat transfer increases with increasing Ri. Flattening of Nu(avg)-Ri curve beyond Ri > 0: 75 is observed at beta = 1/3.

Deployment strategy for controlled morphologies in sessile, mixed colloidal droplets

Colloidal systems offer an effective medium to micro-engineer complex structures without involving sophisticated fabrication procedures. This article presents a deployment strategy of multiple droplets of different colloidal composition and utilizes the inherent capillary flow driven self assembly of nanoparticles to construct stacks of multiple materials on a given glass substrate. Here we used aqueous nano-crystalline titania and nano-amorphous silica solutions as the two materials. Initially, a pure nanotitania (nanosilica) droplet is deployed and allowed to dry partially. Subsequently, a second droplet of pure nanosilica (nanotitania) is deployed co-axially on the partially dried precipitate. The proposed deployment strategy allowed significant morphological differences when the deployment order of nanosilica and nanotitania were interchanged. Compositional analysis performed using EDX (Energy Dispersive X-ray spectroscopy) showed preferential deposition of nanosilica and nanotitania along the radial as well as the axial plane of the final deposit pattern. The underlying mechanism for such a phenomenon could be attributed to the contact line dynamics of a sessile double droplet. We also observe heteroaggregation of the nanosilica-nanotitania interaction along a narrow interface which resulted in nanotitania particles clustering into isolated islands embedded into a matrix of nanosilica particles. Overall, this work elucidates the evaporation driven dynamics of a mixed colloidal system which displays both macroscopic as well as microscopic phenomena. Such a system could be used to generate ordered arrays of functional materials with engineered micro to nano-scale properties.

Room temperature ferromagnetism and white light emissive CdS:Cr nanoparticles synthesized by chemical co-precipitation method

Undoped and Cr (3% and 5%) doped CdS nanoparticles were synthesized by chemical co-precipitation method. The synthesized nanocrystalline particles are characterized by energy dispersive X-ray analysis (EDAX), scanning electron microscope (SEM), X-ray Diffraction (XRD), transmission electron microscopy (TEM), diffuse reflectance spectroscopy (DRS), photoluminescence (PL), Electron paramagnetic resonance (EPR), vibrating sample magnetometer (VSM) and Raman spectroscopy. XRD studies indicate that Cr doping in host CdS result a structural change from Cubic phase to mixed (cubic + hexagonal) phase. Due to quantum confinement effect, widening of the band gap is observed for undoped and Cr doped CdS nanoparticles compared to bulk CdS. The average particle size calculated from band gap values is in good agreement with the TEM study calculation and it is around 4-5 nm. A strong violet emission band consisting of two emission peaks is observed for undoped CdS nanoparticles, whereas for CdS:Cr nanoparticles, a broad emission band ranging from 420 nm to 730 nm with a maximum at similar to 587 nm is observed. The broad emission band is due to the overlapped emissions from variety of defects. EPR spectra of CdS:Cr samples reveal resonance signal at g = 2.143 corresponding to interacting Cr3+ ions. VSM studies indicate that the diamagnetic CdS nanoparticles are transform to ferromagnetic for 3% Cr3+ doping and the ferromagnetic nature is diminished with increasing the doping concentration to 5%. (C) 2015 Elsevier B.V. All rights reserved.

Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk

Complex systems inspired analysis suggests a hypothesis that financial meltdowns are abrupt critical transitions that occur when the system reaches a tipping point. Theoretical and empirical studies on climatic and ecological dynamical systems have shown that approach to tipping points is preceded by a generic phenomenon called critical slowing down, i.e. an increasingly slow response of the system to perturbations. Therefore, it has been suggested that critical slowing down may be used as an early warning signal of imminent critical transitions. Whether financial markets exhibit critical slowing down prior to meltdowns remains unclear. Here, our analysis reveals that three major US (Dow Jones Index, S&P 500 and NASDAQ) and two European markets (DAX and FTSE) did not exhibit critical slowing down prior to major financial crashes over the last century. However, all markets showed strong trends of rising variability, quantified by time series variance and spectral function at low frequencies, prior to crashes. These results suggest that financial crashes are not critical transitions that occur in the vicinity of a tipping point. Using a simple model, we argue that financial crashes are likely to be stochastic transitions which can occur even when the system is far away from the tipping point. Specifically, we show that a gradually increasing strength of stochastic perturbations may have caused to abrupt transitions in the financial markets. Broadly, our results highlight the importance of stochastically driven abrupt transitions in real world scenarios. Our study offers rising variability as a precursor of financial meltdowns albeit with a limitation that they may signal false alarms.

Small-Signal Stability Analysis of an Open-Loop Induction Motor Drive Including the Effect of Inverter Deadtime

This paper demonstrates light-load instability in a 100-kW open-loop induction motor drive on account of inverter deadtime. An improved small-signal model of an inverter-fed induction motor is proposed. This improved model is derived by linearizing the nonlinear dynamic equations of the motor, which include the inverter deadtime effect. Stability analysis is carried out on the 100-kW415-V three-phase induction motor considering no load. The analysis brings out the region of instability of this motor drive on the voltage versus frequency (V-f) plane. This region of light-load instability is found to expand with increase in inverter deadtime. Subharmonic oscillations of significant amplitude are observed in the steady-state simulated and measured current waveforms, at numerous operating points in the unstable region predicted, confirming the validity of the stability analysis. Furthermore, simulation and experimental results demonstrate that the proposed model is more accurate than an existing small-signal model in predicting the region of instability.

Comments on ``Influence of chemical reaction and viscous dissipation on MHD mixed convection flow'' by K. Das JMST 28 (5) (2014) 1881 similar to 1885] and ``Cu-water nanofluid flow and heat transfer over a shrinking sheet'' by K. Das JMST 28 (12) 5089 similar to 5094]

In this letter, we submit our comment on the following recently published papers by Kalidas Das: (1) ``Influence of chemical reaction and viscous dissipation on MHD mixed convection flow,'' Journal of Mechanical Science and Technology 28 (5) (2014) 1881-1885; and (2) ``Cu-water nanofluid flow and heat transfer over a shrinking sheet,'' Journal of Mechanical Science and Technology 28 (12) (2014) 5089-5094. The authors attempt to present the similarity solutions in both papers. We comment that the similarity transformations considered in Refs. 1, 2] are incorrect. Thus, the results presented by Kalidas Das lead to invalid conclusions.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

Effect of strain rate response and pin diameter on mechanically mixed layer formation and wear mechanisms in a Ti6Al4V-SS316L pair

Three mechanisms operate during wear of materials. These mechanisms include the Strain Rate Response (SRR - effect of strain rate on plastic deformation), Tribo-Chemical Reactions (TCR) and formation of Mechanically Mixed Layers (MML). The present work investigates the effect of these three in context of the formation of MML. For this wear experiments are done on a pin-on-disc machine using Ti64 as the pin and SS316L as the disc. It is seen that apart from the speed and load, which control the SRR and TCR, the diameter of the pin controls the formation of MML, especially at higher speeds.