Analytical approach to quantile estimation in regional frequency analysis based on fuzzy framework

Regional frequency analysis is widely used for estimating quantiles of hydrological extreme events at sparsely gauged/ungauged target sites in river basins. It involves identification of a region (group of watersheds) resembling watershed of the target site, and use of information pooled from the region to estimate quantile for the target site. In the analysis, watershed of the target site is assumed to completely resemble watersheds in the identified region in terms of mechanism underlying generation of extreme event. In reality, it is rare to find watersheds that completely resemble each other. Fuzzy clustering approach can account for partial resemblance of watersheds and yield region(s) for the target site. Formation of regions and quantile estimation requires discerning information from fuzzy-membership matrix obtained based on the approach. Practitioners often defuzzify the matrix to form disjoint clusters (regions) and use them as the basis for quantile estimation. The defuzzification approach (DFA) results in loss of information discerned on partial resemblance of watersheds. The lost information cannot be utilized in quantile estimation, owing to which the estimates could have significant error. To avert the loss of information, a threshold strategy (TS) was considered in some prior studies. In this study, it is analytically shown that the strategy results in under-prediction of quantiles. To address this, a mathematical approach is proposed in this study and its effectiveness in estimating flood quantiles relative to DFA and TS is demonstrated through Monte-Carlo simulation experiments and case study on Mid-Atlantic water resources region, USA. (C) 2015 Elsevier B.V. All rights reserved.

Oriented nanometric aggregates of partially inverted zinc ferrite: One-step processing and tunable high-frequency magnetic properties

In this work, it is demonstrated that the in situ growth of oriented nanometric aggregates of partially inverted zinc ferrite can potentially pave a way to alter and tune magnetocrystalline anisotropy that, in turn, dictates ferromagnetic resonance frequency (f(FMR)) by inducing strain due to aggregation. Furthermore, the influence of interparticle interaction on magnetic properties of the aggregates is investigated. Mono-dispersed zinc ferrite nanoparticles (<5 nm) with various degrees of aggregation were prepared through decomposition of metal-organic compounds of zinc (II) and iron (III) in an alcoholic solution under controlled microwave irradiation, below 200 degrees C. The nanocrystallites were found to possess high degree of inversion (>0.5). With increasing order of aggregation in the samples, saturation magnetization (at 5 K) is found to decrease from 38 emu/g to 24 emu/g, while coercivity is found to increase gradually by up to 100% (525 Oe to 1040 Oe). Anisotropy-mediated shift of f(FMR) has also been measured and discussed. In essence, the result exhibits an easy way to control the magnetic characteristics of nanocrystalline zinc ferrite, boosted with significant degree of inversion, at GHz frequencies. (C) 2015 AIP Publishing LLC.

Decreasing intensity of monsoon low-frequency intraseasonal variability over India

Understanding the changing nature of the intraseasonal oscillatory (ISO) modes of Indian summer monsoon manifested by active and break phase, and their association with extreme rainfall events are necessary for probabilistic estimation of flood-related risks in a warming climate. Here, using ground-based observed rainfall, we define an index to measure the strength of monsoon ISOs and show that the relative strength of the northward-propagating low-frequency ISO (20-60 days) modes have had a significant decreasing trend during the past six decades, possibly attributed to the weakening of large-scale circulation in the region during monsoon season. This reduction is compensated by a gain in synoptic-scale (3-9 days) variability. The decrease in low-frequency ISO variability is associated with a significant decreasing trend in the percentage of extreme events during the active phase of the monsoon. However, this decrease is balanced by significant increasing trends in the percentage of extreme events in the break and transition phases. We also find a significant rise in the occurrence of extremes during early and late monsoon months, mainly over eastern coastal regions. Our study highlights the redistribution of rainfall intensity among periodic (low-frequency) and non-periodic (extreme) modes in a changing climate scenario.

A zero charge-pump mismatch current tracking loop for reference spur reduction in PLLs

The charge-pump (CP) mismatch current is a dominant source of static phase error and reference spur in the nano-meter CMOS PLL implementations due to its worsened channel length modulation effect. This paper presents a charge-pump (CP) mismatch current reduction technique utilizing an adaptive body bias tuning of CP transistors and a zero CP mismatch current tracking PLL architecture for reference spur suppression. A chip prototype of the proposed circuit was implemented in 0.13 mu m CMOS technology. The frequency synthesizer consumes 8.2 mA current from a 13 V supply voltage and achieves a phase noise of -96.01 dBc/Hz @ 1 MHz offset from a 2.4 GHz RF carrier. The charge-pump measurements using the proposed calibration technique exhibited a mismatch current of less than 0.3 mu A (0.55%) over the VCO control voltage range of 0.3-1.0 V. The closed loop measurements show a minimized static phase error of within +/- 70 ps and a similar or equal to 9 dB reduction in reference spur level across the PLL output frequency range 2.4-2.5 GHz. The presented CP calibration technique compensates for the DC current mismatch and the mismatch due to channel length modulation effect and therefore improves the performance of CP-PLLs in nano-meter CMOS implementations. (C) 2015 Elsevier Ltd. All rights reserved.

Soft Real Time Implementation of a Cognitive Radio Testbed for Frequency Hopping Primary Satisfying QoS Requirements

The Cognitive Radio (CR) is a promising technology which provides a novel way to subjugate the issue of spectrum underutilization caused due to the fixed spectrum assignment policies. In this paper we report the design and implementation of a soft-real time CR MAC, consisting of multiple secondary users, in a frequency hopping (Fit) primary scenario. This MAC is capable of sensing the spectrum and dynamically allocating the available frequency bands to multiple CR users based on their QoS requirements. As the primary is continuously hopping, a method has also been implemented to detect the hop instant of the primary network. Synchronization usually requires real time support, however we have been able to achieve this with a soft-real time technique which enables a fully software implementation of CR MAC layer. We demonstrate the wireless transmission and reception of video over this CR testbed through opportunistic spectrum access. The experiments carried out use an open source software defined radio package called GNU Radio and a basic radio hardware component USRP.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Tuning the chiro-plasmonic response using high refractive index-dielectric templates

Chiral metamaterials have recently gained attention due to their applicability in developing polarization devices and in the detection of chiral molecules. A common approach towards fabricating plasmonic chiral nanostructures has been decorating metallic nanoparticles on dielectric chiral scaffolds, such as a helix. This resulted in the generation of a large chiro-optical response over a wide range of the electromagnetic spectrum. It has been shown previously that the optical tunability of these chiral metamaterials depends on the geometrical aspects of the overall structure, as well as the nature of the plasmonic constituents. In this study, we have investigated the role of the underlying dielectric scaffold with numerical simulations, and experimentally demonstrated that it is possible to enhance and engineer their chiro-plasmonic response significantly by choosing dielectric scaffolds of appropriate materials.

Tuning the metal-insulator transition in NdNiO3 heterostructures via Fermi surface instability and spin fluctuations

We employed in situ pulsed laser deposition (PLD) and angle-resolved photoemission spectroscopy (ARPES) to investigate the mechanism of the metal-insulator transition (MIT) in NdNiO3 (NNO) thin films, grown on NdGaO3(110) and LaAlO3(100) substrates. In the metallic phase, we observe three-dimensional hole and electron Fermi surface (FS) pockets formed from strongly renormalized bands with well-defined quasiparticles. Upon cooling across the MIT in NNO/NGO sample, the quasiparticles lose coherence via a spectral weight transfer from near the Fermi level to localized states forming at higher binding energies. In the case of NNO/LAO, the bands are apparently shifted upward with an additional holelike pocket forming at the corner of the Brillouin zone. We find that the renormalization effects are strongly anisotropic and are stronger in NNO/NGO than NNO/LAO. Our study reveals that substrate-induced strain tunes the crystal field splitting, which changes the FS properties, nesting conditions, and spin-fluctuation strength, and thereby controls the MIT via the formation of an electronic order parameter with QAF similar to (1/4,1/4,1/4 +/- delta).

Tuning of dielectric, pyroelectric and ferroelectric properties of 0.715Bi(0.5)Na(0.5)TiO(3)-0.065BaTiO(3)-0.22SrTiO(3) ceramic by internal clamping

This study systematically investigates the phenomenon of internal clamping in ferroelectric materials through the formation of glass-ceramic composites. Lead-free 0.715Bi(0.5)Na(0.5)TiO(3)-0.065BaTiO(3)-0.22SrTiO(3) (BNT-BT-ST) bulk ferroelectric ceramic was selected for the course of investigation. 3BaO - 3TiO(2) - B2O3 (BTBO) glass was then incorporated systematically to create sintered samples containing 0%, 2%, 4% and 6% glass (by weight). Upon glass induction features like remnant polarization, saturation polarization, hysteresis losses and coercive field could be varied as a function of glass content. Such effects were observed to benefit derived applications like enhanced energy storage density similar to 174 k J/m(3) to similar to 203 k J/m(3) and pyroelectric coefficient 5.7x10(-4) Cm-2K-1 to 6.8x10(-4) Cm-2K-1 by incorporation of 4% glass. Additionally, BNT-BT-ST depolarization temperature decreased from 457K to 431K by addition of 4% glass content. Glass incorporation could systematically increases diffuse phase transition and relaxor behavior temperature range from 70 K to 81K and 20K to 34 K, respectively when 6% and 4% glass content is added which indicates addition of glass provides better temperature stability. The most promising feature was observed to be that of dielectric response tuning. It can be also used to control (to an extent) the dielectric behavior of the host ceramic. Dielectric permittivity and losses decreased from 1278 to 705 and 0.109 to 0.107 for 6% glass, at room temperature. However this reduction in dielectric constant and loss increases pyroelectric figures of merit (FOMs) for high voltage responsivity (F-v) high detectivity (F-d) and energy harvesting (F-e) from 0.018 to 0.037 m(2)C(-1), 5.89 to 8.85 mu Pa-1/2 and 28.71 to 61.55 Jm(-3)K(-2), respectively for 4% added ceramic-glass at room temperature. Such findings can have huge implications in the field of tailoring ferroelectric response for application specific requirements. (C) 2015 Author(s).

Optimum Parameter Selection in Sparse Reconstruction of Frequency-Domain Optical-Coherence Tomography Signals

For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

Dynamic range tuning of graphene nanoresonators

From sensing perspective, smaller electromechanical devices, in general, are expected to be more responsive to the stimuli. This enhanced performance, however, is contingent upon the noise sources remaining unchanged and the onset of nonlinear behavior not being precipitated by miniaturization. In this paper, we study the effect of strain on the nonlinearities and dynamic range in graphene nanoresonators. The dynamic response and the onset of nonlinearity in these devices are sensitive both to the electrostatic field used to actuate the device and the strain. By tuning the strain of the device by two orders of magnitude, we observe an enhancement of 25 dB in the dynamic range leading to a mass resolution of 100 yoctogram. The increase in dynamic range in our devices is modeled as a combined effect of strain and partial cancellation of elastic and electrostatic nonlinearities. (C) 2015 AIP Publishing LLC.

High Performance Modulation of High-Frequency AC Link Inverter

Inverters with high voltage conversion ratio are used in systems with sources such as batteries, photovoltaic (PV) modules or fuel cells. Transformers are often used in such inverters to provide the required voltage conversion ratio and isolation. In this paper, a compact high-frequency (HF) transformer interfaced AC link inverter with lossless snubber is discussed. A high performance synchronized modulation scheme is proposed for this inverter. This modulation addresses the issue of over-voltage spikes due to transformer leakage inductance and it is shown that the circuit can operate safely even when the turn-on delay, such as dead-time, is not used in the HF rectifier section. The problem of spurious turn-on in the HF inverter switches is also mitigated by the proposed modulation method. The circuit performance is validated experimentally with a $900W$ prototype inverter.

A recursive multi-scaling approach to regional flood frequency analysis

Scaling approaches are widely used by hydrologists for Regional Frequency Analysis (RFA) of floods at ungauged/sparsely gauged site(s) in river basins. This paper proposes a Recursive Multi-scaling (RMS) approach to RFA that overcomes limitations of conventional simple- and multi-scaling approaches. The approach involves identification of a separate set of attributes corresponding to each of the sites (being considered in the study area/region) in a recursive manner according to their importance, and utilizing those attributes to construct effective regional regression relationships to estimate statistical raw moments (SMs) of peak flows. The SMs are then utilized to arrive at parameters of flood frequency distribution and quantile estimate(s) corresponding to target return period(s). Effectiveness of the RMS approach in arriving at flood quantile estimates for ungauged sites is demonstrated through leave-one-out cross-validation experiment on watersheds in Indiana State, USA. Results indicate that the approach outperforms index-flood based Region-of-Influence approach, simple- and multi-scaling approaches and a multiple linear regression method. (C) 2015 Elsevier B.V. All rights reserved.

Evaluation of the Index-Flood Approach Related Regional Frequency Analysis Procedures

Index-flood related regional frequency analysis (RFA) procedures are in use by hydrologists to estimate design quantiles of hydrological extreme events at data sparse/ungauged locations in river basins. There is a dearth of attempts to establish which among those procedures is better for RFA in the L-moment framework. This paper evaluates the performance of the conventional index flood (CIF), the logarithmic index flood (LIF), and two variants of the population index flood (PIF) procedures in estimating flood quantiles for ungauged locations by Monte Carlo simulation experiments and a case study on watersheds in Indiana in the U.S. To evaluate the PIF procedure, L-moment formulations are developed for implementing the procedure in situations where the regional frequency distribution (RFD) is the generalized logistic (GLO), generalized Pareto (GPA), generalized normal (GNO) or Pearson type III (PE3), as those formulations are unavailable. Results indicate that one of the variants of the PIF procedure, which utilizes the regional information on the first two L-moments is more effective than the CIF and LIF procedures. The improvement in quantile estimation using the variant of PIF procedure as compared with the CIF procedure is significant when the RFD is a generalized extreme value, GLO, GNO, or PE3, and marginal when it is GPA. (C) 2015 American Society of Civil Engineers.

Design and implementation of spectrum sensing for cognitive radios with a frequency-hopping primary system

In this work, spectrum sensing for cognitive radios is considered in the presence of multiple Primary Users (PU) using frequency-hopping communication over a set of frequency bands. The detection performance of the Fast Fourier Transform (FFT) Average Ratio (FAR) algorithm is obtained in closed-form, for a given FFT size and number of PUs. The effective throughput of the Secondary Users (SU) is formulated as an optimization problem with a constraint on the maximum allowable interference on the primary network. Given the hopping period of the PUs, the sensing duration that maximizes the SU throughput is derived. The results are validated using Monte Carlo simulations. Further, an implementation of the FAR algorithm on the Lyrtech (now, Nutaq) small form factor software defined radio development platform is presented, and the performance recorded through the hardware is observed to corroborate well with that obtained through simulations, allowing for implementation losses. (C) 2015 Elsevier B.V. All rights reserved.