Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.

Quick measurement of H-1-F-19 scalar couplings from the complex NMR spectra by real-time spin edition

Most often the measurement of VHF from the conventional 1D H-1 NMR spectrum is severely hindered consequent to similar magnitudes of JHF and JHH couplings and the spectral multiplicity pattern. The present study reports a new 1D NMR technique based on real time spin edition, which removes all JHF and JHH while retaining only VHF of a chosen fluorine. The obtained spectrum is significantly simplified and permits straightforward determination of all possible VHF values of a chosen fluorine. Due to one dimensional nature, the method is much faster compared to 2D GET-SERF by 1-2 orders of magnitude. (C) 2015 Elsevier B.V. All rights reserved.

Fuzzy State Real-Time Reservoir Operation Model for Irrigation with Gridded Rainfall Forecasts

A short-term real-time operation model with fuzzy state variables is developed for irrigation of multiple crops based on earlier work on long-term steady-state policy. The features of the model that distinguish it from the earlier work are (1) apart from inclusion of fuzziness in reservoir storage and in soil moisture of crops, spatial variations in rainfall and soil moisture of crops are included in the real-time operation model by considering gridded command area with a grid size of 0.5 degrees latitude by 0.5 degrees longitude; (2) the water allocation model and soil moisture balance equations are integrated with the real-time operation model with consideration of ponding water depth for Paddy crop; the model solution specifies reservoir releases for irrigation in a 10-day time period and allocations among the crops on a daily basis at each grid by maintaining soil moisture balance at the end of the day; and (3) the release policy is developed using forecasted daily rainfall data of each grid and is implemented for the current time period using actual 10-day inflow and actual daily rainfall of each grid. The real-time operation model is applied to Bhadra Reservoir in Karnataka, India. The results obtained using the real-time operation model are compared with those of the standard operating policy model. Inclusion of fuzziness in reservoir storage and soil moisture of crops captures hydrologic uncertainties in real time. Considerations of irrigation decisions on a daily basis and the gridded command area result in variations in allocating water to the crops, variations in actual crop evapotranspiration, and variations in soil moisture of the crops on a daily basis for each grid of the command area. (C) 2015 American Society of Civil Engineers.

A real-time coherent dedispersion pipeline for the giant metrewave radio telescope

A fully real-time coherent dedispersion system has been developed for the pulsar back-end at the Giant Metrewave Radio Telescope (GMRT). The dedispersion pipeline uses the single phased array voltage beam produced by the existing GMRT software back-end (GSB) to produce coherently dedispersed intensity output in real time, for the currently operational bandwidths of 16 MHz and 32 MHz. Provision has also been made to coherently dedisperse voltage beam data from observations recorded on disk. We discuss the design and implementation of the real-time coherent dedispersion system, describing the steps carried out to optimise the performance of the pipeline. Presently functioning on an Intel Xeon X5550 CPU equipped with a NVIDIA Tesla C2075 GPU, the pipeline allows dispersion free, high time resolution data to be obtained in real-time. We illustrate the significant improvements over the existing incoherent dedispersion system at the GMRT, and present some preliminary results obtained from studies of pulsars using this system, demonstrating its potential as a useful tool for low frequency pulsar observations. We describe the salient features of our implementation, comparing it with other recently developed real-time coherent dedispersion systems. This implementation of a real-time coherent dedispersion pipeline for a large, low frequency array instrument like the GMRT, will enable long-term observing programs using coherent dedispersion to be carried out routinely at the observatory. We also outline the possible improvements for such a pipeline, including prospects for the upgraded GMRT which will have bandwidths about ten times larger than at present.

Corona Degradation of the Polymer Insulator Samples under Different Fog Conditions

Corona discharges resulting from the metal parts of insulators and the line hardware affect the long term performance of the polymeric insulators used for outdoor application and can lead to its eventual failure. The authors previous work, involved in developing a new methodology to evaluate the performance of polymeric shed materials subjected to corona stresses in the presence of natural fog condition, results revealed more surface hydroxylation thereby resulting in more loss of hydropobhicity. With the increase in industrialization, there is an increase in acidic component of the rain as well as the fog (moisture). The present work, reports the effect of acid fog on the corona performance of the polymeric insulators for both AC and DC excitation, interesting results are obtained. A comparison of the experimental investigations revealed that the acidic fog has more effect than that of the normal fog. This fact has been confirmed by physico-chemical analysis like the scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), x-ray photoelectron spectroscopy (XPS) and contact angle measurement. The effect of DC corona is found to be lesser in comparison with the AC; however the hydroxylation induced by the DC corona under the presence of fog is similar with that of AC excitation.

A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm

Among the multiple advantages and applications of remote sensing, one of the most important uses is to solve the problem of crop classification, i.e., differentiating between various crop types. Satellite images are a reliable source for investigating the temporal changes in crop cultivated areas. In this letter, we propose a novel bat algorithm (BA)-based clustering approach for solving crop type classification problems using a multispectral satellite image. The proposed partitional clustering algorithm is used to extract information in the form of optimal cluster centers from training samples. The extracted cluster centers are then validated on test samples. A real-time multispectral satellite image and one benchmark data set from the University of California, Irvine (UCI) repository are used to demonstrate the robustness of the proposed algorithm. The performance of the BA is compared with two other nature-inspired metaheuristic techniques, namely, genetic algorithm and particle swarm optimization. The performance is also compared with the existing hybrid approach such as the BA with K-means. From the results obtained, it can be concluded that the BA can be successfully applied to solve crop type classification problems.

Integration of holographic sensors into microfluidics for the real-time pH sensing of L. casei metabolism

We describe developments in the integration of analyte specific holographic sensors into PDMS-based microfluidic devices for the purpose of continuous, low-impact monitoring of extra-cellular change in micro-bioreactors. Holographic sensors respond to analyte concentration via volume change, which makes their reduction in size and integration into spatially confined fluidics difficult. Through design and process modification many of these constraints have been addressed, and a microfluidics-based device capable of real-time monitoring of the pH change caused by Lactobacillus casei fermentation is presented as a general proof-of-concept for a wide array of possible devices.