Zero-Crossings Based Spectrum Sensing Under Noise Uncertainties

In this work, the hypothesis testing problem of spectrum sensing in a cognitive radio is formulated as a Goodness-of-fit test against the general class of noise distributions used in most communications-related applications. A simple, general, and powerful spectrum sensing technique based on the number of weighted zero-crossings in the observations is proposed. For the cases of uniform and exponential weights, an expression for computing the near-optimal detection threshold that meets a given false alarm probability constraint is obtained. The proposed detector is shown to be robust to two commonly encountered types of noise uncertainties, namely, the noise model uncertainty, where the PDF of the noise process is not completely known, and the noise parameter uncertainty, where the parameters associated with the noise PDF are either partially or completely unknown. Simulation results validate our analysis, and illustrate the performance benefits of the proposed technique relative to existing methods, especially in the low SNR regime and in the presence of noise uncertainties.

Microwave Spectrum of Hexafluoroisopropanol and Torsional Behavior of Molecules with a CF3-C-CF3 Group

This paper presents the first microwave spectroscopic investigation on hexafluoroisopropanol (HFIP). A pulsed nozzle Fourier transform microwave spectrometer has been used to determine the rotational constants for HFIP as A = 2105.12166(18) MHz, B = 1053.99503(12) MHz, and C = 932.33959(13) MHz. In addition, five isotopologues of HFIP have been observed experimentally to determine the accurate structure of HFIP. The observed spectrum could be assigned to the most stable conformer of HFIP, called antiperiplanar. Available spectroscopic information and ab initio calculations on five prototype molecules helped in exploring the torsional behavior of molecules having a CF3-C-CF3 group. Two-dimensional potential energy surfaces have been analyzed for all molecules, which explained the presence/absence of doubling in the rotational transitions. With the help of natural bond orbital (NBO) analysis, reasons for the conformational preference of HFIP have been explained.

Effect of Coldfog on the Corona Induced Degradation of Silicone Rubber Samples

Corona is an unavoidable phenomena in high voltage power transmission system, in spite of suitably designed insulator accessories and transmission line hardware. It is a proven fact that the continuous occurrence of corona can subject the polymeric insulator to a severe degradation. Further, moisture in the air has a positive influence on the corona activity. This paper presents the methodology to evaluate the corona performance of the silicone rubber housing material with simultaneous application of cold fog. Analysis conducted after corona treatment by the Fourier Transform Infrared Spectroscopy (FTIR) present an interesting results showing a higher hydroxylation of sample surface under the moisture application than in the normal condition for both AC and DC excitation. FTIR spectrum also indicates the presence of nitric acid on the treated surface with coldfog application. Results obtained from SEM analysis are also presented.

Recent advances in purely organic phosphorescent materials

Luminescent organic materials have attracted significant attention in recent times owing to their opportunities in various functional applications. Interestingly, unlike fluorescence, opportunities hidden within the phosphorescence properties of organic compounds have received considerably less attention even until last few years. It is only in the second decade of the 21st century, within a time span of less than last 5 years, that the concepts and prospects of organic compounds as phosphorescent materials have evolved rapidly. The previously perceived limitations of organic compounds as phosphorescent materials have been overcome and several molecules have been designed using old and new concepts, such as heavy atom effects, matrix assisted isolation, hydrogen bonding and halogen bonding, thereby gaining access to a significant number of materials with efficient phosphorescent features. In addition, significant improvements have been made in the development of RTP (room temperature phosphorescent) materials, which can be used under ambient conditions. In this review, we bring together the vastly different approaches developed by various researchers to understand and appreciate this recent revolution in organic luminescent materials.

Continuous synthesis of high quality CdSe quantum dots in supercritical fluids

We demonstrate in here a powerful scalable technology to synthesize continuously high quality CdSe quantum dots (QDs) in supercritical hexane. Using a low cost, highly thermally stable Cd-precursor, cadmium deoxycholate, the continuous synthesis is performed in 400 mu m ID stainless steel capillaries resulting in CdSe QDs having sharp full-width-at-half-maxima (23 nm) and high photoluminescence quantum yields (45-55%). Transmission electron microscopy images show narrow particles sizes distribution (sigma <= 5%) with well-defined crystal lattices. Using two different synthesis temperatures (250 degrees C and 310 degrees C), it was possible to obtain zinc blende and wurtzite crystal structures of CdSe QDs, respectively. This synthetic approach allows achieving substantial production rates up to 200 mg of QDs per hour depending on the targeted size, and could be easily scaled to gram per hour.

Seismic hazard maps and spectrum for Patna considering region-specific seismotectonic parameters

The objective of this paper was to develop the seismic hazard maps of Patna district considering the region-specific maximum magnitude and ground motion prediction equation (GMPEs) by worst-case deterministic and classical probabilistic approaches. Patna, located near Himalayan active seismic region has been subjected to destructive earthquakes such as 1803 and 1934 Bihar-Nepal earthquakes. Based on the past seismicity and earthquake damage distribution, linear sources and seismic events have been considered at radius of about 500 km around Patna district center. Maximum magnitude (M (max)) has been estimated based on the conventional approaches such as maximum observed magnitude (M (max) (obs) ) and/or increment of 0.5, Kijko method and regional rupture characteristics. Maximum of these three is taken as maximum probable magnitude for each source. Twenty-seven ground motion prediction equations (GMPEs) are found applicable for Patna region. Of these, suitable region-specific GMPEs are selected by performing the `efficacy test,' which makes use of log-likelihood. Maximum magnitude and selected GMPEs are used to estimate PGA and spectral acceleration at 0.2 and 1 s and mapped for worst-case deterministic approach and 2 and 10 % period of exceedance in 50 years. Furthermore, seismic hazard results are used to develop the deaggregation plot to quantify the contribution of seismic sources in terms of magnitude and distance. In this study, normalized site-specific design spectrum has been developed by dividing the hazard map into four zones based on the peak ground acceleration values. This site-specific response spectrum has been compared with recent Sikkim 2011 earthquake and Indian seismic code IS1893.

ANRC Hybrid Test Bed Implementation and an End-to-End Performance Characterization of Dynamic Spectrum Access

An abundance of spectrum access and sensing algorithms are available in the dynamic spectrum access (DSA) and cognitive radio (CR) literature. Often, however, the functionality and performance of such algorithms are validated against theoretical calculations using only simulations. Both the theoretical calculations and simulations come with their attendant sets of assumptions. For instance, designers of dynamic spectrum access algorithms often take spectrum sensing and rendezvous mechanisms between transmitter-receiver pairs for granted. Test bed designers, on the other hand, either customize so much of their design that it becomes difficult to replicate using commercial off the shelf (COTS) components or restrict themselves to simulation, emulation /hardware-in-Ioop (HIL), or pure hardware but not all three. Implementation studies on test beds sophisticated enough to combine the three aforementioned aspects, but at the same time can also be put together using COTS hardware and software packages are rare. In this paper we describe i) the implementation of a hybrid test bed using a previously proposed hardware agnostic system architecture ii) the implementation of DSA on this test bed, and iii) the realistic hardware and software-constrained performance of DSA. Snapshot energy detector (ED) and Cumulative Summation (CUSUM), a sequential change detection algorithm, are available for spectrum sensing and a two-way handshake mechanism in a dedicated control channel facilitates transmitter-receiver rendezvous.

Risk-Sensitive Ergodic Control of Continuous Time Markov Processes With Denumerable State Space

In this article, we study risk-sensitive control problem with controlled continuous time Markov chain state dynamics. Using multiplicative dynamic programming principle along with the atomic structure of the state dynamics, we prove the existence and a characterization of optimal risk-sensitive control under geometric ergodicity of the state dynamics along with a smallness condition on the running cost.

A Perspective to Adopt Continuous Dynamic Cognition for Malicious Node Detection in Heterogeneous Networks

The current day networks use Proactive networks for adaption to the dynamic scenarios. The use of cognition technique based on the Observe, Orient, Decide and Act loop (OODA) is proposed to construct proactive networks. The network performance degradation in knowledge acquisition and malicious node presence is a problem that exists. The use of continuous time dynamic neural network is considered to achieve cognition. The variance in service rates of user nodes is used to detect malicious activity in heterogeneous networks. The improved malicious node detection rates are proved through the experimental results presented in this paper. (C) 2015 The Authors. Published by Elsevier B.V.

PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application's throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based lookahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from Amazon AWS IaaS public cloud. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

General framework for acoustic emission during plastic deformation

Despite the long history, so far there is no general theoretical framework for calculating the acoustic emission spectrum accompanying any plastic deformation. We set up a discrete wave equation with plastic strain rate as a source term and include the Rayleigh-dissipation function to represent dissipation accompanying acoustic emission. We devise a method of bridging the widely separated time scales of plastic deformation and elastic degrees of freedom. While this equation is applicable to any type of plastic deformation, it should be supplemented by evolution equations for the dislocation microstructure for calculating the plastic strain rate. The efficacy of the framework is illustrated by considering three distinct cases of plastic deformation. The first one is the acoustic emission during a typical continuous yield exhibiting a smooth stress-strain curve. We first construct an appropriate set of evolution equations for two types of dislocation densities and then show that the shape of the model stress-strain curve and accompanying acoustic emission spectrum match very well with experimental results. The second and the third are the more complex cases of the Portevin-Le Chatelier bands and the Luders band. These two cases are dealt with in the context of the Ananthakrishna model since the model predicts the three types of the Portevin-Le Chatelier bands and also Luders-like bands. Our results show that for the type-C bands where the serration amplitude is large, the acoustic emission spectrum consists of well-separated bursts of acoustic emission. At higher strain rates of hopping type-B bands, the burst-type acoustic emission spectrum tends to overlap, forming a nearly continuous background with some sharp acoustic emission bursts. The latter can be identified with the nucleation of new bands. The acoustic emission spectrum associated with the continuously propagating type-A band is continuous. These predictions are consistent with experimental results. More importantly, our study shows that the low-amplitude continuous acoustic emission spectrum seen in both the type-B and type-A band regimes is directly correlated to small-amplitude serrations induced by propagating bands. The acoustic emission spectrum of the Luders-like band matches with recent experiments as well. In all of these cases, acoustic emission signals are burstlike, reflecting the intermittent character of dislocation-mediated plastic flow.

A Mitigation Technique for Harmonic Downconversion in Wideband Spectrum Sensors

The down conversion of radio frequency components around the harmonics of the local oscillator (LO), and its impact on the accuracy of white space detection using integrated spectrum sensors, is studied. We propose an algorithm to mitigate the impact of harmonic downconversion by utilizing multiple parallel downconverters in the system architecture. The proposed algorithm is validated on a test-board using commercially available integrated circuits and a test-chip implemented in a 130-nm CMOS technology. The measured data show that the impact of the harmonic downconversion is closely related to the LO characteristics, and that much of it can be mitigated by the proposed technique.

Near-Optimal Detection Thresholds for Bayesian Spectrum Sensing Under Fading

This paper considers the problem of energy-based, Bayesian spectrum sensing in cognitive radios under various fading environments. Under the well-known central limit theorem based model for energy detection, we derive analytically tractable expressions for near-optimal detection thresholds that minimize the probability of error under lognormal, Nakagami-m, and Weibull fading. For the Suzuki fading case, a generalized gamma approximation is provided, which saves on the computation of an integral. In each case, the accuracy of the theoretical expressions as compared to the optimal thresholds are illustrated through simulations.

Multi-dimensional Goodness-of-Fit Tests for Spectrum Sensing Based on Stochastic Distances

In this paper, we study two multi-dimensional Goodness-of-Fit tests for spectrum sensing in cognitive radios. The multi-dimensional scenario refers to multiple CR nodes, each with multiple antennas, that record multiple observations from multiple primary users for spectrum sensing. These tests, viz., the Interpoint Distance (ID) based test and the h, f distance based tests are constructed based on the properties of stochastic distances. The ID test is studied in detail for a single CR node case, and a possible extension to handle multiple nodes is discussed. On the other hand, the h, f test is applicable in a multi-node setup. A robustness feature of the KL distance based test is discussed, which has connections with Middleton's class A model. Through Monte-Carlo simulations, the proposed tests are shown to outperform the existing techniques such as the eigenvalue ratio based test, John's test, and the sphericity test, in several scenarios.

Chemical Shifts to Metabolic Pathways: Identifying Metabolic Pathways Directly from a Single 2D NMR Spectrum

Identifying cellular processes in terms of metabolic pathways is one of the avowed goals of metabolomics studies. Currently, this is done after relevant metabolites are identified to allow their mapping onto specific pathways. This task is daunting due to the complex nature of cellular processes and the difficulty in establishing the identity of individual metabolites. We propose here a new method: ChemSMP (Chemical Shifts to Metabolic Pathways), which facilitates rapid analysis by identifying the active metabolic pathways directly from chemical shifts obtained from a single two-dimensional (2D) C-13-H-1] correlation NMR spectrum without the need for identification and assignment of individual metabolites. ChemSMP uses a novel indexing and scoring system comprised of a ``uniqueness score'' and a ``coverage score''. Our method is demonstrated on metabolic pathways data from the Small Molecule Pathway Database (SMPDB) and chemical shifts from the Human Metabolome Database (HMDB). Benchmarks show that ChemSMP has a positive prediction rate of >90% in the presence of deduttered data and can sustain the same at 60-70% even in the presence of noise, such as deletions of peaks and chemical shift deviations. The method tested on NMR data acquired for a mixture of 20 amino acids shows a success rate of 93% in correct recovery of pathways. When used on data obtained from the cell lysate of an unexplored oncogenic cell line, it revealed active metabolic pathways responsible for regulating energy homeostasis of cancer cells. Our unique tool is thus expected to significantly enhance analysis of NMIR-based metabolomics data by reducing existing impediments.