Environments of extended radio sources in the Australia Telescope Low-Brightness Survey

We present a study of the environments of extended radio sources in the Australia Telescope Low-Brightness Survey (ATLBS). The radio sources were selected from the ATLBS Extended Source Sample, which is a well defined sample containing the most extended of radio sources in the ATLBS sky survey regions. The environments were analysed using 4-m Cerro-Tololo Inter-American Observatory Blanco telescope observations carried out for ATLBS fields in the Sloan Digital Sky Survey r(') band. We have estimated the properties of the environments using smoothed density maps derived from galaxy catalogues constructed using these optical imaging data. The angular distribution of galaxy density relative to the axes of the radio sources has been quantified by defining anisotropy parameters that are estimated using a new method presented here. Examining the anisotropy parameters for a subsample of extended double radio sources that includes all sources with pronounced asymmetry in lobe extents, we find good evidence for environmental anisotropy being the dominant cause for lobe asymmetry in that higher galaxy density occurs almost always on the side of the shorter lobe, and this validates the usefulness of the method proposed and adopted here. The environmental anisotropy parameters have been used to examine and compare the environments of Fanaroff-Riley Class I (FRI) and Fanaroff-Riley Class II (FRII) radio sources in two redshift regimes (z < 0.5 and z > 0.5). Wide-angle tail sources and head-tail sources lie in the most overdense environments. The head-tail source environments (for the HT sources in our sample) display dipolar anisotropy in that higher galaxy density appears to lie in the direction of the tails. Excluding the head-tail and wide-angle tail sources, subsamples of FRI and FRII sources from the ATLBS appear to lie in similar moderately overdense environments, with no evidence for redshift evolution in the regimes studied herein.

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Deep searches for decametre-wavelength pulsed emission from radio-quiet gamma-ray pulsars

We report the results of extensive follow-up observations of the gamma-ray pulsar J1732-3131, which has recently been detected at decametre wavelengths, and the results of deep searches for the counterparts of nine other radio-quiet gamma-ray pulsars at 34 MHz, using the Gauribidanur radio telescope. No periodic signal from J1732-3131 could be detected above a detection threshold of 8 sigma, even with an effective integration time of more than 40 h. However, the average profile obtained by combining data from several epochs, at a dispersion measure of 15.44 pc cm(-3), is found to be consistent with that from the earlier detection of this pulsar at a confidence level of 99.2 per cent. We present this consistency between the two profiles as evidence that J1732-3131 is a faint radio pulsar with an average flux density of 200-400 mJy at 34 MHz. Despite the extremely bright sky background at such low frequencies, the detection sensitivity of our deep searches is generally comparable to that of higher frequency searches for these pulsars, when scaled using reasonable assumptions about the underlying pulsar spectrum. We provide details of our deep searches, and put stringent upper limits on the decametre-wavelength flux densities of several radio-quiet gamma-ray pulsars.

Differential Multi-phase DLL for Reconfigurable Radio Frequency Synthesizer

A multi phase, delay-locked loop (DLL) based frequency synthesizer is designed for harmonic rejection mixing in reconfigurable radios. This frequency synthesizer uses a 1 GHz input reference frequency, and achieves <= 20ns settling time by utilizing a wide loop bandwidth. The circuit has been designed in 0.13-mu m CMOS technology. It is designed for a frequency range of 500 MHz to 3 GHz with stuck/harmonic lock removal assist. Index Terms-stuck lock, harmonic lock, delay-locked loops, multi phase, phase detector, frequency synthesis

Effect of radio frequency power and thickness on the electrochemical properties of Li2-x MnO3-y thin films

In the present work, Li2-x MnO3-y (LMO) thin films have been deposited by radio frequency (RF) reactive magnetron sputtering using acid-treated Li2MnO3 powder target. Systematic investigations have been carried out to study the effect of RF power on the physicochemical properties of LMO thin films deposited on platinized silicon substrates. X-ray diffraction, electron microscopy, surface chemical analysis and electrochemical studies were carried out for the LMO films after post deposition annealing treatment at 500 A degrees C for 1 h in air ambience. Galvanostatic charge discharge studies carried out using the LMO thin film electrodes, delivered a highest discharge capacity of 139 mu Ah mu m(-1) cm(-2) in the potential window 2.0-3.5 V vs. Li/Li+ at 100 W RF power and lowest discharge capacity of 80 mu Ah mu m(-1) cm(-2) at 75 W RF power. Thereafter, the physicochemical properties of LMO films deposited using optimized RF power 100 W on stainless steel substrates has been studied in the thickness range of 70 to 300 nm as a case study. From the galvanostatic charge discharge experiments, a stable discharge capacity of 68 mu Ah mu m(-1) cm(-2) was achieved in the potential window 2.0-4.2 V vs. Li/Li+ tested up to 30 cycles. As the thickness increased, the specific discharge capacity started reducing with higher magnitude of capacity fading.

SARAS MEASUREMENT OF THE RADIO BACKGROUND AT LONG WAVELENGTHS

SARAS is a correlation spectrometer connected to a frequency independent antenna that is purpose-designed for precision measurements of the radio background at long wavelengths. The design, calibration, and observing strategies admit solutions for the internal additive contributions to the radiometer response, and hence a separation of these contaminants from the antenna temperature. We present here a wideband measurement of the radio sky spectrum by SARAS that provides an accurate measurement of the absolute brightness and spectral index between 110 and 175MHz. Accuracy in the measurement of absolute sky brightness is limited by systematic errors of magnitude 1.2%; errors in calibration and in the joint estimation of sky and system model parameters are relatively smaller. We use this wide-angle measurement of the sky brightness using the precision wide-band dipole antenna to provide an improved absolute calibration for the 150 MHz all-sky map of Landecker and Wielebinski: subtracting an offset of 21.4 K and scaling by a factor of 1.05 will reduce the overall offset error to 8 K (from 50 K) and scale error to 0.8% (from 5%). The SARAS measurement of the temperature spectral index is in the range -2.3 to -2.45 in the 110-175MHz band and indicates that the region toward the Galactic bulge has a relatively flatter index.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

Action Recognition from Motion Capture Data using Meta-cognitive RBF Network Classifier

Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

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.