Gas Sensing Characteristics of Superconducting Cuprates

Gas sensing characteristics of YBa2Cu3O7−δ, La2−x SrxCuO4, and Bi2Y1−xCaxSr2Cu2O8 have been examined. La2−x SrxCuO4 (x = 0.075), and Bi2YSr2Cu2O8 are found to show good sensitivity (≈10 ppm) to ethyl alcohol and such vapours.

Characterization of a large-area PVDF thin film for electro-mechanical and ultrasonic sensing applications

Large-area PVDF thin films have been prepared and characterized for quasi-static and high frequency dynamic strain sensing applications. These films are prepared using hot press method and the piezoelectric phase (beta-phase) has been achieved by thermo-mechanical treatment and poling under DC field. The fabricated films have been characterized for quasi-static strain sensing and the linear strain-voltage relationship obtained is promising. In order to evaluate the ultrasonic sensing properties, a PZT wafer has been used to launch Lamb waves in a metal beam on which the PVDF film sensor is bonded at a distance. The voltage signals obtained from the PVDF films have been compared with another PZT wafer sensor placed on the opposite surface of the beam as a reference signal. Due to higher stiffness and higher thickness of the PZT wafer sensors, certain resonance patterns significantly degrade the sensor sensitivity curves. Whereas, the present results show that the large-area PVDF sensors can be superior with the signal amplitude comparable to that of PZT sensors and with no resonance-induced effect, which is due to low mechanical impedance, smaller thickness and larger area of the PVDF film. Moreover, the developed PVDF sensors are able to capture both A(0) and S-0 modes of Lamb wave, whereas the PZT sensors captures only A(0) mode in the same scale of voltage output. This shows promises in using large-area PVDF films with various surface patterns on structures for distributed sensing and structural health monitoring under quasi-static, vibration and ultrasonic situations. (C) 2010 Elsevier B.V. All rights reserved.

Semi-Supervised Classification Using Sparse Gaussian Process Regression

Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

An optimal parallel algorithm for sparse matrix bandwidth reduction on a linear array

A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is proposed. It involves column-row permutations and is well-suited to map onto the linear array topology of the SIMD architectures. The efficiency of the algorithm is compared with the other existing algorithms. The interconnectivity and the memory requirement of the linear array are discussed and the complexity of its layout area is derived. The parallel version of the algorithm mapped onto the linear array is then introduced and is explained with the help of an example. The optimality of the parallel algorithm is proved by deriving the time complexities of the algorithm on a single processor and the linear array.

Monitoring Fatigue Crack Propagation in Compact Tension Specimens via Remote Sensing of Back Face Strain

Back face strain (BFS) measurement is now well-established as an indirect technique to monitor crack length in compact tension (CT) fracture specimens [1,2]. Previous work [2] developed empirical relations between fatigue crack propagation (FCP) parameters. BFS, and number of cycles for CT specimens subjected to constant amplitude fatigue loading. These predictions are experimentally validated in terms of the variations of mean values of BFS and load as a function of crack length. Another issue raised by this study concerns the validity of assigning fixed values for the Paris parameters C and n to describe FCP in realistic materials.

Adaptive Keeper Design for Dynamic Logic Circuits Using Rate Sensing Technique

The increasing variability in device leakage has made the design of keepers for wide OR structures a challenging task. The conventional feedback keepers (CONV) can no longer improve the performance of wide dynamic gates for the future technologies. In this paper, we propose an adaptive keeper technique called rate sensing keeper (RSK) that enables faster switching and tracks the variation across different process corners. It can switch upto 1.9x faster (for 20 legs) than CONV and can scale upto 32 legs as against 20 legs for CONV in a 130-nm 1.2-V process. The delay tracking is within 8% across the different process corners. We demonstrate the circuit operation of RSK using a 32 x 8 register file implemented in an industrial 130-nm 1.2-V CMOS process. The performance of individual dynamic logic gates are also evaluated on chip for various keeper techniques. We show that the RSK technique gives superior performance compared to the other alternatives such as Conditional Keeper (CKP) and current mirror-based keeper (LCR).

V-CE Sensing for IGBT Protection in NPC Three Level Converters-Causes For Spurious Trippings and Their Elimination

Neutral point clamped (NPC), three level converters with insulated gate bipolar transistor devices are very popular in medium voltage, high power applications. DC bus short circuit protection is usually done, using the sensed voltage across collector and emitter (i.e., V-CE sensing), of all the devices in a leg. This feature is accommodated with the conventional gate drive circuits used in the two level converters. The similar gate drive circuit, when adopted for NPC three level converter protection, leads to false V-CE fault signals for inner devices of the leg. The paper explains the detailed circuit behavior and reasons, which result in the occurrence of such false V-CE fault signals. This paper also illustrates that such a phenomenon shows dependence on the power factor of the supplied three-phase load. Finally, experimental results are presented to support the analysis. It is shown that the problem can be avoided by blocking out the V-CE sense fault signals of the inner devices of the leg.

High sensitive Static fiber Bragg grating strain sensing using lasers locked to relative frequency reference

A novel high sensitive fiber Bragg grating (FBG) strain sensing technique using lasers locked to relative frequency reference is proposed and analyzed theoretically. Static strain on FBG independent of temperature can be measured by locking frequency of diode laser to the mid reflection frequency of matched reference FBG, which responds to temperature similar to that of the sensor FBG, but is immune to strain applied to the same. Difference between light intensities reflected from the sensor and reference FBGs (proportional to the difference between respective pass band gains at the diode laser frequency) is not only proportional to the relative strain between the sensor and reference FBGs but also independent of servo residual frequency errors. Usage of relative frequency reference avoids all complexities involved in the usage of absolute frequency reference, hence, making the system simple and economical. Theoretical limit for dynamic and static strain sensitivities considering all major noise contributions are of the order of 25 (p epsilon) / root Hz and 1.2 n epsilon / root Hz respectively.

Understanding changes in the Himalayan cryosphere using remote sensing techniques

In the Himalayas, a large area is covered by glaciers and seasonal snow and changes in its extent can influence availability of water in the Himalayan Rivers. In this paper, changes in glacial extent, glacial mass balance and seasonal snow cover are discussed. Glacial retreat was estimated for 1868 glaciers in 11 basins distributed in the Indian Himalaya since 1962. The investigation has shown an overall reduction in glacier area from 6332 to 5329km2 from 1962 to 2001/2 - an overall deglaciation of 16%. Snow line at the end of ablation season on the Chhota Shigri glacier observed using field and satellite methods suggests a change in altitude from 4900 to 5200m from the late 1970s to present. Seasonal snow cover was monitored in the 28 river sub-basins using normalized difference snow index (NDSI) technique in Central and Western Himalaya. The investigation has shown that in the early part of winter, i.e. from October to December, a large amount of snow retreat was observed. For many basins located in lower altitude and in the south of the Pir Panjal range, snow ablation was observed throughout the winter season. In addition, average stream runoff of the Baspa basin for the month of December increased by 75%. This combination of glacial retreat, negative mass balance, early melting of seasonal snow cover and winter-time increase in stream runoff might suggest an influence of global warming on the Himalayan cryosphere.

Self-assembly of neutral and cationic Pd-II organometallic molecular rectangles: synthesis, characterization and nitroaromatic sensing

Design and synthesis of three novel 2 + 2] self-assembled molecular rectangles 1-3 via coordination driven self-assembly of predesigned Pd(II) ligands is reported. 1,8-Diethynylanthracene was assembled with trans-Pd(PEt3)(2)Cl-2 in the presence of CuCl catalyst to yield a neutral rectangle 1 via Pd-C bond formation. Complex 1 represents the first example of a neutral molecular rectangle obtained via C-Pd coordination driven self-assembly. A new Pd-2(II) organometallic building block with 180 degrees bite-angle 1,4-bistrans-(ethynyl)Pd(PEt3)(2)(NO3)] benzene (M-2) containing ethynyl functionality was synthesized in reasonable yield by employing Sonagashira coupling reaction. Self-assembly of M-2 with two organic clip-type donors (L-2-L-3) afforded 2 + 2] self-assembled molecular rectangles 2 and 3, respectively L-2 = 1,8-bis(4-pyridylethynyl) anthracene; L-3 = 1,3-bis(3-pyridyl) isophthalamide]. The macrocycles 1-3 were fully characterized by multinuclear NMR and ESI-MS spectroscopic techniques, and in case of 1 the structure was unambiguously determined by single crystal X-ray diffraction analysis. Incorporation of Pd-ethynyl bonds helped to make the assemblies p-electron rich and fluorescent in nature. Complexes 1-2 showed quenching of fluorescence intensity in solution in presence of nitroaromatics, which are the chemical signatures of many commercially available explosives.

Cooperative Spectrum Sensing Algorithms For OFDM Systems with Frequency Selective Channels

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate the effects of some common model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. The performance of the proposed algorithms are studied via simulations. We show that the performance of the energy detector is not affected by the frequency selective channel. We also provide a theoretical analysis for some of our algorithms.

Bayesian Decentralized Spectrum Sensing in Cognitive Radio Networks

This paper considers the problem of spectrum sensing, i.e., the detection of whether or not a primary user is transmitting data by a cognitive radio. The Bayesian framework is adopted, with the performance measure being the probability of detection error. A decentralized setup, where N sensors use M observations each to arrive at individual decisions that are combined at a fusion center to form the overall decision is considered. The unknown fading channel between the primary sensor and the cognitive radios makes the individual decision rule computationally complex, hence, a generalized likelihood ratio test (GLRT)-based approach is adopted. Analysis of the probabilities of false alarm and miss detection of the proposed method reveals that the error exponent with respect to M is zero. Also, the fusion of N individual decisions offers a diversity advantage, similar to diversity reception in communication systems, and a tight bound on the error exponent is presented. Through an analysis in the low power regime, the number of observations needed as a function of received power, to achieve a given probability of error is determined. Monte-Carlo simulations confirm the accuracy of the analysis.

Bayesian Learning for Joint Sparse OFDM Channel Estimation and Data Detection

The impulse response of a typical wireless multipath channel can be modeled as a tapped delay line filter whose non-zero components are sparse relative to the channel delay spread. In this paper, a novel method of estimating such sparse multipath fading channels for OFDM systems is explored. In particular, Sparse Bayesian Learning (SBL) techniques are applied to jointly estimate the sparse channel and its second order statistics, and a new Bayesian Cramer-Rao bound is derived for the SBL algorithm. Further, in the context of OFDM channel estimation, an enhancement to the SBL algorithm is proposed, which uses an Expectation Maximization (EM) framework to jointly estimate the sparse channel, unknown data symbols and the second order statistics of the channel. The EM-SBL algorithm is able to recover the support as well as the channel taps more efficiently, and/or using fewer pilot symbols, than the SBL algorithm. To further improve the performance of the EM-SBL, a threshold-based pruning of the estimated second order statistics that are input to the algorithm is proposed, and its mean square error and symbol error rate performance is illustrated through Monte-Carlo simulations. Thus, the algorithms proposed in this paper are capable of obtaining efficient sparse channel estimates even in the presence of a small number of pilots.

Self-assembled molecular squares containing metal-based donor: synthesis and application in the sensing of nitro-aromatics

Self-assemblies between a linear Pt-based donor and ferrocene- chelated metallic acceptors produced novel heterometallic squares 4 and 5, which show fluorescence quenching upon the addition of nitro-aromatics.

Spectral Sensing of Adaptive Frequency Hopping Signal for Cognitive Radio

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.