Design and performance analysis of a signal detector based on suprathreshold stochastic resonance

This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation sigma of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum sigma also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum sigma depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. (C) 2012 Elsevier B.V. All rights reserved.

Delay Optimal Event Detection on Ad Hoc Wireless Sensor Networks

We consider a small extent sensor network for event detection, in which nodes periodically take samples and then contend over a random access network to transmit their measurement packets to the fusion center. We consider two procedures at the fusion center for processing the measurements. The Bayesian setting, is assumed, that is, the fusion center has a prior distribution on the change time. In the first procedure, the decision algorithm at the fusion center is network-oblivious and makes a decision only when a complete vector of measurements taken at a sampling instant is available. In the second procedure, the decision algorithm at the fusion center is network-aware and processes measurements as they arrive, but in a time-causal order. In this case, the decision statistic depends on the network delays, whereas in the network-oblivious case, the decision statistic does not. This yields a Bayesian change-detection problem with a trade-off between the random network delay and the decision delay that is, a higher sampling rate reduces the decision delay but increases the random access delay. Under periodic sampling, in the network-oblivious case, the structure of the optimal stopping rule is the same as that without the network, and the optimal change detection delay decouples into the network delay and the optimal decision delay without the network. In the network-aware case, the optimal stopping problem is analyzed as a partially observable Markov decision process, in which the states of the queues and delays in the network need to be maintained. A sufficient decision statistic is the network state and the posterior probability of change having occurred, given the measurements received and the state of the network. The optimal regimes are studied using simulation.

Fluoranthene based fluorescent chemosensors for detection of explosive nitroaromatics

A novel fluoranthene based fluorescent chemosensor for the detection of picric acid (PA) at the parts per billion (ppb) level was evaluated. Static fluorescence quenching was the dominant process by intercalative pi-pi interaction between fluoranthene (S-1) and nitroaromatics.

Incremental Cycle Detection, Topological Ordering, and Strong Component Maintenance

We present two online algorithms for maintaining a topological order of a directed n-vertex acyclic graph as arcs are added, and detecting a cycle when one is created. Our first algorithm handles m arc additions in O(m(3/2)) time. For sparse graphs (m/n = O(1)), this bound improves the best previous bound by a logarithmic factor, and is tight to within a constant factor among algorithms satisfying a natural locality property. Our second algorithm handles an arbitrary sequence of arc additions in O(n(5/2)) time. For sufficiently dense graphs, this bound improves the best previous bound by a polynomial factor. Our bound may be far from tight: we show that the algorithm can take Omega(n(2)2 root(2lgn)) time by relating its performance to a generalization of the k-levels problem of combinatorial geometry. A completely different algorithm running in Theta (n(2) log n) time was given recently by Bender, Fineman, and Gilbert. We extend both of our algorithms to the maintenance of strong components, without affecting the asymptotic time bounds.

Vehicle Detection Tool - VDtect

The report talks about the implementation of Vehicle Detection tool using opensource software - WxPython. The main functionality of this tool includes collection of data, plotting of magnetometer data and the count of the vehicles detected. The report list about how installation process and various functionality of the tool.

Guided Wave based Damage Detection in a Composite T-joint using 3D Scanning Laser Doppler Vibrometer

Composite T-joints are commonly used in modern composite airframe, pressure vessels and piping structures, mainly to increase the bending strength of the joint and prevents buckling of plates and shells, and in multi-cell thin-walled structures. Here we report a detailed study on the propagation of guided ultrasonic wave modes in a composite T-joint and their interactions with delamination in the co-cured co-bonded flange. A well designed guiding path is employed wherein the waves undergo a two step mode conversion process, one is due to the web and joint filler on the back face of the flange and the other is due to the delamination edges close to underneath the accessible surface of the flange. A 3D Laser Doppler Vibrometer is used to obtain the three components of surface displacements/velocities of the accessible face of the flange of the T-joint. The waves are launched by a piezo ceramic wafer bonded on to the back surface of the flange. What is novel in the proposed method is that the location of any change in material/geometric properties can be traced by computing a frequency domain power flow along a scan line. The scan line can be chosen over a grid either during scan or during post-processing of the scan data off-line. The proposed technique eliminates the necessity of baseline data and disassembly of structure for structural interrogation.

Electrochemical Detection of Bisphenol A Using Graphene-Modified Glassy Carbon Electrode

Graphene's nano-dimensional nature and excellent electron transfer properties underlie its electrocatalytic behavior towards certain substances. In this light, we have used graphene in the electrochemical detection of bisphenol A. Graphene sheets were produced via soft chemistry route involving graphite oxidation and chemical reduction. X-ray diffraction, Fourier transform infra-red (FT-IR) and Raman spectroscopy were used for the characterization of the as-synthesized graphene. Graphene exhibited amorphous structure in comparison with pristine graphite from XRD spectra. FTIR showed that graphene exhibits OH and COOH groups due to incomplete reduction. Raman spectroscopy revealed that multi-layered graphene was produced due to low intensity of the 2D-peak. Glassy carbon electrode was modified with graphene by a simple drop and dry method. Cyclic voltammetry was used to study the electrochemical properties of the prepared graphene-modified glassy carbon electrode using potassium ferricyanide as a redox probe. The prepared graphene- modified glassy carbon electrode exhibited more facile electron kinetics and enhanced current of about 75% when compared to the unmodified glassy carbon electrode. The modified electrode was used for the detection of bisphenol A. Under the optimum conditions, the oxidation peak current of bisphenol A varied linearly with concentration over a wide range of 5 x 10(-8) mol L-1 to 1 x 10(-6) mol L-1 and the detection limit of this method was as low as 4.689 x 10(-8) M. This method was also employed to determine bisphenol A in a real sample

Differential Diffractive Reflectance Modulation Sensing

We fabricated a reflectance based sensor which relies on the diffraction pattern generated from a bio-microarray where an underlying thin film structure enhances the diffracted intensity from molecular layers. The zero order diffraction represents the background signal and the higher orders represent the phase difference between the array elements and the background. By taking the differential ratio of the first and zero order diffraction signals we get a quantitative measure of molecular binding while simultaneously rejecting common mode fluctuations. We improved the signal-to-noise ratio by an order of magnitude with this ratiometric approach compared to conventional single channel detection. In addition, we use a lithography based approach for fabricating microarrays which results in spot sizes as small as 5 micron diameter unlike the 100 micron spots from inkjet printing and is therefore capable of a high degree of multiplexing. We will describe the real-time measurement of adsorption of charged polymers and bulk refractometry using this technique. The lack of moving parts for point scanning of the microarray and the differential ratiometric measurements using diffracted orders from the same probe beam allows us to make real-time measurements in spite of noise arising from thermal or mechanical fluctuations in the fluid sample above the sensor surface. Further, the lack of moving parts leads to considerable simplification in the readout hardware permitting the use of this technique in compact point of care sensors.

Ultrasound Assisted Optical Tomography: Estimation of phase Shift experienced by photon on transit through US insonified region for detection of breast tumor

A Monte Carlo model of ultrasound modulation of multiply scattered coherent light in a highly scattering media has been carried out for estimating the phase shift experienced by a photon beam on its transit through US insonified region. The phase shift is related to the tissue stiffness, thereby opening an avenue for possible breast tumor detection. When the scattering centers in the tissue medium is exposed to a deterministic forcing with the help of a focused ultrasound (US) beam, due to the fact that US-induced oscillation is almost along particular direction, the direction defined by the transducer axis, the scattering events increase, thereby increasing the phase shift experienced by light that traverses through the medium. The phase shift is found to increase with increase in anisotropy g of the medium. However, as the size of the focused region which is the region of interest (ROI) increases, a large number of scattering events take place within the ROI, the ensemble average of the phase shift (Delta phi) becomes very close to zero. The phase of the individual photon is randomly distributed over 2 pi when the scattered photon path crosses a large number of ultrasound wavelengths in the focused region. This is true at high ultrasound frequency (1 MHz) when mean free path length of photon l(s) is comparable to wavelength of US beam. However, at much lower US frequencies (100 Hz), the wavelength of sound is orders of magnitude larger than l(s), and with a high value of g (g 0.9), there is a distinct measurable phase difference for the photon that traverses through the insonified region. Experiments are carried out for validation of simulation results.

Selective colorimetric detection of nanomolar Cr (VI) in aqueous solutions using unmodified silver nanoparticles

In this study we present a colorimetric detection method for Cr (VI) in aqueous solution based on as synthesized silver nanoparticles (Ag NPs) without surface functionalization. The method principle involves reduction of Cr (VI) to Cr (III) by excess reductant present in as synthesized Ag NP dispersion, and subsequent aggregation of Ag NPs by Cr (III) leading to red-shift of the surface plasmon resonance (SPR) peak. The UV-vis absorption spectra. Zeta potentials, dynamic light scattering measurements, and scanning electron microscopy (SEM) confirmed the aggregation of the Ag NPs. Under the optimized conditions, a good linear relationship (correlation coefficient r=0.981) was obtained between the ratio of the absorbance at 550 nm to that at 390 nm (A(550/390)) and the concentration of Cr (VI) over the range of 10(-3)-10(-9) M 50 mg/L to 50 ng/L]. The reported probe has a limit of detection down to 1 nM, which, to the best of our knowledge, is the lowest ever reported for the colorimetric detection of Cr (VI). Furthermore, a remarkable feature of this method is that it involves a simple technique exhibiting high selectivity to Cr (VI) over other tested heavy metal ions. (C) 2012 Elsevier BM. All rights reserved.

Cascaded walks in protein sequence space: use of artificial sequences in remote homology detection between natural proteins

Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.

Carbon dioxide detection by boron nitride nanotubes

The effect of gas molecule adsorption is investigated on the density of states of (9,0) zigzag boron nitride nanotube within a random tight-binding Hamiltonian model. The Green function approach and coherent potential approximation have been implemented. The results show that the adsorption of carbon dioxide gas molecules by boron atoms only leads to a donor type semiconductor while the adsorption by nitrogen atoms only leads to an acceptor. Since the gas molecules are adsorbed by both boron and nitrogen atoms, a reduction of the band gap is found. In all cases, increasing the gas concentration causes an increase in the height of the peaks in the band gap. This is due to an increasing charge carrier concentration induced by adsorbed gas molecules.

Green synthesis of biopolymer-silver nanoparticle nanocomposite: An optical sensor for ammonia detection

Biopolymer used for the production of nanoparticles (NPs) has attracted increasing attention. In the presence article we use aqueous solution of polysaccharide Cyamopsis tetragonaloba commonly known as guar gum (GG), from plants. GG acts as reductive preparation of silver nanoparticles which are found to be <10. nm in size. The uniformity of the NPs size was measured by the SEM and TEM, while a face centered cubic structure of crystalline silver nanoparticles was characterized using powder X-ray diffraction technique. Aqueous ammonia sensing study of polymer/silver nanoparticles nanocomposite (GG/AgNPs NC) was performed by optical method based on surface plasmon resonance (SPR). The performances of optical sensor were investigated which provide the excellent result. The response time of 2-3. s and the detection limit of ammonia solution, 1. ppm were found at room temperature. Thus, in future this room temperature optical ammonia sensor can be used for clinical and medical diagnosis for detecting low ammonia level in biological fluids, such as plasma, sweat, saliva, cerebrospinal liquid or biological samples in general for various biomedical applications in human. © 2012 Elsevier B.V.