Detection of a periodic structure embedded in surface roughness, for various correlation functions

This paper deals with surface profilometry, where we try to detect a periodic structure, hidden in randomness using the matched filter method of analysing the intensity of light, scattered from the surface. From the direct problem of light scattering from a composite rough surface of the above type, we find that the detectability of the periodic structure can be hindered by the randomness, being dependent on the correlation function of the random part. In our earlier works, we had concentrated mainly on the Cauchy-type correlation function for the rough part. In the present work, we show that this technique can determine the periodic structure of different kinds of correlation functions of the roughness, including Cauchy, Gaussian etc. We study the detection by the matched filter method as the nature of the correlation function is varied.

Detection and determination of manganese concentration in water using a fiber Bragg grating coupled with nanotechnology

Through this paper we experimentally demonstrate the fabrication of a fiber Bragg grating (FBG) chemical sensor to detect and determine the manganese concentration in water and compare our results with sophisticated spectroscopic methods, such as atomic absorption spectrometry and the inductively coupled plasma method. Here we propose a simple method to develop a thin layer of gold nanoparticles above the etched grating region to enhance the sensitivity of the reflected spectrum of the FBG. By doing so, we achieve a sensitivity of 1.26 nm/parts per million in determining the trace level of Mn in water. Proper reagents are used to detect manganese in water. (C) 2011 Optical Society of America

Relay Precoder Optimization in MIMO-Relay Networks With Imperfect CSI

In this paper, we consider robust joint designs of relay precoder and destination receive filters in a nonregenerative multiple-input multiple-output (MIMO) relay network. The network consists of multiple source-destination node pairs assisted by a MIMO-relay node. The channel state information (CSI) available at the relay node is assumed to be imperfect. We consider robust designs for two models of CSI error. The first model is a stochastic error (SE) model, where the probability distribution of the CSI error is Gaussian. This model is applicable when the imperfect CSI is mainly due to errors in channel estimation. For this model, we propose robust minimum sum mean square error (SMSE), MSE-balancing, and relay transmit power minimizing precoder designs. The next model for the CSI error is a norm-bounded error (NBE) model, where the CSI error can be specified by an uncertainty set. This model is applicable when the CSI error is dominated by quantization errors. In this case, we adopt a worst-case design approach. For this model, we propose a robust precoder design that minimizes total relay transmit power under constraints on MSEs at the destination nodes. We show that the proposed robust design problems can be reformulated as convex optimization problems that can be solved efficiently using interior-point methods. We demonstrate the robust performance of the proposed design through simulations.

Robust Observer Design with Application to Fault Detection

A new scheme for robust estimation of the partial state of linear time-invariant multivariable systems is presented, and it is shown how this may be used for the detection of sensor faults in such systems. We consider an observer to be robust if it generates a faithful estimate of the plant state in the face of modelling uncertainty or plant perturbations. Using the Stable Factorization approach we formulate the problem of optimal robust observer design by minimizing an appropriate norm on the estimation error. A logical candidate is the 2-norm, corresponding to an H�¿ optimization problem, for which solutions are readily available. In the special case of a stable plant, the optimal fault diagnosis scheme reduces to an internal model control architecture.

Low-Complexity Detection in Large-Dimension MIMO-ISI Channels Using Graphical Models

In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models. A key contribution in the paper is the demonstration that near-optimal performance in MIMO-ISI channels with large dimensions can be achieved at low complexities through simple yet effective simplifications/approximations, although the graphical models that represent MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1) use of Markov random field (MRF)-based graphical model with pairwise interaction, in conjunction with message damping, and 2) use of factor graph (FG)-based graphical model with Gaussian approximation of interference (GAI). The per-symbol complexities are O(K(2)n(t)(2)) and O(Kn(t)) for the MRF and the FG with GAI approaches, respectively, where K and n(t) denote the number of channel uses per frame, and number of transmit antennas, respectively. These low-complexities are quite attractive for large dimensions, i.e., for large Kn(t). From a performance perspective, these algorithms are even more interesting in large-dimensions since they achieve increasingly closer to optimum detection performance for increasing Kn(t). Also, we show that these message passing algorithms can be used in an iterative manner with local neighborhood search algorithms to improve the reliability/performance of M-QAM symbol detection.

Electrochemical detection and removal of lead in water using poly(propylene imine) modified re-compressed exfoliated graphite electrodes

Modification of exfoliated graphite (EG) electrode with generation 2 poly(propylene imine) dendrimer by electrodeposition resulted in an electrochemical sensor which was used to detect lead ions in water to a limit of 1 ppb and a linear response between 2.5 and 40 ppb using square wave anodic stripping voltammetry (SW-ASV). Pb(II) was also removed from spiked water sample using a 40-mm diameter unmodified EG electrode with an applied potential of -1,000 mV for 180 min. A removal efficiency of 99% was calculated from a 150 mL sample. The results obtained in both cases using SW-ASV, correlated with atomic absorption spectroscopy.

Wireless sensor networks forhuman intruder detection

In this paper we report on the outcomes of a research and demonstration project on human intrusion detection in a large secure space using an ad hoc wireless sensor network. This project has been a unique experience in collaborative research, involving ten investigators (with expertise in areas such as sensors, circuits, computer systems,communication and networking, signal processing and security) to execute a large funded project that spanned three to four years. In this paper we report on the specific engineering solution that was developed: the various architectural choices and the associated specific designs. In addition to developing a demonstrable system, the various problems that arose have given rise to a large amount of basic research in areas such as geographical packet routing, distributed statistical detection, sensors and associated circuits, a low power adaptive micro-radio, and power optimising embedded systems software. We provide an overview of the research results obtained.

In-situ formation of graphene-lead oxide composite and its use in trace arsenic detection

Reduced graphene oxide-lead dioxide composite is formed when EGO coated surface is electrochemically reduced along with lead ions in the solution. This composite has been shown to be an excellent material for low level detection of arsenic. Various functional groups present on EGO, in a wide pH range of 2-11, are responsible for the favorable interaction between metal ion and the modified electrode surface and subsequent trace level detection. X-ray photoelectron spectroscopy and Raman spectroscopic techniques confirm the formation of composite and its composition. Thin layer of lead dioxide along with reduced exfoliated graphene oxide has been shown to be responsible for the enhanced activity of the surface. The detection limit of arsenic is found to be 10 nM. This study opens up the possibility of using the composites for sensing applications and possibly simultaneous detection of arsenic and lead. (C) 2011 Elsevier B.V. All rights reserved.

Role of Spectral Studies in Detection of Antibacterial Phytoelements and Phytochemicals of Moringa oleifera

This paper reports, the Laser Induced Breakdown Spectroscopy (LIBS) studies and structure elucidation of compounds isolated from the fruit extract of Moringa oleifera and also deals with their possible effects on some bacterial strains viz. Staphylococcus aureus, Klebsiella pneumonia, Escherichia coli and Pseudomonas aeruginosa. The extract was found to be active against all four microorganisms used. Extent of inhibitory effect of extract was assessed at different concentrations of 25, 50, 75 mg/ml by measuring diameter of inhibition zone (DIZ). Our results clearly showed that the 75 mg/ml concentration of the extract had 14, 12 and 18 mm of the DIZ against Staphylococcus aureus, Klebsiella pneumonia and Pseudomonas aeruginosa and 14 mm with 50 mg/ml concentration against Escherichia coli. The results were compared with the standard antibiotic `ampicillin' of 1 mg/ml concentration. LIBS was recorded with high power pulsed laser beam from Nd: YAG Laser (Continuum Surelite III-10), focused on the surface of the material, which was in liquid form, to generate plasma on the surface of the sample. LIBS data clearly demonstrate the presence of trace elements, magnesium and iron, in high concentration in the extract. Whereas, from the phytochemical profile reveals the presence of two new compounds, S-ethyl-N-{4-[(alpha-L-rhamnosyloxy) benzyl]} thiocarbamate and 2-acetoxy {4-[(2',3',4'-tri-O-acetyl-alpha-L-rhamnosyloxy) benzyl]} acetonitrile as the major constituents. This study is the first report on synergetic effect of the phytoconstituents and certain set of elements present in their defined role in bacterial management against different bacterial strains.

Efficient Runtime Detection and Toleration of Asymmetric Races

We introduce ToleRace, a runtime system that allows programs to detect and even tolerate asymmetric data races. Asymmetric races are race conditions where one thread correctly acquires and releases a lock for a shared variable while another thread improperly accesses the same variable. ToleRace provides approximate isolation in the critical sections of lock-based parallel programs by creating a local copy of each shared variable when entering a critical section, operating on the local copies, and propagating the appropriate copies upon leaving the critical section. We start by characterizing all possible interleavings that can cause races and precisely describe the effect of ToleRace in each case. Then, we study the theoretical aspects of an oracle that knows exactly what type of interleaving has occurred. Finally, we present software implementations of ToleRace and evaluate them on multithreaded applications from the SPLASH2 and PARSEC suites.

Simultaneous multilayer scanning and detection for multiphoton fluorescence microscopy

Fast three-dimensional (3D) imaging requires parallel optical slicing of a specimen with an efficient detection scheme. The generation of multiple localized dot-like excitation structures solves the problem of simultaneous slicing multiple specimen layers, but an efficient detection scheme is necessary. Confocal theta detection (detection at 90 degrees to the optical axis) provides a suitable detection platform that is capable of cross-talk-free fluorescence detection from each nanodot (axial dimension approximate to 150 nm). Additionally, this technique has the unique feature of imaging a specimen at a large working distance with super-resolution capabilities. Polarization studies show distinct field structures for fixed and fluid samples, indicating a non-negligible field-dipole interaction. The realization of the proposed imaging technique will advance and diversify multiphoton fluorescence microscopy for numerous applications in nanobioimaging and optical engineering.