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.

Lead ion sensor with electrodes modified by imidazole-functionalized polyaniline

Glassy carbon electrodes (GCE) and carbon paste electrodes (CPE) were modified with imidazole functionalized polyaniline with the aim to develop a sensor for lead (II) in both acidic and basic aqueous solution. The electrodes were characterized by cyclic voltammetry and differential pulse adsorptive stripping voltammetry. The limit of detections obtained with glassy carbon electrode and carbon paste electrode are 20 ng mL(-1) and 2 ng mL(-1) of lead ion, respectively. An interference study was carried out with Cd(II), As(III), Hg(II) and Co(II) ions. Cd(II) ions interfere significantly (peak overlap) and As(III) has a depressing effect on the lead signal. The influence of pH was investigated indicating that bare and modified GCE and CPE show optimum response at pH 4.0 +/- 0.05.

Surface Modified CaTiO3 Loaded in Polyaniline by Sodium Dodecyl Benzene Sulphonic Acid for Humidity Sensor

Polyaniline-CaTiO3 nanocomposites with their various weight percentages were prepared by chemical oxidative in situ polymerization technique. The prepared composites were characterized by Fourier transform infrared spectroscopy, scanning electronic microscope, and X-ray diffraction. The temperature-dependent dc conductivity of polyaniline-CaTiO3 nanocomposite was studied within the range of 40-200 degrees C and found that 50 wt% shows high conductivity compared to other composites. Humidity sensor properties of polyaniline-CaTiO3 nanocomposite show better sensing properties and exhibit good linearity in sensing response curve, which discuss the implications of distortions and nonstoichiometry on their physical properties. Among all composites, 50 wt% of polyaniline-CaTiO3 nanocomposites show high sensitivity up to similar to 90% and their response-recovery times are 500 and 453 s, respectively.

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.

Zinc Oxide Modified Au Electrode as Sensor for an Efficient Detection of Hydrazine

ZnO nanoparticles (ZnO NPs) prepared by microwave heating technique are used to modify a gold electrode (ZnO/Au) for the hydrazine detection study. The synthesized product is well characterized by various techniques. Detailed electrochemical investigation of the oxidation of hydrazine on the ZnO/Au electrode in 0.02 M phosphate buffer solution (PBS) of pH 7.4 was carried out. A very low detection limit of 66 nM (S/N=4) and a wide linearity in current for a concentration range from 66.0X10-3 to 415 mu M was achieved by amperometry. The electrode was found to be stable for over a month when preserved in PBS.

Bond Graph Modeling for Energy-Harvesting Wireless Sensor Networks

Researchers can use bond graph modeling, a tool that takes into account the energy conservation principle, to accurately assess the dynamic behavior of wireless sensor networks on a continuous basis.

An approach to multi-temporal MODIS image analysis using image classification and segmentation

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation for extracting water-covered regions. Analysis of MODIS satellite images is applied in three stages: before flood, during flood and after flood. Water regions are extracted from the MODIS images using image classification (based on spectral information) and image segmentation (based on spatial information). Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification (SVM and ANN) and region-based image segmentation is an accurate and reliable approach for the extraction of water-covered regions. (c) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

An Exfoliated Graphite-Based Bisphenol A Electrochemical Sensor

The use of an exfoliated graphite (EG) electrode in the square wave voltammetric detection of bisphenol A (a model phenolic pollutant) in water, whereby the phenolic electrode fouling challenge is mitigated, is described. The oxidation peak of BPA was observed at about 0.45 V in phosphate buffer solution at pH 10. The current response exhibited a linear relationship with the concentration over a range from 1.56 mu M-50 mu M. The detection limit was calculated to be 0.76 mu M. The EG electrode surface was renewed after each measurement with excellent reproducibility. A real sample application was also investigated.

A CMOS Gas Sensor Array Platform With Fourier Transform Based Impedance Spectroscopy

A CMOS gas sensor array platform with digital read-out containing 27 sensor pixels and a reference pixel is presented. A signal conditioning circuit at each pixel includes digitally programmable gain stages for sensor signal amplification followed by a second order continuous time delta sigma modulator for digitization. Each sensor pixel can be functionalized with a distinct sensing material that facilitates transduction based on impedance change. Impedance spectrum (up to 10 KHz) of the sensor is obtained off-chip by computing the fast Fourier transform of sensor and reference pixel outputs. The reference pixel also compensates for the phase shift introduced by the signal processing circuits. The chip also contains a temperature sensor with digital readout for ambient temperature measurement. A sensor pixel is functionalized with polycarbazole conducting polymer for sensing volatile organic gases and measurement results are presented. The chip is fabricated in a 0.35 CMOS technology and requires a single step post processing for functionalization. It consumes 57 mW from a 3.3 V supply.

A weighted average-based external clock synchronisation protocol for wireless sensor networks

Wireless Sensor Networks (WSNs) have many application scenarios where external clock synchronisation may be required because a WSN may consist of components which are not connected to each other. In this paper, we first propose a novel weighted average-based internal clock synchronisation (WICS) protocol, which synchronises all the clocks of a WSN with the clock of a reference node periodically. Based on this protocol, we then propose our weighted average-based external clock synchronisation (WECS) protocol. We have analysed the proposed protocols for maximum synchronisation error and shown that it is always upper bounded. Extensive simulation studies of the proposed protocols have been carried out using Castalia simulator. Simulation results validate our above theoretical claim and also show that the proposed protocols perform better in comparison to other protocols in terms of synchronisation accuracy. A prototype implementation of the WICS protocol using a few TelosB motes also validates the above conclusions.

A phenanthrene based highly selective fluorogenic and visual sensor for Cu2+ ion with nanomolar detection limit and its application in live cell imaging

A new phenanthrene based chemosensor has been synthesized and investigated to act as highly selective fluorescence and visual sensor for Cu2+ ion with very low detection limit of 1.58 nM: this has also been used to image Cu2+ in human cervical HeLa cancer cells. (C) 2012 Elsevier B.V. All rights reserved.

Tuning the Sensitivity of a Metal-Based Piezoresistive Sensor Using Electromigration

We report a simple method to enhance the piezoresistive sensitivity of a gold film by more than 30 times and demonstrate it using a microcantilever resonator. Our method depends on controlled electromigration that we use to tune the resistance and sensitivity of the piezoresistive sensor. We attribute the enhancement in strain sensitivity to the creation of an inhomogeneous conduction medium at a predefined location by directed and controlled electromigration. We understand this phenomenon with tunneling-percolation model, which was originally hypothesized to explain nonuniversal percolation behavior of composite materials. 2012-0174]

Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices

In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.

Design and analysis of a peer-to-peer based distributed clock synchronisation protocol for wireless sensor networks

Clock synchronisation is an important requirement for various applications in wireless sensor networks (WSNs). Most of the existing clock synchronisation protocols for WSNs use some hierarchical structure that introduces an extra overhead due to the dynamic nature of WSNs. Besides, it is difficult to integrate these clock synchronisation protocols with sleep scheduling scheme, which is a major technique to conserve energy. In this paper, we propose a fully distributed peer-to-peer based clock synchronisation protocol, named Distributed Clock Synchronisation Protocol (DCSP), using a novel technique of pullback for complete sensor networks. The pullback technique ensures that synchronisation phases of any pair of clocks always overlap. We have derived an exact expression for a bound on maximum synchronisation error in the DCSP protocol, and simulation study verifies that it is indeed less than the computed upper bound. Experimental study using a few TelosB motes also verifies that the pullback occurs as predicted.