412 resultados para pressure sensor


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In this paper, we are concerned with energy efficient area monitoring using information coverage in wireless sensor networks, where collaboration among multiple sensors can enable accurate sensing of a point in a given area-to-monitor even if that point falls outside the physical coverage of all the sensors. We refer to any set of sensors that can collectively sense all points in the entire area-to-monitor as a full area information cover. We first propose a low-complexity heuristic algorithm to obtain full area information covers. Using these covers, we then obtain the optimum schedule for activating the sensing activity of various sensors that maximizes the sensing lifetime. The scheduling of sensor activity using the optimum schedules obtained using the proposed algorithm is shown to achieve significantly longer sensing lifetimes compared to those achieved using physical coverage. Relaxing the full area coverage requirement to a partial area coverage (e.g., 95% of area coverage as adequate instead of 100% area coverage) further enhances the lifetime.

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In this paper, we are concerned with algorithms for scheduling the sensing activity of sensor nodes that are deployed to sense/measure point-targets in wireless sensor networks using information coverage. Defining a set of sensors which collectively can sense a target accurately as an information cover, we propose an algorithm to obtain Disjoint Set of Information Covers (DSIC), which achieves longer network life compared to the set of covers obtained using an Exhaustive-Greedy-Equalized Heuristic (EGEH) algorithm proposed recently in the literature. We also present a detailed complexity comparison between the DSIC and EGEH algorithms.

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The variation of resistivity in an amorphous As30Te70-xSix system of glasses with high pressure has been studied for pressures up to 8 GPa. It is found that the electrical resistivity and the conduction activation energy decrease continuously with increase in pressure, and samples become metallic in the pressure range 1.0-2.0 GPa. Temperature variation studies carried out at a pressure of 0.92 GPa show that the activation energies lie in the range 0.16-0.18eV. Studies on the composition/average co-ordination number (r) dependence of normalized electrical resistivity at different pressures indicate that rigidity percolation is extended, the onset of the intermediate phase is around (r) = 2.44, and completion at (r) = 2.56, respectively, while the chemical threshold is at (r) = 2.67. These results compare favorably with those obtained from electrical switching and differential scanning calorimetric studies.

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The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

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We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

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Novel chromogenic thiourea based sensors 4,4'-bis-[3-(4-nitrophenyl) thiourea] diphenyl ether 1 and 4,4'-bis-[3-(4-nitrophenyl) thiourea] diphenyl methane 2 having nitrophenyl group as signaling unit have been synthesized and characterized by spectroscopic techniques and X-ray crystallography. The both sensors show visual detection, UV-vis and NMR spectral changes in presence of fluoride and cyanide anions in organic solvent as well as in aqueous medium. The absorption spectra indicated the formation of complex between host and guest is in 1:2 stoichiometric ratios. (C) 2010 Elsevier B.V. All rights reserved.

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Optimization in energy consumption of the existing synchronization mechanisms can lead to substantial gains in terms of network life in Wireless Sensor Networks (WSNs). In this paper, we analyze ERBS and TPSN, two existing synchronization algorithms for WSNs which use widely different approach, and compare their performance in large scale WSNs each of which consists of different type of platform and has varying node density. We, then, propose a novel algorithm, PROBESYNC, which takes advantage of differences in power required to transmit and receive a message on ERBS and TPSN and leverages the shortcomings of each of these algorithms. This leads to considerable improvement in energy conservation and enhanced life of large scale WSNs.

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We describe a noniterative method for recovering optical absorption coefficient distribution from the absorbed energy map reconstructed using simulated and noisy boundary pressure measurements. The source reconstruction problem is first solved for the absorbed energy map corresponding to single- and multiple-source illuminations from the side of the imaging plane. It is shown that the absorbed energy map and the absorption coefficient distribution, recovered from the single-source illumination with a large variation in photon flux distribution, have signal-to-noise ratios comparable to those of the reconstructed parameters from a more uniform photon density distribution corresponding to multiple-source illuminations. The absorbed energy map is input as absorption coefficient times photon flux in the time-independent diffusion equation (DE) governing photon transport to recover the photon flux in a single step. The recovered photon flux is used to compute the optical absorption coefficient distribution from the absorbed energy map. In the absence of experimental data, we obtain the boundary measurements through Monte Carlo simulations, and we attempt to address the possible limitations of the DE model in the overall reconstruction procedure.

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We describe here a novel sensor for cGMP based on the GAF domain of the cGMP-binding, cGMP-specific phosphodiesterase 5 (PDE5) using bioluminescence resonance energy transfer (BRET). The wild type GAFa domain, capable of binding cGMP with high affinity, and a mutant (GAFaF163A) unable to bind cGMP were cloned as fusions between GFP and Rluc for BRET2 assays. BRET2 ratios of the wild type GAFa fusion protein, but not GAFaF163A, increased in the presence of cGMP but not cAMP. Higher basal BRET2 ratios were observed in cells expressing the wild type GAFa domain than in cells expressing GAFaF163A. This was correlated with elevated basal intracellular levels of cGMP, indicating that the GAF domain could act as a sink for cGMP. The tandem GAF domains in full length PDE5 could also sequester cGMP when the catalytic activity of PDE5 was inhibited. Therefore, these results describe a cGMP sensor utilizing BRET2 technology and experimentally demonstrate the reservoir of cGMP that can be present in cells that express cGMP-binding GAF domain-containing proteins. PDE5 is the target for the anti-impotence drug sildenafil citrate; therefore, this GAF-BRET2 sensor could be used for the identification of novel compounds that inhibit cGMP binding to the GAF domain, thereby regulating PDE5 catalytic activity.

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We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

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We report the synthesis of Cd-substituted ZnO nanostructures (Zn1-xCdxO with x up to approximate to 0.09) by the high-pressure solution growth method. The synthesized nanostructures comprise nanocrystals that are both particles (similar to 10-15 nm) and rods which grow along the [002] direction as established by transmission electron microscope (TEM) and x-ray diffraction (XRD) analysis. Rietveld analysis of the XRD data shows a monotonic increase of the unit cell volume with the increase of Cd concentration. The optical absorption, as well as the photoluminescence (PL), shows a red shift on Cd substitution. The line width of the PL spectrum is related to the strain inhomogeneity and it peaks in the region where the CdO phase separates from the Zn1-xCdxO nanostructures. The time-resolved photoemission showed a long-lived (similar to 10 ns) component. We propose that the PL behaviour of the Zn1-xCdxO is dominated by strain in the sample with the red shift of the PL linked to the expansion of the unit cell volume on Cd substitution.

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The change in extension-twist Coupling due to delamination in antisymmetric laminates is experimentally measured. Experimental results are compared with the results from analytical expression existing in literature and finite element analysis. The application of the Macro-Fiber Composite (MFC) developed at the NASA Langley Research Center for sensing the delamination in the laminates is investigated. While many applications have been reported in the literature using the MFC as an actuator, here its use as a twist sensor has been studied. The real-life application envisaged is structural health monitoring of laminated composite flexbeams taking advantage of the symmetry in the structure. Apart from the defect detection under symmetric conditions, other methods of health monitoring for the same structure are reported for further validation. Results show that MFC works well as a sensor.

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A chenodeoxycholic acid based K+ ion sensor has been designed using a modular approach in which a fluorophore and a cation receptor are attached to the bile acid backbone. In the absence of K+ the fluorescence of the molecule is quenched because of through-space, photo-induced electron-transfer from the aza-crown unit. Fluorescence enhancement was observed upon titration with K+ (and other alkali metal ions too). In methanol, good selectivity towards the sensing of K+ has been observed.

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Wear of etched near-eutectic aluminium silicon alloy slid against a steel ball under ambient is explored. The sliding velocity is kept low (0.01 m/s) and the nominal contact pressure is varied in a 15-40 MPa range. Four stages of wear are identified; ultra mild wear, mild wear, severe wear and post severe oxidative wear. The first transition is controlled by the protrusions of silicon particles, projecting out of the aluminium alloy matrix. Once these protrusions disappear under pressure and sliding, oxidation and bulk energy dissipation mechanisms take over to institute transitions to other stages of wear. The phenomenological characteristics of wear stages are explored using a variety of techniques including nanoindentation, focused ion beam milling, electron microscopy, X-ray photoelectron spectroscopy (XPS), energy dispersive X-ray spectroscopy (EDS) and optical interferometry. (c) 2010 Elsevier B.V. All rights reserved.

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The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.