981 resultados para SELECTIVE DETECTION


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We study the problem of decentralized sequential change detection with conditionally independent observations. The sensors form a star topology with a central node called fusion center as the hub. The sensors transmit a simple function of their observations in an analog fashion over a wireless Gaussian multiple access channel and operate under either a power constraint or an energy constraint. Simulations demonstrate that the proposed techniques have lower detection delays when compared with existing schemes. Moreover we demonstrate that the energy-constrained formulation enables better use of the total available energy than a power-constrained formulation.

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With technology scaling, vulnerability to soft errors in random logic is increasing. There is a need for on-line error detection and protection for logic gates even at sea level. The error checker is the key element for an on-line detection mechanism. We compare three different checkers for error detection from the point of view of area, power and false error detection rates. We find that the double sampling checker (used in Razor), is the simplest and most area and power efficient, but suffers from very high false detection rates of 1.15 times the actual error rates. We also find that the alternate approaches of triple sampling and integrate and sample method (I&S) can be designed to have zero false detection rates, but at an increased area, power and implementation complexity. The triple sampling method has about 1.74 times the area and twice the power as compared to the Double Sampling method and also needs a complex clock generation scheme. The I&S method needs about 16% more power with 0.58 times the area as double sampling, but comes with more stringent implementation constraints as it requires detection of small voltage swings.

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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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An imaging technique is developed for the controlled generation of multiple excitation nano-spots for far-field microscopy. The system point spread function (PSF) is obtained by interfering two counter-propagating extended depth-of-focus PSF (DoF-PSF), resulting in highly localized multiple excitation spots along the optical axis. The technique permits (1) simultaneous excitation of multiple planes in the specimen; (2) control of the number of spots by confocal detection; and (3) overcoming the point-by-point based excitation. Fluorescence detection from the excitation spots can be efficiently achieved by Z-scanning the detector/pinhole assembly. The technique complements most of the bioimaging techniques and may find potential application in high resolution fluorescence microscopy and nanoscale imaging.

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DNA amplification using Polymerase Chain Reaction (PCR) in a small volume is used in Lab-on-a-chip systems involving DNA manipulation. For few microliters of volume of liquid, it becomes difficult to measure and monitor the thermal profile accurately and reproducibly, which is an essential requirement for successful amplification. Conventional temperature sensors are either not biocompatible or too large and hence positioned away from the liquid leading to calibration errors. In this work we present a fluorescence based detection technique that is completely biocompatible and measures directly the liquid temperature. PCR is demonstrated in a 3 ILL silicon-glass microfabricated device using non-contact induction heating whose temperature is controlled using fluorescence feedback from SYBR green I dye molecules intercalated within sensor DNA. The performance is compared with temperature feedback using a thermocouple sensor. Melting curve followed by gel electrophoresis is used to confirm product specificity after the PCR cycles. (c) 2007 Elsevier B.V. All rights reserved.

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A nanoscale-sized cage with a trigonal prismatic shape is prepared by coordination-driven self-assembly of a predesigned organometallic Pt-3 acceptor with an organic clip-type ligand. This trigonal prism is fluorescent and undergoes efficient fluorescence quenching by nitroaromatics, which are the chemical signatures of many explosives.

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Synchronising bushcricket males achieve synchrony by delaying their chirps in response to calling neighbours. In multi-male choruses, males that delay chirps in response to all their neighbours would remain silent most of the time and be unable to attract mates. This problem could be overcome if the afferent auditory system exhibited selective attention, and thus a male interacted only with a subset of neighbours. We investigated whether individuals of the bushcricket genus Mecopoda restricted their attention to louder chirps neurophysiologically, behaviourally and through spacing. We found that louder leading chirps were preferentially represented in the omega neuron but the representation of softer following chirps was not completely abolished. Following chirps that were 20 dB louder than leading chirps were better represented than leading chirps. During acoustic interactions, males synchronised with leading chirps even when the following chirps were 20 dB louder. Males did not restrict their attention to louder chirps during interactions but were affected by all chirps above a particular threshold. In the field, we found that males on average had only one or two neighbours whose calls were above this threshold. Selective attention is thus achieved in this bushcricket through spacing rather than neurophysiological filtering of softer signals.

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Boron neutron capture therapy (BNCT) is a radiotherapy that has mainly been used to treat malignant brain tumours, melanomas, and head and neck cancer. In BNCT, the patient receives an intravenous infusion of a 10B-carrier, which accumulates in the tumour area. The tumour is irradiated with epithermal or thermal neutrons, which result in a boron neutron capture reaction that generates heavy particles to damage tumour cells. In Finland, boronophenylalanine fructose (BPA-F) is used as the 10B-carrier. Currently, the drifting of boron from blood to tumour as well as the spatial and temporal accumulation of boron in the brain, are not precisely known. Proton magnetic resonance spectroscopy (1H MRS) could be used for selective BPA-F detection and quantification as aromatic protons of BPA resonate in the spectrum region, which is clear of brain metabolite signals. This study, which included both phantom and in vivo studies, examined the validity of 1H MRS as a tool for BPA detection. In the phantom study, BPA quantification was studied at 1.5 and 3.0 T with single voxel 1H MRS, and at 1.5 T with magnetic resonance imaging (MRSI). The detection limit of BPA was determined in phantom conditions at 1.5 T and 3.0 T using single voxel 1H MRS, and at 1.5 T using MRSI. In phantom conditions, BPA quantification accuracy of ± 5% and ± 15% were achieved with single voxel MRS using external or internal (internal water signal) concentration references, respectively. For MRSI, a quantification accuracy of <5% was obtained using an internal concentration reference (creatine). The detection limits of BPA in phantom conditions for the PRESS sequence were 0.7 (3.0 T) and 1.4 mM (1.5 T) mM with 20 × 20 × 20 mm3 single voxel MRS, and 1.0 mM with acquisition-weighted MRSI (nominal voxel volume 10(RL) × 10(AP) × 7.5(SI) mm3), respectively. In the in vivo study, an MRSI or single voxel MRS or both was performed for ten patients (patients 1-10) on the day of BNCT. Three patients had glioblastoma multiforme (GBM), and five patients had a recurrent or progressing GBM or anaplastic astrocytoma gradus III, and two patients had head and neck cancer. For nine patients (patients 1-9), MRS/MRSI was performed 70-140 min after the second irradiation field, and for one patient (patient 10), the MRSI study began 11 min before the end of the BPA-F infusion and ended 6 min after the end of the infusion. In comparison, single voxel MRS was performed before BNCT, for two patients (patients 3 and 9), and for one patient (patient 9), MRSI was performed one month after treatment. For one patient (patient 10), MRSI was performed four days before infusion. Signals from the tumour spectrum aromatic region were detected on the day of BNCT in three patients, indicating that in favourable cases, it is possible to detect BPA in vivo in the patient’s brain after BNCT treatment or at the end of BPA-F infusion. However, because the shape and position of the detected signals did not exactly match the BPA spectrum detected in the in vitro conditions, assignment of BPA is difficult. The opportunity to perform MRS immediately after the end of BPA-F infusion for more patients is necessary to evaluate the suitability of 1H MRS for BPA detection or quantification for treatment planning purposes. However, it could be possible to use MRSI as criteria in selecting patients for BNCT.