292 resultados para sensor uncertainty


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Expectations about the magnitude of impending pain exert a substantial effect on subsequent perception. However, the neural mechanisms that underlie the predictive processes that modulate pain are poorly understood. In a combined behavioral and high-density electrophysiological study we measured anticipatory neural responses to heat stimuli to determine how predictions of pain intensity, and certainty about those predictions, modulate brain activity and subjective pain ratings. Prior to receiving randomized laser heat stimuli at different intensities (low, medium or high) subjects (n=15) viewed cues that either accurately informed them of forthcoming intensity (certain expectation) or not (uncertain expectation). Pain ratings were biased towards prior expectations of either high or low intensity. Anticipatory neural responses increased with expectations of painful vs. non-painful heat intensity, suggesting the presence of neural responses that represent predicted heat stimulus intensity. These anticipatory responses also correlated with the amplitude of the Laser-Evoked Potential (LEP) response to painful stimuli when the intensity was predictable. Source analysis (LORETA) revealed that uncertainty about expected heat intensity involves an anticipatory cortical network commonly associated with attention (left dorsolateral prefrontal, posterior cingulate and bilateral inferior parietal cortices). Relative certainty, however, involves cortical areas previously associated with semantic and prospective memory (left inferior frontal and inferior temporal cortex, and right anterior prefrontal cortex). This suggests that biasing of pain reports and LEPs by expectation involves temporally precise activity in specific cortical networks.

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This paper presents a novel platform for the formation of cost-effective PCB-integrated optical waveguide sensors. The sensor design relies on the use of multimode polymer waveguides that can be formed directly on standard PCBs and commercially-available chemical dyes, enabling the integration of all essential sensor components (electronic, photonic, chemical) on low-cost substrates. Moreover, it enables the detection of multiple analytes from a single device by employing waveguide arrays functionalised with different chemical dyes. The devices can be manufactured with conventional methods of the PCB industry, such as solder-reflow processes and pick-and-place assembly techniques. As a proof of principle, a PCB-integrated ammonia gas sensor is fabricated on a FR4 substrate. The sensor operation relies on the change of the optical transmission characteristics of chemically functionalised optical waveguides in the presence of ammonia molecules. The fabrication and assembly of the sensor unit, as well as fundamental simulation and characterisation studies, are presented. The device achieves a sensitivity of approximately 30 ppm and a linear response up to 600 ppm at room temperature. Finally, the potential to detect multiple analytes from a single device is demonstrated using principal-component analysis. © 1983-2012 IEEE.

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An accurate description of sound propagation in a duct is important to obtain the sound power radiating from a source in both near and far fields. A technique has been developed and applied to decompose higher-order modes of sound emitted into a duct. Traditional experiments and theory based on two-sensor methods are limited to the plane-wave contribution to the sound field at low frequency. Due to the increase in independent measurements required, a computational method has been developed to simulate sensitivities of real measurements (e.g., noise) and optimize the set-up. An experimental rig has been constructed to decompose the first two modes using six independent measurements from surface, flush-mounted microphones. Experiments were initially performed using a loudspeaker as the source for validation. Subsequently, the sound emitted by a mixed-flow fan has been investigated and compared to measurements made in accordance with the internationally standardized in-duct fan measurement method. This method utilizes large anechoic terminations and a procedure involving averaging over measurements in space and time to account for the contribution from higher-order modes. The new method does not require either of these added complications and gives detail about the underlying modal content of the emitted sound.

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A fast response sensor for measuring carbon dioxide concentration has been developed for laboratory research and tested on a spark ignition engine. The sensor uses the well known infra-red absorption technique with a miniaturized detection system and short capillary sampling tubes, giving a time constant of approximately 5 milliseconds; this is sufficiently fast to observe changes in CO2 levels on a cycle-by-cycle basis under normal operating conditions. The sensor is easily located in the exhaust system and operates continuously. The sensor was tested on a standard production four cylinder spark-ignition engine to observe changes in CO2 concentration in exhaust gas under steady state and transient operating conditions. The processed sensor signal was compared to a standard air-to-fuel ratio (AFR) sensor in the exhaust stream and the results are presented here. The high frequency response CO2 measurements give new insights into both engine and catalyst transient operation. Copyright © 1999 Society of Automotive Engineers, Inc.

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A novel real time smoke sensor is described, which is mounted in the exhaust manifold and detects the smoke by virtue of the natural electrical charge which is carried on the smoke. The somewhat obscure origin of the charge on the smoke is briefly considered, as well as the operation of the sensor itself. The use of the sensor as part of a feedback control shows that it can be very effective in reducing smoke puffs. Copyright © 1987 Society of Automotive Engineers, Inc.

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Single-sensor maximum power point tracking algorithms for photovoltaic systems are presented. The algorithms have the features, characteristics and advantages of the widely used incremental conductance (INC) algorithm. However; unlike the INC algorithm which requires two sensors (the voltage sensor and the current sensor), the single-sensor algorithms are more desirable because they require only one sensor: the voltage sensor. The algorithms operate by maximising power at the DC-DC converter output, instead of the input. © 2013 The Institution of Engineering and Technology.

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This paper addresses the design of mobile sensor networks for optimal data collection. The development is strongly motivated by the application to adaptive ocean sampling for an autonomous ocean observing and prediction system. A performance metric, used to derive optimal paths for the network of mobile sensors, defines the optimal data set as one which minimizes error in a model estimate of the sampled field. Feedback control laws are presented that stably coordinate sensors on structured tracks that have been optimized over a minimal set of parameters. Optimal, closed-loop solutions are computed in a number of low-dimensional cases to illustrate the methodology. Robustness of the performance to the influence of a steady flow field on relatively slow-moving mobile sensors is also explored © 2006 IEEE.

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The development of a novel label-free graphene sensor array is presented. Detection is based on modification of graphene FET devices and specifically monitoring the change in composition of the nutritive components in culturing medium. Micro-dispensing of Escherichia coli in medium shows feasibility of accurate positioning over each sensor while still allowing cell proliferation. Graphene FET device fabrication, sample dosing, and initial electrical characterisation have been completed and show a promising approach to reducing the sample size and lead time for diagnostic and drug development protocols through a label-free and reusable sensor array fabricated with standard and scalable microfabrication technologies. Copyright © 2012 Ronan Daly et al.

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Operational uncertainties such as throttle excursions, varying inlet conditions and geometry changes lead to variability in compressor performance. In this work, the main operational uncertainties inherent in a transonic axial compressor are quantified to deter- mine their effect on performance. These uncertainties include the effects of inlet distortion, metal expansion, ow leakages and blade roughness. A 3D, validated RANS model of the compressor is utilized to simulate these uncertainties and quantify their effect on polytropic efficiency and pressure ratio. To propagate them, stochastic collocation and sparse pseudospectral approximations are used. We demonstrate that lower-order approximations are sufficient as these uncertainties are inherently linear. Results for epistemic uncertainties in the form of meshing methodologies are also presented. Finally, the uncertainties considered are ranked in order of their effect on efficiency loss. © 2012 AIAA.