967 resultados para Sensor array processing
Resumo:
We report the performance of a group of adult dyslexics and matched controls in an array-matching task where two strings of either consonants or symbols are presented side by side and have to be judged to be the same or different. The arrays may differ either in the order or identity of two adjacent characters. This task does not require naming – which has been argued to be the cause of dyslexics’ difficulty in processing visual arrays – but, instead, has a strong serial component as demonstrated by the fact that, in both groups, Reaction times (RTs) increase monotonically with position of a mismatch. The dyslexics are clearly impaired in all conditions and performance in the identity conditions predicts performance across orthographic tasks even after age, performance IQ and phonology are partialled out. Moreover, the shapes of serial position curves are revealing of the underlying impairment. In the dyslexics, RTs increase with position at the same rate as in the controls (lines are parallel) ruling out reduced processing speed or difficulties in shifting attention. Instead, error rates show a catastrophic increase for positions which are either searched later or more subject to interference. These results are consistent with a reduction in the attentional capacity needed in a serial task to bind together identity and positional information. This capacity is best seen as a reduction in the number of spotlights into which attention can be split to process information at different locations rather than as a more generic reduction of resources which would also affect processing the details of single objects.
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We experimentally investigate the use of an arrayed waveguide grating (AWG) to interrogate interferometric sensors. A single broad-band light source is used to illuminate the system. Reflected spectral information is directed to an AWG with integral photodetectors providing 40 electrical outputs. We show that using the dual-wavelength technique we can measure the length of a Fabry-Pérot cavity by determining the optical phase changes of the scanned interferometric pattern, which produced a maximum unambiguous range of 1440 μm with an active sensor and a maximum unambiguous range of 300 μm with the introduction of a second processing interferometer, which allows the sensor to be passive. © 2005 IEEE.
Resumo:
In this letter, an energy-efficient adaptive code position modulation scheme is proposed for wireless sensor networks to provide the relatively stable bit error ratio (BER) performance expected by the upper layers. The system is designed with focus on the adaptive control of transmission power, which is adjusted based on the measured power density of background noise. Interfaces among the modulation module, packet scheduling module and upper layer are provided for flexible adjustments to adapt to the background noise and deliver expected application quality. Simulations with Signal Processing Worksystem (SPW) validate the effectiveness of the scheme. © 2005 IEEE.
Resumo:
The number of nodes has large impact on the performance, lifetime and cost of wireless sensor network (WSN). It is difficult to determine, because it depends on many factors, such as the network protocols, the collaborative signal processing (CSP) algorithms, etc. A mathematical model is proposed in this paper to calculate the number based on the required working time. It can be used in the general situation by treating these factors as the parameters of energy consumption. © 2004 IEEE.
Resumo:
In this paper, multiplexed sensor network capable of monitoring the shape changes of the torso for respiratory function monitoring is developed. As a demonstration, LPGs written into refractive index insensitive, progressive three layered fibre are embedded into supporting material is then placed on a resuscitation training manikin simulating respiration. A derivative spectroscopy interrogation technique is implemented and the bend sensitivity of the LPGs is used to reconstruct the shape of the manikin's torso. © 2003 IEEE.
Resumo:
Controlling the water content within a product has long been required in the chemical processing, agriculture, food storage, paper manufacturing, semiconductor, pharmaceutical and fuel industries. The limitations of water content measurement as an indicator of safety and quality are attributed to differences in the strength with which water associates with other components in the product. Water activity indicates how tightly water is "bound," structurally or chemically, in products. Water absorption introduces changes in the volume and refractive index of poly(methyl methacrylate) PMMA. Therefore for a grating made in PMMA based optical fiber, its wavelength is an indicator of water absorption and PMMA thus can be used as a water activity sensor. In this work we have investigated the performance of a PMMA based optical fiber grating as a water activity sensor in sugar solution, saline solution and Jet A-1 aviation fuel. Samples of sugar solution with sugar concentration from 0 to 8%, saline solution with concentration from 0 to 22%, and dried (10ppm), ambient (39ppm) and wet (68ppm) aviation fuels were used in experiments. The corresponding water activities are measured as 1.0 to 0.99 for sugar solution, 1.0 to 0.86 for saline solution, and 0.15, 0.57 and 1.0 for the aviation fuel samples. The water content in the measured samples ranges from 100% (pure water) to 10 ppm (dried aviation fuel). The PMMA based optical fiber grating exhibits good sensitivity and consistent response, and Bragg wavelength shifts as large as 3.4 nm when the sensor is transferred from dry fuel to wet fuel. © 2014 Copyright SPIE.
Resumo:
Cardiovascular health of the human population is a major concern for medical clinicians, with cardiovascular diseases responsible for 48% of all deaths worldwide, according to the World Health Organisation. Therefore the development of new practicable and economical diagnostic tools to scrutinise the cardiovascular health of humans is a major driver for clinicians. We offer a new technique to obtain seismocardiographic signals covering both ballistocardiography (below 20Hz) and audible heart sounds (20Hz upwards). The detection scheme is based upon an array of curvature/displacement sensors using fibre optic long period gratings interrogated using a variation of the derivative spectroscopy interrogation technique. © 2014 SPIE.
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We demonstrate a bi-metal coated (platinum and gold or silver), localized surface plasmon resonance fiber sensor with an index sensitivity exceeding 11,900 nm/RIU, yielding an index resolution of 2 × 10-5 in the aqueous index regime. This is one of the highest index sensitivities achieved with an optical fiber sensor. The coatings consist of arrays of bi-metal nano-wires (typically 36 nm in radius and 20 μm in length), supported by a silicon dioxide thin film on a thin substrate of germanium, the nano-wires being perpendicular to the longitudinal axis of the D-shaped fiber.
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This work bridges the gap between the remote interrogation of multiple optical sensors and the advantages of using inherently biocompatible low-cost polymer optical fiber (POF)-based photonic sensing. A novel hybrid sensor network combining both silica fiber Bragg gratings (FBG) and polymer FBGs (POFBG) is analyzed. The topology is compatible with WDM networks so multiple remote sensors can be addressed providing high scalability. A central monitoring unit with virtual data processing is implemented, which could be remotely located up to units of km away. The feasibility of the proposed solution for potential medical environments and biomedical applications is shown.
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Optical fibre strain sensors using Fibre Bragg Gratings (FBGs) are poised to play a major role in structural health monitoring in a variety of application from aerospace to civil engineering. At the heart of technology is the optoelectronic instrumentation required to convert optical signals into measurands. Users are demanding compact, lightweight, rugged and low cost solutions. This paper describes development of a new device based on a blazed FBG and CCD array that can potentially meet the above demands. We have shown that this very low cost technique may be used to interrogate a WDM array of sensor gratings with highly accurate and highly repeatable results unaffected by the polarisation state of the radiation. In this paper, we present results showing that sensors may be interrogated with an RMS error of 1.7pm, drift below 0.12pm and dynamic range of up to 65nm.
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A highly sensitive liquid level monitoring system based on microstructured polymer optical fiber Bragg grating (mPOFBG) array sensors is reported for the first time. The configuration is based on five mPOFBGs inscribed in the same fiber in the 850 nm spectral region, showing the potential to interrogate liquid level by measuring the strain induced in each mPOFBG embedded in a silicone rubber (SR) diaphragm, which deforms due to hydrostatic pressure variations. The sensor exhibits a highly linear response over the sensing range, a good repeatability, and a high resolution. The sensitivity of the sensor is found to be 98 pm/cm of water, enhanced by more than a factor of 9 when compared to an equivalent sensor based on a silica fiber around 1550 nm. The temperature sensitivity is studied and a multi-sensor arrangement proposed, which has the potential to provide level readings independent of temperature and the liquid density.
Resumo:
A high performance liquid-level sensor based on microstructured polymer optical fiber Bragg grating (mPOFBG) array sensors is reported in detail. The sensor sensitivity is found to be 98pm/cm of liquid, enhanced by more than a factor of 9 compared to a reported silica fiber-based sensor.
Resumo:
For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.
Resumo:
A high-performance fuel gauging sensor is described that uses five diaphragm-based pressure sensors, which are monitored using a linear array of polymer optical fiber Bragg gratings. The sensors were initially characterized using water, revealing a sensitivity of 98 pm/cm for four of the sensors and 86 pm/cm for the fifth. The discrepancy in the sensitivity of the fifth sensor has been explained as being a result of the annealing of the other four sensors. Initial testing in JET A-1 aviation fuel revealed the unsuitability of silicone rubber diaphragms for prolonged usage in fuel. A second set of sensors manufactured with a polyurethane-based diaphragm showed no measurable deterioration over a three month period immersed in fuel. These sensors exhibited a sensitivity of 39 pm/cm, which is less than the silicone rubber devices due to the stiffer nature of the polyurethane material used.
Resumo:
The move from Standard Definition (SD) to High Definition (HD) represents a six times increases in data, which needs to be processed. With expanding resolutions and evolving compression, there is a need for high performance with flexible architectures to allow for quick upgrade ability. The technology advances in image display resolutions, advanced compression techniques, and video intelligence. Software implementation of these systems can attain accuracy with tradeoffs among processing performance (to achieve specified frame rates, working on large image data sets), power and cost constraints. There is a need for new architectures to be in pace with the fast innovations in video and imaging. It contains dedicated hardware implementation of the pixel and frame rate processes on Field Programmable Gate Array (FPGA) to achieve the real-time performance. ^ The following outlines the contributions of the dissertation. (1) We develop a target detection system by applying a novel running average mean threshold (RAMT) approach to globalize the threshold required for background subtraction. This approach adapts the threshold automatically to different environments (indoor and outdoor) and different targets (humans and vehicles). For low power consumption and better performance, we design the complete system on FPGA. (2) We introduce a safe distance factor and develop an algorithm for occlusion occurrence detection during target tracking. A novel mean-threshold is calculated by motion-position analysis. (3) A new strategy for gesture recognition is developed using Combinational Neural Networks (CNN) based on a tree structure. Analysis of the method is done on American Sign Language (ASL) gestures. We introduce novel point of interests approach to reduce the feature vector size and gradient threshold approach for accurate classification. (4) We design a gesture recognition system using a hardware/ software co-simulation neural network for high speed and low memory storage requirements provided by the FPGA. We develop an innovative maximum distant algorithm which uses only 0.39% of the image as the feature vector to train and test the system design. Database set gestures involved in different applications may vary. Therefore, it is highly essential to keep the feature vector as low as possible while maintaining the same accuracy and performance^