Solvent-Resistant Polymeric Sensors for Adulteration Detection in Liquid Fuels

Polymeric sensors with improved resistance to organic solvents were produced via the layer-by-layer thin film deposition followed by chemical cross-linking. According to UV-vis spectroscopy, the mass loss of polyaniline/poly(vinyl alcohol) and polyaniline/novolac-type resin based films deposited onto glass slides was less than 20% when they were submitted to successive immersions (up to 3,000 immersion cycles) into commercially available ethanol and gasoline fuel samples. Polyallylamine hydrochloride/nickel tetrasulfonated phthalocyanine films presented similar stability. The electrical responses assessed by impedance spectroscopy of films deposited onto Au-interdigitated microelectrodes were relatively unaffected after continuous or cyclic immersions into both fuels. After these studies, an array including these polymeric sensors was employed to detect adulteration in ethanol and gasoline samples. After principal component analysis, it was possible to conclude that the proposed sensor array is capable to discriminate with remarkable reproducibility ethanol samples containing different amounts of water or else gasoline samples containing different amounts of ethanol. In both examples, more than 90% of data variance was retained in the first principal component. For each type of sample, ethanol and gasoline, it was found a linear correlation between one of the principal components and the sample's composition. These findings allow one to conclude that these films present great potential for the development of reliable and low-cost sensors for fuel analysis in liquid phase.

Adaptive sensing for target tracking applications

In a statistical inference scenario, the estimation of target signal or its parameters is done by processing data from informative measurements. The estimation performance can be enhanced if we choose the measurements based on some criteria that help to direct our sensing resources such that the measurements are more informative about the parameter we intend to estimate. While taking multiple measurements, the measurements can be chosen online so that more information could be extracted from the data in each measurement process. This approach fits well in Bayesian inference model often used to produce successive posterior distributions of the associated parameter. We explore the sensor array processing scenario for adaptive sensing of a target parameter. The measurement choice is described by a measurement matrix that multiplies the data vector normally associated with the array signal processing. The adaptive sensing of both static and dynamic system models is done by the online selection of proper measurement matrix over time. For the dynamic system model, the target is assumed to move with some distribution and the prior distribution at each time step is changed. The information gained through adaptive sensing of the moving target is lost due to the relative shift of the target. The adaptive sensing paradigm has many similarities with compressive sensing. We have attempted to reconcile the two approaches by modifying the observation model of adaptive sensing to match the compressive sensing model for the estimation of a sparse vector.

Compact low-power cortical recording architecture for compressive multichannel data acquisition

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

Arranjos de sensores orientados à missão para a geração automática de mapas temáticos em VANTs

O uso de veículos aéreos não tripulados (VANTs) tem se tornado cada vez mais comum, principalmente em aplicações de uso civil. No cenário militar, o uso de VANTs tem focado o cumprimento de missões específicas que podem ser divididas em duas grandes categorias: sensoriamento remoto e transporte de material de emprego militar. Este trabalho se concentra na categoria do sensoriamento remoto. O trabalho foca a definição de um modelo e uma arquitetura de referência para o desenvolvimento de sensores inteligentes orientados a missões específicas. O principal objetivo destas missões é a geração de mapas temáticos. Neste trabalho são investigados processos e mecanismos que possibilitem a geração desta categoria de mapas. Neste sentido, o conceito de MOSA (Mission Oriented Sensor Array) é proposto e modelado. Como estudos de caso dos conceitos apresentados são propostos dois sistemas de mapeamento automático de fontes sonoras, um para o caso civil e outro para o caso militar. Essas fontes podem ter origem no ruído gerado por grandes animais (inclusive humanos), por motores de combustão interna de veículos ou por atividade de artilharia (incluindo caçadores). Os MOSAs modelados para esta aplicação são baseados na integração de dados provenientes de um sensor de imageamento termal e uma rede de sensores acústicos em solo. A integração das informações de posicionamento providas pelos sensores utilizados, em uma base cartográfica única, é um dos aspectos importantes tratados neste trabalho. As principais contribuições do trabalho são a proposta de sistemas MOSA, incluindo conceitos, modelos, arquitetura e a implementação de referência representada pelo sistema de mapeamento automático de fontes sonoras.

Exploring the spatial variation of tides for seafloor mapping data corrections

Senior thesis written for Oceanography 445

A three dimensional surface measurement and reconstruction system for respiratory function analysis

Respiration is a complex activity. If the relationship between all neurological and skeletomuscular interactions was perfectly understood, an accurate dynamic model of the respiratory system could be developed and the interaction between different inputs and outputs could be investigated in a straightforward fashion. Unfortunately, this is not the case and does not appear to be viable at this time. In addition, the provision of appropriate sensor signals for such a model would be a considerable invasive task. Useful quantitative information with respect to respiratory performance can be gained from non-invasive monitoring of chest and abdomen motion. Currently available devices are not well suited in application for spirometric measurement for ambulatory monitoring. A sensor matrix measurement technique is investigated to identify suitable sensing elements with which to base an upper body surface measurement device that monitors respiration. This thesis is divided into two main areas of investigation; model based and geometrical based surface plethysmography. In the first instance, chapter 2 deals with an array of tactile sensors that are used as progression of existing and previously investigated volumetric measurement schemes based on models of respiration. Chapter 3 details a non-model based geometrical approach to surface (and hence volumetric) profile measurement. Later sections of the thesis concentrate upon the development of a functioning prototype sensor array. To broaden the application area the study has been conducted as it would be fore a generically configured sensor array. In experimental form the system performance on group estimation compares favourably with existing system on volumetric performance. In addition provides continuous transient measurement of respiratory motion within an acceptable accuracy using approximately 20 sensing elements. Because of the potential size and complexity of the system it is possible to deploy it as a fully mobile ambulatory monitoring device, which may be used outside of the laboratory. It provides a means by which to isolate coupled physiological functions and thus allows individual contributions to be analysed separately. Thus facilitating greater understanding of respiratory physiology and diagnostic capabilities. The outcome of the study is the basis for a three-dimensional surface contour sensing system that is suitable for respiratory function monitoring and has the prospect with future development to be incorporated into a garment based clinical tool.

Bottleneck Problem Solution using Biological Models of Attention in High Resolution Tracking Sensors

Every high resolution imaging system suffers from the bottleneck problem. This problem relates to the huge amount of data transmission from the sensor array to a digital signal processing (DSP) and to bottleneck in performance, caused by the requirement to process a large amount of information in parallel. The same problem exists in biological vision systems, where the information, sensed by many millions of receptors should be transmitted and processed in real time. Models, describing the bottleneck problem solutions in biological systems fall in the field of visual attention. This paper presents the bottleneck problem existing in imagers used for real time salient target tracking and proposes a simple solution by employing models of attention, found in biological systems. The bottleneck problem in imaging systems is presented, the existing models of visual attention are discussed and the architecture of the proposed imager is shown.

Under-ice fauna, sea-ice concentration, sea-ice thickness and under-ice water parameters from the Eurasian central Arctic Ocean during POLARSTERN cruise ARK-XXVII/3 (PS80) in August-September 2012

Arctic sea-ice decline is expected to have a significant impact on Arctic marine ecosystems. Ice-associated fauna play a key role in this context because they constitute a unique part of Arctic biodiversity and transmit carbon from sea-ice algae into pelagic and benthic food webs. Our study presents the first regional-scale record of under-ice faunal distribution and the environmental characteristics of under-ice habitats throughout the Eurasian Basin. Sampling was conducted with a Surface and Under-Ice Trawl, equipped with a sensor array recording ice thickness and other physical parameters during trawling. We identified 2 environmental regimes, broadly coherent with the Nansen and Amundsen Basins. The Nansen Basin regime was distinguished from the Amundsen Basin regime by heavier sea-ice conditions, higher surface salinities and higher nitrate + nitrite concentrations. We found a diverse (28 species) under-ice community throughout the Eurasian Basin. Change in community structure reflected differences in the relative contribution of abundant species. Copepods (Calanus hyperboreus and C. glacialis) dominated in the Nansen Basin regime. In the Amundsen Basin regime, amphipods (Apherusa glacialis, Themisto libellula) dominated. Polar cod Boreogadus saida was present throughout the sampling area. Abrupt changes from a dominance of ice-associated amphipods at ice-covered stations to a dominance of pelagic amphipods (T. libellula) at nearby ice-free stations emphasised the decisive influence of sea ice on small-scale patterns in the surface-layer community. The observed response in community composition to different environmental regimes indicates potential long-term alterations in Arctic marine ecosystems as the Arctic Ocean continues to change.

DESIGN AND APPLICATION OF WIRELESS PASSIVE MAGNETOELASTIC RESONANCE AND MAGNETOHARMONIC FORCE SENSORS

The objective of the work described in this dissertation is the development of new wireless passive force monitoring platforms for applications in the medical field, specifically monitoring lower limb prosthetics. The developed sensors consist of stress sensitive, magnetically soft amorphous metallic glass materials. The first technology is based on magnetoelastic resonance. Specifically, when exposed to an AC excitation field along with a constant DC bias field, the magnetoelastic material mechanically vibrates, and may reaches resonance if the field frequency matches the mechanical resonant frequency of the material. The presented work illustrates that an applied loading pins portions of the strip, effectively decreasing the strip length, which results in an increase in the frequency of the resonance. The developed technology is deployed in a prototype lower limb prosthetic sleeve for monitoring forces experienced by the distal end of the residuum. This work also reports on the development of a magnetoharmonic force sensor comprised of the same material. According to the Villari effect, an applied loading to the material results in a change in the permeability of the magnetic sensor which is visualized as an increase in the higher-order harmonic fields of the material. Specifically, by applying a constant low frequency AC field and sweeping the applied DC biasing field, the higher-order harmonic components of the magnetic response can be visualized. This sensor technology was also instrumented onto a lower limb prosthetic for proof of deployment; however, the magnetoharmonic sensor illustrated complications with sensor positioning and a necessity to tailor the interface mechanics between the sensing material and the surface being monitored. The novelty of these two technologies is in their wireless passive nature which allows for long term monitoring over the life time of a given device. Additionally, the developed technologies are low cost. Recommendations for future works include improving the system for real-time monitoring, useful for data collection outside of a clinical setting.