735 resultados para Sensor Fusion
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A Norfloxacina (NFX) é um antibiótico antibacteriano indicado para combater bactérias Gram-negativas e amplamente utilizado para o tratamento de infeções no trato respiratório e urinário. Com a necessidade de realizar estudos clínicos e farmacológicos esenvolveram-se métodos de análise rápida e sensitiva para a determinação da Norfloxacina. Neste trabalho foi desenvolvido um novo sensor eletroquímico sensível e seletivo para a deteção da NFX. O sensor foi construído a partir de modificações efetuadas num elétrodo de carbono vítreo. Inicialmente o elétrodo foi modificado com a deposição de uma suspensão de nanotubos de carbono de paredes múltiplas (MWCNT) de modo a aumentar a sensibilidade de resposta analítica. De seguida um filme polímerico molecularmente impresso (MIP) foi preparado por eletrodeposição, a partir de uma solução contendo pirrol (monómero funcional) e NFX (template). Um elétrodo de controlo não impresso foi também preparado (NIP). Estudouse e caraterizou-se a resposta eletroquímica do sensor para a oxidação da NFX por voltametria de onda quadrada. Foram optimizados diversos parâmetros experimentais, tais como, condições ótimas de polimerização, condições de incubação e condições de extração. O sensor apresenta um comportamento linear entre a intensidade da corrente do pico e o logaritmo da concentração de NFX na gama entre 0,1 e 8μM. Os resultados obtidos apresentam boa precisão, com repetibilidade inferior a 6% e reprodutibilidade inferior a 9%. Foi calculado a partir da curva de calibração um limite de deteção de 0,2 μM O método desenvolvido é seletivo, rápido e de fácil manuseamento. O sensor molecularmente impresso foi aplicado com sucesso na deteção da NFX em amostras de urina real e água.
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Dissertação apresentada para obtenção do grau de Mestre em Bioquímica Estrutural e Funcional, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertação apresentada à Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para complementar os requerimentos para a obtenção do grau de Mestre em Engenharia Biomédica
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Neste trabalho faz-se uma pesquisa e análise dos conceitos associados à navegação inercial para estimar a distância percorrida por uma pessoa. Foi desenvolvida uma plataforma de hardware para implementar os algoritmos de navegação inercial e estudar a marcha humana. Os testes efetuados permitiram adaptar os algoritmos de navegação inercial para humanos e testar várias técnicas para reduzir o erro na estimativa da distância percorrida. O sistema desenvolvido é um sistema modular que permite estudar o efeito da inserção de novos sensores. Desta forma foram adaptados os algoritmos de navegação para permitir a utilização da informação dos sensores de força colocados na planta do pé do utilizador. A partir desta arquitetura foram efetuadas duas abordagens para o cálculo da distância percorrida por uma pessoa. A primeira abordagem estima a distância percorrida considerando o número de passos. A segunda abordagem faz uma estimação da distância percorrida com base nos algoritmos de navegação inercial. Foram realizados um conjunto de testes para comparar os erros na estimativa da distância percorrida pelas abordagens efetuadas. A primeira abordagem obteve um erro médio de 4,103% em várias cadências de passo. Este erro foi obtido após sintonia para o utilizador em questão. A segunda abordagem obteve um erro de 9,423%. De forma a reduzir o erro recorreu-se ao filtro de Kalman o que levou a uma redução do erro para 9,192%. Por fim, recorreu-se aos sensores de força que permitiram uma redução para 8,172%. A segunda abordagem apesar de ter um erro maior não depende do utilizador pois não necessita de sintonia dos parâmetros para estimar a distância para cada pessoa. Os testes efetuados permitiram, através dos sensores de força, testar a importância da força sentida pela planta do pé para aferir a fase do ciclo de marcha. Esta capacidade permite reduzir os erros na estimativa da distância percorrida e obter uma maior robustez neste tipo de sistemas.
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Ammonia is an important gas in many power plants and industrial processes so its detection is of extreme importance in environmental monitoring and process control due to its high toxicity. Ammonia’s threshold limit is 25 ppm and the exposure time limit is 8 h, however exposure to 35 ppm is only secure for 10 min. In this work a brief introduction to ammonia aspects are presented, like its physical and chemical properties, the dangers in its manipulation, its ways of production and its sources. The application areas in which ammonia gas detection is important and needed are also referred: environmental gas analysis (e.g. intense farming), automotive-, chemical- and medical industries. In order to monitor ammonia gas in these different areas there are some requirements that must be attended. These requirements determine the choice of sensor and, therefore, several types of sensors with different characteristics were developed, like metal oxides, surface acoustic wave-, catalytic-, and optical sensors, indirect gas analyzers, and conducting polymers. All the sensors types are described, but more attention will be given to polyaniline (PANI), particularly to its characteristics, syntheses, chemical doping processes, deposition methods, transduction modes, and its adhesion to inorganic materials. Besides this, short descriptions of PANI nanostructures, the use of electrospinning in the formation of nanofibers/microfibers, and graphene and its characteristics are included. The created sensor is an instrument that tries to achieve a goal of the medical community in the control of the breath’s ammonia levels being an easy and non-invasive method for diagnostic of kidney malfunction and/or gastric ulcers. For that the device should be capable to detect different levels of ammonia gas concentrations. So, in the present work an ammonia gas sensor was developed using a conductive polymer composite which was immobilized on a carbon transducer surface. The experiments were targeted to ammonia measurements at ppb level. Ammonia gas measurements were carried out in the concentration range from 1 ppb to 500 ppb. A commercial substrate was used; screen-printed carbon electrodes. After adequate surface pre-treatment of the substrate, its electrodes were covered by a nanofibrous polymeric composite. The conducting polyaniline doped with sulfuric acid (H2SO4) was blended with reduced graphene oxide (RGO) obtained by wet chemical synthesis. This composite formed the basis for the formation of nanofibers by electrospinning. Nanofibers will increase the sensitivity of the sensing material. The electrospun PANI-RGO fibers were placed on the substrate and then dried at ambient temperature. Amperometric measurements were performed at different ammonia gas concentrations (1 to 500 ppb). The I-V characteristics were registered and some interfering gases were studied (NO2, ethanol, and acetone). The gas samples were prepared in a custom setup and were diluted with dry nitrogen gas. Electrospun nanofibers of PANI-RGO composite demonstrated an enhancement in NH3 gas detection when comparing with only electrospun PANI nanofibers. Was visible higher range of resistance at concentrations from 1 to 500 ppb. It was also observed that the sensor had stable, reproducible and recoverable properties. Moreover, it had better response and recovery times. The new sensing material of the developed sensor demonstrated to be a good candidate for ammonia gas determination.
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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In-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability.
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Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.
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A new immunosensor is presented for human chorionic gonadotropin (hCG), made by electrodepositing chitosan/gold-nanoparticles over graphene screen-printed electrode (SPE). The antibody was covalently bound to CS via its Fc-terminal. The assembly was controlled by electrochemical Impedance Spectroscopy (EIS) and followed by Fourier Transformed Infrared (FTIR). The hCG-immunosensor displayed linear response against the logarithm-hCG concentration for 0.1–25 ng/mL with limit of detection of 0.016 ng/mL. High selectivity was observed in blank urine and successful detection of hCG was also achieved in spiked samples of real urine from pregnant woman. The immunosensor showed good detection capability, simplicity of fabrication, low-cost, high sensitivity and selectivity.
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6th Graduate Student Symposium on Molecular Imprinting
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1st ASPIC International Congress
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Dissertação para obtenção do Grau de Mestre em Bioorgânica
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IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.
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Molecular imprinting is a useful technique for the preparation of functional materials with molecular recognition properties. A Biomimetic Sensor Potentiometric System was developed for assessment of doxycycline (DOX) antibiotic. The molecularly imprinted polymer (MIP) was synthesized by using doxycycline as a template molecule, methacrylic acid (MAA) and/or acrylamide (AA) as a functional monomer and ethylene glycol dimethacrylat (EGDMA) as a cross-linking agent. The sensing elements were fabricated by the inclusion of DOX imprinted polymers in polyvinyl chloride (PVC) matrix. The sensors showed a high selectivity and a sensitive response to the template in aqueous system. Electrochemical evaluation of these sensors under static (batch) mode of operation reveals near-Nernstian response. MIP/MAA membrane sensor was incorporated in flow-through cells and used as detectors for flow injection analysis (FIA) of DOX. The method has the requisite accuracy, sensitivity and precision to assay DOX in tablets and biological fluids.