A área de sensores é uma das mais importantes do mundo tecnológico e científico moderno. O monitoramento contínuo de processos através de variáveis de diversas naturezas está presente em áreas como indústria, agricultura, biologia, meio ambiente, e centros de pesquisa. Os sensores químicos de pH fazem parte deste conjunto por analisar um dos parâmetros mais importantes em muitas áreas. Neste trabalho, o uso de filmes finos de polianilina (PANI) eletrodepositada em sensores de pH foi estudado. Duas configurações do sensor EGFET (Extended Gate Field-Effect Transistor) foram estudadas: o sensor Single-EGFET (S-EGFET) e o sensor Instrumental Amplifier-EGFET (IA-EGFET). Os filmes foram analisados nos dois sistemas e a sensibilidade e linearidade de cada sensor, comparada. Valores iniciais de sensibilidade no sensor IA-EGFET foram reduzidas devido a protonação interna do polímero quando medidos no sensor S-EGFET. Observamos uma relação entre quantidade de material polimérico depositado e o grau de alteração dos parâmetros. Os filmes de PANI foram estudados em sensores IA-EGFET como passo inicial para aplica-los em sensores diferencias, Diferencial-IA-EGFET (D-IA-EGFET). Desenvolveu-se o sensor diferencial por esse apresentar a vantagem de ser insensível a ruído (temperatura, tempo, sistema eletrônico, concentração, etc.) sobre o sensor simples. Para este sensor temos um filme principal com alta sensibilidade ao íon de interesse, um filme de contraste com baixa sensibilidade aos íons de interesse e igual sensibilidade às fontes indesejáveis. Esses pares de filmes foram compostos por PANI, protonada e não protonada, óxido de estanho dopado com flúor e dióxido de titânio. Medidas diferenciais em função de temperatura, concentração da solução de estudo e tempo mostraram que um mecanismo de sensibilidade a íons e propriedades elétricas similares dos filmes gera um sensor diferencial bom e estável. A PANI é um material poli-eletrocrômico, isto é, seu estado de oxidação altera sua coloração. Utilizando filmes finos de PANI, que sofrem reações de protonação e desprotonação em contato com soluções ácidas e básicas, obtivemos um sensor ótico analisando os espectros de reflexão das amostras. Uma resposta aprimorada por polarização elétrica das amostras mostrou aumento da sensibilidade e diminuição da linearidade do sensor em função da variação da polarização, fazendo necessária a obtenção de um ponto ótimo de trabalho. / The study of sensors is one of the most important in the technological and scientific modern world. Continuous monitoring of processes, using variables of different types, is present in such areas as industry, agriculture, biology, environment, and research centers. Chemical pH sensors are part of this group due to its capability to analyze important parameter in many fields. In this MS we investigated the use of electrodeposited polyaniline (PANI) thin films as pH sensors. Two configurations of the EGFET (Extended Gate Field-Effect Transistor) sensor were studied: the Single-EGFET (S-EGFET) and the Instrumental Amplifier-EGFET (IA-EGFET). The films were analyzed in both systems and the sensitivity and linearity of each sensor were compared. Initial sensitivities measured in the IA-EGFET were reduced due to polymer bulk protonation after sequential measurement in the S-EGFET system. A relationship between the amount of deposited polymer and the degree of sensitivity change was observed. The films of PANI were studied in IA-EGFET sensors prior to its application in differential mode sensors, the Differential-IA-EGFET (D-IA-EGFET). The differential mode of operation was developed due to its advantage of being insensitivity to noise (temperature, electronic, time and buffer concentration variations) over the single one. The sensor has a principal film possessing high sensitivity to the target ion and a contrast film with a low sensitivity to the target ion, and both with the same sensitivity to the noise sources. These films were made of PANI, protonated and non-protonated, fluorine tin oxide, and titanium dioxide. Differential measurements as function of temperature, buffer concentration and time showed that similarity in ion-sensing mechanisms and electrical properties of the single films is necessary for the fabrication of good and stable differential sensors. PANI is a polyelectrochromic material, in other words, its oxidation state changes its color. Thin films of PANI (which can be protonated or deprotonated in contact to acid or basic solutions) were used in optical sensors by means of its reflective spectra. A bias-enhanced reflective response increased the films sensitivity and decreases its linearity, inducing the determination of an optimized working point.

Diversas aplicações são responsáveis por gerar dados ao longo do tempo de maneira contínua, ordenada e ininterrupta em um ambiente dinâmico, denominados fluxo de dados. Entre possíveis tarefas que podem ser realizadas com estes dados, classificação é uma das mais proeminentes. Devido à natureza não estacionária do ambiente responsável por gerar os dados, as características que descrevem os conceitos das classes do problema de classificação podem se alterar ao longo do tempo. Por isso, classificadores de fluxo de dados requerem constantes atualizações em seus modelos para que a taxa de acerto se mantenha estável ao longo do tempo. Na etapa de atualização a maior parte das abordagens considera que, após a predição de cada exemplo, o seu rótulo correto é imediatamente disponibilizado sem qualquer atraso de tempo (latência nula). Devido aos altos custos do processo de rotulação, os rótulos corretos nem sempre podem ser obtidos para a maior parte dos dados ou são obtidos após um considerável atraso de tempo. No caso mais desafiador, encontram-se as aplicações em que após a etapa de classificação dos exemplos, os seus respectivos rótulos corretos nunca sã disponibilizados para o algoritmo, caso chamado de latência extrema. Neste cenário, não é possível o uso de abordagens tradicionais, sendo necessário o desenvolvimento de novos métodos que sejam capazes de manter um modelo de classificação atualizado mesmo na ausência de dados rotulados. Nesta tese, além de discutir o problema de latência na tarefa de classificação de fluxo de dados não estacionários, negligenciado por boa parte da literatura, também sã propostos dois algoritmos denominados SCARGC e MClassification para o cenário de latência extrema. Ambas as propostas se baseiam no uso de técnicas de agrupamento para a adaptação à mudanças de maneira não supervisionada. Os algoritmos propostos são intuitivos, simples e apresentam resultados superiores ou equivalentes a outros algoritmos da literatura em avaliações com dados sintéticos e reais, tanto em termos de acurácia de classificação como em tempo computacional. Aléem de buscar o avanço no estado-da-arte na área de aprendizado em fluxo de dados, este trabalho também apresenta contribuições para uma importante aplicação tecnológica com impacto social e na saúde pública. Especificamente, explorou-se um sensor óptico para a identificação automática de espécies de insetos a partir da análise de informações provenientes do batimento de asas dos insetos. Para a descrição dos dados, foi verificado que os coeficientes Mel-cepstrais apresentaram os melhores resultados entre as diferentes técnicas de processamento digital de sinais avaliadas. Este sensor é um exemplo concreto de aplicação responsável por gerar um fluxo de dados em que é necessário realizar classificações em tempo real. Durante a etapa de classificação, este sensor exige a adaptação a possíveis variações em condições ambientais, responsáveis por alterar o comportamento dos insetos ao longo do tempo. Para lidar com este problema, é proposto um Sistema com Múltiplos Classificadores que realiza a seleção dinâmica do classificador mais adequado de acordo com características de cada exemplo de teste. Em avaliações com mudanças pouco significativas nas condições ambientais, foi possível obter uma acurácia de classificação próxima de 90%, no cenário com múltiplas classes e, cerca de 95% para a identificação da espécie Aedes aegypti, considerando o treinamento com uma única classe. No cenário com mudanças significativas nos dados, foi possível obter 91% de acurácia em um problema com 5 classes e 96% para a classificação de insetos vetores de importantes doenças como dengue e zika vírus. / Many applications are able to generate data continuously over t ime in an ordered and uninterrupted way in a dynamic environment , called data streams. Among possible tasks that can be performed with these data, classification is one of the most prominent . Due to non-stationarity of the environment that generates the data, the features that describe the concepts of the classes can change over time. Thus, the classifiers that deal with data streams require constants updates in their classification models to maintain a stable accuracy over time. In the update phase, most of the approaches assume that after the classification of each example from the stream, their actual class label is available without any t ime delay (zero latency). Given the high label costs, it is more reasonable to consider that this delay could vary for the most portion of the data. In the more challenging case, there are applications with extreme latency, where in after the classification of the examples, heir actual class labels are never available to the algorithm. In this scenario, it is not possible to use traditional approaches. Thus, there is the need of new methods that are able to maintain a classification model updated in the absence of labeled data. In this thesis, besides to discuss the problem of latency to obtain actual labels in data stream classification problems, neglected by most of the works, we also propose two new algorithms to deal with extreme latency, called SCARGC and MClassification. Both algorithms are based on the use of clustering approaches to adapt to changes in an unsupervised way. The proposed algorithms are intuitive, simpleand showed superior or equivalent results in terms of accuracy and computation time compared to other approaches from literature in an evaluation on synthetic and real data. In addition to the advance in the state-of-the-art in the stream learning area, this thesis also presents contributions to an important technological application with social and public health impacts. Specifically, it was studied an optical sensor to automatically identify insect species by the means of the analysis of information coming from wing beat of insects. To describe the data, we conclude that the Mel-cepst ral coefficients guide to the best results among different evaluated digital signal processing techniques. This sensor is a concrete example of an applicat ion that generates a data st ream for which it is necessary to perform real-time classification. During the classification phase, this sensor must adapt their classification model to possible variat ions in environmental conditions, responsible for changing the behavior of insects. To address this problem, we propose a System with Multiple Classifiers that dynamically selects the most adequate classifier according to characteristics of each test example. In evaluations with minor changes in the environmental conditions, we achieved a classification accuracy close to 90% in a scenario with multiple classes and 95% when identifying Aedes aegypti species considering the training phase with only the positive class. In the scenario with considerable changes in the environmental conditions, we achieved 91% of accuracy considering 5 species and 96% to classify vector mosquitoes of important diseases as dengue and zika virus.

Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2017-02-01T18:32:19Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) DM Henrique Patriota Alves.pdf: 2961953 bytes, checksum: cd856b581753170ffb1c56ff445144f8 (MD5) / Made available in DSpace on 2017-02-01T18:32:19Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) DM Henrique Patriota Alves.pdf: 2961953 bytes, checksum: cd856b581753170ffb1c56ff445144f8 (MD5) Previous issue date: 2016-07-22 / CNPQ / Esta dissertação apresenta uma modelagem computacional da dinâmica de rugosidade de superfície gerada durante o processo de corrosão de um elemento transdutor metálico do sensor à fibra óptica. Tal modelagem é implementada num software dedicado de simulação multifísica que faz uso do Método dos Elementos Finitos. Considerando que a rugosidade de superfície pode ser definida por geometria fractal, que pode ser complexa, é proposta nesta dissertação uma forma alternativa e simples para modelar a superfície rugosa e a sua dinâmica sob corrosão. Para a modelagem computacional, é definida uma função periódica, chamada de função rugosidade, onde seus parâmetros são ajustados com dados experimentais do processo de corrosão. Os resultados da simulação computacional são comparados com um modelo analítico, que faz uso das equações de Fresnel. Nos resultados da simulação, é observado o acoplamento do sinal óptico na superfície rugosa do filme metálico. Esse acoplamento observado é explicado pelo fenômeno de Ressonância de Plásmon de Superfície. A modelagem proposta nesta dissertação apresenta excelente ajuste aos resultados experimentais. / This dissertation presents a computer modeling of the surface roughness dynamics generated during the corrosion process of a metallic element transducer of the fiber-optic sensor. This modeling is implemented in dedicated software that uses the Finite Element Method. Since the surface roughness can be defined by the fractal geometry, which can be complex, it is proposed in this dissertation an alternative and simple way to model the surface roughness and its dynamics under corrosion. The proposed modeling uses a roughness function that is defined by a periodic function, where their parameters are obtained from experimental data of the corrosion process. The computer simulation results are compared to an analytical model, which uses the Fresnel’s equations. In the simulation results, it is observed the optical signal coupling with the rough surface of the metallic film. This observed coupling is explained by the phenomenon of Surface Plasmon Resonance. The proposed modeling and simulations presents excellent fitting to the experimental results.

Orientador: Ivo Milton Raimundo Junior / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-04T22:55:02Z (GMT). No. of bitstreams: 1 Pinheiro_SilviaCristinaLopes_M.pdf: 5873346 bytes, checksum: 978465ffcf96f296fbc2acb75ab9102a (MD5) Previous issue date: 2005 / Mestrado / Quimica Analitica / Mestre em Química

Deer Creek Reservoir in Utah has a history of high algae concentrations. Despite recent nutrient reduction efforts, seasonal algae continue to present problems. Cost effective, accurate, and comprehensive monitoring is important to understand the reservoir processes driving this problem and characterizing the algae spatial and temporal distributions are an important part of this effort. Current laboratory methods for accurately measuring algae are expensive and time consuming and are based on water samples taken in the field and transported to the laboratory. This approach only provides data for relatively few point samples because of the time and expense of sample collection and analysis. These relatively few samples do not describe the complex spatial and temporal trends in the algal data. Algae exhibit non-uniform distributions, especially in the vertical direction. In situ probes are able to measure chlorophyll-a and provide a less expensive measuring alternative than laboratory methods. These probes provide relatively quick, high resolution vertical profile measurements, which allows for more comprehensive horizontal and temporal sampling. To have confidence in the probe data, good correlations between in situ chlorophyll-a measurements and laboratory algae or chlorophyll measurements are important, but these correlations can be reservoir and time dependant as reservoir conditions change. Therefore, they must be developed for each study site. This study reports on efforts at Deer Creek Reservoir to develop these correlations and provide a general description of the dynamic reservoir algal processes. I found that chlorophyll-a is weakly correlated to most algae species in the reservoir. However, it correlated well with total phytoplankton biovolume and the dominant algal species, which for this study was the diatom. Variations in correlation strength among the several algae species was assumed to most likely be affected by environmental factors, sample methods, algae species diversity, and the accuracy of the optical chlorophyll-a sensor. The data analysis indicate that the field methods used to obtain laboratory samples may have been a significant source of error because of the difficulty of matching the location of a probe measurement to the location of a sample. Field samples were not taken at the same depths as probe measurements and field samples from two locations were either mixed before laboratory analysis or the sample was a composite over a 2-meter range. Based on my observations, I have made several recommendations to improve the accuracy of the correlation between algae and chlorophyll-a.

This research developed two innovative test methods that were used to experimentally evaluate the performance of a novel blade tip timing (BTT) system from Prime Photonics, LC. The research focused on creating known blade tip offsets and tip vibrations so that the results from a BTT system can be validated. The topic of validation is important to the BTT field as the results between many commercial systems still are not consistent. While the system that was tested is still in development and final validation is not complete, the blade tip offset and vibration frequency validation results show that this BTT system will be a valuable addition to turbomachinery research and development programs once completed. For the first test method custom rotors were created with specified blade tip offsets. For the blade tip offset alternate measurement, the rotors were optically scanned and analyzed in CAD software with a tip location uncertainty of 0.1 mm. The BTT system agreed with the scanned results to within 0.13 mm. Tests were also conducted to ensure that the BTT system identified and indexed the blades properly. The second developed test method used an instrumented piezoelectric blade to create known dynamic deflections. The active vibration rotor was able to create measureable deflection over a range of frequencies centered on the first bending mode of the blade. The results for the 110 Hz, 150 Hz, 180 Hz first bending resonance, 200 Hz, and 1036 Hz second bending resonance cases are presented. A strain gage and piezoelectric sensor were attached to the active blade during the dynamic deflection tests to provide an alternate method for determining blade vibration frequency. The BTT system correctly identified the active blade excitation frequencies as well as a 120 Hz frequency from the drive motor. This thesis also explored applying BTT methods and testing to more realistic blade geometry and vibration. Blade vibrations are usually classified by their frequency relative to the rotation speed. Synchronous vibrations are integer multiples of the rotational speed and are often excited by struts or vanes fixed to the engine case. For this reason, special probe placement algorithms were explored that use sine curve fitting to optimize the probe placement. Knowing how the blade will vibrate at operation before testing is critical as well. In preparation for future research, ANSYS Mechanical was used to predict the first three modes of a PT6A-28 first stage rotor blade at 1,966, 5,539, and 7,144 Hz. These frequencies were validated to within 4% using scanning laser vibrometry. The simulation was repeated at speed to produce a Campbell Diagram to highlight synchronous excitation crossings. / Master of Science

Optical fibers are getting significant considerations in the field of the sensors and sensing beyond its applications in optical communications. Because of several advantages, e.g., low profile of the sensors, immunity to electromagnetic noises, the ability of multiplexing, etc., the use of the fiber optic sensor is increasing in the field of physical, chemical, and biomedical sensing. In this study, we have developed two new fiber optic sensors based on fiber loop ringdown technique (FLRD) and have demonstrated their applications in the field of sensing. In the first part of this study, we report on the development of a high-sensitivity FLRD strain sensor. For the design of the strain sensor, the fiber loop was cut at the middle, and then the two fiber ends from broken fiber loop were cleaved and aligned carefully to couple the light from one end to another end. Any strain during the measurement changes the alignment of the fiber ends, consequently, the ringdown time changes. With this scheme, the FLRD strain sensor has shown the strain detection limit of 65 nanostrain, which is five times better than any FLRD strain sensors reported in the literature. Furthermore, The FLRD strain sensors were successfully embedded into prestressed concrete-beams.The FLRD strain sensor was able to monitor stress on a post-tensioned rod, as well as the load applied on the concrete-beam during the three-point loading test, thus exhibiting immense potential in structural health monitoring. For the chemical sensor, a new scheme of interrogation for a fiber optic surface plasmon sensor was developed with the use of the FLRD technique. A gold nanolayer was deposited on an uncladded fiber section, and the fiber section was integrated into the FLRD system as a sensor head. The gold layer facilitates for increased interaction of sample of interest, with the light pulse confined in the fiber waveguide. Moreover, with the affinity of the gold with specific biomolecules, the sensor has the potential for applications in biochemical sensing. In the experiment, the SP-FLRD sensor was used for refractive index sensing, and index detection limit of 4.6×10-5 RIU was achieved.

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No description available.

Nanoscale materials have great applications in many areas. One of these applications is for manufacturing ultra-compact and efficient sensors for chemical and biological molecule detection. Noble metals, such as gold (Au) and silver (Ag), because of their distinguished optical property"localized surface plasmon resonances (LSPRs) that exhibit low loss, are ideal materials to fabricate these nanoscale plasmonic particles or structures. This work addresses the synthesis, characterization, and sensing applications of Au and Ag nanoparticles (NPs). The progress on certain subjects related to our work"NP synthesis, surface functionalization, Au sphere-film structure and two-photon fluorescence"are reviewed in Chapter 1. We also show the calculation results of LSPRs of Au nanosphere suspensions using Mie theory. The measured extinction spectra of Au nanosphere suspensions agree with the calculated results very well. Chapter 2 is a chapter describing the chemical synthesis of a variety of NPs, such as Ag prisms and cubes, Au spheres, rods, and bipyramids. These experiments involved different synthetic mechanisms and methods which enabled us to prepare NPs with desired shapes and optical properties. To put these NPs into application, it is desirable and sometimes necessary to functionalize their surfaces. In Chapter 3, we present the functionalization of Ag cubes with poly(allylamine hydrochloride) (PAH) and poly(allylamine hydrochloride)-dithiocarbamate (PAH-DTC), which follows our previous work on Au NPs. The purpose of studying Ag instead of Au is to use the stronger plasmonic enhancement in Ag when applied to two-photon imaging applications. However, we found that PAH-DTC shrank the Ag cubes. We also functionalized the cationic hexadecyltrimethylammonium bromide (CTAB)-stabilized Au NRs with anionic poly(sodium 4-styrenesulfonate) (PSS). Coated with the strong polyelectrolyte PSS, the NRs become more manageable and can be stable for over six months and are easily immobilized onto positively charged substrate. We put PSS-functionalized Au NPs into use and studied their adsorption process onto PAH-coated optical fiber tapers by monitoring the transmission light through the fiber. When the diameter of the fiber taper gets smaller, stronger coupling occurred between transmitted light inside the taper and the Au NPs on the taper surface (cylinder). This coupling resulted in a loss of the guided light at the plasmon resonance wavelength of the NPs. By monitoring this loss, we can study the adsorption rate of Au NPs onto the fiber. In Chapter 4, we used Au nanospheres to study the adsorption rate on substrates with different curvatures. We also established a theoretical model to explain this phenomenon for cylindrical surface as well as planar and spherical surfaces. Our results fit well with the theory, which predicts that particle adsorption rates depend strongly on surface geometry, and can exceed the planar surface deposition rate by over two orders of magnitude when the diffusion length of the particle is large compared to the surface curvature. In Chapter 5, we studied the optical properties of Au nanospheres separated from a thick Au film by a polyelectrolyte multilayer (PEM) film assembled from PAH and PSS under specific pH condition. The PEM film undergoes swelling and shrinking when the environmental pH is changed as a result of charging and discharging of the polyelectrolytes. Therefore, the PEM film provides an efficient means to tune the distance between Au spheres and Au film. The extinction peak blue-shifted as much as 100 nm when the pH of the water changed from pH 10 to pH 3 for 100 nm diameter Au spheres on a PEM film assembled at pH 9.5. Our preliminary estimates that the gap between sphere and surface can be as small as a few nm even though the film itself is tens of nm thick when it is not constrained by Au spheres. We studied two-photon excitation fluorescence (TPEF) from Ag triangles in Chapter 6. The triangles were fabricated by nanosphere lithography, which used convective self-assembly to make the nanosphere mask. The LSPRs of the nanotriangles were tuned to be in the 800--900 nm range to match with the Ti:Sapphire pulse laser at 880 nm. We found that certain spots on the fluorescence images gave rise to larger fluorescence intensity than rest of the area. SEM imaging reveals that the unusually bright spots seen on the surface were related to regions where the triangles transformed to spherical particles. The larger intensity is tentatively ascribed to the plasmon resonance of those spherical particles in ~400 nm range. / Ph. D.