abstract: Detection of molecular interactions is critical for understanding many biological processes, for detecting disease biomarkers, and for screening drug candidates. Fluorescence-based approach can be problematic, especially when applied to the detection of small molecules. Various label-free techniques, such as surface plasmon resonance technique are sensitive to mass, making it extremely challenging to detect small molecules. In this thesis, novel detection methods for molecular interactions are described. First, a simple detection paradigm based on reflectance interferometry is developed. This method is simple, low cost and can be easily applied for protein array detection. Second, a label-free charge sensitive optical detection (CSOD) technique is developed for detecting of both large and small molecules. The technique is based on that most molecules relevant to biomedical research and applications are charged or partially charged. An optical fiber is dipped into the well of a microplate. It detects the surface charge of the fiber, which does not decrease with the size (mass) of the molecule, making it particularly attractive for studying small molecules. Third, a method for mechanically amplification detection of molecular interactions (MADMI) is developed. It provides quantitative analysis of small molecules interaction with membrane proteins in intact cells. The interactions are monitored by detecting a mechanical deformation in the membrane induced by the molecular interactions. With this novel method small molecules and membrane proteins interaction in the intact cells can be detected. This new paradigm provides mechanical amplification of small interaction signals, allowing us to measure the binding kinetics of both large and small molecules with membrane proteins, and to analyze heterogeneous nature of the binding kinetics between different cells, and different regions of a single cell. Last, by tracking the cell membrane edge deformation, binding caused downstream event – granule secretory has been measured. This method focuses on the plasma membrane change when granules fuse with the cell. The fusion of granules increases the plasma membrane area and thus the cell edge expands. The expansion is localized at the vesicle release location. Granule size was calculated based on measured edge expansion. The membrane deformation due to the granule release is real-time monitored by this method. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

Nowadays due to the increase of renewable energy sources, Distributed Generations (DGs) assumed an important role in distribution and sub transmission systems. However, abnormal operating conditions of the distribution system may cause that the DG remains isolated from the main system and connected to part of distribution system feeding its local loads. This operating condition is known as DG islanding. There are many island detection techniques however they can fail in some situation, such as in cases of low power unbalance. This work aims to present three news passive island detection technique for synchronous Distributed Generation that has better performance than the traditional one. The first technique aims to attenuates the oscillations caused in the frequency by short circuits and load switching using Mathematical Morphology. The MM reduces frequency oscillations, and in this way it allows to reduce the thresholds. With smaller thresholds is possible the detection of small power mismatch and in a much smaller time. The second technique is based on Frequency Oscillation Estimation in order to distinguish the islanding from other events that may occur in distribution systems. This island detection algorithm uses a small time window to estimate the oscillation frequency, obtaining faster responses than the existing methods which use larger windows to estimate the damping and frequency of oscillation. The third method aims to recognize de frequency shape through a pattern recognition algorithm. The algorithm uses singular value decomposition and linear discrimination analysis to classify the events. The algorithms performances have been tested considering several generation and load scenarios including short circuits, load and capacitor switching, DG outage and islanding. The proposed methods were compared with the island detection method commonly used, i.e. Rate of Change of Frequency and Under / Overfrequency. The proposed methods are reliable since they do not trip for the most of non-islanding event. Among the tested methodologies, the method of the Frequency Oscillation Estimation has the best performance. Its detection time is less than 40ms and it Non Detection Zone is smallest than the range between + 3.2% and -1.6% of the GD rated power. The mathematical simplicity of EFO is adequate for practical relay implementation and the results show that EFO performs better than the other techniques. / Atualmente, devido ao aumento das fontes de energia renováveis, a Geração Distribuída (GD) assumiu um papel importante nos sistemas de distribuição e subtransmissão. No entanto, condições anormais de operação podem fazer com que a GD seja desconectada do sistema principal e permaneça conectada a uma parte menor do sistema, alimentando apenas suas cargas locais. Esta condição de operação é conhecida como ilhamento não intencional da GD. Existem diversas técnicas de detecção de ilhamento, porém, estas podem falhar em determinadas situações como em casos de baixo desbalanço de potência. Este trabalho apresenta três novas técnicas para detecção de ilhamento de gerações distribuídas com geradores síncronos, as quais apresentam melhores desempenhos que as técnicas tradicionais. A primeira metodologia proposta utiliza a Morfologia Matemática (MM) e visa atenuar as oscilações de frequência causadas por curtos-circuitos e comutação de carga. A MM reduz as oscilações e desta forma permite a redução dos limiares de detecção. Com limiares menores é possível detectar desbalanços de potência menores e em um tempo muito menor. A segunda técnica utiliza a Estimação da Frequência de Oscilação (EFO) e busca distinguir ilhamentos de outros eventos que podem ocorrer no sistema de distribuição. Nesse caso, o algoritmo de detecção de ilhamento utiliza uma pequena janela de tempo para estimar a frequência de oscilação. Assim, obtém uma resposta mais rápida do que os métodos até então existentes, que estimam o amortecimento e a frequência de oscilação. O terceiro visa reconhecer a forma da frequência através de um algoritmo de reconhecimento de padrão. O algoritmo utiliza decomposição em valores singulares e análise linear discriminante para promover a classificação dos eventos. Os desempenhos dos algoritmos foram avaliados com base em diversos cenários de geração e de carga, incluindo curtos-circuitos, chaveamentos de carga e de banco de capacitores, saída de GD e ilhamento. Os métodos propostos foram comparados com os algoritmos de detecção de ilhamentos comumente utilizados, ou seja, a Taxa de Variação da Frequência e Sub/Sobrefrequência. Os métodos propostos se mostraram confiáveis uma vez que não operam para a maioria dos eventos que não se caracterizam como ilhamentos. Dentre as metodologias testadas, o método da estimação da frequência de oscilação é o que apresentou melhor desempenho. Seu tempo de detecção é menor que 40ms e sua Zona de Não Detecção (ZND) é inferior a faixa situada entre +3,2% e -1,6% da potência nominal da GD. A simplicidade matemática da EFO favorece sua implementação prática, e os resultados mostram um desempenho bem superior quando comparado a outras técnicas já implementadas.

De nos jours, les biocapteurs électrochimiques constituent des outils rapides, fiables, rentables et sans marquage pour la détection sur site des polluants environnementaux et l’évaluation des critères de sécurité alimentaire et pour la détection des résidus militaires sur le terrain. Nous avons développé des biocapteurs d’affinité basés sur des récepteurs biologiques pour la détection électrochimique de l'estradiol dans des échantillons environnementaux et de molécules odorantes dans l'adultération de viande de porc. Des biocapteurs sensibles, sélectifs, rapides, simples reproductible, stables et efficaces ont été élaborés. En outre, une autre stratégie basée sur des nanomatériaux intégrés a été employée pour élaborer un capteur biomimétique pour la détection d’explosifs, qui a montré de bonnes qualités dans la protection de l'environnement. A la fin du manuscrit, certaines perspectives sont discutées / Nowadays, electrochemical biosensors are rapid, reliable, cost-effective and label-free tools for in field monitoring of environmental pollutants, for assessing the food safety criterion and for detection of the territory military residues. We developed biological receptors based affinity biosensors for electrochemical detection of estradiol in environment samples and odorant molecules in pork meat adulteration. The sensitive, selective, rapid, simple, repetitive, stable and effective biosensors were produced. In addition, another strategy entrapment based on integrated nano-material was used to produce a biomimetic sensor for explosives detection, which has shown good valuable in environmental protection and homeland security. In the end, certain significant prospective are discussed

Ce travail porte sur l’étude des structures cohérentes dans une couche limite de plaque plane à hauts nombres de Reynolds (Reθ=9830 et Reθ=19660). L'estimation Stochastique Linéaire est utilisée pour reconstruire un champ de vitesses résolu en espace et en temps à partir des mesures aux fils chauds à 30 KHz et des mesures PIV à 4 Hz. Une base de données DNS d’un écoulement de canal turbulent a été utilisée pour valider la procédure de reconstruction. Le champ de vitesse reconstruit est comparé à un champ de référence extrait de la DNS avec la visualisation des contours du champ de vitesse, l’analyse spectrale, les corrélations, etc. Par ailleurs, une analyse statistique est réalisée sur le champ de PIV originale, les données issues des fils chauds et celles reconstruites. Les résultats obtenus sont comparés à ceux de Carlier et Stanislas (2005) qui servent de référence. Des algorithmes ont été développés pour extraire les structures cohérentes du champ reconstruit. Les régions de vitesse uniforme sont caractérisées avec leur diamètre hydraulique, leur durée de vie et leur contribution aux tenseurs de Reynolds. Pour les tourbillons, on leur associe un rayon, une circulation et une vorticité en plus de leur durée de vie et leur nombre calculé à une distance fixe de la paroi. L’organisation spatiale des structures est étudiée avec la corrélation de leurs fonctions indicatives. Le modèle simplifié à grandes échelles qui en découle est comparé à ceux qui existent dans la littérature / This study lies in the context of large scale coherent structures (uniform momentum regions and vortical motions) investigation in a near wall turbulent boundary layer at high Reynolds numbers (Reθ=9830 and Reθ=19660).   With a Linear Stochastic Estimation procedure based on correlations computation, a full time-resolved 3 component field is reconstructed at high frequency from stereo-PIV at 4 Hz and hot wire data at 30 kHz . A DNS database of turbulent channel flow was used to validate the reconstruction method. To evaluate the quality of the method, reconstructed velocity fluctuations are compared to refence ones extracted directly from the DNS database.  Furthermore,  a statistical analysis is performed on HWA, PIV and LSE velocity fields. The results obtained are compared to those from Carlier and Stanislas (2005). Algorithms were developed to extract coherent structures from the reconstructed field. Uniform momentum regions are characterized with their mean hydraulic diameter in the YZ plane, their life time and their contribution to Reynolds stresses. The vortical motions are characterized by their position, radius, circulation and vorticity in addition to their life time and their number computed at a fixed position from the wall. The spatial organization of the structures was investigated through a correlation of their respective indicative functions in the spanwise direction . The simplified large scale model that arised is compared to the ones in the literature

Concrete has for decades been one of the main materials used to construct important structuressuch as dams and bridges. However, after years of service, the concrete structuresstart deteriorating and signs of damages start showing on the structure. The inspectionof such structures is compulsory to assess their state and plan repairing operations ifnecessary. The main inspection method has for long been field inspection, however, thismethod presents several problems, namely, the complexity to access some parts of thestructures and the subjectivity of the decisions. These difficulties make the operationtime-consuming and prone to error, thus a need for a new methodology that would benumerical and more automated.One of the damages that affect the carrying capacity the most in concrete structuresare surface-cracks. In this work, the focus is brought on this type of damage and a solutionfor the inspection methodology is presented and applied to a case study.The methodology first consists in using the photogrammetry technology, which allows theproduction of a 3D point cloud model of the structure by taking multiple pictures of it usingUAVs to facilitate access to its complex parts. From this point cloud, surface-openingcracks could be visualized and an orthoimage featuring the damages can be produced.Then, an image-based crack detection program will be used on the orthoimage to extractthe crack. From this, a program is developed to find the coordinates of the crack in thestructure and to process the model of the crack. Then a program is made to importthe crack model to a finite element software, and from there the extended finite elementmethod (XFEM) combined with the concrete damaged plasticity (CDP) method will beused to assess the carrying capacity of the structure and to study the evolution of itscrack pattern.The methodology was tested in a case study. In this case study, a steel-reinforced concretebeam was damaged and all of the methodology steps were applied. An adaptationto some steps was needed due to challenges raised by the test set-up.A three-point bending experience was carried out on the beam while recording the forceand displacement data and the crack pattern evolution. Numerically, this experience wasreproduced and relevant results were extracted and compared to the experimental ones.Differences in the carrying capacity were observed and multiple numerical analyses werecarried out to test the taken assumptions and detect the source of error. On the otherhand, for the crack pattern, satisfying results were achieved. Moreover, the degree of thedetailing in the crack model and its effect on the results is discussed.Globally, it can be concluded that the methodology can effectively in a numericalsemi-automated way capture the surface cracks in concrete structures and import theirmodel to a finite element software to apply analyses to assess the capacity of the damagedstructure and study the evolution of the cracks.This methodology could be further developed in the future by including more technologiessuch as lasergrammetry to make it go from a 2D surface-based damage analysis to a 3Danalysis. Moreover, criteria specialized for inspection and repairing purposes could becreated and implemented in the methodology.

<p dir="ltr">The detection of explosives and explosive devices based upon the volatile compounds they emit is a long-standing tool for law enforcement and physical security. Towards that end, solid-phase microextraction (SPME) combined with gas chromatography-mass spectrometry (GC-MS) has become a crucial analytical tool for the identification of volatiles emitted by explosives. Previous SPME studies have identified many volatile compounds emitted by common explosive formulations that serve as the main charge in explosive devices. However, limited research has been conducted on initiators like fuses, detonating cords, and boosters. In this study, a variety of SPME fiber coatings (i.e., polydimethylsiloxane (PDMS), polydimethylsiloxane/divinylbenzene (PDMS/DVB), divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS), carboxen/polydimethylsiloxane (CAR/PDMS), and polyacrylate (PA)) were employed for the extraction and analysis of volatiles from Composition C-4 (cyclohexanone, 2-ethyl-1-hexanol, and 2,3-dimethyl-2,3-dinitrobutane (DMNB)) and Red Dot double-base smokeless powder (nitroglycerine, phenylamine). The results revealed that a PDMS/DVB fiber was optimal. Then, an assortment of explosive items (i.e., detonation cord, safety fuse, slip-on booster, and shape charge) were analyzed with a PDMS/DVB fiber. A variety of volatile compounds were identified, including plasticizers (tributyl acetyl citrate, N-butylbenzenesulfonamide), taggants (DMNB), and degradation products (2-ethyl-1-hexanol). </p><p dir="ltr">Taggants, like DMNB, are one of the pivotal components added to explosives. These distinctive chemical markers, deliberately introduced during manufacturing to facilitate the identification of explosives, are commonly detected using SPME GC- MS, but their quantitation remains underexplored. To address this, we investigated total vaporization headspace (TV- HS) GC- MS for quantifying taggants in the headspace of Composition C4. Factors effecting the extraction of DMNB, such as shape and age of the sample, and surface depletion, were also examined. The results revealed that the shape of the sample did not affect the amount of DMNB in the headspace but the older the sample, the more DMNB was detected in the headspace. Surface depletion was also seen in samples that were exposed to air for more than one week. Then calibration curves with calibrants of DMNB in acetone were established for quantitation. The average concentration of DMNB in the headspace was determined to be 125 parts per million (ppm).</p><p><br></p>

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-07-11T12:33:28Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) silas-dissertacao-versao-final-2016.pdf: 1708159 bytes, checksum: 6c0efc5f2f0b27c79306418c9de516f1 (MD5) / Made available in DSpace on 2016-07-11T12:33:28Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) silas-dissertacao-versao-final-2016.pdf: 1708159 bytes, checksum: 6c0efc5f2f0b27c79306418c9de516f1 (MD5) Previous issue date: 2015-02-27 / FACEPE / A extração de conhecimento em ambientes com fluxo contínuo de dados é uma atividade que vem crescendo progressivamente. Diversas são as situações que necessitam desse mecanismo, como o monitoramento do histórico de compras de clientes; a detecção de presença por meio de sensores; ou o monitoramento da temperatura da água. Desta maneira, os algoritmos utilizados para esse fim devem ser atualizados constantemente, buscando adaptar-se às novas instâncias e levando em consideração as restrições computacionais. Quando se trabalha em ambientes com fluxo contínuo de dados, em geral não é recomendável supor que sua distribuição permanecerá estacionária. Diversas mudanças podem ocorrer ao longo do tempo, desencadeando uma situação geralmente conhecida como mudança de conceito (concept drift). Neste trabalho foi realizado um estudo comparativo entre alguns dos principais métodos de detecção de mudanças: ADWIN, DDM, DOF, ECDD, EDDM, PL e STEPD. Para execução dos experimentos foram utilizadas bases artificiais – simulando mudanças abruptas, graduais rápidas, e graduais lentas – e também bases com problemas reais. Os resultados foram analisados baseando-se na precisão, tempo de execução, uso de memória, tempo médio de detecção das mudanças, e quantidade de falsos positivos e negativos. Já os parâmetros dos métodos foram definidos utilizando uma versão adaptada de um algoritmo genético. De acordo com os resultados do teste de Friedman juntamente com Nemenyi, em termos de precisão, DDM se mostrou o método mais eficiente com as bases utilizadas, sendo estatisticamente superior ao DOF e ECDD. Já EDDM foi o método mais rápido e também o mais econômico no uso da memória, sendo superior ao DOF, ECDD, PL e STEPD, em ambos os casos. Conclui-se então que métodos mais sensíveis às detecções de mudanças, e consequentemente mais propensos a alarmes falsos, obtêm melhores resultados quando comparados a métodos menos sensíveis e menos suscetíveis a alarmes falsos. / Knowledge extraction from data streams is an activity that has been progressively receiving an increased demand. Examples of such applications include monitoring purchase history of customers, movement data from sensors, or water temperatures. Thus, algorithms used for this purpose must be constantly updated, trying to adapt to new instances and taking into account computational constraints. When working in environments with a continuous flow of data, there is no guarantee that the distribution of the data will remain stationary. On the contrary, several changes may occur over time, triggering situations commonly known as concept drift. In this work we present a comparative study of some of the main drift detection methods: ADWIN, DDM, DOF, ECDD, EDDM, PL and STEPD. For the execution of the experiments, artificial datasets were used – simulating abrupt, fast gradual, and slow gradual changes – and also datasets with real problems. The results were analyzed based on the accuracy, runtime, memory usage, average time to change detection, and number of false positives and negatives. The parameters of methods were defined using an adapted version of a genetic algorithm. According to the Friedman test with Nemenyi results, in terms of accuracy, DDM was the most efficient method with the datasets used, and statistically superior to DOF and ECDD. EDDM was the fastest method and also the most economical in memory usage, being statistically superior to DOF, ECDD, PL and STEPD, in both cases. It was concluded that more sensitive change detection methods, and therefore more prone to false alarms, achieve better results when compared to less sensitive and less susceptible to false alarms methods.

The deals of thesis were described methods for designing safety applications, made analysis of possible microcontroller faults of long-run system, described software and hardware methods for fault detection in microcontroller and applied some March test to microcontroller. To application were chosen MATS+, PMOVI and March SS tests. These tests were modified to word-oriented memory. Further it was made analysis of modified tests to determination fault coverage, testing times and program memory requirement. To determination of fault coverage was created virtual memory with fault function models. March tests were compared with each other and with another pattern test (checkboard test).

This master’s thesis deals with flame detection methods. The purpose of the project was to create a flame detector, which uses the alternative method of flame detection. The introduction of this thesis gives the summary overview of the existing methods for flame detection. Further, the existing flame detectors and their applications are described. Two alternative algorithms for flame detection which are based on the digital signal analysis were realized on the PC. Flame detector, which utilizes the digital analysis of audio signal, was realized on 8 bit microcontroller Atmega128 and achieved results are presented.

Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to improve integrity and performance of DGs while maintaining multi-DG islanding detection capability. In this thesis, the following questions have been addressed: How to utilize the transient behavior arising from an islanding condition to improve detectability and robust performance of IDMs in a distributive manner? How to reduce the negative stability impact of the well-known Sandia Frequency Shift (SFS) IDM while maintaining its islanding detection capability? How to incorporate the perturbations provided by each of DGs in such a way that the negative interference of different IDMs is minimized without the need of any type of communication among the different DGs? It is shown that the proposed techniques are local, scalable and robust against different loading conditions and topology changes. Also, the proposed techniques can successfully distinguish an islanding condition from other disturbances that may occur in power system networks. This work improves the efficiency, reliability and safety of integrated DGs, which presents a necessary advance toward making electric power grids a smart grid.