Orientador: Marcia Miguel Castro Ferreira / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-10T22:13:52Z (GMT). No. of bitstreams: 1 Ribeiro_FabianaAlvesdeLima_D.pdf: 3726334 bytes, checksum: 73ef285be301366b14be78adce7c034e (MD5) Previous issue date: 2007 / Resumo: Imagens são utilizadas na investigação científica há muito tempo, inicialmente apenas como ferramentas para a representação da prática científica, e após o surgimento das técnicas de microscopia, como instrumento para registro e análise instrumental. Com o aperfeiçoamento das técnicas de obtenção de imagens, cresceu a demanda por técnicas quantitativas e sistematizadas para extrair-lhes informações, e capazes de estabelecer critérios estatisticamente confiáveis para, por exemplo, detectar similaridades, padrões, classificar, e até mesmo gerar modelos preditivos. Neste trabalho, métodos quimiométricos foram utilizados como ferramenta quantitativa para a análise de imagens nível de cinza, utilizando como exemplos imagens de microscopia de força atômica de fibras capilares de diferentes classes. Fibras capilares são frequentemente utilizadas em clínicas, indústrias ambientais e análises forenses, para o diagnóstico de doenças, avaliação da exposição aos agentes tóxicos e poluentes e detecção de abuso de drogas. Para este trabalho foram utilizados dois conjuntos de dados: um deles formado por amostras de fibras caucasianas submetidas ao tratamento de descoloração e outro com fibras de diferentes etnias. O objetivo foi utilizar métodos quimiométricos para construir modelos classificatórios capazes de identificar corretamente novas imagens. Diversas estratégias foram testadas e os melhores resultados foram obtidos utilizando os métodos SIMCA (Soft Independent Modeling of Class Analogy), PARAFAC (Parallel Factor Analysis), MPCA (Multi-way Principal Component Analysis) e NPLS (Multi-way Partial Least Squares). Os modelos quantitativos apresentaram erros de calibração abaixo de 10% e erros de predição em torno de 10%. Com exceção de uma das aplicações, que é específica para fibras capilares, os outros métodos de análise de imagens propostos podem ser utilizados na análise quantitativa de qualquer tipo de imagem nível de cinza / Abstract: Images have been used in scientific investigation for a long time, initially as a tool for representation of the scientific practice and, after the microscopy development, as an instrument for registration and instrumental analysis. With the improvement of microscopic techniques, there was an increase on the demand for quantitative and systematic tools to extract relevant information from images and for techniques capable to establish reliable statistical approaches, for example, to detect similarities, patterns and for classification. In this work, multivariate methods were used as quantitative tools for the analysis of nível de cinza images of different classes of hair fibers. These images were obtained by atomic force microscopy. Hair fibers are frequently used in medical clinics, environmental industries and forensic analyses, for the diagnosis of diseases, evaluation of the exposure to toxic agents and pollutants, and detection of abuse of drugs. In this work two data sets were used: the first one contained caucasian hair fibers submitted to peroxide treatment and the second one contained fibers from different ethnic origin (oriental, african and caucasian). The goal was to use chemometric methods to build classification models capable to identify new images correctly. Several strategies were tested and the best results were obtained by using SIMCA (Soft Independent Modeling of Class Analogy), PARAFAC (Parallel Factor Analysis), MPCA (Multi-way Principal Component Analysis) and NPLS (Multi-way Partial Least Squares). The models presented calibration errors below 10% and prediction errors around 10 %. With exception of the descriptor analysis, which is specific for hair fibers images, the proposed methods can be useful for quantitative analysis of any kind of nível de cinza images / Doutorado / Físico-Química / Doutor em Ciências

Videoconferencing is increasingly becoming a trend worldwide in applications where clients need to access lectures, meeting proceedings, communicating with family and friends etc. It provides a platform enabling the visual, audio and video communication between clients. The aim of this project is to utilize the open source Java software to build a desktop application enabling communication between clients. When a user needs to transfer a secured file, it’s unsafe to send it using social networking sites because of lack of security. So, with the “Multi-Way Communication System” (MWCS) we resolve some security issues. The MWCS is a highly secure way for file transfer, text and video conferencing.

En esta Tesis Doctoral, se aborda la aplicación de metodologías de análisis de datos de múltiples vías, a datos tridimensionales de fluorescencia molecular de excitación-emisión obtenidos a lo largo de una reacción, para obtener de forma rápida información de interés en el desarrollo de técnicas basadas en procesos de eliminación oxidativa de contaminantes orgánicos. Se afrontan dos casos en particular: la foto-degradación de una mezcla de hidrocarburos policíclicos aromáticos (benzo[a]antraceno, benzo[a]pireno, benzo[k]fluoranteno, dibenzo[a,h]antraceno)y la foto-catálisis del fenol. Los espectros de fluorescencia de excitación y emisión registrados para cada muestra analizada constituyen una matriz o datos de segundo orden. Información cualitativa y cuantitativa acerca de las especies que participan en los procesos en estudio se ha extraido trabajando con métodos de análisis multivariante, que permiten analizar datos de múltiples vías como son el método de resolución de curvas basado en el análisis de factores paralelo (PARAFAC)yelbasadoenlaoptimizaciónpormínimoscuadrados(M CR -ALS),asícomoel método de calibración multivariante en mínimos cuadrados parciales para datos de múltiples vías (N -PLS). En la Tesis doctoral se realiza un análisis comparativo de los resultados encontrados por lo diferentes métodos de análisis multivariante. Los resultados encontrados fueron validados al comparar los resultados con los obtenidos cuando el seguimiento cuantitativo se realizaba mediante cromatografía líquida de alta resolución (H PLC), considerada como técnica de referencia para el seguimiento de este tipo de reacciones. La rapidez que aportan estas metodologías es una característica valiosa en estudios de optimización de dichos procesos. En esta Tesis empleando estas metodologías para el cálculo de constantes cinéticas se ha abordado el análisis simultáneo, empleando técnicas de diseño de experimentos, de variables de interés en el desarrollo de los procesos de foto-degradación. Del estudio realizado se derivan los siguientes resultados: *En la foto-degradación de una mezcla de hidrocarburos poli cíclicos aromáticos se evidenció la interacción de las variables experimentales y la importancia del análisis conjunto de sus efectos sobre el proceso para la selección de las condiciones óptimas de trabajo. En el dominio experimental en estudio, se encontró que la degradación es más rápida cuando se trabaja a pH ácido utilizando etanol como solvente e irradiando con una lámpara de baja presión de mercurio. *Tanto al aplicar PARAFAC como M CR -ALS el número de factores significativos fue de cuatro, uno por cada analito presente en la muestra. La bondad de los espectros recuperados en ambos casos fue evaluada calculando el coeficiente de similitud que resultó tener valor superior a 0.98 en todas las situaciones. Cuando los valores de concentración obtenidosenelprocesodedegradaciónmediantePARAFACoM CR -ALSaplicadosadatos EEM fueron representados frente a los obtenidos mediante H PLC se obtuvo una línea de regresión mediante mínimos cuadrados, con pendiente próxima a 1 e intercesión en el origen próxima a 0. El test conjunto de la pendiente y la ordenada en el origen para corroborar la ausencia de sesgo fue superado para todos los analitos. *En la determinación del fenol y sus dihidroxiderivados el error de predicción global tanto para PARAFAC como para M CR -ALS, era admisible y de ello se concluye que es posible realizar un seguimiento rápido y cuantitativo de la concentración del fenol y de la concentración de sus intermediarios, catecol, resorcinol e hidroquinona en un proceso de foto-degradación a partir de sus espectros fluorescentes de excitación-emisión. *El fenol y la hidroquinona se resuelven perfectamente y se obtienen errores bajos a los diferentes niveles de concentración analizados, mientras que catecol y el resorcinol que están fuertemente solapados presentan errores significativamente mayores. * Con el propósito de analizar si los errores encontrados fundamentalmente para el catecol y resorcinol eran susceptibles de mejora, se trabajó con mínimos cuadrados parciales para datos de múltiples vías (N -PLS), en particular tri-PLS1. Los valores encontrados de aplicar este método y los anteriormente descritos a un nuevo conjunto de mezclas representativas del proceso en estudio fueron comparados en términos del error global cometido. *El análisis de los efectos de las variables implicadas en el proceso de degradación en estudio:tipo de catalizador, pH del medio y concentración del sustrato en la constante de velocidad de la reacción permitió concluir que todas ellas interaccionan entre sí y la importancia de sus efectos resultó significativa a un nivel de confianza del 95% cuando se realizó un test estadístico A N O V A . A partir de los resultados encontrados en el desarrollo de esta Tesis, hemos corroborado que la utilización conjunta de la espectrofluorimetría de EEM y la aplicación de diferentes métodos de análisis de datos de múltiples vías, es una opción válida y atractiva para la monitorización cuantitativa de la foto-degradación de una mezcla de hidrocarburos policíclicos aromáticos y de la evolución de la degradación foto-catalítica del fenol y sus intermediarios, así como para el análisis cinético de los procesos estudiados .

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Data is distributed across interconnected relations in relational databases. Relationships between tuples can be rearranged in distinct relations by matching the values of the join attribute, a process called equi-join operation. Unlike standard attempts to design efficient join algorithms in this thesis, an approach is proposed to align tuples in relation so that joins can be readily and effectively done. We position tuples in their respective relationships, called relations alignment, which has matching join attribute values in the corresponding positions. We also address how to align relations and perform joins on aligned relations. The experiments were conducted in this research to measure and analyze the efficiency of the proposed approach compared to standard MySQL joins.

In this thesis, a novel iterative receiver and its improved version are proposed for relay-assisted multiuser communications, in which multiple users transmit to a destination with the help of a relay and using fast frequency-hopping modulation. Each user employs a channel encoder to protect its information and facilitate interference cancellation at the receiver. The signal received at the relay is either amplified, or partially decoded with a simple energy detector, before being forwarded to the destination. Under flat Rayleigh fading channels, the receiver at the destination can be implemented non-coherently, i.e., it does not require the instantaneous channel information to demodulate the users’ transmitted signals. The proposed iterative algorithm at the destination exploits the soft outputs of the channel decoders to successively extract the maximum likelihood symbols of the users and perform interference cancellation. The iterative method is successfully applied for both cases of amplify-and-forward and partial decode-and-forward relaying. The error performance of the proposed iterative receiver is investigated by computer simulation. Under the same spectral efficiency, simulation results demonstrate the excellent performance of the proposed receiver when compared to the performance of decoding without interference cancellation as well as the performance of the maximum likelihood multiuser detection previously developed for uncoded transmission. Simulation results also suggest that a proper selection of channel coding schemes can help to support significant more users without consuming extra system resources. In addition, to further enhance the receiver’s performance in terms of the bit error rate, an improved version of the iterative receiver is presented. Such an improved receiver invokes inner-loop iterations between the channel decoders and the demappers in such a way that the soft outputs of the channel decoders are also used to refine the outputs of the demappers for every outer-loop iteration. Simulation results indicate a performance gain of about 2.5dB by using the two-loop receiver when compared to the performance of the first proposed receiver.

The master's thesis deals with a theoretical analysis of properties of a multi-way wheelframe and a selection of an appropriate method for the human operator control. Based on the analysis will be designed hardware and software of the control unit for controlling the movement of the robot's multi-way wheelframe. The electronic system will ensure a real-time processing the operator's instructions to control signals for the motors that will drive and implement the required angles of two driven wheels of the chassis. The proposal also reflects a sufficient equipment with input-output channels for any subsequent extension of additional sensors for testing the autonomous robot operation.

Submitted by Erika Demachki (erikademachki@gmail.com) on 2014-12-29T15:33:04Z No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Anderson Rogério Cunha - 2014.pdf: 4853685 bytes, checksum: d50cf557f1a067a91c2034443ee62df2 (MD5) / Approved for entry into archive by Erika Demachki (erikademachki@gmail.com) on 2014-12-29T15:39:23Z (GMT) No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Anderson Rogério Cunha - 2014.pdf: 4853685 bytes, checksum: d50cf557f1a067a91c2034443ee62df2 (MD5) / Made available in DSpace on 2014-12-29T15:39:23Z (GMT). No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Anderson Rogério Cunha - 2014.pdf: 4853685 bytes, checksum: d50cf557f1a067a91c2034443ee62df2 (MD5) Previous issue date: 2014-02-19 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Spatial join is one of the spatial operations of higher computational cost. Its complexity increases significantly when it involves multiple databases (multi-way spatial join). Traditional processing strategies of multi-way spatial join apply combinations of binary join algorithms on centralized computing environments. For complex queries, this approach requires much computational power, making it often unfeasible in centralized environments. This work proposes the Distributed Synchronous Traversal algorithm (DST), whose goal is to enable the distributed processing of multi-way spatial joins on a cluster of computers. The DST algorithm is based on Synchronous Traversal algorithm and processes the multiway spatial join in a single synchronous descent upon R-Trees levels of the database entries (the final outcome is built incrementally, without creating temporary databases). To the best of our knowledge, there are no other proposals in the literature that deal with this problem in a distributed fashion and on a peer-to-peer architecture. Many challenges had to be overcome, such as the definition of data structures that enabled the mapping of the semantics of queries of multi-way spatial join and coordination of the required distributed processing. DST proved to be satisfactorily parallelizable and scalable process real datasets in experiments performed in clusters of 1, 2, 4 and 8 servers. / A junção espacial (Spatial Join) é uma das operações espaciais de maior custo computacional. Sua complexidade aumenta significativamente quando envolve múltiplas bases de dados (multi-way spatial join). Estratégias tradicionais de processamento do multi-way spatial join aplicam combinações de algoritmos de junção binária sobre ambientes computacionais centralizados. Em consultas complexas, esse tipo de abordagem exige grande capacidade computacional muitas vezes inviável em ambientes centralizados. Neste trabalho é proposto o algoritmo Distributed Synchronous Traversal (DST), cujo objetivo é tornar viável a execução distribuída do multi-way spatial join em um cluster de computadores. O DST se baseia no algoritmo Synchronous Traversal e processa o multiway spatial join em uma única descida síncrona sobre os níveis das R-Trees das bases de dados de entrada. O resultado final é construído incrementalmente, sem a consolidação de dados intermediários. Até onde conhecemos, não há outras propostas na literatura para multi-way spatial join distribuído sobre uma arquitetura peer-to-peer. Muitos desafios tiveram que ser superados, como a definição de estruturas de dados que possibilitassem o mapeamento da semântica das consultas de multi-way spatial join e a coordenação do processamento distribuído das mesmas. O DST se mostrou satisfatoriamente paralelizável e escalável ao processar bases de dados reais em clusters de até 8 servidores.

Une Interface Cerveau-Machine (ICM) est un système permettant de transformer l'activité neurale du cerveau en une commande d'effecteurs externes. Cette étude correspond à une étape vers une ICM totalement autonome fonctionnant dans un environnement naturel ce qui est d'une importance cruciale pour les futures applications cliniques d'une ICM. Pour représenter l'environnement naturel, des expériences avec une ICM binaire asynchrone ont été réalisées avec des animaux libres de se mouvoir. En comparaison avec les études précédentes, des expériences sur le long terme ont été réalisées, ce qui est plus conforme aux exigences des applications de la vie réelle. L'objectif principal de cette étude est de différencier le modèle spécifique neuronal lié à l'intention d'action de l'activité de fond du cerveau chez des animaux libres de tous mouvements. Pour atteindre le niveau nécessaire de sélectivité, l'analyse Multi-Voies PLS a été choisie sachant qu'elle fournit simultanément un traitement du signal dans plusieurs domaines, à savoir, temporel, fréquentiel et spatial. Pour améliorer la capacité de l'approche générique Multi-Voies PLS pour le traitement de données à grandes dimensions, l'algorithme « Itérative NPLS » est introduit dans notre travail. En ayant des besoins plus faibles en mémoire, cet algorithme fournit des traitements de grands ensembles de données, permet une résolution élevée, préserve l'exactitude de l'algorithme générique et démontre une meilleure robustesse. Pour la calibration adaptative d'un système ICM, l'algorithme récursif NPLS est proposé. Finalement, l'algorithme pénalisé NPLS est développé pour la sélection efficace d'un sous-ensemble de fonctions, à savoir, un sous-ensemble d'électrodes. Les algorithmes proposés ont été testés sur des ensembles de données artificielles et réelles. Ils ont démontré une performance qui est comparable à celle d'un algorithme générique NPLS. Leur efficacité de calcul est acceptable pour les applications en temps réel. Les algorithmes développés ont été appliqués à la calibration d'un système ICM et ont été utilisés dans des expériences d'ICM avec bouclage en temps réel chez des animaux. Enfin, les méthodes proposées représentent une approche prospective pour de futurs développements de systèmes ICM humains. / Brain Computer Interface (BCI) is a system for translation of brain neural activity into commands for external devices. This study was undertaken as a step toward the fully autonomous (self-paced) BCI functioning in natural environment which is of crucial importance for BCI clinical applications. To model the natural environment binary self-paced BCI experiments were carried out in freely moving animals. In comparison to the previous works, the long-term experimental sessions were carried out, which better comply with the real-life applications requirements. The main goal of the study was to discriminate the specific neuronal pattern related to the animal's control action against background brain activity of freely-moving animal. To achieve the necessary level of selectivity the Multi-Way Analysis was chosen since it provides a simultaneous signal processing in several domains, namely, temporal, frequency and spatial. To improve the capacity of the generic Multy-Way PLS approach for treatment of high-dimensional data, the Iterative NPLS algorithm is introduced in the current study. Having lower memory requirements it provides huge datasets treatment, allows high resolution, preserves the accuracy of the generic algorithm, and demonstrates better robustness. For adaptive calibration of BCI system the Recursive NPLS algorithm is proposed. Finally, the Penalized NPLS algorithm is developed for effective selection of feature subsets, namely, for subset of electrodes. The proposed algorithms were tested on artificial and real datasets. They demonstrated performance which either suppress or is comparable with one of the generic NPLS algorithm. Their computational efficiency is acceptable for the real-time applications. Developed algorithms were applied for calibration of the BCI system and were used in the real-time close-loop binary BCI experiments in animals. The proposed methods represent a prospective approach for further development of a human BCI system.

Orientador: Ronei Jesus Poppi / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-22T08:18:21Z (GMT). No. of bitstreams: 1 Avila_ThiagoCarvalhode_M.pdf: 7831860 bytes, checksum: 010f2295e00f097a9ecfaf3f498a7069 (MD5) Previous issue date: 2013 / Resumo: Este trabalho visou o uso de Espectroscopia Raman e de Quimiometria para monitoramento e controle da fermentação de glicose por Saccharomyces cerevisiae. Na primeira etapa, foi utilizada calibração multivariada baseada no método dos Mínimos Quadrados Parciais (PLS) para quantificação de glicose, etanol, glicerol, ácido acético e células. Os modelos foram desenvolvidos baseados nos valores de concentração obtidos pelos métodos de referência, cromatografia líquida de alta eficiência ¿ HPLC e espectrofotometria UV/Vis. Tanto na etapa de calibração quanto na de validação, a otimização foi realizada com eliminação de amostras anômalas, baseada nos valores de leverage, resíduos e escores. Na segunda etapa, cartas de controle multivariadas foram usadas para identificação de falhas em bateladas durante o processo de fermentação. Foram construídos modelos MPCA (Análise de Componentes Principais Multimodo) a partir de bateladas NOC (Condições Normais de Operação). As cartas de controle multivariadas foram aplicadas em dois modos de desdobramento dos dados obtidos durante o monitoramento, um preservando a direção das bateladas e outro a direção do tempo. As falhas estudadas foram temperatura, mudança no substrato e contaminação do sistema. No modo de desdobramento por bateladas, a carta de controle Q foi eficiente para detecção das falhas estudas, fato comprovado pela classificação correta de três bateladas NOC como dentro de controle. No entanto, a carta de controle T2 não foi capaz de identificar as falhas estudadas corretamente como fora de controle. O modo de desdobramento pelo tempo também apresentou classificações corretas das falhas estudadas / Abstract: This work aims the use of Raman Spectroscopy and Chemometrics in the monitoring and control in the fermentation of the glucose by Saccharomyces cerevisiae. In the first step, it was applied the multivariate calibration based on Partial Least Squares (PLS) for the quantification of glucose, ethanol, glycerol, acetic acid and cells. The developed of calibration models was performed against the concentration values obtained by the reference methods, High Performance Liquid Chromatography and UV/Vis spectrophotometer. The optimization of the calibration and validation steps, the elimination of outliers was performed based on the values of leverage, residues and scores. In the second step, multivariate control charts were used for identification of batch-fault during the fermentation process. Multi-way Principal Component Analysis (MPCA) models were developed from batch NOC (Normal Operation Conditions). The multivariate control charts were based on two modes of unfolding the multi-way data, obtained during monitoring, one preserving the direction of the batch and another the direction of time. The fault studied were temperature, changes in the substrate and contamination of the system. In unfolding batch mode, the chart Q was effective for detection of the faults studied, proven by the correctly classification of 3 NOC batches as in control. However, the chart T2 failed to identify faults studied. The unfolding in time mode, also presented correct classifications of the faults studied / Mestrado / Quimica Analitica / Mestre em Química