L’objectif de ce travail de thèse est d’envisager les apports de l’Emission Acoustique (EA) en tant qu’outil de diagnostic et de surveillance des structures et ouvrages en bois. Nous avons appliqué cet outil et développé des méthodes de suivi de la fissuration. Si l’objectif affiché est l’utilisation de l’EA pour de la surveillance in-situ, un passage par des manipulations en laboratoire a été nécessaire pour valider les méthodes mises en œuvre. Des essais de chargement à déplacement imposé ont été réalisés sur des éprouvettes de Douglas (DCB à inertie constante) soumises à un chargement en mode I, pour deux teneurs en eaux distinctes. En parallèle du système d’acquisition acoustique, un système d’acquisition d’images a été utilisé pour suivre l’évolution de la fissuration sur les faces principales des éprouvettes.Dans un premier temps, nous avons constaté que la cinétique de fissuration était corrélée à l’énergie acoustique des signaux enregistrés. Une écoute globale, sans filtration des données, fournit une indication sur l’évolution de l’endommagement d’une structure.En effectuant un premier traitement des données, en considérant les évènements acoustiques et en utilisant des courbes de correction de localisation et d’amplitude des signaux, nous avons pu déterminer la position d’un (ou plusieurs) pic(s) d’activité acoustique. La courbe d’évolution de la position de ce(s) pic(s) d’activité donne un résultat similaire à celle de la pointe de fissure obtenue avec le système d’imagerie. Nous avons ainsi pu estimer un taux de restitution d’énergie moyen Gc. Dans le but de passer à des applications in situ, nous avons mis en œuvre cette méthode lors d’un essai de fluage sur une éprouvette à inertie variable. L’EA a su prendre le relais lorsque les relevés visuels étaient absents. L’EA a aussi pu fournir des informations complémentaires sur l’initiation et la propagation de la fissuration et ce, sur une durée surveillance longue.La méthode de détection des pics d’activités par EA montre que les évènements acoustiques de forte amplitude sont localisés de part et d’autre de la pointe de fissure obtenue par imagerie. Dans un deuxième temps, en effectuant un parallèle avec les méthodes développées dans les matériaux composites, le bois pouvant y être assimilé par certains aspects, nous avons pu, par une utilisation conjointe des outils statistiques, de l’imagerie électronique (MEB) et de l’analyse des formes d’ondes, identifier les mécanismes de ruine présents lors des essais.Après un travail de filtration des données obtenues sur des essais à mode de ruine choisi (traction, flexion et cisaillement), quatre familles d’évènements ont pu être mis en évidence. Par l’étude de leurs formes d’ondes respectives, ces familles ont pu être associées à de la rupture de fibre, de la fissuration de matrice, de la décohésion et du délaminage telles qu’on les retrouve dans les matériaux composites. L’étude au MEB a confirmé qu’une multitude de mécanismes étaient présents sur les plans de fissuration des éprouvettes et la vraisemblance des résultats obtenus.D’un point de vue quantitatif, deux mécanismes de ruine principaux ressortent : la rupture de fibres et la fissuration matricielle. Il s’agit là d’indicateurs dont l’évolution peut constituer un indicateur, précurseur à la ruine d’un ouvrage. Le travail effectué dans cette thèse constitue un pas dans l’emploi de l’EA dans la surveillance des structures et des ouvrages en bois et laisse entrevoir d’autres emplois notamment en mécanique de la rupture et dans l’étude des zones d’élaboration. / The aim of this thesis is to consider what Acoustic Emission (AE) can provide as a tool for diagnosis and assessment of wood structures and works. We applied this tool and developed methods for tracking crack propagation. If our intention is using AE for the in-situ monitoring, we have to do experiments in laboratory to validate the methods developped. Loading tests under imposed displacement were conducted on Douglas samples (DCB constant inertia) subjected to a loading in mode I, for two levels of moisture content. In tandem of the acoustic emission emission system, an image acquisition system was used to record crack propagation on the main faces of the samples.First, we showed that the cracking kinetics correlates with the acoustic energy of the recorded signals. A global analysis, with unfiltered data, provides a good indication of the evolution of the damage within a structure. Then by performing a first data processing, by taking into account the acoustic events and by using correction curves of localization and amplitude, we were able to determine the position of one (or more) peak(s) of acoustic activity. The evolution curve of the position of this (these) peak(s) of activity gives a result similar of the crack tip evolution obtained with the digital image acquisition system. By this way we were able to estimate an average restoration level of critical energy Gc. In the purpose of making in situ applications, we have implemented this method during a creep test on a specimen with variable inertia. A previously loaded sample was placed to a relative humidity variation - from a humid atmosphere to a dry atmosphere. Only spot measurements of the crack tip position has been made. AE was able to take over when visual statements were absent. AE was also able to provide additional information on the initiation and propagation of cracks over a long term monitoring. The method for detecting peaks of activities by AE shows that acoustic events with high amplitude are located on both side of the crack tip obtained by imaging.Secondly, by comparing with the methods developed in composite materials, wood could be considered as such, we were able, by joint use of statistical tools, electronic imaging (SEM) and analysis of waveforms, to identify failure mechanisms which were present during testing. After processing data obtained on failure specific mode test (tensile, bending and shear), four clusters of events have been highlighted. By studying their respective waveforms and signal caracteristics, these families have been associated with the rupture of fiber, matrix cracking, debonding and delamination such as those found in composites. The study of SEM images made from owr samples has confirmed the presence of a multitude of mechanisms on the cracking path of the wood samples. This confirms the reasonableness of results obtained. From a quantitative perspective, two major failure mechanisms stand out: the breaking of fibers and matrix cracking. The evolution of these indicators may be a precursor to the ruin of a structure.The work undertaken in this thesis is a step in the use of AE in monitoring structures and wooden structures. It suggests other purposes for the use of AE in wood. We could imaging using AE in order to study the process zones by using mTDCB samples.

The main purpose of thesis is creation and evaluation of models for change detection of arable land to grassland by Hybrid-based Change Detection method, which combined approaches based on the Vegetation Indices, Image Differencing and Principal Component Analysis. Six locations with different seasonal configuration of images with high resolution and one locality covered by image with very high resolution were used. The areas were spread across the foothill areas of the Czech Republic. The selection of predictors and the most suitable model was supported by statistical calculation. Application selected models were carried out using a multi-temporal object classification and their accuracy were verified using reference data. The benefit of this thesis is finding generally applicable model useful to investigate the land cover change and evaluation of the potentially most appropriate seasonal configuration of images. Valuable is also methodology in this thesis which focus on selection of predictors and calculation the order of the most appropriate models, which is unique in the available literature. The thesis provides useful findings fitting to insufficiently explored issue of Change Detection arable land to grassland. Powered by TCPDF (www.tcpdf.org)

This thesis is concerned with data analysis, especially with principal component analysis and its sparse modi cation (SPCA), which is NP-hard-to- solve. SPCA problem can be recast into the regression framework in which spar- sity is usually induced with ℓ1-penalty. In the thesis, we propose to use iteratively reweighted ℓ2-penalty instead of the aforementioned ℓ1-approach. We compare the resulting algorithm with several well-known approaches to SPCA using both simulation study and interesting practical example in which we analyze voting re- cords of the Parliament of the Czech Republic. We show experimentally that the proposed algorithm outperforms the other considered algorithms. We also prove convergence of both the proposed algorithm and the original regression-based approach to PCA. vi

Magister Scientiae - MSc / Many hydrocarbon reservoirs are situated in barren sequences that display poor stratigraphic control. Correlation between the wells can become extremely difficult and traditional correlation techniques can prove to be inadequate. Past studies have shown that trace and major element concentrations can be used as a correlation tool. This practice of using geochemical fingerprints to characterize between wells is called Chemostratigraphic analysis. (Pearce et al, 1999) Chemostratigraphy has been recognized as a very important correlation technique as it can be used for rocks of any age, in any geological setting as well as sequences that are traditionally defined as barren. Chemostratigraphic analyses can be used as a means of getting rid of ambiguities within data produced by traditional correlation methods such as Biostratigraphy, Lithostratigraphy and Geophysical Logging. In areas where stratigraphic data is not available it can be used to construct correlation frameworks for the sequences found in the area. The motivation behind this study is that the research is not only worthy of academic investigation, but can also provide the industry with new insights into areas that were previously misunderstood because traditional correlation methods were not adequate. The study area, the Orange basin, is located offshore South Africa and is largely underexplored. The basin, that hosts two gas field namely the Ibhubesi and the Kudu gas fields, has large potential but in the past has not been given due attention with only 34 wells being drilled in the area. The Orange basin has recently been the topic of investigation because of the belief that it may be hosts to more hydrocarbons. This study will utilise Chemostratigraphy to attempt to provide geological information on this relatively under-explored basin. The aim of this research study is to produce a chemostratigraphic framework -scheme for the Orange Basin in order to facilitate reservoir scale interwell correlation. The Objectives of this research study will be to identify chemostratigraphic units or indices, to prove the adequate use of chemostratigraphy as an independent correlation technique and to integrate the chemostratigraphy and petrophysical characteristics of the four wells to facilitate lithological identification. / South Africa

This thesis aims to identify main driving market risk factors of different strategies implemented by hedge funds by looking at correlation coefficients, implementing Principal Component Analysis and analyzing "loadings" for first three principal components, which explain the largest portion of the variation of hedge funds' returns. In the next step, a stepwise regression through iteration process includes and excludes market risk factors for each strategy, searching for the combination of risk factors which will offer a model with the best "fit", based on The Akaike Information Criterion - AIC and Bayesian Information Criterion - BIC. Lastly, to avoid counterfeit results and overcome model uncertainty issues a Bayesian Model Average - BMA approach was taken. Key words: Hedge Funds, hedge funds' strategies, market risk, principal component analysis, stepwise regression, Akaike Information Criterion, Bayesian Information Criterion, Bayesian Model Averaging Author's e-mail: aleksaradosavcevic@gmail.com Supervisor's e-mail: mp.princ@seznam.cz

La prospection géoélectrique est largement utilisée au Maroc pour des reconnaissances hydrogéologique. Le but de ce travail et de proposer de nouvelles techniques d’interprétation des sondages électriques verticaux en un temps réduit, et aussi de bien exploiter une base de données de sondages électriques, par l’établissement entre autre des images 2D horizontales et verticales de l’estimation de la distribution des résistivités électriques apparentes (modélisation géostatistique, inversion, etc.). Dans le but de caractériser électriquement le secteur d’étude (nord-est du Bassin de Saïss), une analyse statistique des résistivités apparentes de sondages électriques verticaux a été réalisée. Cette simple analyse descriptive est suivie par une étude statistique multidirectionnelle : analyse en composantes principales (ACP) et par une classification hiérarchique ascendante (CHA). (...) Les résultats des analyses statistiques et géostatistiques complétés par les inversions des sondages moyens pas classe, ont mis en évidence la fiabilité de ces techniques pour l’interprétation d’un nombre important de sondages électriques au lieu de la méthode ordinaire qui se base sur l’inversion des sondages un par un et les corréler ultérieurement pour construire la structure globale du domaine étudié. Avec les techniques utilisées, dans le cadre de ce travail, des résultats très satisfaisants en un temps plus réduit sont obtenus. Les profils étudiés et inversés à l’aide du logiciel RES2Dinv montrent tous les trois grandes structures définies auparavant (Résistant-Conductrice-Résistant), par contre on note des variations intra formations. De plus, l’organisation spatiale des formations permet de confirmer l’existence de failles cohérentes avec la structure en horst et graben du bassin. / The Geoelectric prospection is usually used in Morocco for hydrogeological recognition. The purpose of this work is to propose new techniques for interpreting vertical electric soundings in a reduced time, and also to fully exploit a database of stored electrical soundings by the establishment, amongst other things, of the horizontal and vertical 2D images, estimating the distribution of apparent electrical resistivity (geostatistic modeling, inversion, etc.). In order to characterize electrically the study area (north-east of the Saïss Basin), a statistical analysis of apparent resistivity of vertical electric soundings was performed. This simple descriptive analysis is followed by a statistical analysis (principal component analysis PCA and ascending hierarchical classification HAC.) (...)The results of statistical analysis and geostatistical supplemented by inversion of the average electric sounding per class, highlighted the reliability of these techniques to the interpretation of a large number of electrical soundings instead of the usual method which is based on the inversion of the electrical sounding one by one and correlate them later, to build the global structure of the area studied. With the techniques used in this work, very satisfactory results in a more reduced time, for interpreting vertical electric soundings, are obtained. VIThe studied profiles and inverted using the software RES2Dinv show all three structures defined previously (Resistant – Conductive - resistant), on the other hand, there are variations within the same formation. In addition, the spatial organization of the formation makes it possible to confirm the existence of faults coherent with the structure in horst and graben basin.

The feasibility of FTIR-based spectroscopy as a tool to measure cellular response to therapeutics was investigated. Fourier transform mid-infrared spectroscopy has been used in conjunction with multivariate analysis (MVA) to assess the chemistry of many clinically relevant biological materials; however, the technique has not yet found its place in a clinical setting. One issue that has held the technique back is due to the spectral distortions caused by resonant Mie scattering (RMieS), which affects the ability to confidently assign molecular assignments to the spectral signals from biomaterials. In the light of recently improved understanding of RMieS, resulting in a novel correction algorithm, the analytical robustness of corrected FTIR spectra was validated against multi-discipline methods to characterise a set of renal cell lines which were selected for their difference in morphology.After validation of the FTIR methodology by discriminating different cell lines, the second stage of analyses tested the sensitivity of FTIR technique by determining if discrete chemical differences could be highlighted within a cell population of the same origin. The renal carcinoma cell line 2245R contains a sub-population to contain a sub-population of cells displaying 'stem-cell like' properties. These stem-like cells, however, are difficult to isolate and characterise by conventional '-omic' means. Finally, cellular response to chemotherapeutics was investigated using the established renal cell lines CAKI-2 and A-498. For the model, 5-fluorouracil (5FU), an established chemotherapeutic agent with known mechanisms of action was used. Novel gold-based therapeutic compounds were also assessed in parallel to determine their efficacy against renal cell carcinoma. The novel compounds displayed initial activity, as the FTIR evidence suggested compounds were able to enter the cells in the first instance, evoking a cellular response. The long-term performance, tracked with standard proliferation assays and FTIR spectroscopy in the renal cancer cell model, however, was poor. Rather than dismissing the compounds as in-active, the compounds may simply be more effective in cancer cell types of a different nature. The FTIR-based evidence provided the means to suggest such a conclusion. Overall, the initial results suggest that the combination of FTIR and MVA, in the presence of the novel RMieS-EMSC algorithm can detect differences in cellular response to chemotherapeutics. The results were also in-line with complimentary biological-based techniques, demonstrating the powerful potential of the technique as a promising drug screening tool.

For multivariate data, when testing homogeneity of covariance matrices arising from two or more groups, Bartlett's (1937) modified likelihood ratio test statistic is appropriate to use under the null hypothesis of equal covariance matrices where the null distribution of the test statistic is based on the restrictive assumption of normality. Zhang and Boos (1992) provide a pooled bootstrap approach when the data cannot be assumed to be normally distributed. We give three alternative bootstrap techniques to testing homogeneity of covariance matrices when it is both inappropriate to pool the data into one single population as in the pooled bootstrap procedure and when the data are not normally distributed. We further show that our alternative bootstrap methodology can be extended to testing Flury's (1988) hierarchy of covariance structure models. Where deviations from normality exist, we show, by simulation, that the normal theory log-likelihood ratio test statistic is less viable compared with our bootstrap methodology. For functional data, Ramsay and Silverman (2005) and Lee et al (2002) together provide four computational techniques for functional principal component analysis (PCA) followed by covariance structure estimation. When the smoothing method for smoothing individual profiles is based on using least squares cubic B-splines or regression splines, we find that the ensuing covariance matrix estimate suffers from loss of dimensionality. We show that ridge regression can be used to resolve this problem, but only for the discretisation and numerical quadrature approaches to estimation, and that choice of a suitable ridge parameter is not arbitrary. We further show the unsuitability of regression splines when deciding on the optimal degree of smoothing to apply to individual profiles. To gain insight into smoothing parameter choice for functional data, we compare kernel and spline approaches to smoothing individual profiles in a nonparametric regression context. Our simulation results justify a kernel approach using a new criterion based on predicted squared error. We also show by simulation that, when taking account of correlation, a kernel approach using a generalized cross validatory type criterion performs well. These data-based methods for selecting the smoothing parameter are illustrated prior to a functional PCA on a real data set.

Atualmente, o ambiente industrial é caracterizado pela intensa globalização, competição entre cadeias de suprimentos, manutenção das competências centrais e terceirização dos demais serviços. Desta forma, a gestão das relações entre os agentes independentes da cadeia de suprimentos e do processo de aquisição são fatores potenciais para o aumento da competitividade empresarial. No contexto da construção civil, a seleção adequada dos parceiros de negócios é um elemento fundamental para o sucesso dos projetos, uma vez que uma grande proporção das atividades podem ser sub-contratadas e possuem relação de precedência entre si. Os suprimentos representam um percentual significativo dos custos das construções, 60%, dado que demonstra o potencial de lucratividade passível de ser atingida ao estruturar o processo de seleção de fornecedores na construção civil. Seleções baseadas no preço prejudicam os sub-empreiteiros e fornecedores mais responsáveis na concorrência, contribuindo para a queda do nível de desempenho e redução da eficiência global do projeto, uma vez que as ineficiências são somadas ao longo da cadeia. Através da estruturação do processo de seleção de fornecedores, é possível mitigar os riscos de suprimentos oriundos de falhas destes contratados ao longo da relação. O objetivo deste trabalho foi desenvolver uma sistemática para seleção de fornecedores críticos, considerando diversos critérios além do preço, entre qualitativos e quantitativos. A abordagem visa também, a eliminação da subjetividade do processo e a extração do melhor fornecedor de forma objetiva. Para tanto, foram definidas dimensões competitivas para avaliar os fornecedores e posteriormente foram utilizados dois métodos quantitativos, Teoria dos Conjuntos Difusos (TCD) e Análise de Componentes Principais (ACP), para selecionar o melhor fornecedor dentre as alternativas, com base na avaliação de múltiplos agentes. / Currently, the industrial environment is characterized by intense globalization, competition between supply chains, maintenance of core competencies and outsourcing of other services. Thus, the management of relationships between independent agents of the supply chain and the procurement process are potential factors for increasing enterprise competitiveness. In the construction context, the proper selection of business partners is a key element for the success of projects, since a large proportion of the activities can be sub-contracted and have precedence relationship between them. Supplies represent a significant percentage of the cost of buildings, 60%, information that demonstrates the potential of profitability that can be achieved by structuring the process of supplier selection in the construction industry. Selection based on price take off from competition the sub-contractors and suppliers more responsible, contributing to the decline in the level of performance and reduction in the overall project efficiency, since inefficiencies are summed through the chain. By structuring the supplier selection process, it is possible to mitigate the supply risk arising from failures of these suppliers during the relationship. The objective of this study was to develop a systematic for selection of critical suppliers, considering several criteria other than price, among qualitative and quantitative. The approach also aims at eliminating the subjectivity of the process and the extraction of the best supplier in an objective way. In order to that, competitive dimensions were set to evaluate vendors and subsequently two quantitative methods, Fuzzy Sets Theory (FST) and Principal Component Analysis (PCA) were used to select the best supplier among the alternatives based on multiple agents evaluation.

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