Visible and near-infrared diffuse reflectance spectroscopy has been demonstrated to be a fast and cheap tool for estimating a large number of chemical and physical soil properties, and effective features extracted from spectra are crucial to correlating with these properties. We adopt a novel methodology for feature extraction of soil spectroscopy based on fractal geometry. The spectrum can be divided into multiple segments with different step–window pairs. For each segmented spectral curve, the fractal dimension value was calculated using variation estimators with power indices 0.5, 1.0 and 2.0. Thus, the fractal feature can be generated by multiplying the fractal dimension value with spectral energy. To assess and compare the performance of new generated features, we took advantage of organic soil samples from the large-scale European Land Use/Land Cover Area Frame Survey (LUCAS). Gradient-boosting regression models built using XGBoost library with soil spectral library were developed to estimate N, pH and soil organic carbon (SOC) contents. Features generated by a variogram estimator performed better than two other estimators and the principal component analysis (PCA). The estimation results for SOC were coefficient of determination (R2) = 0.85, root mean square error (RMSE) = 56.7 g/kg, the ratio of percent deviation (RPD) = 2.59; for pH: R2 = 0.82, RMSE = 0.49 g/kg, RPD = 2.31; and for N: R2 = 0.77, RMSE = 3.01 g/kg, RPD = 2.09. Even better results could be achieved when fractal features were combined with PCA components. Fractal features generated by the proposed method can improve estimation accuracies of soil properties and simultaneously maintain the original spectral curve shape.

Les agrégats de suie émis par les processus de combustion dans les turbines aéronautiques contribuent à modifier le bilan radiatif de l'atmosphère et la qualité de l'air. La connaissance de leurs caractéristiques physiques et chimiques est indispensable pour évaluer leur rôle dans les processus physico-chimiques atmosphériques et leur impact sur l'environnement et la santé publique. Dans ce contexte, notre étude vise à déterminer la taille et la morphologie d'agrégats de suie aéronautique à partir de mesures expérimentales menées en microscopie électronique en transmission (MET) et en tomographie électronique.Nous avons réalisé des clichés MET d'agrégats de suie émis par des turboréacteurs aéronautiques. Nous avons établi une méthode pour caractériser la morphologie des agrégats en déterminant leur allongement, leur compacité et la tortuosité de leur contour en analysant leur projection. Nous avons également développé un logiciel de traitement et d'analyse des images MET qui permet de reconstruire en 3D un agrégat à partir de ses projections et l'analyse de ses caractéristiques dimensionnelles et morphologiques à partir de sa reconstruction. Les résultats obtenus nous ont permis d'étudier la validité des relations liant les caractéristiques microphysiques 2D et 3D proposées dans la littérature et d'en proposer de nouvelles pour les agrégats étudiés.Ces résultats constituent la première caractérisation morphologique 3D d'agrégats de suie aéronautique à partir d'analyses par MET et tomographie électronique. Ils montrent que les propriétés morphologiques de ces agrégats ne permettent pas d'utiliser la méthode d'ensemble pour déterminer la dimension fractale massique. / Soot aggregates emitted by aircraft engines' combustion processes are involved in the modification of the global radiative budget and the air quality. The knowledge of their physical and chemical characteristics is a prerequisite to any evaluation of the way they may act in the atmospheric physical and chemical processes and their impact on the environment and public health. In this context, our study aims at determining the size and morphological characteristics of aircraft soot aggregates on the basis of experimental measurements by transmission electron microscopy (TEM) and electron tomography.We have acquired TEM pictures of soot aggregates emitted by aircraft engines. We have established a method to characterize the morphology of these aggregates by determining their elongation, their compacity and the tortuosity of their edge. This method is based on the analysis of their TEM projection. Besides, we have developed a software to process and analyse TEM pictures. It allows to reconstruct aggregates from their projections and to determine their size and morphological characteristics. Our results have lead us to study the validity of the relationships linking the 2D and 3D microphysical characteristics presented in the literature and to suggest new ones for the studied aggregates.These results constitute the first 3D morphological and size characterizations of aircraft soot aggregates using TEM and electron tomography. They highlight the fact that the morphological properties of these aggregates do not fulfil the hypotheses required for the use of the collective method to determine the mass fractal dimension.

Cette thèse est une étude théorique d’un système d’équations de Cahn-Hilliard/Allen-Cahn couplées qui représente un mélange binaire en séparation de phase. Le but principal de l’étude est le comportement asymptotique des solutions en termes d’attracteurs exponentiels/globaux. Pour cette raison, l’existence et l’unicité de la solution sont étudiées tout d’abord. Une des principales applications de ce modèle d’équations est la cristallographie.Dans la première partie de la thèse, on examine le modèle proposé avec des conditions de type Dirichlet sur le bord et une non linéarité régulière de type polynomial : on réussit à trouver un attracteur exponentiel et par conséquence un attracteur global de dimension finie. Une non linéarité singulière de type logarithmique est ensuite prise dans la deuxième partie, cette fonction étant approchée par une suite de fonctions régulières et l’existence d’un attracteur global est démontrée sous des conditions au bord de type Dirichlet.Enfin, dans la dernière partie, le système est couplé avec une équation pour la température: suivant la loi de Fourrier premièrement, puis la loi de type III de la thermo-élasticité. Dans les deux cas, la dynamique de l’équation est étudiée et un attracteur exponentiel est trouvé malgré la difficulté créée par l’équation hyperbolique dans le deuxième cas. / This thesis is a theoretical study of a coupled system of equations of Cahn-Hilliard and Allen-Cahn that represents phase separation of binary alloys. The main goal of this study is to investigate the asymptotic behavior of the solution in terms of exponential/global attractors. For this reason, the existence and unicity of the solution are first studied. One of the most important applications of this proposed model of equations is crystallography. In the first part of the thesis, the system is studied with boundary conditions of Dirichlet type and a regular nonlinearity (a polynomial). There, we prove the existence of an exponential attractor that leads to the existence of a global attractor of finite dimension. Then, a singular nonlinearity (a logarithmic potential) is considered in the second part. This function is approximated by a sequence of regular ones and a global attractor is found.At the end, the system of equations is coupled with temperature: with the Fourrier law in the first case, then with the type III law (in the context of thermoelasticity) in the second case. The dynamics of the equations are studied and the existence of an exponential attractor is obtained.

La connaissance de la dynamique des matières en suspension (MES) et des turbidités en milieu côtier est un élément clé pour comprendre les écosystèmes marins. Les processus de floculation/défloculation représentent des mécanismes essentiels contrôlant la dynamique des caractéristiques physiques des MES et, par conséquent, leur devenir dans l’environnement. Cette thèse a pour objectif de mieux comprendre la caractérisation des MES et leur variabilité de l’échelle tidale à l’échelle annuelle en mer côtière, en réponse aux différents forçages hydrodynamiques, hydrologiques et biologiques ayant lieu à l’interface entre estuaire et baie. À cette fin, des capteurs optiques et acoustiques ont été déployés in situ, lors de 6 campagnes en mer réalisées en 2016, en vue de caractériser et de quantifier les MES dans la colonne d’eau, à la sortie de l’embouchure de l’estuaire de Seine (France). Une analyse critique des mesures granulométriques issues du LISST-100X est proposée. Un travail de quantification des incertitudes de mesure associées à l’estimation de la concentration en MES a mis en avant le risqué lié à un rinçage insuffisant des filtres et a conduit à définir une masse minimum à filtrer, de l'ordre de 10 mg, quelle que soit la concentration. Ce travail a notamment permis de proposer une méthode d’estimation d’un volume optimal de filtration basée sur une mesure préalable de turbidité de référence. Les mesures à haute fréquence ont montré que la dynamique des caractéristiques physiques des MES en termes de concentration et de taille médiane sont contrôlées par le cycle advection-floculation-sédimentation-remise en suspension. Ces résultats ont permis de hiérarchiser les paramètres de contrôle des processus de floculation. La turbulence a été identifiée comme le principal paramètre de contrôle à l’échelle tidale et semi-lunaire, la taille médiane maximale des flocs étant inversement corrélée à l’intensité des courants. À l’échelle saisonnière, la variation des caractéristiques des MES (taille, densité, vitesse de chute) est liée à la variabilité du contenu en matière organique (MO), avec une floculation favorisée quand le taux de MO particulaire augmente. Ces flocs plus grands et moins denses sont également plus résistants à la fragmentation induite par cisaillement turbulent. Ces travaux ont également permis de discuter le concept de structuration fractale des flocs.La dynamique de la dimension fractale, déterminée en combinant des données in situ de concentration en MES et de distribution en classe de taille, peut traduire des variations de composition des MES, mais peut aussi résulter d'incertitudes de mesure associées aux instruments. Ces dernières sont discutées dans cette thèse. La variabilité saisonnière des caractéristiques des MES est plus prononcée au large que dans la zone sous influence de l’estuaire de Seine. À partir des observations ponctuelles en Baie de Seine et d’une série de mesure long terme dans la zone côtière belge acquise par le laboratoire RBINS, les méthodes acoustiques et optiques sont combinées. Ces dernières ont mis en avant une augmentation de la rétrodiffusion acoustique lorsque la densité moyenne des flocs diminue. / The knowledge of suspended particulate matter (SPM) and turbidity dynamics in coastal waters is essential for studying marine ecosystems. Flocculation/deflocculation processes are crucial mechanisms controlling the dynamics of SPM physical characteristics and thus, the fate of these SPM in the environment. This PhD thesis focuses on the SPM characteristics and their dynamics in coastal waters, from tidal to annual scales, in response to hydrodynamic, hydrological and biological forcing that take place at the interface between estuaries and coastal seas. To this end, optical and acoustic sensors were deployed in situ through 6 field campaigns in 2016, in order to characterize and quantify SPM in the water column, near the mouth of the Seine estuary (France). A critical analysis of LISST-100X measurements in coastal waters is presented. The quantification of uncertainties on SPM concentration measurements is investigated: it highlights the crucial effect of salt retention, and the need for a minimum mass to filter, around 10 mg. A method for estimating an optimal filtration volume based on a reference turbidity measurement is proposed. High frequency measurements show that the dynamics of SPM and median diameter are controlled by the advection-flocculationsedimentation-resuspension cycle.These results allow to classify the factors controlling flocculation processes. Turbulence is identified as the main factor at the semi-diurnal and semi-lunar tidal scales, as the maximum median size of flocs decreases when the tidal currents intensify.At the seasonal scale, the variation of SPM characteristics (size, density, settling velocity) is correlated to the variability of the organic matter (OM) content: in particular, flocculation is enhanced by an increase of the particular OM fraction. The resulting larger and lesser dense flocs are also more resistant to the fragmentation induced by shear. This work also investigates the fractal approach applied to flocs. The fractal dimension variability, calculated by combining in situ data of SPM concentration and particle size distribution, can be associated to variations of the SPM composition, but can also result from uncertainties linked to instrument limitations. The latter are discussed in this PhD thesis. The seasonal variability of SPM characteristics is more pronounced offshore than at the mouth of the Seine estuary. From short-term observations in the Seine Bay and from long-term series in the Belgian coastal zone provided by the RBINS, optical turbidity and acoustic backscatter measurements are combined. They highlight an increase of the acoustic backscatter intensity when mean floc density.

Les avalanches de débris, qui résultent du démantèlement des flancs des édifices volcaniques et montagneux, sont des écoulements granulaires rapides et dangereux dont le monteur est la gravité et qui présentent des distances de transport extrêmement importantes. La dynamique de leur mise en place et leurs mécanismes de transport permettant cette très grande mobilité sont des phénomènes qui demeurent encore mal compris. De nombreux modèles existent pour expliquer la grande mobilité des avalanches de débris et incluent des processus basés sur la lubrification ou la fluidification de la masse granulaire mais également sur le phénomène de désintégration dynamique des éléments. Cependant la grande majorité des modèles proposés souffre du manque d’observations de terrain et de quantification de l’évolution des matériaux au cours de leur transport au sein de la masse granulaire. Afin d’identifier les principaux mécanismes de transport des avalanches de débris, nous proposons dans ce travail une étude de terrain détaillée de dépôts d’avalanches de débris volcaniques qui résultent du démantèlement d’un volcan bouclier océanique, le Piton des Neiges (île de La Réunion, océan Indien). L’approche est couplée à un examen morphométrique (dimension fractale et circularité), exoscopique et granulométrique des particules présentes dans les dépôts. Elle est complétée par l’examen de la fabrique des dépôts basée sur l’anisotropie de la susceptibilité magnétique (ASM). Les données obtenues nous permettent de mettre en évidence une évolution de la dynamique de transport et de mise en place des dépôts d’avalanches de débris depuis les zones sources jusqu’aux domaines de dépôt distaux. On montre également que la désintégration dynamique et le gonflement dispersif qui l’accompagne opèrent tout au long du transport et à toutes les échelles au-dessus d’une limite inférieure de broyage à 500 μm. En dessous de cette limite, la réduction granulométrique résulte uniquement de processus d’attrition par friction entre les particules. La grande mobilité des avalanches de débris pourrait ainsi être expliquée par l’effet combiné de la libération d’énergie élastique par la désintégration dynamique des particules > 500μm et par une réduction de la friction interne à la matrice liée aux interactions dispersives des particules fines (< 500 μm). L’ensemble des données permettent également de préciser les directions de transport et l’ampleur des avalanches de débris liées aux déstabilisations du massif du Piton des Neiges. / Debris avalanches, resulting from flank collapses that shape volcanic and mountainous edifices are rapidand dangerous gravity-driven granular flows that travel long run out distances. The dynamic and the transport mechanisms behind this high mobility remain poorly understood. The numerous models proposed to explain this high mobility include processes based on lubrication or fluidisation of the granular mass of the flow body, but also the dynamic disintegration of the transported particles. To date,all these proposed mechanisms lack observational support and quantification of the state of the particles of the granular mass during the transport. To identify the main transport mechanisms, we propose here detailed field studies of volcanic debris avalanches deposits resulting of flank-collapse events on an oceanic shield volcano, the Piton des Neiges (La Réunion Island, Indian Ocean). This study has been combined with morphometric (fractal dimension and circularity), exoscopic and grain-size analyses. Moreover, the fabric of the deposits has been investigated by with the characteristics of the anisotropy of the magnetic susceptibility (ASM). From these data we highlight a proximal to distal evolution of the debris avalanches transport and emplacement dynamics. We demonstrate that syn-transport dynamic disintegration continuously operates with the distance from the source down to a grinding limit of 500μm. Below this limit, the particle size reduction exclusively results from the attrition of the particles by frictional interactions. Thus, the exceptional mobility of debris avalanches may be explained by thecombined effect of elastic energy release during the dynamic disintegration of the larger clasts (> 500μm) and frictional reduction within the matrix due to the dispersive interactions between the finer particles (< 500 μm). All these data also allow to specify the transport direction and the approximate size of the debris avalanches related to the Piton des Neiges destabilisations.

No description available.

This thesis investigates the potential of fractal dimension (FD) as a tool for enhancing airborne magnetic data. More specifically, this thesis investigates the potential of FD-based texture transform images as tools for aiding in the interpretation of airborne magnetic data. A series of different methods of estimating FD are investigated, specifically: • geometric methods (1D and 2D variation methods and 1D line divider method); • stochastic methods (1D and 2D Hurst methods and 1D and 2D semi-variogram methods), and; • spectral methods (1D and 2D wavelet methods and 1D and 2D Gabor methods). All of these methods are able to differentiate between varying theoretical FD in synthetic profiles. Moreover, these methods are able to differentiate between theoretical FDs when applied to entire profiles or in a moving window along the profile. Generally, the accuracy of the estimated FD improves when window size is increased. Similarly, the standard deviation of estimated FD decreases as window size increases. This result implied that the use of moving window FD estimates will require a trade off between the quality of the FD estimates and the need to use small windows to allow better spatial resolution. Application of the FD estimation methods to synthetic datasets containing simple ramps, ridges and point anomalies demonstrates that all of the 2D methods and most of the 1D methods are able to detect and enhance these features in the presence of up to 20% Gaussian noise. In contrast, the 1D Hurst and line divider methods can not clearly detect these features in as little as 10% Gaussian noise. Consequently, it is concluded that the 1D Hurst and line divider methods are inappropriate for enhancing airborne magnetic data. The application of these methods to simple synthetic airborne magnetic datasets highlights the methods’ sensitivity to very small variations in the data. All of the methods responded strongly to field lines some distance from the causative magnetic bodies. This effect was eliminated through the use of a variety of tolerances that essentially required a minimum level of difference between data points in order for FD to be calculated. Whilst this use of tolerances was required for synthetic datasets, its use was not required for noise corrupted versions of the synthetic magnetic data. The results from applying the FD estimation techniques to the synthetic airborne magnetic data suggested that these methods are more effective when applied to data from the pole. Whilst all of the methods were able to enhance the magnetic anomalies both at the pole and in the Southern hemisphere, the responses of the FD estimation techniques were notably simpler for the polar data. With the exception of the 1D Hurst and line divider methods, all of the methods were also able to enhance the synthetic magnetic data in the presence of 10% Gaussian noise. Application of the FD estimation methods to an airborne magnetic dataset from the Merlinleigh Sub-basin in Western Australia demonstrated their ability to enhance subtle structural features in relatively smooth airborne magnetic data. Moreover, the FD-based enhancements were able to enhance some features of this dataset better than any of the conventional enhancements considered (i.e. an analytic signal, vertical and total horizontal derivatives, and automatic gain control). Most of the FD estimation techniques enhanced similar features to each other. However, the 2D methods generally produced clearer results than their associated 1D methods. In contrast to this result, application of the FD-based enhancements to more variable airborne magnetic data from the Tanami region in the Northern Territory demonstrated that these methods are not as well suited to this style of data. The main conclusion from this work is that FD-based enhancement of relatively smooth airborne magnetic data can provide valuable input into an interpretation process. This suggests that these methods are particularly useful for aiding in the interpretation of airborne magnetic data from regions such as sedimentary basins where the distribution of magnetic sources is relatively smooth and simple. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1339560 / Thesis (Ph.D.) - University of Adelaide, Australian School of Petroleum, 2008

Dysfunction in the central nervous system of the neonate is often first identified through seizures. The diffculty in detecting clinical seizures, which involves the observation of physical manifestations characteristic to newborn seizure, has placed greater emphasis on the detection of newborn electroencephalographic (EEG) seizure. The high incidence of newborn seizure has resulted in considerable mortality and morbidity rates in the neonate. Accurate and rapid diagnosis of neonatal seizure is essential for proper treatment and therapy. This has impelled researchers to investigate possible methods for the automatic detection of newborn EEG seizure. This thesis is focused on the development of algorithms for the automatic detection of newborn EEG seizure using adaptive time-frequency signal processing. The assessment of newborn EEG seizure detection algorithms requires large datasets of nonseizure and seizure EEG which are not always readily available and often hard to acquire. This has led to the proposition of realistic models of newborn EEG which can be used to create large datasets for the evaluation and comparison of newborn EEG seizure detection algorithms. In this thesis, we develop two simulation methods which produce synthetic newborn EEG background and seizure. The simulation methods use nonlinear and time-frequency signal processing techniques to allow for the demonstrated nonlinear and nonstationary characteristics of the newborn EEG. Atomic decomposition techniques incorporating redundant time-frequency dictionaries are exciting new signal processing methods which deliver adaptive signal representations or approximations. In this thesis we have investigated two prominent atomic decomposition techniques, matching pursuit and basis pursuit, for their possible use in an automatic seizure detection algorithm. In our investigation, it was shown that matching pursuit generally provided the sparsest (i.e. most compact) approximation for various real and synthetic signals over a wide range of signal approximation levels. For this reason, we chose MP as our preferred atomic decomposition technique for this thesis. A new measure, referred to as structural complexity, which quantifes the level or degree of correlation between signal structures and the decomposition dictionary was proposed. Using the change in structural complexity, a generic method of detecting changes in signal structure was proposed. This detection methodology was then applied to the newborn EEG for the detection of state transition (i.e. nonseizure to seizure state) in the EEG signal. To optimize the seizure detection process, we developed a time-frequency dictionary that is coherent with the newborn EEG seizure state based on the time-frequency analysis of the newborn EEG seizure. It was shown that using the new coherent time-frequency dictionary and the change in structural complexity, we can detect the transition from nonseizure to seizure states in synthetic and real newborn EEG. Repetitive spiking in the EEG is a classic feature of newborn EEG seizure. Therefore, the automatic detection of spikes can be fundamental in the detection of newborn EEG seizure. The capacity of two adaptive time-frequency signal processing techniques to detect spikes was investigated. It was shown that a relationship between the EEG epoch length and the number of repetitive spikes governs the ability of both matching pursuit and adaptive spectrogram in detecting repetitive spikes. However, it was demonstrated that the law was less restrictive forth eadaptive spectrogram and it was shown to outperform matching pursuit in detecting repetitive spikes. The method of adapting the window length associated with the adaptive spectrogram used in this thesis was the maximum correlation criterion. It was observed that for the time instants where signal spikes occurred, the optimal window lengths selected by the maximum correlation criterion were small. Therefore, spike detection directly from the adaptive window optimization method was demonstrated and also shown to outperform matching pursuit. An automatic newborn EEG seizure detection algorithm was proposed based on the detection of repetitive spikes using the adaptive window optimization method. The algorithm shows excellent performance with real EEG data. A comparison of the proposed algorithm with four well documented newborn EEG seizure detection algorithms is provided. The results of the comparison show that the proposed algorithm has significantly better performance than the existing algorithms (i.e. Our proposed algorithm achieved a good detection rate (GDR) of 94% and false detection rate (FDR) of 2.3% compared with the leading algorithm which only produced a GDR of 62% and FDR of 16%). In summary, the novel contribution of this thesis to the fields of time-frequency signal processing and biomedical engineering is the successful development and application of sophisticated algorithms based on adaptive time-frequency signal processing techniques to the solution of automatic newborn EEG seizure detection.

Submitted by FERNANDO PEREIRA DOS SANTOS null (fernando_persan@hotmail.com) on 2016-06-30T21:35:05Z No. of bitstreams: 1 EstudoComparativo_FernandoPereiraSantos.pdf: 17823712 bytes, checksum: fd7d1643bbacb3313ced8e742fda123f (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-07-04T12:57:57Z (GMT) No. of bitstreams: 1 santos_fp_me_sjrp.pdf: 17823712 bytes, checksum: fd7d1643bbacb3313ced8e742fda123f (MD5) / Made available in DSpace on 2016-07-04T12:57:57Z (GMT). No. of bitstreams: 1 santos_fp_me_sjrp.pdf: 17823712 bytes, checksum: fd7d1643bbacb3313ced8e742fda123f (MD5) Previous issue date: 2016-06-16 / Neste trabalho é apresentada uma nova metodologia para a análise e classificação de lesões de pele. O modelo proposto foi dividido em quatro etapas que compreende o pré-processamento das imagens, a segmentação do objeto desejado, a extração de características e a classificação das lesões. Na etapa de pré-processamento, aplica-se o modelo de cor RGB, a quantização de cores e o filtro de difusão anisotrópica. Na segmentação, a imagem suavizada é submetida à operação de fechamento da morfologia matemática, estimativa de peso nos arcos do grafo e à transformada imagem-floresta com apenas duas sementes. A extração de características foi baseada na aplicação da regra ABCD. Na assimetria foi aplicado o conceito de razão de perpendiculares sobre a maior diagonal obtida e, para a borda, o produto vetorial e o ponto de inflexão foram implementados para fornecer o porcentual de curvatura do contorno. Para a cor, valores de média, variância, desvio padrão, homogeneidade e contraste foram calculados. Para a estrutura diferencial foi desenvolvido a dimensão fractal e a energia. Na última etapa, classificação, a floresta de caminhos ótimos foi utilizada. Os resultados da classificação são apresentados por malignidade, quando todos os tipos de lesões estão juntos, e por categorias, quando os tipos de lesão são agrupados dois a dois. Para obter o modelo proposto foram efetuados diversos testes com modelos de cor diferentes, forma de aplicação da quantização, diferenciação no cálculo da quantidade de iterações do filtro de difusão anisotrópica e possibilidade de não aplicar a morfologia matemática. / In this paper a new methodology for the analysis and classification of skin lesions is presented. The suggested model is divided into four steps which comprise the pre processing of images, segmentation of the desired object, feature extraction and lesions classification. In the pre processing step, it is applied the RGB color model, color quantization and anisotropic diffusion filter. In segmentation, the smoothed image is submitted to the closing operation of mathematical morphology, arc-weight estimation in the graph and the image-foresting transform with only two seeds. The feature extraction is based on the application of ABCD rule. In asymmetry was applied the perpendicular ratio concept on the greater diagonal obtained and, to the border, the vector product and the inflection point were implemented to provide the contour curvature percentage. For color, average values, variance, standard deviation, homogeneity and contrast were calculated. For differential structure was developed fractal dimension and energy. In the last stage, classification, optimum-path forest was used. The classification results are presented by malignancy, when all types of lesions are together, and by categories, when the types of lesions are grouped two by two. For the model were performed several tests with different color models, the form of application the quantization, differentiation in the calculation of the quantity of filter iterations of anisotropic diffusion and the possibility of not applying the mathematical morphology.

Made available in DSpace on 2014-12-17T14:09:13Z (GMT). No. of bitstreams: 1 AlvaroBN_TESE.pdf: 1929903 bytes, checksum: 92f40cf4d3b6ab5536ad5ad3d2aa192a (MD5) Previous issue date: 2012-02-29 / The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study. / O presente trabalho proporciona uma metodologia que d? um car?ter preditivo ?s simula??es computacionais baseadas em modelos detalhados da geometria porosa de um meio. N?s utilizando o software FLUENT para investigar o escoamento de um fluido newtoniano viscoso atrav?s de um meio fractal aleat?rio que simplifica um meio poroso desordenado bidimensional representando um reservat?rio de petr?leo. Este modelo fractal ? formado por obst?culos de diversos tamanhos, cuja fun??o de distribui??o segue uma lei de pot?ncia, onde o expoente ? definido como sendo a dimens?o fractal de fracionamento Dff do modelo e caracteriza o processo de fragmenta??o desses obst?culos. Eles s?o aleatoriamente dispostos em um canal retangular. O processo de modelagem incorpora conceitos modernos, leis de escala, para analisar a influ?ncia das heterogeneidades encontradas nos campos da porosidade e da permeabilidade de tal maneira que se possa caracterizar o meio em fun??o de suas propriedades fractais. Este procedimento permite analisar numericamente as medidas da permeabilidade k e do coeficiente de arrasto Cd propondo rela??es, tipo lei de pot?ncia, para essas propriedades sobre v?rios esquemas de modelagem. O prop?sito desta pesquisa ? estudar a variabilidade proporcionada por estas heterogeneidades onde o campo de velocidade e outros detalhes da din?mica dos fluidos viscosos s?o obtidos resolvendo numericamente as equa??es da continuidade e de Navier-Stokes no n?vel de poros e observar como a dimens?o fractal de fracionamento do modelo pode afetar as suas propriedades hidrodin?micas. Neste estudo foram consideradas duas classes de modelos, modelos com porosidade constante, MPC, e modelos com porosidade vari?vel, MPV. Os resultados permitiram-nos encontrar rela??es num?ricas entre a permeabilidade, coeficiente de arrasto e os par?metros geom?tricos do modelo. Com base nestes resultados num?ricos propusemos rela??es de escala envolvendo os par?metros relevantes do fen?meno. Nesta pesquisa foram determinadas equa??es anal?ticas para Dff em fun??o dos par?metros geom?tricos dos modelos. Constatamos tamb?m uma rela??o entre a permeabilidade e o coeficiente de arrasto onde uma ? inversamente proporcional ? outra. Quanto ? diferen?a de comportamento ela ? mais marcante nas classes de modelos MPV. Isto ?, o fato da porosidade variar nestes modelos constitui um fator adicional que desempenha um papel significativo na an?lise de fluxo. Finalmente, os resultados encontrados se mostraram consistentes e satisfat?rios, o que demonstra a efic?cia da referida metodologia para todas as aplica??es analisadas nesta pesquisa.