Made available in DSpace on 2016-03-15T19:37:38Z (GMT). No. of bitstreams: 1 Glauco dos Santos Reis.pdf: 1334999 bytes, checksum: d2d72d3f95a449c19482f55f82b7f61e (MD5) Previous issue date: 2011-08-22 / Fundo Mackenzie de Pesquisa / A new image compression technique is proposed, based on the affine transformations (ATs) that define an iterated function system (IFS). Previous related research in the field has shown that an image may be approximated by iteratively subjecting a set of sub-regions to a group of ATs. In this case, the original image should be partitioned in regions, and each one of the active pixels are transformed by the AT. The new transformed set should be approximated to other image regions. This iterated execution to find ATs for the best set of areas might result in smaller storage space since the similar areas might be replaced by AT coefficients. Despite this advantage, the technique is computationally intensive, because both the sub-regions and the corresponding ATs that have to be searched for. Here, a new form of similarity is proposed, based on the successive points generated by the iteration of affine transformations. By understanding an AT as a discrete dynamical system, with each image point represented by an iteration of the AT, the method captures similarities between these points, namely, those with the same color in the image; by saving the starting point and the transformations coefficients, the points can be iterated back, to reconstruct the original image. This results in lighter computational effort, since the comparison is made point by point, instead of region by region. Experiments were made on a group of 10 images, representing a broad set of distinct features and resolutions. The proposed algorithm competes in terms of storage size, when compared to JPEG, mainly when the image size is small, and the number of colors are reduced, as currently happens for most images used in the Internet. Although the proposed method is faster than the traditional method for IFS compression, it is slower than common file formats like JPEG. / Uma nova técnica para compressão de imagens é proposta, baseada em conjuntos de transformações afins (affine transformations - ATs), normalmente conhecidos como sistemas de funções iteradas (iterated function system -IFS). Pesquisas anteriores mostraram que uma imagem poderia ser aproximada pela aplicação de um grupo de ATs em conjuntos de sub-regiões da imagem, de forma iterativa. Através deste processo, a imagem original seria subdividida em regiões e sobre a coordenada de cada ponto habilitado de cada região seria aplicada uma transformação afim. O resultado representaria um novo conjunto de pontos similares a outras regiões da imagem. A execução de forma iterada deste processo de identificação das ATs para o maior conjunto de regiões similares de uma determinada imagem permitiria uma redução no armazenamento, já que as regiões similares poderiam ser armazenadas como os coeficientes das transformações afins. Apesar desta vantagem em termos de compressão, a técnica é computacionalmente intensiva, pela busca exaustiva de sub-regiões e das ATs geradoras, de forma a proporcionar o melhor preenchimento em outras regiões da imagem. Esta pesquisa propõe uma nova forma de compressão baseada em ATs, utilizando a sequência de pontos gerada pela iteração das ATs. Entendendo uma AT como um sistema dinâmico em tempo discreto, cada novo ponto identificado é consequência direta da iteração da AT sobre o ponto anterior, permitindo a captura de similaridades nesta sequência de pontos. Através do salvamento dos coeficientes das ATs e das coordenadas iniciais, é possível a reconstrução da imagem pela iteração da AT a partir do ponto inicial. Isto pode resultar em menor esforço computacional, pois apenas comparações simples de pontos são necessárias, ao invés de comparações entre os pontos de regiões da imagem. Foram feitos experimentos em um conjunto de 10 classes de imagens, representando um espectro de diferentes características gerais e resoluções. O algoritmo proposto rivaliza em termos de armazenamento quando comparado ao formato JPEG, principalmente para imagens de pequeno tamanho e com número de cores reduzidas, como as utilizadas com frequência na Internet. Apesar de ser mais rápido para a compressão do que outros métodos baseados em IFS, ele é mais lento do que métodos clássicos como o JPEG.

Made available in DSpace on 2016-03-15T19:37:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-08-22 / Fundo Mackenzie de Pesquisa / A new image compression technique is proposed, based on the affine transformations (ATs) that define an iterated function system (IFS). Previous related research in the field has shown that an image may be approximated by iteratively subjecting a set of sub-regions to a group of ATs. In this case, the original image should be partitioned in regions, and each one of the active pixels are transformed by the AT. The new transformed set should be approximated to other image regions. This iterated execution to find ATs for the best set of areas might result in smaller storage space since the similar areas might be replaced by AT coefficients. Despite this advantage, the technique is computationally intensive, because both the sub-regions and the corresponding ATs that have to be searched for. Here, a new form of similarity is proposed, based on the successive points generated by the iteration of affine transformations. By understanding an AT as a discrete dynamical system, with each image point represented by an iteration of the AT, the method captures similarities between these points, namely, those with the same color in the image; by saving the starting point and the transformations coefficients, the points can be iterated back, to reconstruct the original image. This results in lighter computational effort, since the comparison is made point by point, instead of region by region. Experiments were made on a group of 10 images, representing a broad set of distinct features and resolutions. The proposed algorithm competes in terms of storage size, when compared to JPEG, mainly when the image size is small, and the number of colors are reduced, as currently happens for most images used in the Internet. Although the proposed method is faster than the traditional method for IFS compression, it is slower than common file formats like JPEG. / Uma nova técnica para compressão de imagens é proposta, baseada em conjuntos de transformações afins (affine transformations - ATs), normalmente conhecidos como sistemas de funções iteradas (iterated function system - IFS). Pesquisas anteriores mostraram que uma imagem poderia ser aproximada pela aplicação de um grupo de ATs em conjuntos de sub-regiões da imagem, de forma iterativa. Através deste processo, a imagem original seria subdividida em regiões e sobre a coordenada de cada ponto habilitado de cada região seria aplicada uma transformação afim. O resultado representaria um novo conjunto de pontos similares a outras regiões da imagem. A execução de forma iterada deste processo de identificação das ATs para o maior conjunto de regiões similares de uma determinada imagem permitiria uma redução no armazenamento, já que as regiões similares poderiam ser armazenadas como os coeficientes das transformações afins. Apesar desta vantagem em termos de compressão, a técnica é computacionalmente intensiva, pela busca exaustiva de sub-regiões e das ATs geradoras, de forma a proporcionar o melhor preenchimento em outras regiões da imagem. Esta pesquisa propõe uma nova forma de compressão baseada em ATs, utilizando a sequência de pontos gerada pela iteração das ATs. Entendendo uma AT como um sistema dinâmico em tempo discreto, cada novo ponto identificado é consequência direta da iteração da AT sobre o ponto anterior, permitindo a captura de similaridades nesta sequência de pontos. Através do salvamento dos coeficientes das ATs e das coordenadas iniciais, é possível a reconstrução da imagem pela iteração da AT a partir do ponto inicial. Isto pode resultar em menor esforço computacional, pois apenas comparações simples de pontos são necessárias, ao invés de comparações entre os pontos de regiões da imagem. Foram feitos experimentos em um conjunto de 10 classes de imagens, representando um espectro de diferentes características gerais e resoluções. O algoritmo proposto rivaliza em termos de armazenamento quando comparado ao formato JPEG, principalmente para imagens de pequeno tamanho e com número de cores reduzidas, como as utilizadas com frequência na Internet. Apesar de ser mais rápido para a compressão do que outros métodos baseados em IFS, ele é mais lento do que métodos clássicos como o JPEG.

Ce manuscrit de thèse de doctorat présente les travaux de développement d’un granulomètre optique pour la caractérisation de suspensions de nano et microparticules individuelles ainsi que d’agrégats. La mesure repose sur l’analyse suivant différents angles de la diffusion statique et dynamique de l’échantillon placé dans une cuve spectrophotométrique cylindrique. Il intègre différentes solutions originales telles qu’un éclairage par un faisceau laser de forte ellipticité, une détection sous le plan de diffusion conventionnel et l’utilisation d’une méthode de post-traitement qualifiée de « filtre quasi-statique ». Ces solutions permettent d’éliminer l’essentiel des problèmes liés aux réflexions spéculaires et diffuses de la cuve d’analyse, de même que les variations des dimensions du volume de mesure avec l’angle de diffusion et les cas de désalignement même léger du système goniométrique. Les signaux mesurés sont inversés avec des méthodes d’estimation de paramètres. Pour les particules sphériques, le problème direct est résolu avec la théorie de Lorenz-Mie. Pour les agrégats, il l’est avec un modèle d’agrégat fractal, des approximations par dipôles discrets ou Rayleigh-Gans-Debye. Les performances de cet instrument, de conception volontairement simple et robuste, ont été testées avec succès sur des nano et micro suspensions diluées, monomodales et bimodales, de latex et silice colloïdale, de même que des agrégats de particules aciculaires et sphériques. Il permet de caractériser la taille, la morphologie et la concentration absolue de particules dans la gamme de taille 20nm-2µm. / This PhD thesis manuscript presents the work conducted to develop an optical particle siz-ing instrument for the characterization of individual nano and microparticles, as well as their aggregates, in liquid suspensions. The measurement is based on the multi-angular analysis of the static and dynamic light scattering of a sample into a cylindrical spectrophotometric cell. This instrument integrates various innovative solutions such as an illumination by a high ellipticity laser beam, a detection under the conventional scattering plane and a post-processing method operating as a quasi-static filter. These solutions make it possible to elim-inate most of the problems associated with the specular and diffuse reflections of the analy-sis cell, as well as the harmful variations of the probe volume dimension with the detection angle and in case of a slight misalignment of the system. The signal inversion is performed with parameters estimation methods. For spherical particles, the direct problem is solved with the Lorenz-Mie theory. For aggregates, it is solved with a fractal aggregate model and approximations based on discrete dipoles or Rayleigh-Gans-Debye theories. The perfor-mance of this instrument, of a deliberately simple and robust design, has been successfully tested on dilute nano and micro suspensions of latex and colloidal silica, mono and bimodal, as well as aggregates of acicular and spherical particles. It allows to characterize the size, the morphology and the absolute concentration of particles in the size range 20nm-2μm.

Cílem této práce je se seznámení s možnostmi programu Matlab z hlediska detailní analýzy deterministických dynamických systémů. Jedná se především o analýzu časové posloupnosti a o nalezení Lyapunových exponentů. Dalším cílem je navrhnout algoritmus umožňující specifikovat chování systému na základě znalosti příslušných diferenciálních rovnic. To znamená, nalezení chaotických systémů.

Study on nanoparticle additives in multiphase systems (liquid, polymer) are of immense interest in developing new product applications. Critical challenges for nanoparticle additives include their synthesis, formulation and characterization. These challenges are addressed in three application areas: nanofluids for engine lubrication, ultrathin nanocomposites for optical devices, and nanoparticle size distribution characterization. Nanoparticle additives in oligomer mixtures can be used to develop extended temperature range motor oils. A model system includes poly(α-olefin) based oligomers with a modest fraction of poly(dimethylsiloxane) oligomers along with graphite as nanoparticle additive. Partition coefficients of each oligomer are determined since the oligomer mixture phase separated at temperatures less than -15 °C. Also, the surface of graphite additive is quantitatively analyzed and modified via silanization for each oligomer. Thus, upon separation of the oligomer mixture, each functionalized graphite additive migrates to its preferred oligomers and forms a uniform dispersion. Similarly, nanoparticle additives in polymer matrices can be used to develop new low haze ultrathin film optical coatings. A model system included an acrylate monomer as the continuous phase with monodisperse or bidisperse mixtures of silica nanoparticles deposited on glass and polycarbonate substrates. Surface (root mean squared roughness, Wenzel’s contact angle) and optical properties (haze) of these self assembled experimental surfaces were compared to simulated surface structures. Manipulating the size ratios of silica nanoparticle mixtures varied the average surface roughness and the height distributions, producing multimodal structures with different packing fractions. In both nanofluid and nanocomposite applications, nanoparticle additives tend to aggregate/agglomerate depending on various factors including the state of nanoparticles (powder, dispersion). A set of well-characterized ceria and titania nanoparticle products from commercial sources along with in-lab synthesized nanoparticles were studied via fractal theory. Fractal coefficients were obtained through two-dimensional images (from electron microscopy) and particle size distributions (from electron microscopy and dynamic light scattering). For some arbitrary collections of aggregated nanoparticle materials, the fractal coefficients via two-dimensional images correlated well to the average primary particle size. This complementary tool could be used along with conventional nanoparticle characterization techniques when not much is known about the nanoparticle surfaces to characterize agglomeration or aggregation phenomena.

Complexity lies halfway between stochasticity and determinism, suggesting that brain activity is neither fully random nor fully predictable but lives by the rules of nonlinear high- and low-complexity dynamics. One important aspect of brain function is noise-like activity (NLA), defined as background, electrical potential fluctuations in the nervous system distinct from spiking rhythms in the foreground. The objective of this thesis was to investigate the neurodynamical complexity of NLA recorded at the cellular and local network scales in in vitro preparations of mouse and human hippocampal tissue, under healthy and epileptiform conditions. In particular, it was found that neuronal NLA arises out of the physiological contributions of gap junctions and chemical synaptic channels and is characterized by a spectrum of complexity, ranging from high- to low-complexity, that was measured using methods from nonlinear dynamical systems theory. Importantly, the complexity of background, neuronal NLA was shown to depend on the degree of cellular interconnectivity to the surrounding local network. In addition, the complexity and multifractality of NLA was further studied at the cellular and local network scales in epileptiform transitions to seizure-like events, identifying emergent low-complexity and reduced multifractality (bordering on monofractal-type dynamics) in the pathological ictal state. Finally, dual intracellular recordings of hippocampal epileptiform activity were analyzed to measure NLA synchronicity, showing evidence for increased same- and cross-frequency correlations and increased phase synchronization in the pathological ictal state. Convergence towards increased phase synchrony manifested in lower frequency regions including theta (4-10 Hz) and beta (12-30 Hz), but also in higher frequency bands (gamma, 30-80 Hz). In summary, there is evidence to suggest that background NLA captures important neurodynamical information pertinent to the classification and identification of brain state transitions in healthy and epileptiform hippocampal dynamics, using sophisticated neuroengineering analyses of these physiological signals.

La description aux échelles macroscopiques et gigascopiques des feux de forêts permet l'établissement de modèles physiques aptes à représenter l'évolution d'un feu avec une meilleure précision que les modèles empiriques de type Rothermel développés jusqu'alors. Cependant ces modèles nécessitent l'ajustement de paramètres dont la mesure directe est impossible, car les équations associées à ces modèles ne sont pas relatives à l'air et à la matière végétale mais aux milieux équivalents à la végétation pour l'échelle considérée. Les propriétés des milieux équivalents sont alors liées aux propriétés des milieux les constituant, mais la connaissance des propriétés des milieux constitutifs ne permet pas de connaître directement les propriétés du milieu équivalent. Ce travail consistera tout d'abord en la reconstruction du milieu végétal à l'aide d'outils issus de la géométrie fractale. Des méthodes de mesures de paramètres géométriques venant de la foresterie ont ensuite été utilisées pour valider nos modèles de végétation. Enfin, des expériences numériques ont été menées sur nos structures reconstruites afin d'identifier les paramètres macroscopiques qui nous intéressent. Ces expériences permettent également de valider ou non les hypothèses effectuées lors de l'établissement des équations du milieu équivalent. Les paramètres ajustés sont la viscosité du milieu équivalent, le coefficient d'échange convectif et le coefficient d'extinction / The macroscopic and gigascopic scale description of forest fires allows physical modelings of the propagation which can predict the fire evolution with a better accuracy than usually developed empirical Rothermel-like models. However, those models need fitting for their parameters which cannot be measured directly as the models equations are related to the equivalent media at the considered scale and not related to the air and the vegetal material. The equivalent media properties are related to the inner media properties, but the inner media properties knowledge does not allow directly the equivalent media properties knowledge. This work is then aiming on the vegetal medium reconstruction using fractal geometry. Geometrical parameters measurement methods used in forestry sciences are applied for the vegetal modeling validation. Numerical studies are finally done on the reconstructed structures to fit the relevant macroscopic scale parameters. Those studies also allow us to validate or invalidate the assumptions which have been done for the equivalent medium equation development. Those parameters are: the equivalent medium viscosity, the convective heat transfer coefficient and the extinction coefficient

This thesis examines scaling properties of petrol and diesel prices in the Czech Republic and a crude oil price over the period from January 2004 to February 2013. Using generalised Hurst exponent and multifractal detrended fluctuation analysis techniques we find out that crude oil market is efficient, do not contain long memory and the returns exhibit monofractal behaviour. On the other hand, petrol and diesel markets in the Czech Republic are not efficient, because their returns contain long-range dependence in autocorrelations and exhibit multifractal behaviour caused mostly by fat-tailed distribution. Thus, fuels can be modelled by complex methods like Markov switching multifractal model. JEL Classification C15, C16, C46 Keywords petrol, diesel, crude oil, long memory, multifrac- tality, GHE, MF-DFA Author's e-mail martin.baletka@ies-prague.org Supervisor's e-mail kristoufek@ies-prague.org Abstrakt Tato práce zkoumá škálování cen benzínu a motorové nafty v České repub- lice a ceny ropy na datech v období od ledna 2004 do února 2013. Použitím metod zobecněného Hurstova exponentu a multifraktální detrendované fluk- tuační analýzy jsme zjistili, že trh s ropou je efektivní, bez přítomnosti dlouhé paměti v autokorelacích a výnosy na trhu s ropou vykazují monofraktální...

Cette thèse est consacrée à l'application et au développement de méthodes biostatistiques originales pour des applications médicales et cliniques concernant plus particulièrement les pathologies respiratoires. Il s'agit ainsi d'un travail de recherche transversale, visant à la modélisation de données hétérogènes, colinéaires et de grande dimension pour des applications cliniques. Un état de l'art traitant du diagnostic de l'asthme et de hyperactivité bronchique a tout d'abord été dressé, avant de proposer une première application statistique, prenant la forme de modèles de régressions multiples. Ce type de modèle étant particulièrement sensible à la dimension et la colinéarité des données, les chapitres suivants proposent plusieurs améliorations, après avoir explicité en détail l'enjeu et les méthodes actuelles d'analyse de données de grande dimension. Un premier modèle de classification hiérarchique non supervisé a été mis au point et appliqué au cas de la quantification du piégeage aérique. Un algorithme de régression Partial Least Square a également été mis en œuvre, prédisant une ou plusieurs variables Y à partir d'un set de variables X hétérogènes et colinéaires, ce qui a permis de mettre en évidence l'impact de l'âge sur les petites voies aériennes, tout en considérant de nombreux autres paramètres. Enfin, un algorithme d'analyse fractale a été créé, en vue de quantifier en une seule valeur la complexité spatiale et géométrique d'images de scanners thoraciques, cela constituant un innovant outil d'aide au diagnostic radiologique. / This thesis outlines new statistic methods devoted to clinical and medical applications, dealing more precisely with respiratory diseases. Our goal was to model and analyze high-dimensional clinical data, often heterogeneous, and collinear. A clinical state of the art of asthma diagnosis and bronchial hyperreactivity was first stated, before proposing a first statistical application, which took the shape of multiple regression models. This type of models is particularly tricky when treating high-dimensional collinear data, which is why the other chapters are an enhancement of this first model. Firstly, a non-supervised hierarchical classification was carried out and applied to air trapping quantification. A Partial Least Square regression model was also executed, allowing prediction of one or more variables from a set of X variables, which allowed us to highlight the impact of age on small airway impairment. Finally, a fractal analysis was performed, in order to quantify the geometrical and spatial complexity of a CT scan image into a single value. This kind a prospective methodology, where the statistics are directly involved in the clinical work, represents a brand new tool which can help medical diagnosis.

L’étude des propriétés fractales des séries biologiques fait l’objet d’un intérêt croissant. Néanmoins la littérature met en évidence une ambiguïté quand à l’explication causale de la présence de ces séries temporelles ne permettant pas de distinguer entre l’adaptation effective réalisée par un sujet ou ses capacités d’adaptabilité globales. La présente thèse a pour objectif de décorréler ces deux notions, notamment en liant le niveau comportemental au niveau cérébral. Notre première étude a permise de mettre en évidence que les propriétés mono-fractales pourraient refléter l’adaptabilité des sujets tandis que les propriétés multifractales seraient liées à l’adaptation effective réalisée au cours de la tâche. La seconde étude à mise en évidence une corrélation entre les propriétés multifractales et le nombre de réseaux cérébraux mis en oeuvre au cours de la tâche, reflétant l’adaptation effective aux contraintes expérimentales imposées. Les résultats de ces travaux de thèse nous ont permis de mieux comprendre la signification fonctionnelle des analyses fractales en terme d’adaptation effective et d’adaptabilité. / The study of fractal properties in biological time series is of increasing interest. Nevertheless, the literature highlights an ambiguity on the causal explanation of the presence of these time series which does not make it possible to distinguish between the effective adaptation made by a subject or his overall adaptability capacities. The aim of this dissertation is to decorrelate these two notions, notably by linking the behavioral level to the cerebral level. Our first study allowed to highlight that the mono-fractal properties could reflect the adaptability of the subjects whereas the multifractal properties would be related to the effective adaptation carried out during the task. The second study showed a correlation between the multifractal properties and the number of brain networks implemented during the task, reflecting the effective adaptation to the experimental constraints imposed. The results of this work have allowed us to better understand the functional meaning of fractal analyzes in terms of effective adaptation and adaptability.