Made available in DSpace on 2014-12-17T15:48:13Z (GMT). No. of bitstreams: 1 LaurindoSBN.pdf: 1520391 bytes, checksum: 86f5072a56e661766a5174bce88b82d5 (MD5) Previous issue date: 2007-09-21 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / Non-Photorealisitc Rendering (NPR) is a class of techniques that aims to reproduce artistic techniques, trying to express feelings and moods on the rendered scenes, giving an aspect of that they had been made "by hand". Another way of defining NPR is that it is the processing of scenes, images or videos into artwork, generating scenes, images or videos that can have the visual appeal of pieces of art, expressing the visual and emotional characteristics of artistic styles. This dissertation presents a new method of NPR for stylization of images and videos, based on a typical artistic expression of the Northeast region of Brazil, that uses colored sand to compose landscape images on the inner surface of glass bottles. This method is comprised by one technique for generating 2D procedural textures of sand, and two techniques that mimic effects created by the artists using their tools. It also presents a method for generating 21 2D animations in sandbox from the stylized video. The temporal coherence within these stylized videos can be enforced on individual objects with the aid of a video segmentation algorithm. The present techniques in this work were used on stylization of synthetic and real videos, something close to impossible to be produced by artist in real life / Renderiza??o N?o Fotoreal?stica (NPR) ? uma classe de t?cnicas que almejam reproduzir t?cnicas art?sticas, tentado expressar sentimentos e emo??es nas cenas renderizadas, dando um aspecto de que foram feitas "manualmente". Outra forma de definir a NPR ? como o processamento de cenas, imagens ou v?deos para gera??o de trabalhos de arte, gerando cenas, imagens ou v?deos que podem ter o atrativo visual de pe?as art?sticas, expressando caracter?sticas visuais e emocionais do estilo art?stico. Esta disserta??o apresenta um novo m?todo de NPR para estiliza??o de imagens e v?deos baseado em uma express?o art?stica t?pica da regi?o Nordeste do Brasil, que usa areia colorida para compor imagens de paisagens na superf?cie interna de garrafas de vidro. Este m?todo possui uma t?cnica para gera??o de texturas procedurais de areia 2D, e duas t?cnicas que imitam os efeitos criados pelos artes?es usando sua ferramenta. Al?m disso, essa disserta??o apresenta tamb?m um m?todo para gera??o de anima??es 21 2D em caixas de areia a partir do v?deo estilizado. A coer?ncia temporal nos v?deos estilizados pode ser for?ada nos objetos individuais do v?deo com aux?lio de um algoritmo de segmenta??o de v?deo. As t?cnicas apresentadas neste trabalho s?o usadas na estiliza??o de v?deos reais e sint?ticos, algo quase imposs?vel de ser produzido pelo artes?o na vida real

Depuis la mise en place en 2010, d’une nouvelle tarification française sur le tarif de l’énergie géothermique, l’Alsace est la région de France la plus dynamique quant à la réalisation de forages géothermiques profonds à haute température (>150°C). Ainsi, l’approche géologique, qui a été primordiale pour les forages de Rittershoffen, le sera encore davantage pour les projets à venir compte tenu de la méconnaissance géologique de certaines zones profondes du bassin rhénan. Cette étude propose d’appréhender la compréhension de l’architecture stratigraphique et séquentielle des formations de la couverture sédimentaire rhénane. 15 puits profonds ont été réinterprétés et corrélés à travers l’ensemble du bassin, permettant l’élaboration d’une colonne stratigraphique complète incluant le sommet et la base de chaque formation. Ces réinterprétations ont également mis en lumière le signal caractéristique de la diagraphie gamma-ray (GR) de chacune des formations de la colonne stratigraphique rhénane. De plus, la caractérisation lithostratigraphique du passage entre le socle et la couverture sédimentaire a fait l’objet d’un axe important de recherche. / Since the introduction of a new French pricing system for geothermal energy in 2010, Alsace has been the most dynamic region in France for deep geothermal drilling at high temperatures (>150°C). Thus, the geological approach, which has been essential for the Rittershoffen boreholes, will be even more for future projects given the lack of geological knowledge of some deep parts of the URG. This study aims at understanding the stratigraphic and sequential architecture of the formations of the URG sedimentary cover. 15 deep wells were reinterpreted and correlated throughout the basin, allowing the development of a complete stratigraphic column including the top and base of each formation. These reinterpretations also highlighted the characteristic gamma-ray signal (GR) of each of the formations in the URG stratigraphic column. In addition, the lithostratigraphic characterization of the transition between the basement and the sedimentary cover was the subject of an important research focus.

This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well constrained. They present interesting challenges for Bayesian inference, which attempts to quantify our knowledge of the universe given our astrophysical data. A dark energy equation of state reconstruction analysis finds that the data favours the vacuum dark energy equation of state $w {=} -1$ model. Deviations from vacuum dark energy are shown to favour the super-negative ‘phantom’ dark energy regime of $w {< } -1$, but at low statistical significance. The constraining power of various datasets is quantified, finding that data constraints peak around redshift $z = 0.2$ due to baryonic acoustic oscillation and supernovae data constraints, whilst cosmic microwave background radiation and Lyman-$\alpha$ forest constraints are less significant. Specific models with a conformal time symmetry in the Friedmann equation and with an additional dark energy component are tested and shown to be competitive to the vacuum dark energy model by Bayesian model selection analysis: that they are not ruled out is believed to be largely due to poor data quality for deciding between existing models. Recent detections of gravitational waves by the LIGO collaboration enable the first gravitational wave tests of general relativity. An existing test in the literature is used and sped up significantly by a novel method developed in this thesis. The test computes posterior odds ratios, and the new method is shown to compute these accurately and efficiently. Compared to computing evidences, the method presented provides an approximate 100 times reduction in the number of likelihood calculations required to compute evidences at a given accuracy. Further testing may identify a significant advance in Bayesian model selection using nested sampling, as the method is completely general and straightforward to implement. We note that efficiency gains are not guaranteed and may be problem specific: further research is needed.