The aerodynamic integration of an aero-engine intake system with the airframe can pose some notable challenges. This is particularly so for many military air- craft and is likely to become a more pressing issue for both new military systems with highly embedded engines as well as for novel civil aircraft configurations. During the late 1960s with the advent of turbo-fan engines, industry became in- creasingly aware of issues which arise due to inlet total pressure distortion. Since then, inlet-engine compatibility assessments have become a key aspect of any new development. In addition to total temperature and total pressure distortions, flow angularity and the associated swirl distortion are also known to be of notable con- cern. The importance of developing a rigorous methodology to understand the effects of swirl distortion on turbo-machinery has also become one of the major concerns of current design programmes. The goal of this doctoral research was to further the current knowledge on swirl distortion, and its adverse effects on engine performance, focusing on the turbo-machinery components (i.e. fans or compressors). This was achieved by looking into appropriate swirl flow descriptors and by correlating them against the compressor performance parameters (e.g loss in stability pressure ratios). To that end, a number of high-fidelity three-dimensional Computational Fluid Dynamics (CFD) models have been developed using two sets of transonic rotors (i.e. NASA Rotor 67 and 37), and a stator (NASA Stator 67B). For the numerical purpose, a boundary condition methodology for the definition of swirl distortion patterns at the inlet has been developed. Various swirl distortion numerical parametric studies have been performed using the modelled rotor configurations. Two types of swirl distortion pattern were investigated in the research, i.e. the pure bulk swirl and the tightly-wound vortex. Numerical simulations suggested that the vortex core location, polarity, size and strength greatly affect the compressor performance. The bulk swirl simula- tions also showed the dependency on swirl strength and polarity. This empha- sized the importance of quantifying these swirl components in the flow distortion descriptors. For this, a methodology have been developed for the inlet-engine compatibility assessment using different types of flow descriptors. A number of correlations have been proposed for the two types of swirl distortion investigated in the study.

Experimental mole fraction solubilities of several carboxylic acids (2-methoxybenzoic acid, 4-methoxybenzoic acid, 4-nitrobenzoic acid, 4-chloro-3-nitrobenzoic acid, 2-chloro-5-nitrobenzoic acid,2-methylbenzoic acid and ibuprofen) and 9-fluorenone, thianthrene and xanthene were measured in a wide range of solvents of varying polarity and hydrogen-bonding characteristics. Results of these measurements were used to calculate gas-to-organic solvent and water-to-organic solvent solubility ratios, which were then substituted into known Abraham process partitioning correlations. The molecular solute descriptors that were obtained as the result of these computations described the measured solubility data to within an average absolute deviation of 0.2 log units. The calculated solute descriptors also enable one to estimate many chemically, biologically and pharmaceutically important properties for the ten solutes studied using published mathematical correlations.

Orientadores: Hélio Pedrini, William Robson Schwartz / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-24T12:45:45Z (GMT). No. of bitstreams: 1 GonzalezValenzuela_RicardoEugenio_M.pdf: 22940228 bytes, checksum: 972bc5a0fac686d7eda4da043bbd61ab (MD5) Previous issue date: 2014 / Resumo: Descritores locais robustos normalmente compõem-se de vetores de características de alta dimensionalidade para descrever atributos discriminativos em imagens. A alta dimensionalidade de um vetor de características implica custos consideráveis em termos de tempo computacional e requisitos de armazenamento afetando o desempenho de várias tarefas que utilizam descritores de características, tais como correspondência, recuperação e classificação de imagens. Para resolver esses problemas, pode-se aplicar algumas técnicas de redução de dimensionalidade, escencialmente, construindo uma matrix de projeção que explique adequadamente a importancia dos dados em outras bases. Esta dissertação visa aplicar técnicas de redução linear de dimensionalidade aos descritores SIFT e SURF. Seu principal objetivo é demonstrar que, mesmo com o risco de diminuir a precisão dos vetores de caraterísticas, a redução de dimensionalidade pode resultar em um equilíbrio adequado entre tempo computacional e recursos de armazenamento. A redução linear de dimensionalidade é realizada por meio de técnicas como projeções aleatórias (RP), análise de componentes principais (PCA), análise linear discriminante (LDA) e mínimos quadrados parciais (PLS), a fim de criar vetores de características de menor dimensão. Este trabalho avalia os vetores de características reduzidos em aplicações de correspondência e de recuperação de imagens. O tempo computacional e o uso de memória são medidos por comparações entre os vetores de características originais e reduzidos / Abstract: Robust local descriptors usually consist of high dimensional feature vectors to describe distinctive characteristics of images. The high dimensionality of a feature vector incurs into considerable costs in terms of computational time and storage requirements, which affects the performance of several tasks that employ feature vectors, such as matching, image retrieval and classification. To address these problems, it is possible to apply some dimensionality reduction techniques, by building a projection matrix which explains adequately the importance of the data in other basis. This dissertation aims at applying linear dimensionality reduction to SIFT and SURF descriptors. Its main objective is to demonstrate that, even risking to decrease the accuracy of the feature vectors, the dimensionality reduction can result in a satisfactory trade-off between computational time and storage. We perform the linear dimensionality reduction through Random Projections (RP), Independent Component Analysis (ICA), Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Partial Least Squares (PLS) in order to create lower dimensional feature vectors. This work evaluates such reduced feature vectors in a matching application, as well as their distinctiveness in an image retrieval application. The computational time and memory usage are then measured by comparing the original and the reduced feature vectors. OBSERVAÇÃONa segunda folha, do arquivo em anexo, o meu nome tem dois pequenos erros / Mestrado / Ciência da Computação / Mestre em Ciência da Computação

Orientadores: Ricardo da Silva Torres, Hélio Pedrini / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-27T11:52:06Z (GMT). No. of bitstreams: 1 RoccaLayza_VladimirJaime_M.pdf: 7769260 bytes, checksum: a60ae46083facfc74cd79a4ab0c83c23 (MD5) Previous issue date: 2015 / Resumo: Vários sistemas de vigilância baseados no uso de múltiplas câmeras têm sido propostos recentemente. No entanto, a identificação de pessoas em sequências de vídeos obtidas por várias câmeras com vistas não sobrepostas, comumente conhecida como reidentificação de pessoas, é um problema em aberto. As razões para que este problema seja considerado desafiador referem-se principalmente às restrições nas quais o problema deve ser resolvido. Estas restrições são definidas a partir das características do cenário e dos objetos de interesse (as pessoas): primeiro, as características biométricas de pessoas não podem ser utilizadas como características discriminantes; segundo, a aparência das pessoas muda drasticamente em virtude de variações na posição, iluminação e parâmetros de câmera. Tais restrições fazem com que uma mesma pessoa possa ser observada por múltiplas câmeras como uma pessoa diferente para cada uma delas. Nesta pesquisa, busca-se investigar alternativas para a criação de sistemas de vigilância visando à reidentificação de pessoas. Foram empregadas técnicas de recuperação de imagens por conteúdo tais como descritores de imagens tradicionais e propostos recentemente, análise multiescala, e técnicas de rank aggregation. Os experimentos realizados consideram a utilização de quatro bases de dados comumente utilizadas na avaliação de sistemas de reidentificação de pessoas. Os resultados obtidos mostraram que as técnicas de recuperação de imagens por conteúdo são promissoras para a reidentificação de pessoas, obtendo resultados comparáveis aos métodos do estado da arte / Abstract: Several surveillance systems based on the use of multiple cameras have been proposed recently. However, the identification of people in video sequences obtained from several cameras with non-overlapping views, commonly known as the person reidentification problem, is still an open problem. Person reidentification is a challenging problem due to the constraints under which the problem should be solved. These constraints come from the characteristics of the scenario and the objects of interest (people): first, biometric features may not be used as discriminant information; second, appearance is dramatically modified by changes in position, lighting conditions, and camera parameters. Therefore, in these conditions a unique person can be ''seen'' as a distinct person by different cameras. This research is focused on the investigation of alternatives for the creation of surveillance systems aiming at person reidentification. We intend to use content-based image retrieval techniques, such as traditional and recently proposed image descriptors, multiscale analysis, and rank aggregation approaches. Conducted experiments considered the use of four different datasets, commonly used in the evaluation of person reidentification systems. Obtained results show that the content-based image retrieval techniques are promising to reidentify people, producing equivalent results to the state-of-the-art methods / Mestrado / Ciência da Computação / Mestre em Ciência da Computação

This master thesis deals with design and implementation of algorithms for image analysis of object surface texture for the purpose of automating the surface grinding process. In the first part of this thesis, a search was performed in the field of image analysis of object surface texture. The proposed descriptors were tested on the created annotated database of texture images. Subsequently, a scene for image acquisition of the machined object was designed and assembled, and the grinding process was automated based on the results of the previous analysis. The implementation and achieved results were evaluated and other possible improvements were proposed.

Předmětem této práce je vytvoření metody sloužící k identifikaci organismů z metagenomických dat. Doposud k tomuto účelu spolehlivě dostačovaly metody založené na zarovnání sekvencí s referenční databází. Množství dat ovšem s rozvojem sekvenačních technik rapidně roste a tyto metody se tak stávají díky své výpočetní náročnosti nevhodnými. V této diplomové práci je popsán postup nové techniky, která umožňuje klasifikaci metagenomických dat bez nutnosti zarovnání. Metoda spočívá v převedení sekvenovaných úseků na genomické signály ve formě fázových reprezentací, ze kterých jsou následně extrahovány vektory příznaků. Těmito příznaky jsou tři Hjorthovy deskriptory. Ty jsou dále vystaveny metodě maximalizace věrohodnosti směsi Gaussovských rozložení, která umožňuje spolehlivé roztřídění fragmentů podle jejich příslušnosti k organismu.

In order to meet the needs of people with hearing loss today hearing aids are custom designed. Increasingly accurate 3-D scanning technology has contributed to the transition from conventional production scenarios to software based processes. Nonetheless, there is a tremendous amount of manual work involved to transform an input 3-D surface mesh of the outer ear into a final hearing aid shape. This manual work is often cumbersome and requires lots of experience which is why automatic solutions are of high practical relevance. This work is concerned with the recognition of 3-D surface meshes of ear implants. In particular we present a semantic part-labeling framework which significantly outperforms existing approaches for this task. We make at least three contributions which may also be found useful for other classes of 3-D meshes. Firstly, we validate the discriminative performance of several local descriptors and show that the majority of them performs poorly on our data except for 3-D shape contexts. The reason for this is that many local descriptor schemas are not rich enough to capture subtle variations in form of bends which is typical for organic shapes. Secondly, based on the observation that the left and the right outer ear of an individual look very similar we raised the question how similar the ear shapes among arbitrary individuals are? In this work, we define a notion of distance between ear shapes as building block of a non-parametric shape model of the ear to better handle the anatomical variability in ear implant labeling. Thirdly, we introduce a conditional random field model with a variety of label priors to facilitate the semantic part-labeling of 3-D meshes of ear implants. In particular we introduce the concept of a global parametric transition prior to enforce transition boundaries between adjacent object parts with an a priori known parametric form. In this way we were able to overcome the issue of inadequate geometric cues (e.g., ridges, bumps, concavities) as natural indicators for the presence of part boundaries. The last part of this work offers an outlook to possible extensions of our methods, in particular the development of 3-D descriptors that are fast to compute whilst at the same time rich enough to capture the characteristic differences between objects residing in the same class.

Pågående klimatförändringar med påföljande ökad nederbörd ger förhöjd risk för översvämningar. Det är därför viktigt att kunna göra förutsägelser för var översvämning riskerar att ske. Förutsättningarna att göra sådana prediktioner med geografiska informationssystem ökar då Sveriges geografi karteras i allt större utsträckning. Syftet med uppsatsen är att utföra och analysera en modell för kartering av översvämningsrisk av väg. Det görs genom GIS-analys av geografiska data, baserade på platsspecifika egenskaper i landskapet, för ett område i Östersunds kommun där två vägavsnitt översvämmades 2008. De platsspecifika egenskaperna kvantifieras i s.k. fysikaliska avrinningsområdesegenskaper (FAE). Vidare syftar uppsatsen till att undersöka hur dessa FAE kan kopplas till översvämningsrisk, på vilket sätt vägen inverkat på risken för att översvämning uppstår och hur modellen kan användas i ett allmänt syfte att kartera översvämningsrisk. Resultatet visar att det finns en korrelation mellan ett flertal FAE och risken för översvämning. Det kan dock göras gällande från resultatet att dessa inte är så entydiga att det med användning av FAE går att allmänt förutsäga översvämningsrisk och riskkarteringen indikerar inte heller att det förelåg större risk i de områden där översvämning dokumenterades. Slutsatsen gällande om det går att applicera den här metoden allmänt för att kartera översvämningsrisk för andra områden är att det i dagsläget är komplicerat och osäkert att göra den här typen av kartering. Med förfinade metoder och noggrannare kartering av geografin kan den här typen av modellering få större träffsäkerhet då sambanden mellan platsspecifika egenskaper i landskapet och översvämningsrisken är vetenskapligt belagd. / Ongoing climate change with increasing levels of precipitation elevates the risk of flooding. It is therefore important to be able to make predictions of when and where such flooding events will occur. The conditions for making such predictions in geographic information systems is increasing at pace with the mapping of the geography of Sweden. The purpose of this paper is to conduct and analyze a planning model for flood hazard by GIS-analysis for an area located in Östersund municipality where two road sections were flooded in 2008. The analysis is based on site specific properties in the terrain. The site specific properties are quantified as Physical Catchment Descriptors. The purpose is furthermore to investigate how these FAE can be linked to the risk of flooding, which role the road plays in causing flooding and in what way the planning model can be used to map flood hazard. The result shows that there is a correlation between several of the FAE and the risk of flooding. These findings are however not that unambiguous to make use of the FAE as general indicators of flood hazard. The mapping of flood hazard in the studied area did not implicate a clear correlation between flood hazard and the flooding events. The conclusion regarding if it is possible to apply this method for mapping probability of flood hazards is that it is uncertain and complicated. With more sophisticated models and more detailed geographical data this type of modelling can get more accurate, since the relation between FAE and flood hazard has been verified.

Ces dernières années, la quantité de données visuelles produites par divers types de capteurs est en augmentation permanente. L'interprétation et l'indexation automatique de telles données constituent des défis importants pour les domaines liés à la reconnaissance de formes et la vision par ordinateur. Dans ce contexte, la position relative des différents objets d'intérêt composant les images représente une information particulièrement importante pour interpréter leur contenu. Les relations spatiales sont en effet porteuses d'une sémantique riche, qui est fortement liée à la perception humaine. Les travaux de recherche présentés dans cette thèse proposent ainsi d'explorer différentes approches génériques de description de l'information spatiale, en vue de les intégrer dans des systèmes de reconnaissance et d'interprétation d'images de haut niveau. Tout d'abord, nous présentons une approche pour la description de configurations spatiales complexes, où les objets peuvent être imbriqués les uns dans les autres. Cette notion est formalisée par deux nouvelles relations spatiales, nommées enlacement et entrelacement. Nous proposons un modèle qui permet de décrire et de visualiser ces configurations avec une granularité directionnelle. Ce modèle est validé expérimentalement pour des applications en imagerie biomédicale, en télédétection et en analyse d'images de documents. Ensuite, nous présentons un cadre d'apprentissage de relations spatiales composites à partir d'ensembles d'images. Inspirée des approches par sacs de caractéristiques visuelles, cette stratégie permet de construire des vocabulaires de configurations spatiales apparaissant dans les images, à différentes échelles. Ces caractéristiques structurelles peuvent notamment être combinées avec des descriptions locales, conduisant ainsi à des représentations hybrides et complémentaires. Les résultats expérimentaux obtenus sur différentes bases d'images structurées permettent d'illustrer l'intérêt de cette approche pour la reconnaissance et la classification d'images. / In recent years, the amount of visual data produced by various types of sensors has been continuously increasing. The automatic interpretation and indexation of such data constitute an important challenge in the fields of pattern recognition and computer vision. In this context, the relative position of the different objects of interest depicted in images represents particularly important information for the interpretation of their content. Spatial relations indeed carry rich semantics that are strongly tied with human perception. The research work presented in this thesis thus proposes to explore different generic approaches to the description of spatial information, in order to integrate them in high-level image recognition and understanding systems. First, we present an approach for the description of complex spatial configurations, where objects can be imbricated in each other. This notion is formalized by two novel spatial relations, namely enlacement and interlacement. We propose a model to describe and to visualize these configurations with directional granularity. This model is experimentally validated for applications in biomedical imaging, remote sensing and document image analysis. Then, we present a framework for learning composite spatial relations from image datasets. Inspired by bags of visual features approaches, this strategy allows to build vocabularies of spatial configurations occurring across images, at different scales. These structural features can notably be combined with local descriptions, leading to hybrid and complementary representations. Experimental results obtained for different datasets of structured images highlight the interest of this approach for image recognition and classification tasks.

Cette thèse traite de l’utilisation de la couleur en vision par ordinateur. Deux problèmes sont étudiés : - l’estimation d’illuminants, - la mise en correspondance de descripteurs locaux pour la comparaison d’images couleur. Les surfaces achromatiques renvoient un spectre lumineux ayant la même distribution fréquentielle que le spectre de l’illuminant. Les détecter permet donc de recouvrer l'illuminant. En supposant que l’ensemble des couleurs que peut prendre un illuminant est limité (équation de Planck), il est possible de sélectionner les pixels appartenant à une surface potentiellement grise. Une méthode de vote est alors appliquée, permettant de sélectionner un ou plusieurs illuminants. L’algorithme final possède de nombreux avantages : il est efficace, intuitif, ne nécessite pas de phase d’apprentissage et requiert peu de paramètres, qui s’avèrent stables. De plus, la méthode de vote permet de s’adapter aux cas où plusieurs sources lumineuses éclairent la scène photographiée. Les descripteurs locaux sont des outils puissants pour comparer les images. Cependant, le rôle de la couleur dans l’étape d’appariement a fait l’objet de peu d’études. Le problème principal que nous considérons ici est celui de l’apport de la couleur pour l’appariement de descripteurs locaux. Un usage local de la couleur permet-il de désambiguïser les situations où la luminance seule est insuffisante ? Et si oui, dans quelles proportions ? Nous proposons quatre descripteurs permettant de décrire de manière détaillée le contexte local de points clés dans l’optique de les apparier. Les expériences proposées montrent clairement l’apport de la couleur pour la mise en correspondance locale. / This thesis addresses the use of color in image processing and computer vision. Two problems are studied: - illuminant estimation, - local descriptors matching for color images comparison. Achromatic surfaces are defined as surfaces reflecting a spectrum with the same frequency dsitribution than the illuminant. Consequently, revovering these surfaces allows to estimate the illuminant. Assuming that the range of colors taken by an illuminant is limited (Planck equation), it is possible to select the pixels belonging to a potentially gray surface. A voting procedure is then applied to select one or more illuminants. The proposed algorithm has many advantages: it is effective, intuitive, does not rely on a learning phase and requires only few parameters. In addition, the voting procedure can be adapted to handle cases where multiple light sources of different colors illuminate the scene. Local descriptors are powerful tools to compare images. However, few studies concern the influence of color in the matching step. The main problem that we consider here is the contribution of the color matching of local descriptors. Does the local use of color allow to disambiguate situations where the luminance alone is insufficient ? And if so, how much? We propose four descriptors to precisely describe the local context of key points in the matching step. The main idea developed here is that accurate information can only be obtained by describing both the color distributions and transitions between colors. The many experiences presented clearly show the positive contribution of color to the reliability of the local matching.