Steeltown scene : genre, performance and identity in the alternative independent music scene in Hamilton, Ontario

This thesis examines the independent alternative music scene in the city of Hamilton, Ontario, also known, with reference to its industrial heritage, as "Steeltown." Drawing on the growing literature on the relationship between place and popular music, on my own experience as a local musician, direct observation of performances and of venues and other sites of interaction, as well as ethnographic interviews with scene participants, I focus on the role of space, genre and performance within the scene, and their contribution to a sense of local identity. In particular, I argue that the live performance event is essential to the success of the local music scene, as it represents an immediate process, a connection between performers and audience, one which is temporally rooted in the present. My research suggests that the Hamilton alternative music scene has become postmodern, embracing forms of "indie" music that lie outside of mainstream taste, and particularly those which engage in the exploration and deconstruction of pre-existing genres. Eventually, however, the creative successes of an "indiescene" permeate mass culture and often become co-opted into the popular music mainstream, a process which, in turn, promotes new experimentation and innovation at the local level.

Possessions et exorcismes dans l'hagiographie byzantine primitive (IVe-VIIe siècle)

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Coexistence cirrhose biliaire primitive et sclérodermie systémique : étude avec capillaroscopie et immunologie

Objectif : Déterminer la prévalence de la Sclérose systémique (SSc) chez les patients atteints de cirrhose biliaire primitive (CBP) et décrire les caractéristiques cliniques, pronostiques, immunologiques et capillaroscopiques chez les patients avec et sans SSc. Méthode : Étude descriptive de 100 patients avec CBP naïfs de SSc référés par les gastroentérologues. Un examen physique ainsi qu’un prélèvement sanguin et une capillaroscopie ont été réalisés. Résultats : Parmi les 22 patients diagnostiqués avec SSc, 13 n’avaient pas d’atteinte cutanée. Trente-neuf patients présentaient un phénomène de Raynaud. Dix-neuf étaient anticentromères (ACAs) positifs dont 18 avaient une SSc. Le groupe de CBP avec SSc avait un score Mayo meilleur et une atteinte histologique moins sévère. Une capillaroscopie anormale était retrouvée chez 29/100 patients. Les patients sans ACAs avaient une hypertension portale légèrement plus fréquente 14/81 (17,28%, p= 0,876) et une atteinte histologique hépatique plus sévère (89,5%, p=0,125). Le score Mayo était globalement meilleur dans le groupe des ACAs positifs. La sensibilité et la spécificité du test immunologique sont 95,45% et 93,59% respectivement. La capillaroscopie a une sensibilité de 78% et une spécificité de 94% pour le diagnostic de la SSc dans la population de CBP.   Conclusion : La SSc est fréquente dans la CBP, d’où l’intérêt de rechercher systématiquement les signes cliniques subtiles de la SSc, notamment le phénomène de Raynaud, et de demander une sérologie spécifique et une capillaroscopie pour identifier une SSc débutante.

Global Depth Perception from Familiar Scene Structure

In the absence of cues for absolute depth measurements as binocular disparity, motion, or defocus, the absolute distance between the observer and a scene cannot be measured. The interpretation of shading, edges and junctions may provide a 3D model of the scene but it will not inform about the actual "size" of the space. One possible source of information for absolute depth estimation is the image size of known objects. However, this is computationally complex due to the difficulty of the object recognition process. Here we propose a source of information for absolute depth estimation that does not rely on specific objects: we introduce a procedure for absolute depth estimation based on the recognition of the whole scene. The shape of the space of the scene and the structures present in the scene are strongly related to the scale of observation. We demonstrate that, by recognizing the properties of the structures present in the image, we can infer the scale of the scene, and therefore its absolute mean depth. We illustrate the interest in computing the mean depth of the scene with application to scene recognition and object detection.

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Locomotor Virtual Patient Scene

BM1 Locomotor Virtual Patient screenshot

View-dependent information theory quality measures for pixel sampling and scene discretization in flatland

In this paper, we present view-dependent information theory quality measures for pixel sampling and scene discretization in flatland. The measures are based on a definition for the mutual information of a line, and have a purely geometrical basis. Several algorithms exploiting them are presented and compare well with an existing one based on depth differences

Efficient 3D scene modeling and mosaicing

El modelat d'escenes és clau en un gran ventall d'aplicacions que van des de la generació mapes fins a la realitat augmentada. Aquesta tesis presenta una solució completa per a la creació de models 3D amb textura. En primer lloc es presenta un mètode de Structure from Motion seqüencial, a on el model 3D de l'entorn s'actualitza a mesura que s'adquireix nova informació visual. La proposta és més precisa i robusta que l'estat de l'art. També s'ha desenvolupat un mètode online, basat en visual bag-of-words, per a la detecció eficient de llaços. Essent una tècnica completament seqüencial i automàtica, permet la reducció de deriva, millorant la navegació i construcció de mapes. Per tal de construir mapes en àrees extenses, es proposa un algorisme de simplificació de models 3D, orientat a aplicacions online. L'eficiència de les propostes s'ha comparat amb altres mètodes utilitzant diversos conjunts de dades submarines i terrestres.

The counter-propagating Rossby-wave perspective on baroclinic instability. Part III: Primitive-equation disturbances on the sphere

Baroclinic instability of perturbations described by the linearized primitive quations, growing on steady zonal jets on the sphere, can be understood in terms of the interaction of pairs of counter-propagating Rossby waves (CRWs). The CRWs can be viewed as the basic components of the dynamical system where the Hamiltonian is the pseudoenergy and each CRW has a zonal coordinate and pseudomomentum. The theory holds for adiabatic frictionless flow to the extent that truncated forms of pseudomomentum and pseudoenergy are globally conserved. These forms focus attention on Rossby wave activity. Normal mode (NM) dispersion relations for realistic jets are explained in terms of the two CRWs associated with each unstable NM pair. Although derived from the NMs, CRWs have the conceptual advantage that their structure is zonally untilted, and can be anticipated given only the basic state. Moreover, their zonal propagation, phase-locking and mutual interaction can all be understood by ‘PV-thinking’ applied at only two ‘home-bases’—potential vorticity (PV) anomalies at one home-base induce circulation anomalies, both locally and at the other home-base, which in turn can advect the PV gradient and modify PV anomalies there. At short wavelengths the upper CRW is focused in the mid-troposphere just above the steering level of the NM, but at longer wavelengths the upper CRW has a second wave-activity maximum at the tropopause. In the absence of meridional shear, CRW behaviour is very similar to that of Charney modes, while shear results in a meridional slant with height of the air-parcel displacement-structures of CRWs in sympathy with basic-state zonal angular-velocity surfaces. A consequence of this slant is that baroclinically growing eddies (on jets broader than the Rossby radius) must tilt downshear in the horizontal, giving rise to up-gradient momentum fluxes that tend to accelerate the barotropic component of the jet.