Soil surface textures, Salem County, New Jersey /

"October 1986."

Génération souverainiste? L'engagement des jeunes au sein du mouvement souverainiste québécois : le cas du Parti québécois

Depuis la défaite du Oui au référendum de 1995, nous observons une perte de vitesse du mouvement souverainiste québécois. Cette dernière est d’abord perceptible d’un point de vue électoral où nous observons une baisse constante des appuis aux partis souverainistes, et ensuite relativement au fractionnement social et idéologique du mouvement souverainiste. Dans un tel contexte, nous nous attardons, dans le cadre de ce mémoire, à l’engagement des jeunes âgé-e-s de 20 à 26 ans au sein du Parti québécois (PQ). Ces personnes ont commencé à s’impliquer dans ce parti alors que le mouvement souverainiste était déjà caractérisé par une perte de vitesse et n’ont jamais connu les moments effervescents de celui-ci. Suite à seize entrevues semi-directives réalisées avec des militant-e-s du PQ, ce mémoire a pour but de comprendre les processus d’engagement de ces personnes. À l’aide d’une analyse sociologique des parcours d’engagement, nous démontrons d’abord que plusieurs types de parcours ont pu mener ces jeunes à s’engager au PQ. Ensuite, nous soulignons le fait que des éléments du passé, notamment par l’entremise des cours d’histoire et de la socialisation familiale, ont eu une plus grande importance que ceux d’actualité pour leur prise de conscience souverainiste. Nous montrons aussi que ces jeunes appartiennent à une génération politique pour laquelle les grands évènements de l’histoire du mouvement souverainiste ne peuvent plus être considérés comme étant des moments critiques des parcours d’engagement. Nous démontrons finalement que l’analyse des orientations politiques des personnes permet de mieux comprendre les différences entre les différents processus d’engagement.

Génération souverainiste? L'engagement des jeunes au sein du mouvement souverainiste québécois : le cas du Parti québécois

Depuis la défaite du Oui au référendum de 1995, nous observons une perte de vitesse du mouvement souverainiste québécois. Cette dernière est d’abord perceptible d’un point de vue électoral où nous observons une baisse constante des appuis aux partis souverainistes, et ensuite relativement au fractionnement social et idéologique du mouvement souverainiste. Dans un tel contexte, nous nous attardons, dans le cadre de ce mémoire, à l’engagement des jeunes âgé-e-s de 20 à 26 ans au sein du Parti québécois (PQ). Ces personnes ont commencé à s’impliquer dans ce parti alors que le mouvement souverainiste était déjà caractérisé par une perte de vitesse et n’ont jamais connu les moments effervescents de celui-ci. Suite à seize entrevues semi-directives réalisées avec des militant-e-s du PQ, ce mémoire a pour but de comprendre les processus d’engagement de ces personnes. À l’aide d’une analyse sociologique des parcours d’engagement, nous démontrons d’abord que plusieurs types de parcours ont pu mener ces jeunes à s’engager au PQ. Ensuite, nous soulignons le fait que des éléments du passé, notamment par l’entremise des cours d’histoire et de la socialisation familiale, ont eu une plus grande importance que ceux d’actualité pour leur prise de conscience souverainiste. Nous montrons aussi que ces jeunes appartiennent à une génération politique pour laquelle les grands évènements de l’histoire du mouvement souverainiste ne peuvent plus être considérés comme étant des moments critiques des parcours d’engagement. Nous démontrons finalement que l’analyse des orientations politiques des personnes permet de mieux comprendre les différences entre les différents processus d’engagement.

Nodulation, gas exchanges and production of peanut cultivated with Bradyrhizobium in soils with different textures.

Nitrogen fertilization from biological source is an uncommon practice for peanut growers due to the limited results, mainly in environments with water restriction. In this study, the response of a commercial Bradyrhizobium was evaluated on the nodulation and production of peanuts grown in sandy and medium textured soils. Two experiments using different soils were carried out in the field during the dry season, in Campina Grande, Paraíba State, Brazil. Three peanut genotypes were submitted to the following treatments: 1-no nitrogen fertilization (control), 2- chemical fertilization (ammonium sulfate) and 3- inoculation with Bradyrhizobium [commercial strain BR 1405 (SEMIA 6144)]. A completely randomized 3x3 factorial design was adopted with five repetitions for both experiments. The evaluates variables were: height of the main stem, number of nodes/plant, root length, root dry weight, weight of pods/plant and number of pods/plant. In addition, gas exchanges were estimated using IRGA apparatus. Both genotypes (BRS Havana and L7 Bege) were benefited in relation to production due to an inoculation with SEMIA 6144. No physiological response was verified in genotypes or N-treatments to gas exchange, excepting for the Ci/Ca ratio in the medium textured soil experiment. BRS Havana showed low Ci/Ca ratio in Bradyrhizobium treatment, indicating that SEMIA 6144 improved the plants photosynthetic efficiency.

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.

Volcanic stratigraphy, alteration zoning, and vein paragenesis of the Sascha-Pelligrini low-sulphidation epithermal system, Santa Cruz, Argentina

The Sascha-Pelligrini low-sulphidation epithermal system is located on the western edge of the Deseado Massif, Santa Cruz Province, Argentina. Outcrop sampling has returned values of up to 160g/t gold and 796g/t silver, with Mirasol Resources and Coeur D.Alene Mines currently exploring the property. Detailed mapping of the volcanic stratigraphy has defined three units that comprise the middle Jurassic Chon Aike Formation and two units that comprise the upper Jurassic La Matilde Formation. The Chon Aike Formation consists of rhyodacite ignimbrites and tuffs, with the La Matilde Formation including rhyolite ash and lithic tuffs. The volcanic sequence is intruded by a large flow-banded rhyolite dome, with small, spatially restricted granodiorite dykes and sills cropping out across the study area. ASTER multispectral mineral mapping, combined with PIMA (Portable Infrared Mineral Analyser) and XRD (X-ray diffraction) analysis defines an alteration pattern that zones from laumontite-montmorillonite, to illite-pyritechlorite, followed by a quartz-illite-smectite-pyrite-adularia vein selvage. Supergene kaolinite and steam-heated acid-sulphate kaolinite-alunite-opal alteration horizons crop out along the Sascha Vein trend and Pelligrini respectively. Paragenetically, epithermal veining varies from chalcedonic to saccharoidal with minor bladed textures, colloform/crustiform-banded with visible electrum and acanthite, crustiform-banded grey chalcedonic to jasperoidal with fine pyrite, and crystalline comb quartz. Geothermometry of mineralised veins constrains formation temperatures from 174.8 to 205.1¡ÆC and correlates with the stability field for the interstratified illite-smectite vein selvage. Vein morphology, mineralogy and associated alteration are controlled by host rock rheology, permeability, and depth of the palaeo-water table. Mineralisation within ginguro banded veins resulted from fluctuating fluid pH associated with selenide-rich magmatic pulses, pressure release boiling and wall-rock silicate buffering. The study of the Sascha-Pelligrini epithermal system will form the basis for a deposit-specific model helping to clarify the current understanding of epithermal deposits, and may serve as a template for exploration of similar epithermal deposits throughout Santa Cruz.

Particulate texture image analysis with applications

Texture analysis and textural cues have been applied for image classification, segmentation and pattern recognition. Dominant texture descriptors include directionality, coarseness, line-likeness etc. In this dissertation a class of textures known as particulate textures are defined, which are predominantly coarse or blob-like. The set of features that characterise particulate textures are different from those that characterise classical textures. These features are micro-texture, macro-texture, size, shape and compaction. Classical texture analysis techniques do not adequately capture particulate texture features. This gap is identified and new methods for analysing particulate textures are proposed. The levels of complexity in particulate textures are also presented ranging from the simplest images where blob-like particles are easily isolated from their back- ground to the more complex images where the particles and the background are not easily separable or the particles are occluded. Simple particulate images can be analysed for particle shapes and sizes. Complex particulate texture images, on the other hand, often permit only the estimation of particle dimensions. Real life applications of particulate textures are reviewed, including applications to sedimentology, granulometry and road surface texture analysis. A new framework for computation of particulate shape is proposed. A granulometric approach for particle size estimation based on edge detection is developed which can be adapted to the gray level of the images by varying its parameters. This study binds visual texture analysis and road surface macrotexture in a theoretical framework, thus making it possible to apply monocular imaging techniques to road surface texture analysis. Results from the application of the developed algorithm to road surface macro-texture, are compared with results based on Fourier spectra, the auto- correlation function and wavelet decomposition, indicating the superior performance of the proposed technique. The influence of image acquisition conditions such as illumination and camera angle on the results was systematically analysed. Experimental data was collected from over 5km of road in Brisbane and the estimated coarseness along the road was compared with laser profilometer measurements. Coefficient of determination R2 exceeding 0.9 was obtained when correlating the proposed imaging technique with the state of the art Sensor Measured Texture Depth (SMTD) obtained using laser profilometers.

Current AI in games : a review

As the graphics race subsides and gamers grow weary of predictable and deterministic game characters, game developers must put aside their “old faithful” finite state machines and look to more advanced techniques that give the users the gaming experience they crave. The next industry breakthrough will be with characters that behave realistically and that can learn and adapt, rather than more polygons, higher resolution textures and more frames-per-second. This paper explores the various artificial intelligence techniques that are currently being used by game developers, as well as techniques that are new to the industry. The techniques covered in this paper are finite state machines, scripting, agents, flocking, fuzzy logic and fuzzy state machines decision trees, neural networks, genetic algorithms and extensible AI. This paper introduces each of these technique, explains how they can be applied to games and how commercial games are currently making use of them. Finally, the effectiveness of these techniques and their future role in the industry are evaluated.

Dynamic texture reconstruction from sparse codes for unusual event detection in crowded scenes

Unusual event detection in crowded scenes remains challenging because of the diversity of events and noise. In this paper, we present a novel approach for unusual event detection via sparse reconstruction of dynamic textures over an overcomplete basis set, with the dynamic texture described by local binary patterns from three orthogonal planes (LBPTOP). The overcomplete basis set is learnt from the training data where only the normal items observed. In the detection process, given a new observation, we compute the sparse coefficients using the Dantzig Selector algorithm which was proposed in the literature of compressed sensing. Then the reconstruction errors are computed, based on which we detect the abnormal items. Our application can be used to detect both local and global abnormal events. We evaluate our algorithm on UCSD Abnormality Datasets for local anomaly detection, which is shown to outperform current state-of-the-art approaches, and we also get promising results for rapid escape detection using the PETS2009 dataset.

Unusual Event Detection in Crowded Scenes Using Bag of LBPs in spatio-temporal patches

Modelling events in densely crowded environments remains challenging, due to the diversity of events and the noise in the scene. We propose a novel approach for anomalous event detection in crowded scenes using dynamic textures described by the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) descriptor. The scene is divided into spatio-temporal patches where LBP-TOP based dynamic textures are extracted. We apply hierarchical Bayesian models to detect the patches containing unusual events. Our method is an unsupervised approach, and it does not rely on object tracking or background subtraction. We show that our approach outperforms existing state of the art algorithms for anomalous event detection in UCSD dataset.

Falls in Parkinson’s disease : evidence for altered stepping strategies on compliant surfaces

Background: Real-world environments comprise surfaces of different textures, densities and gradients, which can threaten postural stability and increase falls risk. However, there has been limited research that has examined how walking on compliant surfaces influences gait and postural stability in older people and PD patients. Methods: PD patients (n = 49) and age-matched controls (n = 32) were assessed using three dimensional motion analysis during self-paced walking on both firm and foam walkways. Falls were recorded prospectively over 12 months using daily falls calendars. Results: Walking on a foam surface influenced the temporospatial characteristics for all groups, but PD fallers adopted very different joint kinematics compared with controls. PD fallers also demonstrated reduced toe clearance and had increased mediolateral head motion(relative to walking velocity) compared with control participants. Conclusions: Postural control deficits in PD fallers may impair their capacity to attenuate surface-related perturbations and control head motion. The risk of falling for PD patients may be increased on less stable surfaces.

Adaptive bilateral filtering using saliency map for deblocking low bit rate videos

This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. The experimental results demonstrate that the proposed algorithm is effective in deblocking highly compressed video sequences and to avoid over-blurring of edges and textures in salient regions of image.

Compressive behaviour of nanocrystalline Mg-5Al alloys

Magnesium alloys are attracting increasing research interests due to their low density, high specific strength, good machinability and availability as compared to other structural materials. However, the deformation and failure mechanisms of nanocrystalline (nc) Mg alloys have not been well understood. In this work, the deformation behaviour of nc Mg-5Al alloys was investigated using compression test, with focus on the effects of grain size. The average grain size of the Mg- Al alloy was changed from 13 to 50 nm via mechanical milling. The results showed that grain size had a significant influence on the yield stress and ductility of the Mg alloys, and the materials exhibited increased strain rate sensitivity with a decrease in grain size. The deformation mechanisms were also strongly dependent on the grain sizes.