Développement des compétences informationnelles à l\u27université Laval : l\u27approche par compétences (Le)

Intervention aux 5èmes Rencontres FORMIST (Lyon, 9 juin 2005). Depuis de nombreuses années la bibliothèque de l\u27université Laval tente par différents moyens de rendre les étudiants compétents dans la maîtrise de l\u27usage de l\u27information. Suite à l\u27étude sur les connaissance en recherche documentaire des étudiants entrant en premier cycle dans les universités québécoises réalisée par la Crepuq, la bibliothèque a reconnu l\u27urgence de repenser son action en élaborant un programme de formation documentaire basé sur une approche différente par compétences

Panthéon de la guerre; panorama of the world war and its heroes, the largest painting in the world, 402 feet long--45 feet high, painted by twenty-eight famous French artists, assisted by more than one hundred other artists under the direction of Pierre Carrier-Belleuse and Auguste-Francois Gorguet and ...

The Panthéon de la Guerre was the world\u27s largest painting ever produced upon its unveiling in 1918. The painting contained over 5,000 life-size portraits of war heroes, royalty and government officials, predominantly French, from the Allies of World War I. Painting in book folds out to nearly ten feet, with description on the reverse side of reproduction of the painting. All text and images are presented as best as possible given size and condition of book.https://digicom.bpl.lib.me.us/books_pubs/1353/thumbnail.jp

A simple, efficient, and general treatment of the singularities in Hartree-Fock and exact-exchange Kohn-Sham methods for solids

We present a general scheme for treating the integrable singular terms within exact exchange (EXX) Kohn-Sham or Hartree-Fock (HF) methods for periodic solids. We show that the singularity corrections for treating these divergencies depend only on the total number and the positions of k-points and on the lattice vectors, in particular the unit cell volume, but not on the particular positions of atoms within the unit cell. The method proposed here to treat the singularities constitutes a stable, simple to implement, and general scheme that can be applied to systems with arbitrary lattice parameters within either the EXX Kohn-Sham or the HF formalism. We apply the singularity correction to a typical symmetric structure, diamond, and to a more general structure, trans-polyacetylene. We consider the effect of the singularity corrections on volume optimisations and k-point convergence. While the singularity corrections clearly depends on the total number of k-points, it exhibits a remarkably small dependence upon the choice of the specific arrangement of the k-points.Comment: 24 pages, 5 Figures, re-submitted to Phys. Rev. B after revision

Leveraging noisy side information for disentangling of factors of variation in a supervised setting

Ce mémoire est composé de trois articles et présente les résultats de travaux de recherche effectués dans le but d'améliorer les techniques actuelles permettant d'utiliser des données associées à certaines tâches dans le but d'aider à l'entraînement de réseaux de neurones sur une tâche différente. Les deux premiers articles présentent de nouveaux ensembles de données créés pour permettre une meilleure évaluation de ce type de techniques d'apprentissage machine. Le premier article introduit une suite d'ensembles de données pour la tâche de reconnaissance automatique de chiffres écrits à la main. Ces ensembles de données ont été générés à partir d'un ensemble de données déjà existant, MNIST, auquel des nouveaux facteurs de variation ont été ajoutés. Le deuxième article introduit un ensemble de données pour la tâche de reconnaissance automatique d'expressions faciales. Cet ensemble de données est composé d'images de visages qui ont été collectées automatiquement à partir du Web et ensuite étiquetées. Le troisième et dernier article présente deux nouvelles approches, dans le contexte de l'apprentissage multi-tâches, pour tirer avantage de données pour une tâche donnée afin d'améliorer les performances d'un modèle sur une tâche différente. La première approche est une généralisation des neurones Maxout récemment proposées alors que la deuxième consiste en l'application dans un contexte supervisé d'une technique permettant d'inciter des neurones à apprendre des fonctions orthogonales, à l'origine proposée pour utilisation dans un contexte semi-supervisé.The thesis is composed of three articles and presents the results of research done in order to improve the current methods for improving a neural network's performance on a given task by taking advantage of data from other tasks. The two first articles present new datasets created to allow better evaluation of this type of machine learning methods. The first article introduces a dataset suite for the task of handwritten digit recognition. This dataset suite was created from the existing dataset MNIST to which new factors of variation have been added. The second article introduces a new dataset for the task of facial expression recognition. It is composed of images of faces that were automatically collected from the Web and then labelled. The third and last article presents two new approaches to improving performance on a task of interest by leveraging labels from another task in the context of multi-task learning. The first approach is a generalization of the recently introduced Maxout Networks designed for multi-task learning. The second approach consists in the application in a fully-supervised setting of the previously introduced Contractive Discriminant Analysis penalty, originally used in the semi-supervised setting to make groups of neurons learn features orthogonal to each other

A Biologically Based Dynamic Model for Predicting the Disposition of Methanol and Its Metabolites in Animals and Humans

A multicompartment biologically based dynamic model was developed to describe the time evolution of methanol and its metabolites in the whole body and in accessible biological matrices of rats, monkeys, and humans following different exposure scenarios. The dynamic of intercompartment exchanges was described mathematically by a mass balance differential equation system. The model's conceptual and functional representation was the same for rats, monkeys, and humans, but relevant published data specific to the species of interest served to determine the critical parameters of the kinetics. Simulations provided a close approximation to kinetic data available in the published literature. The average pulmonary absorption fraction of methanol was estimated to be 0.60 in rats, 0.69 in monkeys, and 0.58-0.82 in human volunteers. The corresponding average elimination half-life of absorbed methanol through metabolism to formaldehyde was estimated to be 1.3, 0.7-3.2, and 1.7 h. Saturation of methanol metabolism appeared to occur at a lower exposure in rats than in monkeys and humans. Also, the main species difference in the kinetics was attributed to a metabolism rate constant of whole body formaldehyde to formate estimated to be twice as high in rats as in monkeys. Inversely, in monkeys and in humans, a larger fraction of body burden of formaldehyde is rapidly transferred to a long-term component. The latter represents the formaldehyde that (directly or after oxidation to formate) binds to various endogenous molecules or is taken up by the tetrahydrofolic-acid-dependent one-carbon pathway to become the building block of synthetic pathways. This model can be used to quantitatively relate methanol or its metabolites in biological matrices to the absorbed dose and tissue burden at any point in time in rats, monkeys, and humans for different exposures, thus reducing uncertainties in the dose-response relationship, and animal-to-human and exposure scenario comparisons. The model, adapted to kinetic data in human volunteers exposed acutely to methanol vapors, predicts that 8-h inhalation exposures ranging from 500 to 2000 ppm, without physical activities, are needed to increase concentrations of blood formate and urinary formic acid above mean background values reported by various authors (4.9-10.3 and 6.3-13 mg/liter, respectively). This leaves blood and urinary methanol concentrations as the most sensitive biomarkers of absorbed methano

Lanczos-based Low-Rank Correction Method for Solving the Dyson Equation in Inhomogenous Dynamical Mean-Field Theory

Inhomogeneous dynamical mean-field theory has been employed to solve many interesting strongly interacting problems from transport in multilayered devices to the properties of ultracold atoms in a trap. The main computational step, especially for large systems, is the problem of calculating the inverse of a large sparse matrix to solve Dyson's equation and determine the local Green's function at each lattice site from the corresponding local self-energy. We present a new efficient algorithm, the Lanczos-based low-rank algorithm, for the calculation of the inverse of a large sparse matrix which yields this local (imaginary time) Green's function. The Lanczos-based low-rank algorithm is based on a domain decomposition viewpoint, but avoids explicit calculation of Schur complements and relies instead on low-rank matrix approximations derived from the Lanczos algorithm, for solving the Dyson equation. We report at least a 25-fold improvement of performance compared to explicit decomposition (such as sparse LU) of the matrix inverse. We also report that scaling relative to matrix sizes, of the low-rank correction method on the one hand and domain decomposition methods on the other, are comparable.Comment: 13 pages, 1 figure, 24th Annual CSP Workshop, University of Georgia, Athens, GA, submitted to Physics Procedia. New version has some of the References correcte