Análisis de prácticas en módulos, quioscos y Vending Machines: Uso de máquinas expendedoras de certificados / documentos en el mundo

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Memory mixed with desire : a preliminary study of philosophy and literature in the works of Friedrich Nietzsche and Milan Kundera

Memory Mixed with Desire: A preliminary study of Philosophy and Literature in the works of Friedrich Nietzsche and Milan Kundera Robert Spinelli Brock University, Department of Philosophy This thesis studies intertextuality in the works of Friedrich Nietzsche and Milan Kundera through the primary themes of memory and forgetting. The thesis starts with two introductory chapters that delineate memory according to Nietzsche and Kundera respectively. From here, I move into a discussion of Nietzsche's Ubermensch as an example of the type of forgetting that Nietzsche sees as a cure for the overabundance of memory that has led to Christian morality. Next, I explore the Kunderan concept of kitsch as the polar opposite of what Nietzsche has sought in his philosophy, finishing the chapter by tying the two thinkers together in a Kunderan critique of Nietzsche. The thesis ends with a chapter devoted to the Eternal Return beginning with an exegesis of Nietzsche's idea and ending with a similar exegesis of Kundera's treatment of this thought. What I suggest in this chapter is that the Eternal Return might itself be a form of kitsch even in its attempt to revalue existence.

Desire and the paths of recognation [sic] in Hegel's intersubjectivity

This thesis poses two fundamental issues regarding Hegel's philosophy of intersubjectivity. Firstly, it examines Kojeve's problematic interpretation of Hegelian intersubjectivity as being solely rooted in the dialectic of lordship and bondage. It is my contention that Kojeve conflates the concepts of recognition {Anerkennung) with that of desire (Begierde), thereby reducing Hegel's philosophy of intersubjectivity to a violent reduction of the other to the same. This is so despite the plenary of examples Hegel uses to define intersubjectivity as the mutual (reciprocal) recognition between the self and the other. Secondly, it examines Hegel's use of Sophocles' Antigone to demonstrate the notion of the individual par excellence. I contend that Hegel's use of Antigone opens a new methodological framework through which to view his philosophy of intersubjectivity. It is Antigone that demonstrates the upheaval of an economy of exchange between the self and the other, whereby the alterity of the other transcends the self Ultimately, Hegel's philosophy of intersubjectivity must be reexamined, not only to dismiss Kojeve's problematic interpretation, but also to pose the possibility that Hegel's philosophy of intersubjectivity can viably account for a philosophy of the other that has a voice in contemporary philosophical debate.

Transforming curriculum leadership: vice principals in independent Christian elementary schools /

The literature on the vice principalship characterizes the position as one filled with clerical record keeping and student discipline and paints a picture of role conflict and general discontent. Research suggests that vice principals desire to take on a more significant role, specifically a role in curriculum leadership. Using open-ended interviews, a focus group interview, document analysis, and my research journal, I have explored the work ofa group of vice principals who have taken on the role of curriculum leader in independent Christian elementary schools in Ontario. When asked to explain their understanding of curriculum, the participants referred to written programs of study. However, their leadership activities reveal a broader understanding of curriculum as something that is in fact dynamic in nature. This leadership is enabled and shaped by their middle position on staff that combines the authority of an administrator and the credibility of a teacher. Although this dual identity creates tension, it also provides opportunities for genuine curriculum leadership. As middle leaders, the participants in this study often pull together or connect elements of the curriculum (teachers, principals, and programs) that have become separated. Such connective leadership is characterized by transformational (Van Brummelen, 2002) tendencies. This research suggests that the further along the continuum one goes from the understanding of curriculum as planned (Eisner, 1994) to acknowledging a lived curriculum (Aoki, 1993), the more transformational one's leadership style becomes.

Decoding algorithms using side-effect machines

Bioinformatics applies computers to problems in molecular biology. Previous research has not addressed edit metric decoders. Decoders for quaternary edit metric codes are finding use in bioinformatics problems with applications to DNA. By using side effect machines we hope to be able to provide efficient decoding algorithms for this open problem. Two ideas for decoding algorithms are presented and examined. Both decoders use Side Effect Machines(SEMs) which are generalizations of finite state automata. Single Classifier Machines(SCMs) use a single side effect machine to classify all words within a code. Locking Side Effect Machines(LSEMs) use multiple side effect machines to create a tree structure of subclassification. The goal is to examine these techniques and provide new decoders for existing codes. Presented are ideas for best practices for the creation of these two types of new edit metric decoders.

A Multi-Objective Genetic Algorithm with Side Effect Machines for Motif Discovery

Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.

Article - "Those darling young women in their flying machines", 1977

A retrospective article written by Dorothy Rungeling as she recalls the the International Air Races that often began or ended in Welland-Port Colborne Airport. The article was published in the Welland Evening Tribune, 9 September 1977.

Machines de vision et changement de paradigme : une étude comparative de l'imagerie scientifique dans les travaux d'Étienne-Jules Marey et de Marcel Duchamp

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

La notion de désir dans la philosophie de Gilles Deleuze

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

The eroticization of space and language through desire in Gail Scott's My Paris

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Building Beyond Limits : Fantastic Collisions Between Bodies and Machines in French and English Fin-de-Siècle Literature

«Construire hors limite: collisions fantastiques entre corps et machines dans la littérature fin-de-siècle française et anglaise» explore un ensemble de textes qui ont surgi à la fin du dix-neuvième siècle en réponse et en réaction à la fulgurante évolution de l’environnement scientifique et technologique, et qui considèrent la relation entre l’homme et la machine en fantasmant sur la zone grise où ils s’intersectent. Les principaux textes étudiés comprennent L’Ève future de Villiers de l’Isle-Adam, Le Surmâle d’Alfred Jarry, Trilby de George Du Maurier, Le Château des Carpathes de Jules Verne, ainsi qu’une sélection de contes dont nous pouvons qualifier de «contes à appareils», notamment «La Machine à parler» de Marcel Schwob. Utilisant la théorie des systèmes comme base méthodologique, cette dissertation cherche à réinterpréter les textes de la fin du dix-neuvième siècle qui naviguent les limites de l’humain et du mécanique et les surfaces sensibles où ils se touchent et interagissent en les réinscrivant dans un projet plus vaste de construction d’identité qui défie le temps chronologique et les échelles mathématiques. Le lien entre la théorie des systèmes et l’architecture – comme méthode d’organisation d’espace blanc en espace habitable – est exploré dans le but de comprendre la manière dont nous façonnons et interprétons le néant à l’origine de l’identité individuelle, et par association collective, en pratiquant littéralement la schématisation et la construction du corps. Des auteurs tels Villiers et Jarry imaginent la construction du corps comme une entreprise scientifique nécessairement fondée et réalisée avec les matériaux et les technologies disponibles, pour ensuite démanteler cette proposition en condamnant le corps technologique à la destruction. La construction d’une identité amplifiée par la technologie prend donc des proportions prométhéennes perpétuellement redessinées dans des actes cycliques de rasage (destruction) et d’érection (édification), et reflétées dans l’écriture palimpsestique du texte. L’intégrité du corps organique étant mis en question, le noyau même de ce que signifie l’être (dans son sens de verbe infinitif) humain pourrait bien s’avérer, si l’on considère la correspondance entre perte de voix et état pathologique dans les textes de Du Maurier, Verne et Schwob, être une structure des plus précaires, distinctement hors sens (unsound).

Improving sampling, optimization and feature extraction in Boltzmann machines

L’apprentissage supervisé de réseaux hiérarchiques à grande échelle connaît présentement un succès fulgurant. Malgré cette effervescence, l’apprentissage non-supervisé représente toujours, selon plusieurs chercheurs, un élément clé de l’Intelligence Artificielle, où les agents doivent apprendre à partir d’un nombre potentiellement limité de données. Cette thèse s’inscrit dans cette pensée et aborde divers sujets de recherche liés au problème d’estimation de densité par l’entremise des machines de Boltzmann (BM), modèles graphiques probabilistes au coeur de l’apprentissage profond. Nos contributions touchent les domaines de l’échantillonnage, l’estimation de fonctions de partition, l’optimisation ainsi que l’apprentissage de représentations invariantes. Cette thèse débute par l’exposition d’un nouvel algorithme d'échantillonnage adaptatif, qui ajuste (de fa ̧con automatique) la température des chaînes de Markov sous simulation, afin de maintenir une vitesse de convergence élevée tout au long de l’apprentissage. Lorsqu’utilisé dans le contexte de l’apprentissage par maximum de vraisemblance stochastique (SML), notre algorithme engendre une robustesse accrue face à la sélection du taux d’apprentissage, ainsi qu’une meilleure vitesse de convergence. Nos résultats sont présent ́es dans le domaine des BMs, mais la méthode est générale et applicable à l’apprentissage de tout modèle probabiliste exploitant l’échantillonnage par chaînes de Markov. Tandis que le gradient du maximum de vraisemblance peut-être approximé par échantillonnage, l’évaluation de la log-vraisemblance nécessite un estimé de la fonction de partition. Contrairement aux approches traditionnelles qui considèrent un modèle donné comme une boîte noire, nous proposons plutôt d’exploiter la dynamique de l’apprentissage en estimant les changements successifs de log-partition encourus à chaque mise à jour des paramètres. Le problème d’estimation est reformulé comme un problème d’inférence similaire au filtre de Kalman, mais sur un graphe bi-dimensionnel, où les dimensions correspondent aux axes du temps et au paramètre de température. Sur le thème de l’optimisation, nous présentons également un algorithme permettant d’appliquer, de manière efficace, le gradient naturel à des machines de Boltzmann comportant des milliers d’unités. Jusqu’à présent, son adoption était limitée par son haut coût computationel ainsi que sa demande en mémoire. Notre algorithme, Metric-Free Natural Gradient (MFNG), permet d’éviter le calcul explicite de la matrice d’information de Fisher (et son inverse) en exploitant un solveur linéaire combiné à un produit matrice-vecteur efficace. L’algorithme est prometteur: en terme du nombre d’évaluations de fonctions, MFNG converge plus rapidement que SML. Son implémentation demeure malheureusement inefficace en temps de calcul. Ces travaux explorent également les mécanismes sous-jacents à l’apprentissage de représentations invariantes. À cette fin, nous utilisons la famille de machines de Boltzmann restreintes “spike & slab” (ssRBM), que nous modifions afin de pouvoir modéliser des distributions binaires et parcimonieuses. Les variables latentes binaires de la ssRBM peuvent être rendues invariantes à un sous-espace vectoriel, en associant à chacune d’elles, un vecteur de variables latentes continues (dénommées “slabs”). Ceci se traduit par une invariance accrue au niveau de la représentation et un meilleur taux de classification lorsque peu de données étiquetées sont disponibles. Nous terminons cette thèse sur un sujet ambitieux: l’apprentissage de représentations pouvant séparer les facteurs de variations présents dans le signal d’entrée. Nous proposons une solution à base de ssRBM bilinéaire (avec deux groupes de facteurs latents) et formulons le problème comme l’un de “pooling” dans des sous-espaces vectoriels complémentaires.

Non invasive classification system of scoliosis curve types using least-squares support vector machines

Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.

A Novel Accelerator Combination for the Low Temperature Curing of Silica-Filled NBR Compounds

Zinc salts of ethyl, isopropyl, and butyl xanthates were prepared in the laboratory. The effect of these xanthates in combination with zinc diethyldithiocarbamate (ZDC) on the vulcanization of silica-filled NBR compounds has been studied at different temperatures. The cure times of these compounds were compared with that of NBR compounds containing tetramethylthiuram disulphide/dibenzthiazyl disulphide. The rubber compounds with the xanthates and ZDC were cured at various temperatures from 60 to 150°C. The sheets were molded and properties such as tensile strength, tear strength, crosslink density, elongation at break, compression set, abrasion resistance, flex resistance, heat buildup, etc. were evaluated. The properties showed that zinc salt of xanthate/ZDC combination has a positive synergistic effect on the cure rate and mechanical properties of NBR compounds.

Synergism of Xanthate/Dithiocarbamate Accelerator in Carbon Black Filled NR Compounds

Zinc salts of ethyl, isopropyl and butyl xanthates were prepared in the laboratory. The effect of these xanthates with zinc diethyldithiocarbamate (ZDC) on the vulcanization of HAF filled NR compound has been studied at different temperatures. The rubber compounds with the three xanthate accelerators and ZDC were cured at various temperatures from 60°C to 150°C. The sheets were moulded and properties such as tensile strength , tear strength , cross-link density, elongation -at-break, compression set, heat build up, abrasion resistance, flex resistance , etc. were evaluated . The properties showed that zinc xanthate/ZDC accelerator combination has a positive synergistic effect on the mechanical properties of NR compounds. The curing of HAF filled NR compound containing zinc xanthate /ZDC is slightly slower than the curing of the corresponding gum compounds . It is observed that, by gradually increasing the amount of the accelerator, the cure time of black filled NR compound can be made equal to that of the gum compou