Short-term follow-up of exercise training program and beta-blocker treatment on quality of life in dogs with naturally acquired chronic mitral valve disease

This study aimed to evaluate the effects of carvedilol treatment and a regimen of supervised aerobic exercise training on quality of life and other clinical, echocardiographic, and biochemical variables in a group of client-owned dogs with chronic mitral valve disease (CMVD). Ten healthy dogs (control) and 36 CMVD dogs were studied, with the latter group divided into 3 subgroups. In addition to conventional treatment (benazepril, 0.3-0.5 mg/kg once a day, and digoxin, 0.0055 mg/kg twice daily), 13 dogs received exercise training (subgroup I; 10.3±2.1 years), 10 dogs received carvedilol (0.3 mg/kg twice daily) and exercise training (subgroup II; 10.8±1.7 years), and 13 dogs received only carvedilol (subgroup III; 10.9±2.1 years). All drugs were administered orally. Clinical, laboratory, and Doppler echocardiographic variables were evaluated at baseline and after 3 and 6 months. Exercise training was conducted from months 3-6. The mean speed rate during training increased for both subgroups I and II (ANOVA, P>0.001), indicating improvement in physical conditioning at the end of the exercise period. Quality of life and functional class was improved for all subgroups at the end of the study. The N-terminal pro-brain natriuretic peptide (NT-proBNP) level increased in subgroup I from baseline to 3 months, but remained stable after training introduction (from 3 to 6 months). For subgroups II and III, NT-proBNP levels remained stable during the entire study. No difference was observed for the other variables between the three evaluation periods. The combination of carvedilol or exercise training with conventional treatment in CMVD dogs led to improvements in quality of life and functional class. Therefore, light walking in CMVD dogs must be encouraged.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels

This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Pretraining Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

Spectral retinal image processing and analysis for ophthalmology

Diabetic retinopathy, age-related macular degeneration and glaucoma are the leading causes of blindness worldwide. Automatic methods for diagnosis exist, but their performance is limited by the quality of the data. Spectral retinal images provide a significantly better representation of the colour information than common grayscale or red-green-blue retinal imaging, having the potential to improve the performance of automatic diagnosis methods. This work studies the image processing techniques required for composing spectral retinal images with accurate reflection spectra, including wavelength channel image registration, spectral and spatial calibration, illumination correction, and the estimation of depth information from image disparities. The composition of a spectral retinal image database of patients with diabetic retinopathy is described. The database includes gold standards for a number of pathologies and retinal structures, marked by two expert ophthalmologists. The diagnostic applications of the reflectance spectra are studied using supervised classifiers for lesion detection. In addition, inversion of a model of light transport is used to estimate histological parameters from the reflectance spectra. Experimental results suggest that the methods for composing, calibrating and postprocessing spectral images presented in this work can be used to improve the quality of the spectral data. The experiments on the direct and indirect use of the data show the diagnostic potential of spectral retinal data over standard retinal images. The use of spectral data could improve automatic and semi-automated diagnostics for the screening of retinal diseases, for the quantitative detection of retinal changes for follow-up, clinically relevant end-points for clinical studies and development of new therapeutic modalities.

The nature of avidyÄ in Buddhism and VedÄ nta

This thesis deals with the nature of ignorance as it was interpreted in the Upani~adic tradition, specifically in Advaita Vedanta, and in early and Mahayana Buddhism , e specially in the Madhyamika school of Buddhism. The approach i s a historical and comparative one. It examines the early thoughts of both the upanis.a ds and Buddhism abou t avidya (ignorance), shows how the notion was treated by the more speculative and philosphically oriented schools which base d themselves on the e arly works, and sees how their views differ. The thesis will show that the Vedinta tended to treat avidya as a topic for metaphysical s peculation as t he s chool developed, drifting from its initial e xistential concerns, while the Madhyamika remained in contact with the e xistential concerns evident in the first discourses of the Buddha. The word "notion" has been chosen for use in referring t o avidya, even though it may have non-intellectual and emotional connotations, to avoid more popular a lternatives such as "concept" or "idea". In neither the Upani,ads, Advaita Vedanta, or Buddhism is ignorance merely a concept or an idea. Only in a secondary sense, in texts and speech , does it become one. Avidya has more to do with the lived situation in which man finds himself, with the subjectobject separation in which he f eels he exists, than with i i i intel lect ual constr ucts . Western thought has begun to r ealize the same with concerns such as being in modern ontology, and has chosen to speak about i t i n terms of the question of being . Avidya, however, i s not a 'question' . If q ue stions we r e to be put regarding the nature of a vidya , they would be more of t he sort "What is not avidya?", though e ven here l anguage bestows a status t o i t which avidya does not have. In considering a work of the Eastern tradition, we f ace t he danger of imposing Western concepts on it. Granted t hat avidya is customari ly r endered i n English as ignorance, the ways i n which the East and West view i gno rance di f f er. Pedagogically , the European cultures, grounded in the ancient Greek culture, view ignorance as a l ack or an emptiness. A child is i gnorant o f certain t hings and the purpose o f f ormal education , in f act if not in theory, is to fill him with enough knowledge so that he can cope wit h t he complexities and the e xpectations of s ociety. On another level, we feel t hat study and research will l ead t o the discovery o f solutions, which we now lack , for problems now defying solut i on . The East, on the o t her hand, sees avidya in a d i fferent light.Ignorance isn't a lack, but a presence. Religious and philosophical l iterature directs its efforts not towards acquiring something new, but at removing t.he ideas and opinions that individuals have formed about themselves and the world. When that is fully accomplished, say the sages , t hen Wisdom, which has been obscured by those opinions, will present itself. Nothing new has to be learned, t hough we do have t o 'learn' that much. The growing interest in t he West with Eastern religions and philosophies may, in time, influence our theoretical and practical approaches to education and learning, not only in the established educati onal institutions, but in religious , p sychological, and spiritual activities as well. However, the requirements o f this thesis do no t permit a formulation of revolutionary method or a call to action. It focuses instead on the textual arguments which attempt to convince readers that t he world in which they take themselves to exist is not, in essence, real, on the ways i n which the l imitations of language are disclosed, and on the provisional and limited schemes that are built up to help students see through their ignorance. The metaphysic s are provisional because they act only as spurs and guides. Both the Upanisadic and Buddhist traditions that will be dealt with here stress that language constantly fails to encompass the Real. So even terms s uch as 'the Real', 'Absolute', etc., serve only to lead to a transcendent experience . The sections dealing with the Upanisads and Advaita Vedanta show some of the historical evolution of the notion of avidya, how it was dealt with as maya , and the q uestions that arose as t o its locus. With Gau?apada we see the beginnings of a more abstract treatment of the topic, and , the influence of Buddhism. Though Sankhara' S interest was primarily directed towards constructing a philosophy to help others attain mok~a ( l iberation), he too introduced t echnica l t e rminology not found in the works of his predecessors. His work is impressive , but areas of it are incomplete. Numbers of his followers tried to complete the systematic presentation of his insi ghts . Their work focuses on expl anat i ons of adhyasa (superimposition ) , t he locus and object of ignorance , and the means by which Brahman takes itself to be the jiva and the world. The section on early Buddhism examines avidya in the context o f the four truths, together with dubkha (suffering), the r ole it p l ays in t he chain of dependent c ausation , a nd t he p r oblems that arise with t he doctrine of anatman. With t he doct rines of e arly Buddhism as a base, the Madhyamika elaborated questions that the Buddha had said t e nded not t o edi f ication. One of these had to do with own - being or svabhava. Thi s serves a s a centr e around which a discussion o f i gnorance unfolds, both i ndividual and coll ective ignorance. There follows a treatment of the cessation of ignorance as it is discussed within this school . The final secti on tries to present t he similarities and differences i n the natures o f ignorance i n t he two traditions and discusses the factors responsible for t hem . ACKNOWLEDGEMENTS I would like to thank Dr. Sinha for the time spent II and suggestions made on the section dealing with Sankara and the Advait.a Vedanta oommentators, and Dr. Sprung, who supervised, direoted, corrected and encouraged the thesis as a whole, but especially the section on Madhyamika, and the final comparison.

The effects of a general excercise program on task self-efficacy and social physique anxiety in older adults

Older adults represent the most sedentary segment of the adult population, and thus it is critical to investigate factors that influence exercise behaviour for this age group. The purpose of this study was to examine the influence of a general exercise program, incorporating cardiovascular, strength, flexibility, and balance components, on task selfefficacy and SPA in older adult men and women. Participants (n=114, Mage = 67 years) were recruited from the Niagara region and randomly assigned to a 12-week supervised exercise program or a wait-list control. Task self-efficacy and SPA measures were taken at baseline and program end. The present study found that task self-efficacy was a significant predictor of leisure time physical activity for older adults. In addition, change in task self-efficacy was a significant predictor of change in SPA. The findings of this study suggest that sources of task self-efficacy should be considered for exercise interventions targeting older adults.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Assessing the Reproducibility of Clustering of Molecular Dynamics Conformations on Self-Organizing Maps

The goal of most clustering algorithms is to find the optimal number of clusters (i.e. fewest number of clusters). However, analysis of molecular conformations of biological macromolecules obtained from computer simulations may benefit from a larger array of clusters. The Self-Organizing Map (SOM) clustering method has the advantage of generating large numbers of clusters, but often gives ambiguous results. In this work, SOMs have been shown to be reproducible when the same conformational dataset is independently clustered multiple times (~100), with the help of the Cramérs V-index (C_v). The ability of C_v to determine which SOMs are reproduced is generalizable across different SOM source codes. The conformational ensembles produced from MD (molecular dynamics) and REMD (replica exchange molecular dynamics) simulations of the penta peptide Met-enkephalin (MET) and the 34 amino acid protein human Parathyroid Hormone (hPTH) were used to evaluate SOM reproducibility. The training length for the SOM has a huge impact on the reproducibility. Analysis of MET conformational data definitively determined that toroidal SOMs cluster data better than bordered maps due to the fact that toroidal maps do not have an edge effect. For the source code from MATLAB, it was determined that the learning rate function should be LINEAR with an initial learning rate factor of 0.05 and the SOM should be trained by a sequential algorithm. The trained SOMs can be used as a supervised classification for another dataset. The toroidal 10×10 hexagonal SOMs produced from the MATLAB program for hPTH conformational data produced three sets of reproducible clusters (27%, 15%, and 13% of 100 independent runs) which find similar partitionings to those of smaller 6×6 SOMs. The χ^2 values produced as part of the C_v calculation were used to locate clusters with identical conformational memberships on independently trained SOMs, even those with different dimensions. The χ^2 values could relate the different SOM partitionings to each other.

Suivi à long terme de l’efficacité d’un traitement de physiothérapie sur l'incontinence urinaire d'effort persistante en période postnatale

L’incontinence urinaire d’effort (IUE) est une condition fréquente en période postnatale pouvant affecter jusqu’à 77% des femmes. Neuf femmes sur dix souffrant d’IUE trois mois après l’accouchement, vont présenter une IUE cinq ans plus tard. Le traitement en physiothérapie de l’IUE par le biais d’un programme d’exercices de renforcement des muscles du plancher pelvien est reconnu comme étant un traitement de première ligne efficace. Les études ont prouvé l’efficacité de cette approche sur l’IUE persistante à court terme, mais les résultats de deux ECR à long terme n’ont pas démontré un maintien de l’effet de traitement. L’effet d’un programme en physiothérapie de renforcement du plancher pelvien intensif et étroitement supervisé sur l’IUE postnatale persistante avait été évalué lors d’un essai clinique randomisé il y a sept ans. Le but principal de la présente étude était d’évaluer l’effet de ce programme sept ans après la fin des interventions de l’ECR initial. Un objectif secondaire était de comparer l’effet de traitement à long terme entre un groupe ayant fait seulement des exercices de renforcement du plancher pelvien et un groupe ayant fait des exercices de renforcement du plancher pelvien et des abdominaux profonds. Un troisième objectif était d’explorer l’influence de quatre facteurs de risques sur les symptômes d’IUE et la qualité de vie à long terme. Les cinquante-sept femmes ayant complétées l’ECR initial ont été invitées à participer à l’évaluation du suivi sept ans. Vingt et une femmes ont participé à l’évaluation clinique et ont répondu à quatre questionnaires, tandis que dix femmes ont répondu aux questionnaires seulement. L’évaluation clinique incluait un pad test et la dynamométrie du plancher pelvien. La mesure d’effet primaire était un pad test modifié de 20 minutes. Les mesures d’effets secondaires étaient la dynamométrie du plancher pelvien, les symptômes d’IUE mesuré par le questionnaire Urogenital Distress Inventory, la qualité de vie mesurée par le questionnaire Incontinence Impact Questionnaire et la perception de la sévérité de l’IUE mesuré par l’Échelle Visuelle Analogue. De plus, un questionnaire portant sur quatre facteurs de risques soit, la présence de grossesses subséquentes, la v présence de constipation chronique, l’indice de masse corporel et la fréquence des exercices de renforcement du plancher pelvien de l’IUE, venait compléter l’évaluation. Quarante-huit pour-cent (10/21) des participantes étaient continentes selon de pad test. La moyenne d’amélioration entre le résultat pré-traitement et le suivi sept ans était de 26,9 g. (écart-type = 68,0 g.). Il n’y avait pas de différence significative des paramètres musculaires du plancher pelvien entre le pré-traitement, le post-traitement et le suivi sept ans. Les scores du IIQ et du VAS étaient significativement plus bas à sept ans qu’en prétraitement (IIQ : 23,4 vs 15,6, p = 0,007) et (VAS : 6,7 vs 5,1, p = 0,001). Les scores du UDI étaient plus élevés au suivi sept ans (15,6) qu’en pré-traitement (11,3, p = 0,041) et en post-traitement (5,7, p = 0,00). La poursuite des exercices de renforcement du plancher pelvien à domicile était associée à une diminution de 5,7 g. (p = 0,051) des fuites d’urine observées au pad test selon une analyse de régression linéaire. Les limites de cette étude sont ; la taille réduite de l’échantillon et un biais relié au désir de traitement pour les femmes toujours incontinentes. Cependant, les résultats semblent démontrer que l’effet du traitement à long terme d’un programme de renforcement des muscles du plancher pelvien qui est intensif et étroitement supervisé, est maintenu chez environ une femme sur deux. Bien que les symptômes d’IUE tel que mesuré par les pad test et le questionnaire UDI, semblent réapparaître avec le temps, la qualité de vie, telle que mesurée par des questionnaires, est toujours meilleure après sept qu’à l’évaluation initiale. Puisque la poursuite des exercices de renforcement du plancher pelvien est associée à une diminution de la quantité de fuite d’urine au pad test, les participantes devraient être encouragées à poursuivre leurs exercices après la fin d’un programme supervisé. Pour des raisons de logistique la collecte de donnée de ce projet de recherche s’est continuée après la rédaction de ce mémoire. Les résultats finaux sont disponibles auprès de Chantale Dumoulin pht, PhD., professeure agrée à l’Université de Montréal.

Youth engagement: the ethics of inclusion and exclusion

This study focuses on the engagement of children and youth in their communities and the ways they are included in and excluded from community life. Using a content analysis of a small town United States newspaper over a one-year period, examples of engagement were identified and classified into 12 categories: programs, clubs and special events; fundraising and community service; business and community support; participation in community events; school events; athletic and other performances; employment; involvement in local planning and decision making; serving as a community representative; visibility and recognition; criminal activity and accidents; and use of public space. Examples of community exclusion were identified as well. Young people were engaged primarily through activities that were adult-directed or supervised, or organized through schools, churches, and youth clubs. There was little involvement in local planning, decision making, or activism. Some evidence existed of peer teaching, leadership, and self-initiated activities, as well as intentional efforts by adults to give youth a greater voice in community activities. Implications include several ethical issues regarding the role of young people in community life, particularly young children, and the need for greater awareness on the part of communities of the contributions young people can make.

L’analyse de composants émotionnels dans des stratégies d’apprentissage

Un certain nombre de théories pédagogiques ont été établies depuis plus de 20 ans. Elles font appel aux réactions de l’apprenant en situation d’apprentissage, mais aucune théorie pédagogique n’a pu décrire complètement un processus d’enseignement en tenant compte de toutes les réactions émotionnelles de l’apprenant. Nous souhaitons intégrer les émotions de l’apprenant dans ces processus d’apprentissage, car elles sont importantes dans les mécanismes d’acquisition de connaissances et dans la mémorisation. Récemment on a vu que le facteur émotionnel est considéré jouer un rôle très important dans les processus cognitifs. Modéliser les réactions émotionnelles d’un apprenant en cours du processus d’apprentissage est une nouveauté pour un Système Tutoriel Intelligent. Pour réaliser notre recherche, nous examinerons les théories pédagogiques qui n’ont pas considéré les émotions de l’apprenant. Jusqu’à maintenant, aucun Système Tutoriel Intelligent destiné à l’enseignement n’a incorporé la notion de facteur émotionnel pour un apprenant humain. Notre premier objectif est d’analyser quelques stratégies pédagogiques et de détecter les composantes émotionnelles qui peuvent y être ou non. Nous cherchons à déterminer dans cette analyse quel type de méthode didactique est utilisé, autrement dit, que fait le tuteur pour prévoir et aider l’apprenant à accomplir sa tâche d’apprentissage dans des conditions optimales. Le deuxième objectif est de proposer l’amélioration de ces méthodes en ajoutant les facteurs émotionnels. On les nommera des « méthodes émotionnelles ». Le dernier objectif vise à expérimenter le modèle d’une théorie pédagogique améliorée en ajoutant les facteurs émotionnels. Dans le cadre de cette recherche nous analyserons un certain nombre de théories pédagogiques, parmi lesquelles les théories de Robert Gagné, Jerome Bruner, Herbert J. Klausmeier et David Merrill, pour chercher à identifier les composantes émotionnelles. Aucune théorie pédagogique n’a mis l’accent sur les émotions au cours du processus d’apprentissage. Ces théories pédagogiques sont développées en tenant compte de plusieurs facteurs externes qui peuvent influencer le processus d’apprentissage. Nous proposons une approche basée sur la prédiction d’émotions qui est liée à de potentielles causes déclenchées par différents facteurs déterminants au cours du processus d’apprentissage. Nous voulons développer une technique qui permette au tuteur de traiter la réaction émotionnelle de l’apprenant à un moment donné au cours de son processus d’apprentissage et de l’inclure dans une méthode pédagogique. Pour atteindre le deuxième objectif de notre recherche, nous utiliserons un module tuteur apprenant basé sur le principe de l’éducation des émotions de l’apprenant, modèle qui vise premièrement sa personnalité et deuxièmement ses connaissances. Si on défini l’apprenant, on peut prédire ses réactions émotionnelles (positives ou négatives) et on peut s’assurer de la bonne disposition de l’apprenant, de sa coopération, sa communication et l’optimisme nécessaires à régler les problèmes émotionnels. Pour atteindre le troisième objectif, nous proposons une technique qui permet au tuteur de résoudre un problème de réaction émotionnelle de l’apprenant à un moment donné du processus d’apprentissage. Nous appliquerons cette technique à une théorie pédagogique. Pour cette première théorie, nous étudierons l’effet produit par certaines stratégies pédagogiques d’un tuteur virtuel au sujet de l’état émotionnel de l’apprenant, et pour ce faire, nous développerons une structure de données en ligne qu’un agent tuteur virtuel peut induire à l’apprenant des émotions positives. Nous analyserons les résultats expérimentaux en utilisant la première théorie et nous les comparerons ensuite avec trois autres théories que nous avons proposées d’étudier. En procédant de la sorte, nous atteindrons le troisième objectif de notre recherche, celui d’expérimenter un modèle d’une théorie pédagogique et de le comparer ensuite avec d’autres théories dans le but de développer ou d’améliorer les méthodes émotionnelles. Nous analyserons les avantages, mais aussi les insuffisances de ces théories par rapport au comportement émotionnel de l’apprenant. En guise de conclusion de cette recherche, nous retiendrons de meilleures théories pédagogiques ou bien nous suggérerons un moyen de les améliorer.

Sequential Machine learning Approaches for Portfolio Management

Cette thèse envisage un ensemble de méthodes permettant aux algorithmes d'apprentissage statistique de mieux traiter la nature séquentielle des problèmes de gestion de portefeuilles financiers. Nous débutons par une considération du problème général de la composition d'algorithmes d'apprentissage devant gérer des tâches séquentielles, en particulier celui de la mise-à-jour efficace des ensembles d'apprentissage dans un cadre de validation séquentielle. Nous énumérons les desiderata que des primitives de composition doivent satisfaire, et faisons ressortir la difficulté de les atteindre de façon rigoureuse et efficace. Nous poursuivons en présentant un ensemble d'algorithmes qui atteignent ces objectifs et présentons une étude de cas d'un système complexe de prise de décision financière utilisant ces techniques. Nous décrivons ensuite une méthode générale permettant de transformer un problème de décision séquentielle non-Markovien en un problème d'apprentissage supervisé en employant un algorithme de recherche basé sur les K meilleurs chemins. Nous traitons d'une application en gestion de portefeuille où nous entraînons un algorithme d'apprentissage à optimiser directement un ratio de Sharpe (ou autre critère non-additif incorporant une aversion au risque). Nous illustrons l'approche par une étude expérimentale approfondie, proposant une architecture de réseaux de neurones spécialisée à la gestion de portefeuille et la comparant à plusieurs alternatives. Finalement, nous introduisons une représentation fonctionnelle de séries chronologiques permettant à des prévisions d'être effectuées sur un horizon variable, tout en utilisant un ensemble informationnel révélé de manière progressive. L'approche est basée sur l'utilisation des processus Gaussiens, lesquels fournissent une matrice de covariance complète entre tous les points pour lesquels une prévision est demandée. Cette information est utilisée à bon escient par un algorithme qui transige activement des écarts de cours (price spreads) entre des contrats à terme sur commodités. L'approche proposée produit, hors échantillon, un rendement ajusté pour le risque significatif, après frais de transactions, sur un portefeuille de 30 actifs.

Étude de l’impact d’un programme d’activité physique (Amazone) auprès de femmes en traitement pour un cancer du sein

Le cancer du sein est la forme de cancer la plus souvent diagnostiquée chez les femmes. Elles doivent vivre avec des séquelles qui nuisent à leur qualité de vie. Plusieurs études ont montré les bienfaits de l’activité physique (AP) sur les composantes physiques et psychologiques des patientes. Toutefois, elles réduisent souvent leur pratique d'AP suite aux traitements en raison de la détérioration de leur condition physique. Or, le maintien à long terme de la pratique d’AP est essentiel pour en conserver les bénéfices. La première section du mémoire présente une recension des écrits sur les bienfaits de l’AP auprès des femmes atteintes d'un cancer du sein et la seconde rend compte d'une étude expérimentale ayant pour objectif d'évaluer l’impact d’un programme d’AP sur le sentiment d’efficacité personnel et sur le plaisir associé à la pratique d'AP. Une enquête de suivi a été menée trois mois après la fin du programme afin d’évaluer le maintien à long terme de la pratique d'AP. L'étude a été réalisée auprès de 18 patientes en cours de traitement. Le groupe expérimental a suivi un programme supervisé d’AP combiné à des séances de counseling sur une période de 16 semaines. Le groupe témoin avait la possibilité de suivre un programme de yoga. Nos résultats indiquent une amélioration statistiquement significative des trois composantes mesurées, soit le sentiment d'efficacité personnelle, le plaisir à faire de l'AP et le maintien de la pratique après la participation au programme.