Projets novateurs réalisés

Hypoxia severity impacts on cortical activity in moderate to severe OSA patients

Obstructive Sleep Apnea (OSA) is an important respiratory disease characterized by recurrent blockages of the throat (‘upper airway’) during sleep. These blockages result in short lapses in breathing. The low oxygen levels and disruption of sleep caused by OSA contribute to many problems including: sleepiness, poor quality of life, awakenings during sleep, hypertension, heart disease, strokes, and dementia. OSA is usually diagnosed by a ‘sleep study’: patients stay overnight in the hospital and many biologic signals (i.e., brain wave patterns, heart rate, oxygen levels, breathing effort) are collected over 8 or more hours. The severity of OSA is usually measured by the apnea-hypopnea index (AHI), which is the number of times the throat closes or narrows per hour of sleep. However, the AHI does not predict symptoms of health outcomes of sleep apnea well. We believe that new ways of looking at the information collected during sleep studies might help predict what problems someone with OSA will have. The purpose of this project is to apply advanced computer techniques to information collected from a large group of patients with sleep apnea in order to develop tools that can better predict brain function in patients with sleep apnea.

Heuristiques pour la gestion des créneaux horaires de livraison

L’objectif général de ce projet est le développement d’heuristiques à la fine pointe des connaissances actuelles pour des problèmes de gestion de créneaux horaires de livraison (PGCHL). L’objectif de telles problématiques est de proposer un ensemble des créneaux horaires à offrir dans chaque zone prédéfinie de la région de livraison ainsi que le plan de livraison associé. Cette solution se doit d’offrir un niveau de service acceptable dans chaque zone et doit également être en mesure de réduire les coûts de livraison. La modélisation des PGCHL donne lieu à des formulations présentant des défis méthodologiques considérables et qui ont été peu traitées dans la littérature. Le produit de ce projet permettra à l’entreprise Clear Destination de mettre à disposition des entreprises de commerce de détail la commerce de détail la technologie de gestion des créneaux horaires de livraisons. Cette nouvelle fonctionnalite sera en mesure m’accroitre la competitivite de ces entreprises et supportera l’expansion du commerce electronique qui est un des segments qui connait la plus forte croissance actuellement.

Individual identification using sleep micro-architecture

Brain fingerprinting is an emerging technique that has significant potential in leveraging individual differences for the improved prediction of behaviour (e.g. memory) and clinical (e.g. neuropsychiatric) outcomes. There is evidence suggesting that certain phenotypes of sleep might be markedly trait-like, however the uniqueness of sleep architecture and microarchitecture underlying the neurophysiological activity during the sleep state has yet to be assessed in a comprehensive manner. During this project, the intern will investigate sleep microarchitecture and individual variations in automatically detected events such as slow oscillations and sleep spindles to understand their potential in predicting behavioural features such as memory consolidation.

Theory Guided Machine Learning Process Modeling of in-situ Automated Fiber Placement

Current manufacturing processes for fiber-reinforced polymer composite materials are slow and rely heavily on manual intervention for quality control. The in-situ manufacturing of thermoplastic composites using Automated Fiber Placement (AFP) eliminates secondary thermal processing, which leads to decreased manufacturing times and cost. However, to reach an industrial implementation, we must improve our understanding of the non-linear and complex relationships that exist between all process parameters. Hence, optimization of the manufacturing process can be achieved by determining the relationships between process conditions (e.g., temperature, pressure, lay-up speed) and the final part quality. To address this knowledge gap, the proposed research project will develop a data-driven model using Theory Guided Machine Learning. The data-driven model will predict the temperature history achieved during AFP manufacturing using experimental data. The developed model can be exploited for more efficient control of the AFP process resulting in improved part quality and increased throughput.

A trajectory optimization-based framework for cooperative multi-robot object transportation

The proposed project on cooperative multi-robot systems addresses one of the recognized major challenges and opportunities in collaborative robotics (Cobots). For multi-robot groups, optimizing transportation efficiency for the workpiece while at the same time achieving whole-body obstacle avoidance in a cluttered manufacturing environment is highly involved due to the physical coupling of the system between the cooperating agents. The project objective is to establish a novel cooperative framework for multi-robot rigid object transportation in an unstructured environment. With the adoption of this framework, the robots should be able to coordinate their motion policies and generate individual control policy intelligently, resembling a human-human collaboration. Moreover, investigations will be conducted on the uncertainty incurred by the varying communication delay in the system with the proposed distributed topology. Experimental validations of the proposed framework will be performed on the Franka Emika Cobots in both home and host institutions.

Equilibrium and Stability of negative energy configurations in General Relativity and Cosmology

La théorie de la Rélativité General (RG) est la resposable pour décrir le mouvement des corps qui subit l’effet d’une force d’atraction gravitationnel, tel que la terre et la lune. En plus, elle est encore capable de décrire comme doivent être les mouvement des galaxies au ciel, et même de quel façon doit-il l’univers évoluer au passé du temp. Bien que capable de faire ceux-ci, la théorie manque encore certain détails. En particulier, il y a deux component dans notre univers qui ne sont pas prévue par la RG et doivent être mise à main aux équations. A savoir, la matière noire (responsable pour la stabilité de galaxie) et l’energie noire (responsable par l’expasion acceléré de l’univers). Ce qui on fera dans mon séjour sera étudier un modéle alternative à celle de la matière noire, en considerant des particules ayant des masses négatives, dont l’existence est raisonnable, sous certaines hypothèses.

Journalistic Role Performance in Climate Change Reporting

Journalists, when curating news, typically rely on enacting certain “voices” and frame content according to established norms.

Using Claudia Mellado’s Journalistic Role Performance methodology — which has divided all journalistic roles into the following categories: the watchdog, citizen-watchdog, the loyal-facilitator, the interventionist-disseminator, the service, the infotainment and the civic roles — evaluate common journalistic roles and perceived role enactments among journalists reporting on climate change in the news.

Based on the trends and findings from a content analysis performed on Canadian news, establish which roles are common, and find ways to refine the methodology. How could journalists improve the way they present climate news to audiences? What do the trends tell us about audience reception to certain role enactments? How might the use of certain technology change audience engagement and reception? How can we innovate to present climate news so it is more engaging and informative?

Hygrothermal effects on adhesively bonded CFRP-to-concrete systems

The use of fibre-reinforced polymer materials has been continuously increasing as an alternative to traditional materials, due to their superior durability (absence of corrosion), lightweight, low maintenance cost, and rapid installation. Adhesive bonding techniques for strengthening existing structures, such as near-surface mounted (NSM) and externally bonded reinforcement (EBR) are usually preferable. The long-term performance of these strengthening techniques under hygrothermal ageing conditions is still not clearly understood, limiting their use. This work aims to give new insights for reliable predictions of the long-term performance of these strengthening techniques, supported by advanced and innovative numerical modelling, properly calibrated with a refined experimental program that will be developed in this work. These outcomes will foster the use of NSM and EBR techniques as alternatives to the traditional ones, conducting more sustainable rehabilitation methods aiming at faster intervention speed, and reduction in energy, raw materials, and construction waste.

Nurturing Landscapes: Bringing together ecology, education and design in the creation of stormwater management systems on school grounds

This research looks to explore the collaboration of ecology, education and design in the creation of built and natural systems to sustainably manage and educate about storm/rain water on school grounds. The research will be conducted through the analysis of 3 key case studies of schoolyard storm/rain water management projects that represent a successful, progressive and collaborative approach to the design, implementation, use and maintenance of the schoolyard water management system. The results of the case study analysis will be used to inform a pilot project to be undertaken at a school in Victoria, BC. During the main research period I will be doing 2 Mitacs internships with Murdoch de Greeff, a Victoria based company specializing in urban storm/rain water design and landscape architecture. Murdoch de Greeff will contribute hands-on professional knowledge to the research process, in turn they will benefit from the results of the research as professional development. By participating in this research Murdoch de Greeff will also be well poised to take on schoolyard design projects as more schools look to improve the water management and outdoor educational environments on their school grounds

Développement d’un béton fibré à ultra haute performance utilisé dans le domaine de la préfabrication de panneaux légers pour la construction modulaire

Ce projet est une collaboration entre l’Université de Sherbrooke et les entreprises Adjuvants Euclid et Duchesne Lac-Mégantic. Il vise à développer un panneau préfabriqué en béton ultra-haute performance pour l’enveloppe des bâtiments. Une version en pierre naturelle de ce type de panneau avec un substrat en fibre de carbone a été déjà été développé et est actuellement commercialisé. Ce projet vise à remplacer la pierre naturelle par un béton à ultra-haute performance qui sera commercialisé par le partenaire Adjuvants Euclid. Ce projet permettra d’élargir l’éventail esthétique et de diminuer le coût pour le rendre accessible à une plus vaste gamme de bâtiments. Ce nouveau panneau d’enveloppe permettra des délais de construction plus courts et un processus de construction plus simple de bâtiments avec des revêtements de grande qualité et de très grande durabilité pour répondre aux demandes du marché canadien dans un contexte de crise du logement.

Real-time Trajectory Tracking Controller of an Aircraft using Imitation NMPC

Autonomous flying vehicles are the future of aerospace industry. They require a robust trajectory tracking algorithm capable of finding an optimal solution in real-time. Optimal control, such as Nonlinear Model Predictive Control (NMPC) is a powerful technique which can handle the nonlinearities of a system by including the restrictions and constraints of its states and controls. However, a major drawback of NMPC is that it requires the optimization problem to be solved online involving a huge amount of real-time calculations.
For increasing the level of autonomy, a data-driven approach such as imitation learning (IL) can be implemented. The Neural Network can be trained by mimicking the optimal trajectory data generated by NMPC. This project aims to develop an Imitation NMPC that combines the optimal control and machine learning to reduce the computational cost in real-time trajectory tracking of fixed-wing aircraft.

The Effects of Large-Scale Social Movements on Language Attitudes: A Mixed-Methods Investigation of Cantonese and Mandarin in Hong Kong

In an era where mass protests are happening with increasing frequency across the globe, there has been a growth in research interest on why people participate in social movements. However, consequences of social movements have received less attention (Louis, 2009). One especially understudied area is how attitudes towards language, a core aspect of group identity, may be affected by large-scale social movements. Having experienced two social movements in 2014 and 2019 respectively, Hong Kong provides a unique context in which to study how collective action impacts language attitudes. The current project will utilize a mixed-methods approach to study how attitudes towards Cantonese and Mandarin shifted in the aftermath of large-scale social movements in Hong Kong. By drawing attention to the oft-overlooked role of language in intergroup relations, findings the project, while directly focusing on Hong Kong, may inform research in other multilingual contexts, including Quebec and other parts of Canada where attitudes towards French and English remain topical.