Projets novateurs réalisés

Designing Machine Learning Models for Predictive Analysis of Pressure Drop and Temperature in Free-Breathing Polymer Electrolyte Membrane Fuel Cell Stacks to find Optimal Fabrication Parameters

Climate change has emerged as one of the most critical problems of the 21st century, driven by the rise in greenhouse gas emissions. The polymer electrolyte membrane fuel cell (PEMFC) is a device that converts chemical energy into clean electricity with zero emissions. The proposed research aims to utilize machine learning algorithms to predict the pressure drop and temperature in PEMFCs by using data sets related to Singapore’s state-of-the-art PEMFCs. By applying different data pre-processing methods, the predictive algorithms will identify optimal fabrication parameters and operating conditions such that these fuel cells operate at their highest efficiency, while reducing cost. As a result, this research will lead to the improvement of PEMFCs such that they can be a competitive alternative to fossil fuel-based energy systems.

The revolving door of reintegration: Understanding the experiences and challenges of previously incarcerated people in Ontario

The transition from incarceration to the community (i.e., reintegration) is often characterized by uncertainty, unease, and instability. While there is a strong understanding reintegrative barriers like a lack of safe and stable housing, employment, and social support, reintegration is often characterized as a series of distinct challenges that determine its success. This overlooks how previously incarcerated people’s interactions with services and supports, or lack thereof, are woven into how they understand and navigate reintegration. Using interviews and secondary documentation, this study aims to (1) identify previously incarcerated people’s needs during reintegration, and the barriers they face in fulfilling these needs; (2) understand the role of reintegrative services and supports, or lack thereof, in shaping their experiences post-release; and (3) explore reintegration as a relational process. Doing so will produce evidence-based research that can advise programs/services in the community and/or correctional facilities and contribute to policy and public education on reintegration.

Geovisual Analytics for Smart Cities: Designing and Developing a User Interface for an Immersive Environment

This proposal represents part of a doctoral thesis aimed at developing an interface for immersive environments, allowing for geovisual analyses targeted at smart cities, using digital twins to investigate flood-related data. The proper application of interface design in this environment enables an improved understanding and perception of emerging risks, which are crucial elements in flood risk management. For the 13 weeks of research, we propose planning, conducting, and analyzing interviews with Canadian users to identify the user profile in developed countries, aiming for a future comparison with the needs of users in middle-income countries. As a result, we expect to finalize the proposed research project with detailed documentation on the needs, functionalities, and specifications of users in this environment.

Stretchable Electronics for 6G Anomalous Reflectors

6G is the next generation of wireless network technologies. 6G signals are millimeter-waves, which are highly prone to blockage from obstacles such as trees or buildings. Due to this, behavior of the wireless environment is highly probabilistic and coverage holes can appear. This project aims to develop a reconfigurable intelligent surface (RIS) which has the potential to mitigate coverage holes and allow for the wireless environment to be more programmable by steering signals. The RIS being explored in this project is an elastic anomalous reflector which can be mechanically stretched to change the direction of beams reflected off the surface. This approach shows promise as it works for millimeter waves, has a fairly large steering range, and is low cost. This project explores optimizations to previous designs of the device in order to increase its beam steering range as well as its reflection efficiency.

This will benefit the Sanada Lab at Osaka University by furthering their progress in research on this RIS. This project will benefit the University of Toronto by bringing unique perspectives and knowledge on 6G technologies, RIS, and metamaterials that may help advance research in related areas.

Post-reform China’s Evolving Compensation and Resettlement Mechanism for Land Expropriation: A Case Study in Shanghai’s Urban Fringe Region

The research will portray the institutional evolution of post-reform China’s compensation and resettlement mechanism for land expropriation through a case study in Shanghai’s urban fringe region. The project will incorporate archive studies (Phase I), interviews with various stakeholders (Phase II), and ground surveys with affected rural households (Phase II). The study will not only probe the effectiveness of policy implementation, but will also contribute to the achievement of a more sustainable and just planning and development approach for cities in the world.

Shifting perceptions of substance use in northwestern Ontario

The Northwestern Health Unit (NWHU) aims to address substance use issues prevalent in its catchment area by integrating two projects. Firstly, targeting high alcohol consumption rates, the initiative will require behavior change strategies to combat the normalization of alcohol use. By tailoring interventions to diverse subgroups, NWHU endeavors to shift cultural attitudes, thus reducing associated health risks. Secondly, addressing misconceptions surrounding harm reduction, particularly in the context of drug use prevalent in the region, the project seeks to educate staff, stakeholders, and the public. By promoting evidence-based interventions, NWHU aims to mitigate stigma and enhance support for harm reduction programs. This holistic approach aims to foster healthier behaviors and attitudes, ultimately improving community well-being.

Innovation dans l’entraînement sportif: optimisation de l’interface d’un simulateur de boxe en réalité virtuelle

Ce projet de recherche a pour but d’améliorer un simulateur de boxe en réalité virtuelle afin d’aider les athlètes de boxe canadiens à s’entraîner de manière plus performante tout en réduisant les risques de blessures, telles que les commotions cérébrales. Le stagiaire sera responsable de l’évaluation de l’interface utilisateur du simulateur, en établissant une étude scientifique visant à comprendre l’expérience d’utilisation par des athlètes de haut niveau, des entraîneurs et des non-athlètes. En se fondant sur les retours des utilisateurs, le stagiaire proposera des suggestions d’améliorations pour rendre l’interface plus conviviale et mieux adaptée aux besoins de chacun.
L’organisme partenaire, l’Institut national du sport du Québec (INS Québec), bénéficiera de ces améliorations puisqu’il aura accès à un nouvel outil d’entraînement novateur qui répondra aux besoins des athlètes professionnels de boxe. Ainsi, il sera possible d’offrir une méthode d’entraînement plus sécuritaire, plus performante et plus efficace que les méthodes de boxe traditionnelles. En développant une solution qui améliore la performance des athlètes de boxe canadienne, l’INS Québec contribuera à accroître la visibilité et la réputation de la boxe canadienne sur la scène mondiale. Cela pourrait mener à davantage de succès sportifs et à plus de médailles.

Explainable time-series machine learning using the tsfresh module

The central idea of this project is the observation that publications using systematic time series feature extraction from the Open Source machine learning library tsfresh, always need to visualize and explain the extracted features. Due to the fact that tsfresh uses 168 algorithms to compute up to 800 time series features, this process can be highly automated using an object oriented approach. This project will contribute towards the development of a Python module for explainable time-series machine learning, which will assists researchers and engineers in the interpretation of their time-series based machine learning models.

Work order Scheduling at maintenance Sites for Commercial Aircraft Fleet

The effective planning of resources when scheduling maintenance tasks and repair jobs is an enormous challenge, especially for heavy industries such as aerospace and transportation manufacturers. In such industries, because of the product complexity and variety, not to mention continuous technological improvements, a broad range of maintenance tasks and high-performance services should be done over the course of a year to guarantee the safety and reliability of the products. The main contribution of the project is to address an important gap in the current theoretical methodologies and market software packages: the lack of an integrated tool to manage the resources in a maintenance site of the commercial aircraft fleets.

Caractérisation sous choc de foudre d’une nouvelle méthode de mise à la terre (MALT) basées sur l’utilisation des géopolymères électriquement conducteurs développés à partir de résidus de production de l’aluminium.

Depuis maintenant plus trois (3) ans, un projet a été initié par Rio Tinto et l’UQAC dans le but de réduire les
résidus issus de la production de l’aluminium sachant que leur entreposage est de plus en plus problématique.
Une des solutions proposées est d’utiliser ces différents résidus pour développer des géopolymères
électriquement conducteurs (GEC). Le présent projet vise donc à développer une application concrète utilisant
une quantité importante de GEC dans le développement d’une nouvelle méthode de mise à la terre (MALT) dédiée
aux équipements des réseaux électriques. La méthode proposée, appelée EE-GEC, est basée sur le principe
d’électrodes (en acier) encastrées (EE) dans un géopolymère électriquement conducteur (GEC). La mise en place
ce nouveau système de MALT va ainsi permettre développer une économie circulaire en permettant de réduire
significativement les résidus de bauxites et en offrant une alternative à l’utilisation du cuivre bientôt considéré
comme un matériau critique.

Designing New Business Models to Transform Bombardier’s Customer Services & Support Department into a Profit Centre

The main purpose of this cluster proposal is to test the hypothesis of whether the Customer Services & Support Department of Bombardier Commercial Aircraft Division can develop new business models to transform itself into a profit center within the Bombardier’s organization. To carry out this test, a thorough investigation of the after-sale needs, wants and concerns of the different users of Bombardier Commercial Aircraft products will be carried out. This investigation covers the whole spectrum of activities taking place within the Customer Services & Support (CS&S) Department, which includes aftermarket service bulletins, supporting customers in modifying their aircrafts’ configuration and operation, competitive intelligence tool development, customer relationship management, technical publications sales and delivery, organizational development for maintenance engineering tasks. This project is beneficial to both the organization and Canada, since it aims at increasing the profitable revenue in Bombardier and contributing to the growth of an important sector in Ontario and Canada – the aerospace sector.

Advancing Dissolvable Fertilizer

Dissolvable Fertilizers are an agricultural innovation with slow and controlled fertilizer release. This technology is posed to reduce application costs and lead to optimized nutrient uptake by plants. Furthermore, it promises to reduce the agricultural, carbon footprint, as the frequency and amount of fertilizer applied is decreased resulting in less environmental pollution from nutrient loss. Excess nitrates and phosphates is leading national governments calling for the reduction in fertilizer use by 20 to 30%. However, the growing global population demands increased food production that is made possible through fertilizers. This project supports the development of dissolvable or glass fertilizer products. Sample compositions and plant growth on canola and/or select cereal crops will be assessed. The results will advance further development and customization of fertilize for improved nutrient ratios and dissolution rates for various crops and climates. The goal of the research outcome is to become commercially available to replace current, competitive fertilizers that do not solve greenhouse gas emissions, that are expensive, that tend to burn seedlings and that perform poorly in colder climates.