Innovative Projects Realized

Identification et caractérisation des propriétés viscoélastiques d’un point trigger localisé dans le muscle gastrocnémien à partir d’une technique d’élastographie par ondes de cisaillement

La douleur d’origine myofasciale (DMF) serait la principale cause des douleurs musculosquelettiques dans le monde et affecterait entre 30 et 85% des individus au courant de leur vie. Or, cette pathologie est actuellement très difficile à diagnostiquer car il existe aucune méthode d’évaluation objective permettant de quantifier les changements que l’on retrouve dans les muscles des personnes qui en souffrent. La DMF est caractérisée par la présence de petit nodules (nœuds) douloureux dans les muscle que l’on nomme les points gâchettes. À ce jour, l’identification de ces nodules s’effectue par palpation, une méthode d’évaluation très subjective. Il existe un besoin criant de valider un outil de mesure qui pourrait caractériser et quantifier les points gâchettes afin de supporter le diagnostic de la DMF et préciser les interventions qui visent cette condition de douleur chronique.

L’échographie par onde de cisaillement pourrait s’avérer être une solution à ce problème. Cette méthode de mesure non invasive et sans douleur a fait ses preuves pour d’autres pathologies.

Le but de cette étude est de vérifier si il est possible d’identifier, de quantifier et de caractériser un point gâchette localisé dans un muscle du mollet à l’aide de l’échographie par onde de cisaillement.

AI-Driven Insights from Knowledge Graphs via Integration with Large Language Models

In the current digital world, users are constantly sending companies signals of their experiences and preferences in various shapes and forms, including likes/dislikes of a particular offer/product, reviews on platforms and social media, and contacting customer service. However, despite the abundance of signals, E-commerce companies are unable to rapidly gain meaningful and actionable insights from those signals to react to the customer experience in a timely manner.

This project aims to address this challenge by leveraging knowledge graphs and Large Language Models (LLMs) to build an AI-based insights engine with a feedback loop to address the challenge of leveraging centralized customer signals/data from multiple sources to generate actionable insights that inform various product initiatives, campaigns and experiments across the organization to improve customer experience and generate business value.

The overarching goal is to provide a tool with an interface that allows business users to set their objectives or priorities and either automatically or manually prompt for hypothesis recommendations related to their product or campaign and receive insights for a complete set of hypotheses while accounting for overlapping initiatives within the company, enabling rapid experimentation.

Projet PISE- Pratiques d’Intégration Saines des Écrans- volet écoles primaires

Ce projet propose d’étudier les usages appropriés des écrans en classe à l’intention des enseignants qui doivent composer avec une présence de plus en plus importante des écrans à usage individuel. Il est développé en parallèle avec autre projet de recherche portant sur les répercussions des usages de l’écran à la maison que nous menons en partenariat avec le FRQSC et la Fédération des comités de parents (FCPQ). Les résultats émanant de ces deux projets de recherche nous permettrons d’avoir un portrait complet de l’usage des écrans en milieu familial et en milieu scolaire.
Nous proposons de 1) Sonder les usages que les enseignants et le personnel éducatif font des écrans et de 2) Analyser ces pratiques aux regards des recommandations canadiennes et québécoises sur l’usage des écrans.
Les conclusions de ce sondage et de cette analyse de pratiques permettront de situer les pratiques enseignantes aux regards des recommandations et de développer un guide de pratiques sur l’utilisation saine des écrans en classe.

Research Proposal: Understanding and Mitigating the Risks of Generative AI in Propaganda and Informational Warfare

THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW

FireBozz – Wildfire Prevention Sprinkler Nozzle System Development

As climate change intensifies, the frequency and intensity of wildfires have surged, demanding innovative solutions to mitigate their destructive impact. In response to this urgent need, FireBozz seeks to develop a specialized sprinkler head tailored specifically for wildfire suppression, aiming to revolutionize firefighting strategies and enhance community resilience. FireBozz, a leading provider of rapidly deployable wildfire fighting equipment, recognizes the inadequacy of traditional agricultural sprinkler systems in effectively combating wildfires. To address this gap, FireBozz envisions the design of a wildfire-specific sprinkler head targeted at effective water usage and dispersion to vulnerable areas to protect assets and prevent the spread of fires. By collaborating with applied research, iterative design, and field testing, FireBozz aims to pioneer a groundbreaking solution that safeguards communities and protects assets from the ravages of wildfires.

Graphene protected silicon alloy-based Li-ion batteries

The proposed research aims to advance energy storage technology by improving the cyclability of silicon-based anodes in lithium-ion batteries. Silicon anodes offer high theoretical capacity but face issues such as volume expansion and capacity fade. The project will explore substituting pure silicon with a silicon-carbon alloy core, hypothesized to enhance cyclability due to its amorphous structure and oxidation resistance. The research involves synthesizing silicon-carbon alloy particles, integrating them into shell/core structures, optimizing electrode casting, and testing electrochemical performance. Successful outcomes could significantly boost the energy density and commercial viability of silicon-based anodes.

Assessing the Alignment Between Proposals for the International Governance of Artificial Intelligence and the Common-Pool Resource Governance Framework

This project will evaluate the extent to which prominent international AI governance frameworks align with the common-pool resources (CPR) governance framework; its execution will consist in semi-structured interviews with experts and extensive literature review. The project aims to clarify how well-suited existing international AI governance proposals are to addressing the collective action problems marring international AI development. This clarification is a step towards mitigating these collective action problems and the risks they entail, as it will provide direction for how these proposals ought to be adapted. My research will also recommend policy outcomes to address current proposals’ blindspots, which will contribute to existing policy goals for international AI governance that may then be vetted by researchers and implemented into future international AI governance policy.
This project is directly aligned with the Centre for International Governance Innovation (CIGI) Digital Policy Hub’s core research focus on AI. One dimension of the CPR framework is the extent to which those associated with a common-pool resource are included in decisions about its governance—that is, CPR governance ought essentially to be democratic. In this sense, one criterion by which I will evaluate proposals is their consistency with democratic principles. To this extent, and considering my project’s focus on risks from AI systems, my research is also aligned with the hub’s research focus on democracy and security.

Demande SSE | Anne-Sophie Perras

Ce projet de recherche présente des avantages significatifs et des répercussions potentielles importantes pour le Canada, tant au niveau de l’industrie que de la société en général. En fournissant une analyse détaillée de l’impact des places de marché telles qu’Amazon et Facebook Marketplace, le projet vise à offrir des stratégies concrètes permettant aux entreprises canadiennes de maximiser leur performance sur ces plateformes. Cette initiative aidera à renforcer la compétitivité des fabricants et détaillants québécois et canadiens sur le marché mondial, stimulant ainsi la croissance économique et l’innovation dans le secteur du commerce électronique.

Emerging Military Technologies and Outer Space Governance

Project Ploughshares internships on Emerging Military Technologies and Space Security Governance

Investigating cellulose nanocrystal blends with PLA

Non-renewable fossil fuel derived plastics are ubiquitous in modern society, leading to negative environmental impacts. Urgent action is needed to reduce our societal reliance on these plastic products. The use of bio-based and/or biodegradable thermoplastics such as poly(lactic acid) (PLA) could be a potential solution, however these materials typically have limited mechanical strength, hindering their practical use in industrial applications. This research project aims to use cellulose nanocrystals (CNCs) – sustainable hydrophilic rod-shaped particles prepared from cellulose, the most abundant natural polymer on Earth – as a reinforcing and nucleating agent for PLA blends. Although CNCs have been previously investigated as reinforcing agents for PLA blends, this typically requires blending with harmful organic solvents or other non-sustainable compatibilization approaches to encourage good CNC dispersion within relatively hydrophobic PLA matrices. Herein, we aim to explore sustainable and scalable compatibilization strategies for preparing effective CNC PLA blends with improved mechanical and crystallization properties.

L2M – Drone-based Search and Rescue (SAR) in Dense Forests

The “Drone-Based Search and Rescue (SAR) System in Dense Forests” project aims to transform SAR operations using a coordinated swarm of drones equipped with advanced computer vision and machine learning algorithms. These drones, launched from DJI dock stations and connected via Starlink satellite technology, will efficiently locate missing persons in densely forested areas. By processing real-time aerial footage and ensuring constant data transfer through Starlink, the project minimizes the need for human SAR teams in hazardous environments, enhancing safety and mission outcomes.

The project’s Market research will focus on swarm SAR operations in forests and swarm forest data gathering and inventory. The project explores the latest drone technologies, computer vision, machine learning algorithms, and optimal trajectory planning for enhanced efficiency and safety in SAR operations. For forest data gathering, drones will provide accurate information on tree species, height, and Diameter at Breast Height (DBH), supporting sustainable forestry management. Analyzing market trends, technological advancements, and potential industry partnerships will help identify opportunities and challenges in deploying drone swarms for these applications.

Supported by Springboard Atlantic and the Atlantic Canada Opportunities Agency (ACOA), the project bridges academia and industry, fostering innovation in Atlantic Canada. It addresses regional innovation challenges by enhancing R&D collaboration, accelerating technology commercialization, and showcasing technological advancements in sectors like cleantech and agrifood. The project’s versatility extends beyond SAR to forest monitoring, wildfire protection, habitat conservation, agricultural monitoring, infrastructure inspection, and emergency response, highlighting its potential to address various environmental and safety challenges, contributing to regional priorities and sustainable development.

L2M – AI-Driven Subsea Video Enhancement with Advanced Filtering for Improved Visibility in Challenging Underwater Conditions

This project aims to enhance subsea video quality for improved underwater visual inspection and analysis, crucial for industries like offshore oil and gas, marine research, underwater construction, and maritime security. Leveraging advanced AI and machine learning techniques, we will address challenges like water turbidity, light attenuation, and visual distortions in underwater images. Through the Lab2Market Validate program and the Mitacs Business Strategy internship, we aim to develop commercially viable solutions tailored to the unique conditions of the Atlantic Ocean. This collaboration will help bridge the gap between innovative academic research and practical applications, enhancing the safety and efficiency of underwater operations and creating valuable commercialization opportunities for advanced technological research.