Projets novateurs réalisés

Integrating Optical and RADARSAT-2 Imagery for Enhanced Lake Ice Monitoring

This project aims to improve how lake ice is monitored in Canada by combining images from optical and RADARSAT-2 satellites with advanced data analysis techniques. Monitoring lake ice is important because it reflects climate changes, which affect both local and global environments. The partner company, ApoSys, specializes in using satellite technology for environmental monitoring, but current methods are limited by factors like cloud cover and lack of detailed data for smaller, remote lakes. By working on this project, ApoSys hopes to overcome these challenges and improve its ability to monitor environmental changes. The results will benefit ApoSys by enhancing its technological expertise, and potentially expanding its business into new markets. Additionally, better lake ice monitoring will support industries like fishing and tourism and contribute to climate change management efforts in Canada.

Rigorous development of database backends

Using a verification-based approach for database storage backends has the potential to avoid such bugs, but specifying the complexity of a modern backend upfront is a daunting task. To decompose the problem into smaller pieces, we base our approach on the following insights: (1) There are two broad classes of backends: eager, state-based maps, vs. lazy, operation-based journals. (2) We can write a high-level, abstract specification that accounts for both. (3) We can prove correctness and equivalence properties from the high-level specification. (4) The specification provides a kind of pseudocode for the implementation. (5) A similar high-level specification accounts for the composition of primitive stores. (6) We can express the complex internal architecture of a modern backend as such a composition.

An initial goal of the internship is to perform an experimental study (of performance and fault tolerance) of the implementation. The focus of the work will tackle items 5 and 6. The intern will design and implement a composition framework, and will use composition to mimic the functionality of an modern backend such as RocksDB. The research objective is to evaluate the backend designed following our rigorous approach, against comparable backends designed in an ad-hoc manner.

Ethnographic researcher – AI industry in Québec

Le projet Art-IA, mené par la Société des Arts et Technologies (SAT), MUTEK, Sporobole et le Metacreation Lab, explore les imaginaires liés à l’intelligence artificielle (IA) dans la création numérique. L’objectif est de créer une plateforme d’échange entre différents projets artistiques numériques pour répondre aux besoins des créateurs et ouvrir de nouvelles pistes de recherche et développement. Ce projet se concentre sur la structuration de communs de l’IA pour la création numérique, avec des séminaires et des groupes de travail. L’étude examine comment les acteurs du projet perçoivent les technologies et l’avenir de l’art en lien avec l’IA. Elle inclut la cartographie des projets artistiques au Québec pour identifier les besoins des créateurs et développer une boîte à outils technologique adaptée. La recherche s’intéresse également à l’utilisation de l’IA dans les projets des partenaires et aux discours sur l’IA sur les réseaux professionnels comme LinkedIn, permettant d’identifier les similitudes et différences dans les visions de la technologie parmi les créateurs et les industries culturelles. La méthodologie combine observation, entrevues avec les artistes et sessions de travail pour enrichir la recherchecréation.

Per- and polyfluoroalkyl substances(PFAS) removal from landfill leachate using Extracellular polymeric substances(EPS) and surfactants

This research project aims to explore new ways to remove harmful chemicals, known as PFAS, from landfill leachate using natural substances called extracellular polymeric substances (EPS) and commercial surfactants. PFAS are difficult to eliminate and pose health risks; nevertheless, existing remediation approaches are costly and entail environmental complications. By testing EPS and surfactants as potential solutions, the project hopes to find a more affordable and eco-friendly approach. The partner organization, Biogénie Canada inc., will benefit by gaining access to new, cost-effective methods for treating wastewater, which could improve their operations and help meet environmental standards more efficiently.

A new low cost device for skin monitoring

This project is aimed to develop an inexpensive device for general public in monitoring skin healthcare condition. The device will be able to take magnified images of skin in order to observe more detailed skin conditions. A low cost version of the device will be able to attach to a smartphone and use the built-in camera on the smartphone to take skin images. Another stand along version of the device will have a camera itself and will be able to wirelessly transmit images taken to other devices, such as PC or tablet. The intern will develop a working prototype for the device and transform it into a commercial product. The partner organization will benefit from the product developed by the intern and be able to further conduct manufacturing based on the intern’s work.

N2SOLVE: A Canadian/French Coordination Chemistry Partnership for Climate Change Solutions

N2SOLVE OVERVIEW: This research pairing between France and Canadian researchers will develop new functional molecules: ligands, transition metal, and main group compounds that promote the equitable use of resources, specifically with regard to the global nitrogen cycle. To ensure the well-being of future generations, innovative approaches that engage sustainable practice must be adopted. With an increasing population, it is essential that as a society, we work to mitigate greenhouse gas emissions, invest in alternative energy sources, and discover superior/more efficient routes for the synthesis of specialty chemicals such as nitrogen-containing compounds from abundant N2 sources. Collectively, this collaboration buttresses a research project devoted to exploiting inorganic and main group chemistry for application in sustainability science, enhancing Canada and France’s reputations for scientific excellence. We will study novel molecules that display unprecedented reactivity patterns, producing high-quality data and HQP. Impact includes identifying new catalysts for multi-electron/proton reductions, providing a route for the transformation of an abundant nitrogen-feedstock stream (N2) into N-containing organics. Together, this work will cement a strong and sustainable economy, protect our environment, and strengthen France and Canada’s knowledge sector.

Using Acoustic Shock Waves from Optically detected Shower Meteors to Constrain Fireball Energetics

The extra-terrestrial mass flux on Earth is not well known with uncertainties of about a factor of ten relative to the estimated averages. We use seismological recordings of acoustic waves generated by meteoroids to calculate their mass and energy, because seismic stations are relatively densely distributed and the recordings are freely available. We want to determine the amplitude- or energy-coupling coefficients between the air wave and the seismic recording which depends on several parameters such as the physical properties of the air and the solid ground and the incidence angle. We want to determine these coupling coefficients for recording sites in North America and their dependencies on seismic installation parameters, geology, topography and azimuthal direction. For this project we combine expertise in meteoroid science (Western University Ontario) and seismology (KIT Karlsruhe) to achieve a step forward in mass flux calculations.

Advanced Financial Integration, Forecasting, and SOP Development

This project aims to enhance Tutor Teach’s financial systems by automating processes, integrating accounting platforms, and improving forecasting tools. Building on previous efforts, the intern will focus on streamlining daily operations and increasing efficiency through automation. The integration of our internal accounting platform with external systems, like QuickBooks, will reduce manual input and discrepancies, enabling real-time financial synchronization. This will not only improve day-to-day financial management but also provide leadership with enhanced financial visibility. The intern will also work on developing predictive models for financial forecasting, incorporating historical data to project future revenue, expenses, and cash flow. These insights will help Tutor Teach make informed, strategic decisions and adapt to seasonal variations. A key piece of this project will also be the creation of Standard Operating Procedures (SOPs) for the new systems, ensuring long-term sustainability and consistency across financial processes. By establishing clear guidelines for data entry, reporting, and system maintenance, these SOPs will guide team members on how to manage financial tasks accurately and efficiently. Overall, the improvements will lead to better financial oversight, reduced operational friction, and greater scalability, allowing Tutor Teach to grow its business more effectively. Through this project, Tutor Teach expects to enhance its ability to respond to financial challenges, optimize resources, and support the company’s long-term goals of providing quality educational services across Canada.

Prompt Engineering for AI-Driven Polymer Materials Data Retrieval

This project aims to tackle a critical challenge in materials science: the efficient extraction of valuable data from a vast array of sources, including scientific literature, patents, and technical reports. By integrating advanced AI language models and tailored prompt engineering, we intend to create an intelligent system that streamlines the process of retrieving polymer-related information.
The anticipated benefit for the partner organization lies in the ability to access relevant materials data more quickly and accurately, ultimately reducing research time and enhancing decision-making. This innovative approach will not only elevate the quality of insights but also accelerate the development of new materials, giving the partner organization a competitive edge in an ever-evolving market. Through this project, we aspire to empower researchers with the tools they need to drive forward the future of materials science.

Informatisation de la gestion des ressources humaines et matérielles en sécurité incendie

En matière de gestion des ressources humaines et matérielles, les corps de pompiers du Québec doivent composer avec plusieurs obligations réglementaires en matière de formation et d’inspections d’équipement. Selon l’étude Portrait sociologique de la profession des pompiers du Québec (St-Denis, 2013), la diversité des types d’intervention constitue l’une des caractéristiques du métier de pompier (ex.?: combat d’incendie, désincarcération, matières dangereuses, prévention, premier secours, sauvetages nautiques et techniques, etc.), ce qui a mené à une multicertification et grande diversité des formations. La gestion des équipements des corps de pompier est également régulée par de nombreuses normes et réglementations. Il s’agit d’un enjeu prioritaire pour la santé et la sécurité au travail.
Jusqu’à présent, peu d’outils informatiques répondent aux besoins spécifiques des corps de pompiers. Le but de ce projet d’innovation est de développer des éléments informatiques qui permettront de faciliter le travail de gestion des ressources humaines et matérielles. Ainsi, les gestionnaires seront en mesure d’acquitter leur tâche de gestion plus efficacement et rapidement en diminuant considérablement les risques et en facilitant les suivis et la conformité.

Photocatalytic degradation of textile dye wastewater using solar energy

Dye wastewaters from textile industries is toxic and often causes serious environmental damage. In this study, an eco-friendly photocatalytic degradtion process which involves the use of a Ag-ZnO catalyst and solar energy will be used to degrade toxic dyes. Therefore, the main objectives of my reserch over the three month period will be to synthesize a solar active photocatalyst and optimizing the photocatalytic degradation process to treat textile dye wastewater. The findings from this research will assist textile industries to meet the wastewater discharge standards. The catalyst could be used to convert black liquor into useable chemicals.

Employing Quantum Machine Learning for Improved Deepfake Audio Detection

This project aims to research and develop on building a real-time deepfake audio detection system that is capable of distinguishing between authentic and spoofed audio voices with the help of Quantum Machine Learning (QML). The primary goal is to identify the limitations of existing classical ML techniques and explore how QML can improve the different existing challenges like processing big data, loading large complex models, improving generalization and detecting new forms of deepfakes.