Projets novateurs réalisés

Stage de recherche sur les techniques des retombées atmosphériques appliquées à l’érosion du sol et la sédimentation

Le stage de recherche vise à approfondir la compréhension par le stagiaire des principes de bases et de l’application des méthodes utilisant les radionucléides de retombées atmosphériques pour reconstruire les processus d’érosion et de sédimentation. Le stagiaire bénéficiera de formations techniques en spectrométrie gamma, et de soutien pour mettre en œuvre les modèles de calcul de redistribution de sol à partir des inventaires de radionucléides, mais aussi pour l’établissement de modèle d’âge pour les archives sédimentaires à partir de mesures de profils de radionucléides.

Cela lui permet d’avoir des compétences et expertises précieuses en matière de gestion des sols face à leur dégradation à l’échelle des bassins versants, notamment dans le contexte du changement climatique.

Landscapes of Minority Language Learning

Both Wales and Quebec are known for the importance they place on promoting the Welsh and French languages, respectively, and have introduced a variety of policy, cultural, and educational initiatives to this end. They owe these successes partly to their history of collaborating and sharing knowledge to enhance language revitalization and education efforts in both contexts. This project will build on this history of collaboration. It will document adult newcomers’ linguistic integration trajectories through formal learning, such as community language classes, as well as informal learning such as seeking out opportunities to speak the minority language during their daily tasks and joining minority-language social groups. This research will benefit both Canadian and Welsh contexts by providing a more complete view of linguistic integration than is currently available. It will also highlight the agency and resourcefulness of adult language learners and will reveal the barriers that hinder their linguistic integration, opening up new opportunities to better support these learners’ full inclusion and participation in their new communities.

Artificial Intelligence through machine learning to explore individual signatures in animal sounds

Our team investigates vocalizations of Savannah Sparrows (Passerculus sandwichensis) to understand how vocalizations are used during the breeding season. Our team previously detected a distinctive call type – the “twitter call”- that was poorly described and understood. The function of this call is unknown. The goal of this project is to explore if the twitter call contains an individual signature allowing birds to identify each other by call alone. Using recordings previously collected in the field, we will work with Dr. Nicolas Mathevon of the University of Saint-Etienne and ENES Bioacoustics Research Lab to use Artificial Intelligence to apply a new method developed by his team to detect individuality in the calls of individual birds. These methods allow a more accurate analysis of calls and increase our ability to detect the specific acoustic features that provide individuality. Knowing if this call is individually specific will increase our understanding of possible functions of this call and direct future experiments to test these functions. This research will additionally benefit Dr. Mathevon and his team by providing a full dataset to continue testing their new methodology, which has been previously used to explore more complex bird songs, rather than simple calls.

Effective Prediction and Recommendation by Concentrating on Dynamicity and Evolution in Charity Data Processing

Individuals (donors) wishing to donate funds to non-profit and/or charitable organizations want to know how the organizations operate and how effectively their donations are used. Dexterity has developed an online service called Place2Give which aims to answer those questions. The research project aims to employ social network analysis and data mining to enhance the data introduced into the databases used by Place2Give from which the data for the analysis of the charitable organizations behavior is extracted on a case by case basis.

Aggregation of Distributed Residential Energy Storage for Enhanced Grid Resilience and Renewable Energy Growth

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Characterisation of binder materials in silicon-graphite electrodes from slurry to lithium-ion battery

The scaling up of lithium-ion battery technology for high energy applications such as powering electric vehicles is not without its challenges. Increasing the capacity of these large energy storage systems is key in addressing consumer concerns about the driving range of electric vehicles, which remains inferior to that of gasoline-powered vehicles on average. The use of new materials within the battery electrodes is a promising avenue to doing just that. As such, the present study focuses on silicon-graphite composite electrodes, which have a significantly higher capacity per unit weight than standard graphite electrodes. However, issues with maintaining this capacity over many uses persist. One way to stabilize these electrodes is to optimize the binder that ensures the cohesion of the electrode material. The present study focuses on polyacrylic acid-based polymers and the effect of modifying several key parameters such as the solution pH, the water content, and the chain length of the polymer on the electrochemical performances of the electrodes. The information gained from this study will help both research groups improve their battery formulations going forward and foster collaboration between Canadian and French universities and industry partners.

Developing predictive models for air pollution and heat exposures in South Africa and Canada

The overall objective of the Mitacs Globalink Project is to develop and assess the validity of models of exposure to air pollutants and temperature variability, using data extracted from a variety of available sources in South Africa and Canada. This objective will be achieved through a series of specific aims.

The first of these aims will be (1) the identification of the sources of available datasets, using established networks in South Africa and Canada to locate, access and extract the relevant data from these sources. Ground station data in both countries is generally available through publicly accessible portals.

Aim (2) will require subjecting these datasets to rigorous and systematic evaluation to determine their quality. This will require using established methods of data checking, and a review of the quality control methods used in data collection. Having determined the quality of the data, the next step is ensuring validity and ground truthing. This will require a variety of methods of data triangulation.

The data will then be used to achieve Aim (3), to use the validated datasets to develop predictive models using machine learning (ML) methods for air pollution and heat exposures using satellite earth observations and ground-level monitoring stations.

Energy Efficient Integrated Design of Flight Management Systems and Autopilots with Terrain Avoidance Capabilities

The amount of emissions to the atmosphere is currently an important environmental concern as policy makers and Heads of State are starting to demonstrate a strong interest in energy efficient transportation, in particular energy efficient aircraft. However, current autopilot technology will often not take into account the energy used to perform a given maneuver which can lead to potentially larger fuel consumption and larger atmospheric emissions than what is strictly necessary. The task of energy optimization is typically left to a flight management system (FMS). However, the next generation aircraft will require additional functionality in fuel efficiency that can benefit from a tighter and better interaction of the FMS and the autopilot subsystems. For such a scenario, this research proposes to perform an integrated design of the FMS-autopilot ensemble to be more energy efficient. A first collaborative effort of the applicants, has involved the study of energy efficient autopilot design methods for fixed set points. We now propose to study optimal control solutions for the interconnection of the FMS to the autopilot and propose new techniques of design of the FMS-autopilot ensemble seen as a synergetic unit.

An Automatic Approach to Transfer Function Tuning Using Reinforcement Learning

Optimizing an interaction to achieve the highest possible performance is desirable for many applications. For instance, even minor improvements in the mapping between a computer mouse’s movement and a cursor on a screen can significantly enhance comfort and usability. Similarly, better mapping an operator’s joystick inputs to crane movements could boost productivity. Both examples emphasize the importance of finding an ideal transfer function (i.e., the mapping between human input and system output). However, while we have the affordance of relying on several decades of tuning when using the transfer function of touchpads and mice, we do not have this convenience when it comes to novel interaction techniques. Correspondingly, we need approaches to automatically determine the ideal transfer function to create the most performant interactive systems possible. We propose using reinforcement learning (RL) to identify optimal input-output mappings for novel inputs. Our approach will first explore familiar devices like touchpads and mice before extending to emerging inputs like electromyography. This work will be supported by a collaboration between a French research lab specializing in transfer functions and a Canadian lab focused on machine learning. Together, we aim to advance the automation of transfer function tuning, creating more efficient and accessible systems.

Dépôt de couches minces nanocomposites TiO2/Fe2O3 par procédé hybride PECVD/injection de solution

Les couches minces nanocomposites (i.e. formées de nanoparticules incluses dans une matrice) sont attractives du fait de leurs propriétés multifonctionnelles. Une approche pour obtenir des matériaux Nanocomposites Multifonctionnels Contrôlés consiste à injecter une solution colloïdale (ici oxyde de fer) dans un plasma (précurseur de TiO2) de manière à obtenir, en une seule étape et sans manipulation directe des nanoparticules, une couche mince nanocomposite. L’application visée concerne la photo-oxydation de molécules-tests pour la dépollution de l’air et de l’eau : en effet, le but de ce projet est de préparer des couches minces nanocomposites possédant des nanoparticules d’oxyde permettant un rendement photocatalytique supérieur aux couches minces de TiO2 seul (sans nanoparticules). Les couches minces seront fabriquées par deux processus différents (pression atmosphérique et basse pression) et leurs structures et fonctionnalités seront caractérisées dans les deux laboratoires (nantais et montréalais).

Caractérisation par imagerie rapide d’un plasma d’onde de surface sous l’influence d’injection pulsée de gaz

Les procédés plasmas assistés par des injections d’aérosols sont commun pour effectuer du dépôt de revêtement fonctionnel, le mode pulsé permettant au plasma de retourner à l’équilibre est par ailleurs préférable au mode continue. Les plasmas d’onde de surface sont reconnus comme étant particulièrement stables et faciles à mettre en place. Cependant, ce mode d’injection semble rompre la stabilité de la décharge. Les injections pulsées d’aérosols dans un plasma d’onde de surface n’étant que très peu documentée, une étude de caractérisation de la décharge dans de telles conditions est alors nécessaire. L’imagerie rapide est un outil de diagnostic permettant d’analyser l’intensité lumineuse du plasma à partir d’image de ce dernier et ainsi de remonter a ses propriétés fondamentales.

Étude de l’effet mémoire d’une décharge à barrière diélectrique dans l’air à la pression atmosphérique

Les décharges à barrière diélectrique diffuses ont un intérêt en industrie pour faire du traitement de surface par exemple. Cependant, ce régime de décharge dépend de nombreux paramètres (gaz, fréquence d’excitation, tension appliquée…) et peut être compliqué à obtenir. Obtenu dans un premier temps dans les gaz noble, ou encore l’azote, il a été montré plus récemment qu’il était possible de l’obtenir dans des gaz moléculaires comme l’air. Quelque soit le gaz utilisé, on distingue l’effet mémoire. En effet, avant d’obtenir la décharge diffuse, on observe un autre régime de décharge appelé le régime filamentaire. Cet effet mémoire est dépendant des électrons germes. Ces électrons sont des électrons présents juste avant la décharge suivante et permettant d’obtenir la décharge diffuse. Dans l’air, les mécanisme permettant d’obtenir ces électrons germes sont mal connus. Ce travail repose donc sur l’étude des mécanismes de surface et/ou de volume permettant l’effet mémoire dans l’air.