Projets novateurs réalisés

Fast optimization of time dependent vehicle routing problems with profits

In this project we will study distribution problems arising when time-sensitive information needs to be collected
and handled appropriately. These problems arise as a business need of our partner organization to support the
decision systems of several customers that require fast and reliable optimization methods to design distribution
plans under tight time considerations. Either the business hours of demand points or their preferences for
inventory replenishment decisions are a crucial part of the problems under interest. This internship will focus on
understanding, modeling and proposing potential avenues of research for handling and integrating the different
complex attributes arising in these distribution problems.

Paramétrisation de stratégies de Gestion de la reprise après panne

Suite à une panne du réseau électrique, les principaux équipements des ménages voient leur consommation énergétique s’accroître pour combler le déficit accumulé pendant la panne. Par exemple, les équipements de chauffage et de climatisation s’activeront à pleine puissance jusqu’au rétablissement des températures de consigne. Il en résulte, au niveau du réseau de distribution, une demande supérieure à celle rencontrée en période de pointe. C’est donc la puissance en période de reprise qui est utilisée aux fins du dimensionnement du réseau de distribution. Si on limitait la puissance associée à la reprise, on pourrait réduire les besoins d’investissements qui seront associés à l’accroissement général de la demande en électricité, qui sera substantielle si on veut atteindre les objectifs de décarbonation de l’économie.
Ce projet vise la coordination des stratégies de contrôle en reprise après panne des principales charges résidentielles (chauffage, chauffe-eau, véhicule électrique) afin qu’elles résultent en un comportement agrégé plus favorable tout en demeurant acceptable pour les consommateurs. Les résultats pourraient alimenter la préparation de nouvelles normes de performance pour ces appareils.

Redesigning Transformer Neural Networks for Data-Efficient Breast Cancer Diagnosis

Transformer neural network models have achieved state of the art results in many areas of machine learning, including natural language processing (e.g. BERT, GPT-3) and computer vision (e.g. ViT, SAM). However, to achieve these results currently requires extremely large training datasets which are not available in every domain. One such domain is medical imaging, in which data is often limited due to privacy concerns and costs. This project aims to overcome this limitation by integrating domain-specific knowledge into a transformer pre-trained on large general datasets. In contrast to previous work, which generally treats the transformer as a black-box, our approach will integrate domain-specific knowledge by modifying the transformer architecture.

Vers une vitrine technologique connectée 5.0

Les vitrines technologiques sont des outils précieux pour les entreprises, offrant des solutions innovantes qui améliorent leur performance et leur compétitivité. Elles favorisent l’innovation en exposant des avancées technologiques de pointe. En adoptant ces nouvelles technologies, les entreprises peuvent augmenter leur productivité, réduire les coûts et améliorer la qualité de leurs produits ou services. Les vitrines technologiques créent également des opportunités de collaboration et de partenariats stratégiques, renforçant ainsi la compétitivité collective de l’industrie. De plus, elles permettent la diffusion des connaissances et des bonnes pratiques, favorisant l’apprentissage mutuel au sein de l’industrie.

Ce projet à pour but de concevoir, déployer et assurer la maintenance continue d’un espace innovant qui exploite les avancées technologiques pour optimiser les processus opérationnels, à accroître l’efficacité, améliorer la performance et la compétitivité des entreprises et à favoriser l’innovation au sein de l’industrie. Il sera question de mettre en œuvre des solutions connectées, telles que l’Internet des objets, l’intelligence artificielle et la réalité augmentée, pour offrir une expérience utilisateur immersive et personnalisée.

Translating Advanced 3D Ultrasound System for Measuring Dysplasia Metrics into Clinical Practice

In this work we seek to deploy a web app to help orthopaedic clinicians all around the world analyse 3D ultrasound (US) volumes of hips to more accurately diagnose developmental dysplasia of the hip in infants. We intend to
develop and evaluate artificial intelligence (AI) models capable of segmenting relevant hip bones from 3D US volume and subsequently calculate geometric metrics indicative of dysplasia. Our primary focus is to develop
novel AI training protocols that enable better generalization and thus ease the deployment of the models to the clinical setting. Specifically, we intend to design methods to augment the data with which the AI models are trained
in ways that are congruent with ultrasound imaging acquisition. Once we evaluate the capabilities of our AI model and address potential translational limitations, our partner will be able to deploy the AI model in the clinical
environment and benefit from advanced analysis techniques that could help better understand and diagnose this condition.

Investigation of Sargassum-Based Bioethanol Blends as a Sustainable Alternative Fuel

This project seeks to contribute to the global cardon emissions reduction agenda through the use of alternative sources of fuel that do not produce carbon emissions. In other words, this approach is known as “CO2 avoidance” through the use of carbon-neutral fuels. The production of biofuel, namely bioethanol using edible feedstock has raised serious humanity concerns along the lines of the issue of malnutrition and hunger prevalent in our day. This has shifted the focus to using non-edible feedstock such as sea-weed (Sargassum) to produce bioethanol and its blends. Sea weeds offers an excellent alternative to displace fossil fuels and from an ecological point of view, sea weeds aid in reducing the carbon dioxide in the atmosphere and supplying oxygen :to the sea. For this reason, sea weed has been proposed as a promising biomass material that can be easily converted to bioethanol based on its low lignin (an unwanted material in the biomass to ethanol conversion process) content.

Pathfinder MVP 2.0 Development Project

Pathfinder365 is a digital community marketplace that focuses on the tourism sector. By harnessing the collective benefits of an interactive two sided marketplace, a map interface, a dynamic suite of features and tools, and an algorithm-free environment, Pathfinder is positioned to become the most influential digital aggregator for the micro-tourism industry. Pathfinder is in its second year of development and is currently undergoing a full market launch and establishing traction in select provinces. It’s also initiating a dynamic sales and marketing strategy.

While Pathfinder is working with an agency team, it’s also bringing developers onto its own internal team, who will work in concert with the agency’s developers. That way Pathfinder establishes its internal team, while benefiting from the stabilizing effect and experience of a seasoned professional agency.

Pathfinder has one awesome developer starting in April on an IRAP Youth Grant, and it has a second highly skilled developer, an international MBA student at the U of S, who’s currently working under the agency, but Pathfinder is looking to migrate him onto a grant program like the Mitacs BSI. Both of these developers will be absolutely essential to moving Pathfinder from the MVP stage to establishing product market fit, and will be the foundation of helping Pathfinder effectively scale throughout Saskatchewan, Manitoba, Alberta and British Columbia.

Catalyst-Aided CO2 Capture with Amine-based Solvents

This project seeks to improve the rate of CO2 removal from the exhaust gases of industrial processes in order to help solve the issues of global warming and climate change. Various carbon abatement techniques have been developed and used. The most used technique is called “carbon capture”. These technologies come with their own challenges such as large equipment sizes and high energy requirements which result in high capital and operating costs. Therefore, the objective of this specific research project is to facilitate this process by developing high performance catalysts with the aim of accelerating the rate of CO2 removal from the exhaust gas while using the most minimal energy in the regeneration process. This will ultimately lower both the capital and operating costs associated with the carbon capture process thereby making the capture process affordable and implementable .

Physicochemical transformation in Mars analogue materials

Instruments onboard the NASA Curiosity rover have revealed that organic matter (OM) is present on Mars; these chlorohydrocarbons are thought to originate from a reaction of OM with Martian perchlorates. We hypothesise the reaction may occur in the Mars near-surface, induced by the harsh radiative environment. Our team is thus investigating the influence of radiation on organic molecules under simulated Mars surface conditions. The Canadian Light Source (CLS) synchrotron allows us to tune the energy of X-rays to the same energies as fluorescence photons released by Fe, Cl, and Si, common elements in Martian surface materials, simulating these radiation sources on Mars. We can expose our samples of OM and simulated Mars regolith to bright beams of X-rays at CLS that allow us to simulate millions of years of exposure in timespans of minutes to hours. We will use this approach to investigate the degradation and chlorination of organic compounds in simulating Martian environments. After X-ray exposure, we will characterize these samples using GC-MS and FTIR. We expect our results will contribute to understanding long-term preservation of OM in Mars’ near-surface, and the chemistry of these compounds as they are generated and degraded through our identification of degradation by-products.

Assessing Plant Damage and Mortality Rates of Root Maggots and Cutworms in the Presence of Entomopathogenic Nematodes (EPNs): A Comparative Study on the efficacy between native and non-native, commercial EPNs

To ensure effective pest control in Alberta, we will compare the efficacy of our local entomopathogenic nematodes (EPNs) with a commercially available strain, S. feltiae. EPNs are microscopic worms that naturally kill pests like black cutworms and cabbage root maggots. Our study will focus on a native EPN strain (strain 213) and a commercial strain of S. feltiae. We will expose pests to these nematodes, observe plant damage, and measure pest mortality rates. This research aims to determine if our local EPNs are more successful than commercial strain in pest control. Positive results would benefit Alberta’s farmers, providing a sustainable and eco-friendly solution against harmful pests. By utilizing our native EPNs, we can minimize crop damage, protect yields, and support the sustainable cultivation of cruciferous crops in our region.

Excitations électroniques dans les cuprates supraconducteurs

Dans le domaine de la supraconductivité à haute température critique, les cuprates sont les matériaux les plus prometteurs, mais aussi les plus complexes, en raison des différentes phases de la matières qui coexistent. En particulier, la phase pseudogap, qui coexiste avec la supraconductivité, demeure un des grands mystères de la physique moderne. L’objectif de ce projet est d’aider à élucider cette mystérieuse phase de la matière. Ceci se fera en mesurant le comportement des électrons dans certains cuprates l’aide de mesure de conduction de la chaleur à très basse température au voisinage du point critique quantique où la phase pseudogap apparait à l’intérieur de la phase supraconductrice.

Development of a Scalable Modular Automated Vegetable Packing System for Canadian Farmers.

The EasyPack machine is designed to process the weighing and packaging of large crops such as potatoes, onions, turnips, and carrots for medium to small-scale farming operations, in order to overcome challenges caused by labor shortages. This solution is capable of weighing and packing potatoes into a variety of bags with capacities ranging from 20-50 kg (40-110 lbs.), as well as big packs. The proposed research project aims to enhance the functionality and efficiency of the packaging machine by incorporating new features through a modular design approach.