Innovative Projects Realized

Définir les objectifs et indicateurs d’adaptation aux changements climatiques

Puisque les changements climatiques sont déjà ressentis et le seront de plus en plus, il est nécessaire de s’adapter à de conditions environnementales sans précédent. Une quantité grandissante de programmes de financement vise maintenant à soutenir les communautés dans leurs démarches d’adaptation; par conséquent, le besoin d’évaluer l’atteinte des cibles d’adaptation devient de plus en plus important. Étant donné que le concept de l’adaptation est en évolution constante, et que les mesures d’adaptation sont généralement plus difficiles à quantifier que celles de lutte (par ex., réduction des émissions carboniques), il est essentiel de définir des indicateur quantifiables pouvant être utilisés par différents paliers de gouvernements (municipalités, régions, etc.) pour mesurer l’atteinte des cibles d’adaptation. L’objectif principal du présent projet est donc de recenser les cibles et les indicateurs d’adaptation aux changements climatiques utilisés à l’échelle mondiale afin de déterminer lesquels pourraient être applicables au contexte québécois. Ce projet aura permettra d’avancer la recherche dans ce domaine et d’interagir avec les acteurs du milieu, et donc permettra de faire rayonner l’organisme partenaire en ce sens.

Analyse et recherche d’optimisation d’un processus d’adaptation de contenu issu de la numérisation 3D à un contenu photo-réaliste et interactif

Le récents progrès dans le domaine de la numérisation 3D (SLAM, Lidar, lumière structurée, photogrammétrie, etc.) ont ouvert de nouvelles portes quant à la possibilité de réaliser des maquettes numériques interactive. Cependant, les outils traditionnels pour traiter les données brutes (nuage de point) de ces capteurs ne permettent pas de générer un modèle numérique adapté à l’utilisation d’une maquette 3D numérique photoréaliste et interactive. PreVu3D désire donc mettre en place son propre processus de traitement de donnée en adaptant les outils actuels et, dans le cas où ces outils n’existent pas, développer ces propres outils adaptés à ce cas particulier.

Greening the Canadian Landscape

Urbanization is rapidly increasing in Canada and these areas are confronting major challenges associated with climatic change. Canadian cities must navigate these challenges and may also significantly contribute to mitigation efforts. However, municipalities and developers lack the state-of-the-art information, policies, and resources necessary to be successful in this endeavour. This research project uses a case study approach to establish state of the art in relation to four themes (low-impact development, stewardship, community well-being, natural assets), consider each in terms of resilience, establish an evidence base of best-practice, execute active experimental trials, and monitor/evaluate their performance. The case study focuses on Prudhommes Landing, a significant Lake Ontario waterfront development. Knowledge generated will be transferable to developments elsewhere, provide a basis for evidence-based decisions, and influence the uptake of best practices. The project will contribute to Vineland’s core mandate for applied research and enhance their industry leader position in resilient landscapes.

Development of LBT-1 as an alternative technology to antibiotic molecules

Antibiotic resistant bacteria are one of the major threats of the 21st century. These superbugs, which are resistant to virtually all our antibiotic arsenal, turns benign infections, such as urinary tract infections, into life threatening diseases. It is estimated that, by 2050, 10 million people will die each year because of antibiotic resistance. We thus need to develop alternative technologies to conventional antibiotics in order to prevent this scenario from unfolding.
This project proposes a totally new approach to eliminate antibiotic resistant bacteria. Instead of using molecules to kill bacteria, we propose to use engineered probiotics capable of recognizing and eliminating specifically antibiotic resistant bacteria. This therapeutic breakthrough approach turns superbugs into regular bugs that we can eliminate.

Assessing the Sustainability of Snowmobiling Trails across Ontario

The proposed research seeks to understand how marginal winter conditions have impacted Ontario snowmobile trails in the past in order to make inferences about the future. The project will combine historic climate data (1989-2019), operational indicators (trail opening/closing, permit sales), and Regional Climate Model (RCM) outputs for the Province of Ontario to explore the implications of persistent marginal snowmobiling conditions and/or loss of district trails on long-term participation in the sport. The results of this study will directly benefit the partner organization by providing insight into which district trails will be climatically viable in the future, along with insight into shifting snowmobiler demand patterns under warmer conditions. The results will allow industry managers to prepare for supply- and demand-side changes in both the near-term (2050s) and longer-term (2080s), guiding decision-making on how best to invest and distribute limited resources (e.g., groomers, fuel, infrastructure) across Ontario’s 30,000km trail network.

Research into Convolutional Neural Network (CNN) Explainability

Machine Learning is advancing at an astounding rate. It is powered by complex models such as deep neural networks (DNNs). These models have a wide range of real-world applications, in fields like Computer Vision, Natural Language Processing, Information Retrieval and others. But Machine Learning is not without some serious limitations and drawbacks. The most serious one is the lack of transparency in their inferences, which works against relying completely in these models and leaves users with little understanding of how particular decisions are made. In this research we will explore new ways to represent the evolution of a CNN during training, and how the artifacts generated by these representations can be traced back to the inputs they’ve used during training. We will also explore the issue of imbalance in datasets, from the perspective of Parallel Coordinates and how to visualize dataset imbalance using this technique. The preliminary prototypes are going to be measured through usability tests with experts within the partner organization.

Application of Behavioral Synthesis to Multimedia Chip Design

In this project, we attempt to investigate the feasibility of using behavioral synthesis

technology for large scale multimedia chip design project. The project will be completed in

Metabacus Inc, an Ontario startup company that develops and markets behavioral synthesis

technology, which automatically converts software into chip designs. Although promising, one

obstacle for the wide deployment of behavioral synthesis as the next generation chip design

methodology is demonstrating the success 01 Ihe technology on large-scale chip project The

proposed research attempts to build a state-of-the-art, multi-standard, multi-resolution video

decoder with Metabacus’ behavioral synthesis technology. The decoder finds many

applications in TV, DVD, portable media players, and automobile entertainment systems. By

building a realistic application of large scale, this research shall provide answer to many key

questions of interest both to academia, and the partner company.

Analysis of socio-demographics with missing values in the UK Biobank

Data acquisition at scale implies missing values: in the biological signals as well as in the demographics and questionnaire data. These missing values are structured –missingness appears as blocks– and often causal –more missing health information for lower income individuals. While there are many works on the treatment of missing values in the clinical trial literature, little so far has been done on the specific case of the UK biobank cross sectional data and the impact of the missing data strategy on the estimation of the statistical links between behavioral or clinical assessments and imaging phenotypes.
The goal of this project is to investigate new strategies for the handling of missing data in population imaging dataset. A standard practice for the treatment of missing values consists in applying multiple imputation procedures. For predictive studies, recent theoretical results show how imputation should be combined with predictive models and cross validation procedures to give a prediction that is optimal when the data are missing at random. However, in population imaging, data are seldom missing at random.

Addressing intermittent water supply problems in developing nations

While most people get drinking water through underground water pipes, in some areas these pipes only provide water for a few hours each week. Globally, more than one billion people are served by these “Intermittent Water Supply Systems (IWS)”. In severely degraded systems, keeping pipes empty most of the time can reduce leakage and conserve source water, but it can also allow mud or sewage to enter through holes or cracks in the pipes, contaminating the water. During my time at the University of Toronto, I am going to create a simple model that will approximate how intermittent systems behave. Most of my work will be in the field of improving equity in IWS. This model will help to create and validate equity-focused models which will enable network designers and managers to maximize the equity in their IWS.

Neuromorphic computing with memristor devices

Neuromorphic computing is an approach to artificial intelligence (AI) that uses hardware elements inspired by the components of the brain and presents an alternative to the dominant von Neumann computing paradigm based on digital hardware. Recently, nano-scale devices known as memristors have been identified to offer area- and energy-efficient solutions when used in neuromorphic computing circuits that would require circuitry consuming hundreds of µm2 of die area to replicate with digital CMOS. Measurement of the static and dynamic electrical properties of memristor devices is therefore a strong concern for developing neuromorphic capabilities. However, given the stochastic nature of memristor switching, acquisition of massive amounts of switching data and a statistical treatment of that data is required for characterizing the devices and designing circuitry based on them. Currently, the lack of efficient testing and data acquisition methods is a major bottleneck facing the development of memristor-based neuromorphic devices.

3D Finite Element Simulation of Residual Stress Distributions Induced by Rough Milling Processes in Large Steel Blocks

This research project aims to identify the defects in large steel blocks and remove them by providing a practical solution which causes to optimize the machining operations and improve the product quality. The solution will be found using simulations instead of expensive, time-consuming experiments, which are impossible to conduct in large blocks to recognize the defects. This will enable the industry to resolve its problem appropriately by saving time and money. Finally, the deliverables in this project will lead a growth in research activities of the partner organization, a rise in productivity, a reduction in production costs, and an increase in demand for high-quality products on the market.

Étude de faisabilité de soudure par FSW sur section de tour 412

SBB désire changer de procédé de soudage pour un de leurs produits. Ils veulent remplacer 3 soudures présentement effectuées à l’arc électrique, par des soudures par friction malaxage (FSW). Le soudage par friction malaxage est un procédé relativement nouveau qui utilise la friction générée par un outil en rotation pour mélanger l’interface de deux pièces et les assembler. Ces soudures sont effectuées sur des tours d’urgences en aluminium servants à rétablir rapidement l’électricité lors de bris de lignes hautes tensions. Le soudage par friction-malaxage est procédé attrayant pour SBB en raison de sa propreté, de son automatisation facile, et de la résistance accrue des soudures comparativement au soudage conventionnel à l’arc. De plus, le projet mettra en pratique un nouvel équipement permettant d’effectuer le soudage et l’usinage du produit dans une seule machine, augmentant potentiellement la cadence de production.