Innovative Projects Realized

Assessment of Corrosion in RC Slabs using NDTs

Concrete is an abundant material present on earth today. It is believed that cement is the second-most abundant material after soil on planet. Infrastructure expansions and developments are close to impossible in the 21st century. Hence, building durable structures is necessary. Reinforced concrete, being a heterogeneous material, the possibilities of defects are immense. To save a structure from these defects, early detection and treatment are necessary. Non-destructive methods have been of great use to solve this problem. However, the conventional non-destructive methods to detect corrosion (using principles of electrolysis) have been very cumbersome. This research provides an innovative opportunity for me, to use Infrared Thermography (IRT) and Ground Penetration Radar (GPR) for detection of corrosion. The opportunities in this research area multiply if we club the use of concepts of Artificial Intelligence and Virtual Reality. Combining these aspects, this project can provide a breakthrough technology in precise corrosion detection in reinforced concrete.

An Alberta-based VAR Structural Model

International Financial Reporting Standards (IFRS) for loss allowances are changing, and financial institutions are proactively adapting existing methodologies and developing new ones to remain compliant. The main ingredient in the myriad of evaluations that banks are required to perform for compliance is risk assessment. The first goal of this research project is to review best practice risk models, with a special focus on modeling the evolution of changes in creditworthiness for industry sectors. In particular the project aims to estimate and forecast the probability a portfolio of loans’ changes in creditworthiness, and thus becomes more or less risky. State of the arts machine learning and time-series techniques are used to improve forecasting abilities of the existing models and allow for model validation using different forecasting samples.

A Finite Element Framework for Anisotropic Material Constitutive Modelling of Additive Manufactured Superalloy Parts

Additive Manufacturing is a rapidly growing technology in the gas turbine industry. Its numerous advantages allow for the design of complex shapes which have not been possible in the past, using conventional manufacturing method. The parts could be manufactured on demand, with reduce cost and lead time. Selective Laser Melting is the common method to additive manufacture metal super alloy parts for combustors and turbines. The anisotropic microstructure from the printing process pose a challenge to numerical simulation and conventional predictive models. To accurately predict the mechanical integrity of the part, an improved constitutive material model that could accurately predict the part non-linear deformation after yielding is crucial. It’s especially important to couple this non-linear deformation model with the thermo-mechanical loading where the temperature could be in phase or out of phase with the loading
This project aims to create an efficient and accurate non-linear deformation for predicting the mechanical deformation of the SLM parts, theirs associated stress and strain, in preparation for future mechanical integrity assessment model. Using mathematical model and empirical factors from material testing, an efficient predictive tool will be developed to extend the current capability within Abaqus finite element software.

Variations in gene co-expression of insulin receptor in the brain (ePRS-IR), working memory, and error-related learning in humans.

A new genetic approach which considers the effect size of single nucleotide polymorphisms (SNPs, selected from co-expression gene networks) over health outcomes, titled expression-based polygenic risk score (ePRS), was created in Prof. Patricia Silveira’s Lab at McGill University. The project aim is to assess in which way two ePRS of insulin receptors, one accounting for insulin receptors on mesocorticolimbic pathway and other linked to hippocampus, impacts working memory and error-related learning in children and adolescents from two cohorts: the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) cohort, using data from children aged 72 months of age; and the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort, using data from adolescents aged 17 years old. This study can impact neuroscience research by showing in which ways genetic variations on brain insulin receptors impact cognitive functions also impaired in people with obesity.

SSE – Leal De Lima Alves

The Women in AI for Good Initiative seeks to inspire, connect and highlight women in the field of good AI to promote more significant female participation in the machine learning industry. We also seek to embolden a vibrant international community working towards good and ethical technological development. Through a profile and mentorship initiative, Women in AI seeks to address three barriers to women’s active involvement in the field, namely: unconscious bias, pay gap and retention. We do this by creating safer spaces for women to connect, collaborate and shine.
The intern will be conducting a series of activities in order to lay the foundation for the deployment of two programs, a profiling initiative and a mentorship initiative.

Harvest Manitoba Community Garden and Growing Initiative

In March 2021, Harvest Manitoba will be launching their Community Garden and Growing initiative. This will be a community lead effort and will offer space in the community for learning about food production, hands on gardening skills and a location for safe community interactions. The purpose of this initiative is to increase access to fresh, locally grown foods, and empower community members to become a part of this process. My role will be a combination of hands on work in the community gardens, organizing the distribution of take-home garden kits and the grow-a-row program, and participate in relationship building and collaboration with other community organizations. By the end of this project, I will complete a feasibility report which will include an assessment of the current program structure and recommendations to enhance future programming in the community garden initiative. I will work towards finding ways for Harvest to better achieve their goal of providing opportunities for food insecure individuals to have access to fresh foods.

Mitacs BSI – Precision.ai

Precision.ai has been able to continue growing while keeping staff, partners and customers safe. An intern would be an important member of our growing agronomy AI team. Precision.ai now needs more agronomy expertise to achieve our growth objectives. The intern will help us accelerate our artificial intelligence model development by applying their expertise to more quickly identify crop and weed plants in the images we have collected.

Rhizome

À travers ce projet, nous souhaitons aborder plusieurs enjeux défis associés à la mesure d’impact social et plus particulièrement dans le contexte entrepreneurial.
Il n’existe pas encore de cadre flexible appliqué pour pouvoir à la fois analyser les résultats au regard de grands objectifs mais aussi de garder le spécifique de chaque organisation
Mais surtout il n’existe pas de cadre aujourd’hui pour pouvoir mesurer et évaluer l’action commune de plusieurs parties prenantes engagées dans une démarche systémique (et qui va plus loin que seulement qu’agréger les actions de chacune des parties prenantes et qui fait appel à de l’intangible).
À travers ce projet, nous ne souhaitons pas développer une n-ième nouvelle méthodologie de mesure d’impact mais nous voulons construire un cadre de mesure flexible et applicable, à partir des meilleures pratiques existantes. Nous pourrons le tester avec un partenaire de Rhizome qui opère dans l’écosystème entrepreneurial (incubateur/accélérateur/fonds d’investissement) et dans un secteur en particulier. Ce premier niveau permettra au partenaire et aux organisations du portfolio de ce partenaire de pouvoir mesurer leur impact social et environnemental et permettra à Rhizome de mieux accompagner ce partenaire dans sa croissance et son potentiel d’impact.
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Vérification numérique de forme

Chaque panneau d’aile d’avion de l’entreprise Sonaca est fabriqué d’une façon unique qui repose majoritairement sur le savoir-faire de ses opérateurs. Actuellement pour valider la conformité de ses panneaux, l’entreprise utilise une technique matérielle et manuelle où les panneaux sont souvent amenés à subir des ajustements avant d’être certifiés conformes vu le caractère unique de leur fabrication. Ce projet vise à remplacer cette méthode de validation manuelle par une méthode automatisée en assistant l’opérateur avec un outil numérique lui permettant de valider la conformité des panneaux. De plus, l’automatisation de cette étape permettra à l’entreprise un gain de temps de cycle de fabrication et lui permettra de mieux utiliser ses opérateurs. Enfin les connaissances et données acquises durant ce projet serviront de base à l’entreprise pour d’autres projets tournés vers l’automatisation de leur technique et une utilisation systématique d’un modèle numérique de leur panneaux

Ferme Guyon

Le stage a pour objectif de contribuer aux différents projets de transformation numérique de la Ferme Guyon, en particulier sur le plan marketing.
La stagiaire sera impliquée comme partie prenante dans plusieurs projets marketing, tant au niveau de la conception que dans les étapes d’exécution des projets.

Les principales activités prévues sont :
– Participer à la refonte de la stratégie de communication,
– Participer au projet de refonte du site web,
– Contribuer aux activités de design des offres et de conception des campagnes,
– Contribuer à l’exécution des campagnes de marketing numérique sur tous les canaux de distribution,
– Créer et rédiger des contenus riches pour supporter les campagnes marketing,
– Suivre les métriques de performances et construire des rapports,
– Collecter et analyser la data clients pour optimiser les stratégies de ventes,
– Rédiger des contenus pour les réseaux sociaux,
– Conduire des sondages de satisfaction client et alimenter le processus d’améliorer de l’Expérience Client,
– Participer à l’amélioration des processus d’affaires supportant le marketing et les stratégies de ventes

Information Literacy and Blockchain Technology

Blockchains have evolved from an obscure technology powering bitcoin to a multi-billion- dollar research area. From the financial tech industry, healthcare, digital identities, and government services, blockchains are touted as a revolutionary new mechanism for communication and transactions. As popularity in blockchain technology increases, many are left in the dark as to how this technology works, why it is important in preserving privacy, and how it can be used. Information Literacy, a concept from the Information Sciences regarding an individual’s ability to find and use information effectively, may help identify gaps in knowledge and develop techniques to educate / inform the public. Using interviews and focus groups, data collection, this study will gain insight into the level of information literacy as it translates to information retrieval habits, as well as to their understanding of blockchain technology. Additionally, this data can be used to better identify the information needs of Lifeguard App users and inform public health strategies in Canada.

SSE – Simard

En contexte de pandémie, notre organisme à but non lucratif poursuit ses activités de financement. Certains défis sont rencontrés puisque tous les contacts se font à distance, ce qui limite la qualité des suivis avec les chercheurs et partenaires. Les activités professionnelles de nos chercheurs financés ont été soit mises en pause, annulées ou reportées, ce qui a créé de la confusion dans les budgets alloués ainsi qu’au niveau des rapports de suivi des activités de recherche. Il est très difficile de poursuivre nos efforts afin de maintenir le suivi des retombées de nos programmes financés.
Le projet de stage aidera Brain Canada à développer une méthode et des indicateurs afin de faciliter l’évaluation des retombées scientifiques des projets de recherche financés par l’organisme et les effets à long terme de ceux-ci sur les carrières des chercheur.e.s financé.e.s et sur l’écosystème de recherche sur le cerveau à l’échelle nationale et internationale. Enfin, il permettra d’évaluer concrètement les effets de la COVID-19 sur la production scientifique à court, moyen et long terme des projets de recherche financés.