Projets novateurs réalisés

Evolving data storage design for a highly regulated financial sector.

Global service providers in highly regulated financial sectors must accommodate an ever-changing, sometimes competing, landscape of regulatory concerns. This project seeks to determine a reasonable path forward in technology design and adoption to accommodate current and anticipated data privacy and data residency concerns, making it possible to keep data within borders while still facilitating collaboration across those borders. Consumers are increasingly aware of the collection of their private data, but are often unaware of cross-border movement of their data. Businesses are cognizant of the limited (or untested) reach of legal and regulatory recourse when their data (and their customers’ data) unnecessarily crosses borders. This project seeks to add technology frameworks to aid in addressing those customer and business concerns.

Improving Social Conditions for Indigenous Youth: A Case Study of Organized Sports in Canoe Lake Cree Nation

This Internship project will look at issues affecting the overall social conditions of First Nation youth in Northern, rural and remote communities, with a specific focus on the Northern community of Canoe Lake Cree Nation. Historically, the people of Canoe Lake lived a traditional lifestyle off the land, including traditional land that was lost to the Cold Lake bombing range. The loss of traditional land and livelihood has had enormous social effects on the community, and its peoples. Organized sport and recreation provide an opportunity to improve social conditions for northern communities, and to rebuild the First Nation youth identity and confidence. There is a tremendous amount of untapped potential for First Nations youth, and this research will highlight how we can better the youth social outcome.

3D Imaging Development for Part Dimensional Measurement

Manual inspection method is still applied by mounting parts on customized checking fixtures and thus dimensions are checked with different gauges/feelers. Typically, it could take 10 -30 minutes to fully inspect the required spatial dimensions of one part. This project will develop an automated 3D dimensional inspection system for deep drawing parts. After manually mounting the part, the system will fully scan the whole part by 3D sensors/scanners. Interested features like primitives, holes, edges, diameters or angles then can be calculated or determined through 3D point clouds data post-processing. Shape and position tolerances will be evaluated if they can meet the customer’s requirements. The expected inspection accuracy and speed will be less than 0.3 mm and 1 min/part respectively.

Installations et aménagements participatifs comme outil touristique

Montréal se positionne avantageusement sur l’échiquier mondial de la recherche et l’innovation dans les domaines de l’informatique, des jeux vidéo, de l’intelligence artificielle, de la robotique et de la créativité numérique. L’avènement et l’utilisation de nouvelles technologies dans les secteurs des transports et de la santé est indéniable. Dans le domaine des arts et de la culture, il s’agit de l’émergence d’un véritable créneau d’innovation : celui de la créativité numérique dédiée à l’espace public pour lequel Montréal devient une référence incontournable. Plusieurs exemples d’installations participatives numériques ont marqué l’imaginaire des montréalais mais également d’autres villes à l’étranger. Six projets du Partenariat du Quartier des spectacles ont voyagé dans 20 villes pendant un an. Ces installations constituent de nouvelles expériences pour les locaux et les visiteurs, tout en contribuant au rayonnement de la ville et de ses créateurs. Il est question ici d’analyser leur impact en tant qu’outil de tourisme culturel, de marketing territorial et relationnel.

Computing algebraic relations in multivariate settings

The aim of this project is to design fast computing a fundamental mathematical object called algebraic relations, particularly on Pade approximants and multivariate interpolants. This is motivated by numerous important applications, within computer algebra itself and in related fields such as cryptology, coding theory, and polynomial optimization. The goal is twofold: first, to design algorithms whose complexity bounds improve over the state of the art; second, to write efficient implementations of these algorithms.

Evaluating effects of local, landscape, and regional factors on Bobolink (Dolichonyx oryzivorus) nest survival

The bobolink (Dolichonyx oryzivorus) is a migratory songbird that is currently a species at risk in Canada due to steep population declines. Because bobolink nest on the ground in pastures, hayfields, and other grassland-type habitats, nest success and abundance may be influenced by various environmental factors. Our goal is to understand whether these factors directly or indirectly affect bobolink nest success. This is important as it will contribute to filling current knowledge gaps regarding bobolink breeding success. We will analyze nest success using nest data collected throughout southern Ontario and will incorporate factors including agricultural use, the landscape surrounding grasslands, and differences across regions (i.e., temperature, weather) to understand which factors are associated with high or low nest success. Results will guide efforts to conserve this species at risk by identifying the environmental conditions favourable for nesting bobolink.

Peer Information and Substance Use Decision Making in Street-Involved Youth

This research aims to learn more about the way that homeless and street-involved evaluate information regarding substance use from their peers. To this end, this research team will work with Operation Come Home, a non-profit organization supporting homeless and at-risk youth in downtown Ottawa. The research team will recruit and interview 40 – 50 youth at Operation Come Home to assess a number of factors relating the way that they evaluate peer information regarding drug use. The interviews will be analyzed to search for themes relating to the way that street-involved youth receive and evaluated substance use information from their peers, and whether the use of peer information is related to subjective indicators of well-being. The results of this research will be directly communicated to the primary care workers at the partner organization, in order to facilitate improvements in their communications of high-quality information regarding substance use to this population of youth.

Extension of AWSOM to Strut-Braced Wings

Bombardier is interested in investigation a novel aircraft configuration known as the strut-braced wing configuration, which is has the potential for improved fuel efficiency relative to current tube and wing aircraft. However, Bombardier’s preliminary multipdisciplinary design optimization tools need to be extended in order to be applicable to this configuration. The intern will extend the capabilities of Bombardier’s tools to enable sizing of strut-braced wing. This will allow accurate estimation of wing weight and stiffness properties of strut-based configurations, thereby facilitating design and evaluation of such configurations. This capability will assist Bombardier as it examines various options for future aircraft.

Combining Seq2Seq Models with Collaborative Filtering Techniques for Explainable Recommendation

Layer 6 builds state-of-the-art recommender systems for TD’s online businesses. Collaborative Filtering (CF) is a common recommendation approach that widely adopted by many e-commerce platforms. Modern CF algorithms attempt to exploit latent features to represent users and items, which can lead to the lack of transparency of the recommender systems. In order to build a trustworthy recommender system, it is necessary to provide explanations associated with each recommendation so that users can understand why a specific item has been suggested. The proposed research project would explore the potential of combining sequence-to-sequence (seq2seq) natural language generation models with collaborative filtering techniques into a multi-task learning setting. The result would be a recommender system that could predict customers’ needs with a high degree of accuracy, while producing effective, personalized explanations. Such explainability would build trust between the recommender system and TD’s customers, and accordingly drive sales and customer loyalty.

Categorisation des charges de proiet: outil d’aide a la decision

quebecoise de genie-conseil et de gestion de projet, qui exerce dans cinq secteurs que sont

I’energie, !’industrie, les transports, les infrastructures et Ie batiment. L’objet de cette etude est de

mettre a la disposition de la haute direction de cette organisation, un outil qui lui permette d’affecter

ses competences internes aux differents projets que realise I’entreprise.

L’interet de cet outil se situe a un double niveau. Premierement, au niveau de I’organisation, il

facilite la constitution rapide des equipes de projet par une affectation rapide et efficiente des

competences. Deuxiemement, au niveau des charges de projets eux-memes, r outil permet une

reconnaissance sociale, en donnant une visibilite sociale des professions.

En fin de compte, routil propose est un moyen de placer rentreprise dans une dynamique de

developpement.

An Artificial Agent for Light Switch

Ecobee is a home automation company that makes thermostats for residential and commercial use. Smart lights are the second-most desired home automation devices after thermostats, but being able to remotely control the lights is only a small part of the vision. ecobee light switches have embedded microphones, a speaker, and far-field voice technology that allows the user to control the lighting, thermostat, and other smart home products. One major goal of this project is to create an artificial agent, which monitors and controls the light switches. To make this concept a reality the agent will gradually learn the residents’ schedule and behavioral patterns, and make decisions accordingly. The light switch agent aims to estimate the probability for turn on and off actions by leveraging machine learning and AI, in a non-deterministic environment.

Examining Media for Fraud Detection

Nowadays a corporation’s public image plays a major role in that company’s decisions and financials. This project involves predicting fraud and errors within the financial statements of publicly traded companies. The goal is to incorporate information such as press releases and industry media coverages to provide an insight to these companies under audit and their industries. Ultimately, this would be used as a tool to assist auditors identify fraud and errors within these financial statements.
This project covers analyzing collected media information for features such as corporate sentiments, public opinions, and trend predictions. This can help identify misstatement within annual financial statements, stock manipulation, and other issues.