Extension of fast hybrid VLM-VPM schemes for helicopter flow simulations

Aircraft flight simulators are important to airworthiness standards and thus safety. The simulators are used in pilot training, as well assisting in the design of flight vehicles. Flight simulators need physical models that reproduce, in the computer, the real devices such as engines, pilot human response, cockpit, etc. In particular, it also needs an aerodynamic […]

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Predicting failures in networking equipment using machine learning

This project is in collaboration with Ciena, an international company specialized in the supply of telecommunications networking equipment and software services. Electrical components produced by Ciena are important in many networking equipment such as routers or switches. Every year, a large number of components is produced. However, the production process may have some flaws, causing […]

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Conversion du modèle d’affaires ContinuumRD en un parcours numérique d’encadrement de l’innovation : Portion gestion de l’innovation

Le stage a pour objectif d’appuyer la transformation du modèle d’affaires de ContinuumRD en une version numérique de cette dernière. Ce stage couvre la portion “Gestion de l’innovation” réalisée par la stagaire Nanette Sene et sera supervisé par M. Riad Hadou en appui l’administrateur de ContinuumRD (Stéphane Carpentier) et jumelé au professeur Fabiano Armellini de […]

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Évaluation des indices de durabilité de bétons armés innovants

Les indices de durabilité représentant les 3 modes de transport de l’eau et des agents agressifs dans le béton (perméabilité, absorption et diffusion) et permettant une évaluation de la durabilité du matériau ont été historiquement mesurés sur des bétons sains. Néanmoins, ces mesures ne reflétaient pas la réalité de structures fissurées et soumises à des […]

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Prédiction des variations de tension artérielle chez le patient chirurgical

Ce projet a comme objectif d’améliorer les outils de monitoring dont dispose le médecin lorsqu’il administre une anesthésie générale à un patient. Nous analyserons l’ensemble des informations disponibles pour prédire l’évolution de la tension artérielle dans le temps. Nous savons que de brèves périodes d’hypotension est délétère pour le patient et augmente son risque de […]

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Uncertainty for prediction quality assessment in clinical settings

Deep learning has the potential to increase efficiency of many routine tasks in medical image analysis. For instance, segmentation, the detection of the boundaries of specific target structures like organs or tumors, is a tedious and time-consuming chore for clinicians. Robust deep learning models could assist medical personnel for this type of task. However, automatic […]

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Battery lifetime optimization for AI @ Edge devices

Optimizing energy consumption of Artificial Intelligence of Things (AIoT) devices is mandatory and challenging. Energy Harvesting (EH) from RF, solar, thermal, wind, and kinetic energy sources can be a good substitute for traditional batteries. EH is expected to have abundant applications in future AIoT and self-powered micro-systems such as wireless sensor networks and wearable devices. […]

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Life-long learning in game development processes

In the game industry, software projects extend over several years: for instance, a typical AAA game is developed for 3 to 5 years. To make the development process easier for the developers, tools are put at their disposal to help with, for instance, the artistic creation process or code integration. Those tools are based on […]

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Simulation des flux de patients au sein des urgences du CHUM

Dans ce projet, nous nous proposons de développer un modèle de simulation qui vise à analyser le flux des patients aux urgences, particulièrement le temps d’attente. Cet outil permettra aux responsables de la coordination du CHUM d’être proactifs dans la gestion des urgences. Il leur servira entre autres à comprendre le comportement du système, identifier […]

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Weakly Supervised Behavioral Modeling for Controllable AI Agents in Video Games

The project aims at developing a new type of Reinforcement Learning algorithm that would allow to retain more control over the artificial agent once its training is completed. This framework would combine modern unsupervised modeling techniques to capture the variability of a set of demonstrations and user-defined programmatic functions that can characterise particularly important factors […]

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An FPGA-based platform for the control of a CMOS quantum chip

Quantum Computing has the potential to tackle problems, unsolvable with the most powerful current high-performance machines. It is expected that quantum technology will enable life-changing discovery in the pharmaceutical industry with new drugs, finance for risk minimization, discovering new materials, clean energy, and more. Today, many different architectural solutions exist for quantum computing – photonic, […]

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Water Monitoring using Flocks of Flying Robots

This project aims at developing an automated system for water sampling along the coast of Nova Scotia using a swarm of flying robots. Currently, water is sampled by hand by teams of 2-5 people each on a number of boats, that must regularly travel to different sites, collect samples, and bring them to land for […]

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