Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

30 508 projets complétés

2882
AB
5105
C.-B.
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projets par catégorie

Brain-Inspired Artificial Intelligence for Sound-Aware Robotics

The lack of robust sound awareness in robotics and autonomous machines is a crucial limiting factor in their usefulness and adoption. Taking a biologically inspired approach offers novel computational mechanisms to solve a variety of challenges in this field. The primary objective of this proposal is to finalize and evaluate a Bayesian auditory artificial intelligence (AI) for robotics and collect data for a subsequent publication. This expands on work done in a successful Canada-Italy Innovation award in 2017. A second but equally important objective is to lay the foundations of a next generation auditory AI that will leverage new techniques in deep-learning neural networks. Preliminary theoretical and pilot work is already underway on these neural networks at the U of L, and the proposed visit will enable initial planning about how to implement these networks in the computational architecture of the cognitive robotics platform iCub.

Voir la description complète du projet
Superviseur du corps professoral :

Matthew Tata

Étudiant :

Partenaire :

Istituto Italiano di Tecnologia

Discipline :

Computer science

Secteur :

Education

Université :

University of Lethbridge

Programme :

Globalink Research Award

Self-Assembly of Amphiphilic Metal-Organic Polyhedra for Membrane applications

Metal-organic polyhedra (MOPs) are discrete molecular capsules formed by coordination of metal ion and organic linkers. They possess a nanoscale cavity which can have potential applications in gas storage, separations, drug delivery or sensing. To enhance their usage for practical purposes, these materials need to be translated into membranes. MOP-polymer composites where MOPs are blended with easily processable and mechanically strong polymers serve as a solution. However, there are shortcomings of this process such as integration and integrity of MOPs in the membrane, which can affect selectivity of gas separations. In this project MOPs with both polar and non-polar linkers would be synthesized which show amphiphile-like self-assembly and would be used for making composites. The amphiphilic MOP aggregates would have better integration with the amphiphilic polymers which are commonly used for preparing the membranes. These MOP aggregates, being bigger in size, shall not be easily entombed by the polymer and should result in membranes with high MOP loading and selectivity.

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Superviseur du corps professoral :

George Shimizu

Étudiant :

Partenaire :

Beijing University of Technology

Discipline :

Life Sciences

Secteur :

Environmental Science and Technology; Energy and Utilities; Nanotechnology

Université :

University of Calgary

Programme :

Globalink Research Award

Iterative learning control to cancel beam loading effect in particle accelerators

Iterative learning control (ILC) is an approach to improve the performance of a system that carries out the same operation repeatedly. It stores error and control output throughout every iteration, and incorporates the stored information into generating new control output. In a cavity resonator, a standing wave electromagnetic field is formed to accelerate charged particles passing through the cavity. In the process of the acceleration, energy is transferred from the accelerating field to the beam. As a result, the cavity voltage drops. This effect is referred to as beam loading. A feedback controller is responsible to maintain constant amplitude and phase for the cavity field oscillation. However, for certain applications, a feedback controller is not fast enough. In this project, we aim to use ILC to reduce beam loading effect in cavity resonators. Since beam loading is a repeating disturbance, the error is repetitive as well, and the controller can use a non-causal learning function to pre-emptively counteract beam loading effect.

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Superviseur du corps professoral :

Guy Dumont

Étudiant :

Partenaire :

Lund University

Discipline :

Engineering

Secteur :

Education

Université :

The University of British Columbia

Programme :

Globalink Research Award

Machine learning applied to drilling in open pit mines

The project involves identifying changes in mineralization during the drilling of the blast holes. During drilling, an experienced driller is able, to a certain extent, to detect signals that indicate that a zone change is occurring: vibration in the cabin, rotation rate, etc. The aim of this research project is to use data collected by the various sensors installed on the drill (specific energy, rotation rate, penetration rate, horizontal and vertical vibrations) to determine patterns among these data which would make it possible to identify a zone change and eventuallly automate this process. Machine Learning techniques are proposed to identify these patterns. The detection of these geological changes is particularly important in coal mines to stop drilling just before reaching the coal bed. This is to prevent blasting from fracturing the coal bed.

Voir la description complète du projet
Superviseur du corps professoral :

Michel Gamache;Richard Labib

Étudiant :

Partenaire :

Peck Tech

Discipline :

Mathematics

Secteur :

Mining; Other

Université :

École Polytechnique de Montréal

Programme :

Accelerate

Détection de la fraude à l’assurance

La fraude à l’assurance est devenue un problème important au Canada et dans de nombreux autres pays. Le partenaire n’est pas satisfait des modèles qu’il utilise pour la détection de la fraude dans ses dossiers de réclamations provenant de divers marchés, dont l’assurance automobile. Il a donc décidé d’entreprendre une collaboration entreprise-université afin d’améliorer sa détection de la fraude. Le financement aidera un étudiant de doctorat à réaliser sa recherche en entreprise. Cette collaboration permettra à l’assureur d’améliorer la performance de ses modèles et au stagiaire d’avoir accès à des professionnels et des données de haute qualité pour développer sa recherche doctorale. Le but du stage est de vérifier comment l’ajout de modèles d’apprentissage machine et d’intelligence artificielle aux modèles traditionnels de gestion de la fraude à l’assurance permettra d’améliorer la performance de la détection de la fraude chez l’assureur.

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Superviseur du corps professoral :

Georges Dionne;François Bellavance

Étudiant :

Partenaire :

Intact

Discipline :

Business

Secteur :

Finance and Insurance; Other

Université :

HEC Montréal

Programme :

Accelerate

Ice Hazard Drift Model Study III

Massive drifting icebergs frequently threaten offshore operations on the Grand Banks because of their massive size, and great mechanical strength. These ice hazards move erratically which complicates efforts to modify their trajectory or undertake evasive action. This MITACS project aims to improve security of offshore workers and help protect wildlife and the environment by allowing more accurate prediction of short-term iceberg drift. The funding partner, ASL Environmental Sciences, will benefit through improved capability to provide world-class services to their clients.

Voir la description complète du projet
Superviseur du corps professoral :

Derek Mueller

Étudiant :

Partenaire :

ASL Environmental Sciences Inc

Discipline :

Earth science

Secteur :

Professional, scientific and technical services

Université :

Carleton University

Programme :

Accelerate

P4 SDN testbed integration

The research will consist of exploring a new language as well as a new paradigm shift in the orchestration and analytics involved in operating a Fiber optical infrastructure equipped with IP routers and Computers. These computers will be equipped with programmable devices that will allow further instructions and detailing about the next generation of internet’s emerging services. These services require more automation and more analytics to become more adaptive if not autonomous. We will research how autonomous can these networks get by involving this new programmable language called P4. We will start by exploring point to point services and then we will move on to point to multi point services and explore the programmable autonomy of these new emerging services as well as collect meaningful statistics to properly define their beginning, their stability as well as their end so that the network can become a programmable reusable service, or device

Voir la description complète du projet
Superviseur du corps professoral :

Changcheng Huang

Étudiant :

Partenaire :

Ciena Corporation (Ottawa, ON)

Discipline :

Engineering

Secteur :

Information and Communications Technology

Université :

Carleton University

Programme :

Accelerate

Analysis of factors impacting views and revenue of digital assets on YouTube

This research project will focus on factors increasing viewership and revenue on Boat Rocker Media’s digital assets on YouTube. Combination of datasets from various sources such as YouTube revenue reporting, YouTube data and analytics Application Program Interfaces (API’s), and social media will be used in an explanatory analysis and statistical modeling to get new insights. The project will involve integration of data from various sources as well as data cleansing. The result of analysis will help Boat Rocker Media increase the number of views on its digital assets, retain the current viewers, understand factors that attract viewers, and create new policies to engage the audience of its digital assets on YouTube.

Voir la description complète du projet
Superviseur du corps professoral :

Nathan Taback

Étudiant :

Partenaire :

Boat Rocker Media

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

University of Toronto

Programme :

Accelerate

Characterizing the role of probiotics in physiologically relevant ex vivo and in vivo models of infectious colitis

In the intestines of people living with inflammatory bowel diseases (IBDs), the balance of beneficial bacteria is shifted. Instead, the intestine is overloaded with potentially harmful bacteria – a phenomenon known as dysbiosis. This shift in bacterial populations is believed to be among the key contributors to the onset of inflammation observed in IBD patients.
Bioactive bacteria that help to re-establish equilibrium in the intestine are known as probiotics. They work by promoting the growth of beneficial bacteria while simultaneously warding off harmful bacteria. Importantly, probiotics may alleviate intestinal injury and inflammation and thereby reduce some symptoms of IBD. However, less is known about the precise ways in which probiotics act on cells lining the intestine, and how this might contribute to improved IBD outcomes. Answering these questions is the underlying goal of the proposed research. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Philip Sherman

Étudiant :

Partenaire :

Lallemand Bio Ingredients

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

University of Toronto

Programme :

Accelerate

ERGO4ALL: Intégration de l’aspect temporel dans l’évaluation du risque de TMS

Les logiciels actuels de DHM (Digital Human Modeling ou d’ergonomie virtuelle) destinés à la conception de situations de travail et de produits demeurent difficiles à utiliser ce qui en limite grandement l’utilisation par les concepteurs et les ergonomes. Pourtant, l’utilisation plus répandue de DHM permettrait d’en arriver à des environnements de travail plus sécuritaires et minimisant les risques pour la santé des travailleurs. Il apparaît donc utile de concevoir les logiciels de DHM en tenant compte des caractéristiques et exigences (i.e., conception centrée sur l’opérateur humain) de leurs utilisateurs, lesquels sont en grande majorité non ergonomes. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Daniel Imbeau

Étudiant :

Partenaire :

Dassault Systèmes

Discipline :

Engineering

Secteur :

Aerospace; Automotive; Technology

Université :

École Polytechnique de Montréal

Programme :

Accelerate

Évaluation de la capacité de dépuration chez le homard américain (Homarus americanus) après une contamination aux hydrocarbures pétroliers en relation avec un indice d’état de santé du homard

Au Québec, 5 000 tonnes de homard sont pêchées annuellement en Gaspésie et aux Îles-de-la-Madeleine. Les risques pour les pêches maritimes liés au transport de matières dangereuses, tels que les hydrocarbures, augmentent. Notre projet vise à optimiser le suivi en usine de la qualité du homard vivant, par trois biotests qui renseigneront sur l’état de santé des homards. Ils seront appliqués à évaluer la capacité de décontamination des homards après une contamination en laboratoire aux hydrocarbures pétroliers. Les réponses fournies permettront de connaître la période minimale obligatoire de fermeture de la zone de pêche, advenant une contamination du stock par un déversement d’hydrocarbures pétroliers. Le développement d’un tel outil d’évaluation sur le stock de homard fournira des arguments pour l’évaluation des mesures compensatoires (indemnisation des pêcheurs). De plus, la connaissance acquise par le projet, appuiera la prise de décision lors des interventions d’urgence en cas de déversement d’hydrocarbures pétroliers.

Voir la description complète du projet
Superviseur du corps professoral :

Richard Saint Louis

Étudiant :

Partenaire :

Merinov (Rimouski, QC)

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

Université du Québec à Rimouski

Programme :

Accelerate

Development of a clinical protocol for the validation of a detection test for ??amyloid aggregates in retinal scan images.

Alzheimer’s disease (AD) is a neurodegenerative disorder that is difficult to detect early before apparent manifestations of cognitive decline. Current detection methods rely on expensive and hardly accessible imaging techniques (PET scans). Optina Diagnostics developed a new camera as well as innovative image processing methods to propose a non-invasive test to identify the presence of AD biomarkers in evaluated individuals. The objective of this collaborative effort is to develop a clinical protocol to test this new technology. We will define best research design for validation and establish the clinical value of the new test for the detection of early signs of neurodegenerative disorder. This will provide an opportunity of training for a student in a clinical environment and with a partner from the industry in relation to a cutting-edge technology. For Optina Diagnostics, it is an opportunity to mobilize expertise in clinical research, epidemiology and evaluation of new modes of intervention, in order to prepare a sound application for FDA approval of their technology.

Voir la description complète du projet
Superviseur du corps professoral :

Marie Beauséjour;Philippe Broët;Helen Trottier

Étudiant :

Partenaire :

Optina Diagnostics

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Accelerate

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