Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

29670 Completed Projects

2811
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4990
BC
801
MB
663
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825
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8841
ON
9197
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95
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568
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1088
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Projects by Category

Investigating the use of force sensing insoles for understanding running efficiency and power

This work will examine a novel “smart” insole that allows for the quantification of specialized running metrics and will compare the outputs with the gold-standard measure of metabolic work. The insoles work by collecting pressure data from many sensors embedded in the insole, and sending this to an phone app. We are comparing the insoles and their ability to model running power and economy both in the lab and in field conditions where factors that affect the work of running will change. This includes factors such as the running surface, grade, and external resistance. This work will help the company test and improve their predictive algorithms, leading to product improvements and potentially new markets in the fitness and running world.

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Faculty Supervisor:

Jamie Burr

Student:

Partner:

Kinetyx

Discipline:

Life Sciences

Sector:

Arts, entertainment and recreation; Manufacturing

University:

University of Guelph

Program:

Accelerate

Process parameter optimization for metal additive manufacturing: AI modeling

Additive manufacturing (AM) is a product construction process by adding successive layers of materials according to computer-aided design models. Recently, metal AM products have been increasingly applied in aerospace, automotive, and biomedical industries. However, the complex interactions (i.e. thermal field) between metallic components and manufacturing processes make the product qualities inconsistent and unreliable, resulting in expensive product cost. This project aims to construct a model to simulate the thermal field of various metal AM products offline. This model will provide an insight of the whole manufacturing process, and enable constructing relationships between product qualities, key process parameters, and thermal information. With these models, the metal AM process could be monitored, controlled, and optimized effectively, therefore increasing the product quality and reducing the product cost.

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Faculty Supervisor:

Gary Wang

Student:

Partner:

University of Tampere

Discipline:

Engineering

Sector:

Advanced Manufacturing; Artificial Intelligence; Other

University:

Simon Fraser University

Program:

Globalink Research Award

Multibeam echosounder noise classification using machine learning

Icebergs are large masses of ice drifting in ocean under influence of winds in currents. Icebergs are important indicators of climate, they provide nutrients to the ocean ecosystem, but they are also a threat to shipping and offshore industry. Collecting iceberg shapes helps to model climate, predict iceberg drift, and protect offshore facilities and flowlines laying on the ocean floor. Although, icebergs are fascinating to observe, their larger underwater parts are hidden. It is possible to retrieve the iceberg keel geometry by using an echo-sounder, however, data comes noisy. It takes significant amount of time to filter noise manually. This project will try to apply machine learning algorithms to filter data effectively and detect unnecessary noise in the data. Once the data is clean, iceberg shapes will be determined with higher accuracy, providing researchers and engineers with valuable inputs.

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Faculty Supervisor:

Rocky Taylor;Renat Yulmetov

Student:

Partner:

C-CORE

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Developing implantable scaffold for bone regeneration with healing enhancement by local drug delivery and sustained drug release

Over 3 million Canadian suffer from bone disease resulted from trauma, tumor removal and cancer and the number increasing with aging population every year. We plan to use hydrogels to create bioactive scaffold using 3D bioprinting extrusion method with potential for local drug loading and slow drug release for bone regeneration. We develop bioinks with proper mechanical strength and fidelity to keep the shape of the scaffold. I this work with incorporate bone growth factors to accelerate repair of bone defects. Encapsulation growth factors in nanoparticles gives us the opportunity for sustained and prolongation of drug release in a control manner which results in enhancement of bone regeneration and healing.

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Faculty Supervisor:

Mohammad Kohandel

Student:

Partner:

Ability Concepts Inc

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

University of Waterloo

Program:

Accelerate

Développement et qualification d’une approche de type point-of-care (POC) pour le dosage de la ferritine plasmatique par résonance des plasmons de surface (SPR)

Chez un donneur de sang fréquent, il arrive d’observer une chute des réserves de fer1,2. La mesure du taux d’hémoglobine dans le sang des donneurs permet aux banques de sang d’éviter de prélever un individu pour qui les réserves de fer seraient considérées comme étant faibles. La ferritine est un marqueur précoce de la carence en fer et sa mesure permettrait de prévenir un abaissement important des réserves en fer qui pourraient être évité par un changement apporté au régime alimentaire ou par la prise de suppléments adaptés3,4. Par conséquent, le développement d’une méthode simple et rapide permettant une quantification de la ferritine directement sur les lieux de collecte à partir d’un échantillon de sang devient pertinente pour éviter les problèmes associés aux carences en fer chez les donneurs fréquents.
Le but principal de ce projet de recherche vise donc le développement d’une méthode Point of Care6 (POC) par résonance des plasmons de surface (SPR) pour le dosage de la ferritine dans le sang.
La détection par SPR exploite les propriétés plasmoniques de nanomatériaux pour réaliser une mesure de la variation de l’indice de réfraction en réponse à un changement observé en surface d’un prisme recouvert d’une fine couche d’or.

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Faculty Supervisor:

Jean-Francois Masson

Student:

Partner:

Héma-Québec (Montreal)

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

Improving the clinical oculomotor assessment for patients with multiple sclerosis

Clinicians’ ability to detect abnormal eye-movements has powerful implications for the diagnosis, monitoring of disease progression and evaluation of therapeutic outcomes in patients with multiple sclerosis. Despite the advantages of the oculomotor assessment, standard clinical practices are limited and do not capture the dynamic aspects of eye-movement. Sophisticated methods have been developed in the laboratory setting for this purpose, but these are often expensive and hard to adapt to the naturalistic clinical setting. Taking advantage of the digital cameras readily available in mobile devices, lnnodem Neurosciences has developed a cost effective and user–friendly solution to quantify eye-movement perturbations. If successful, this would reduce the need for expensive laboratory exams for the diagnosis and monitoring of disease progression in patients with multiple sclerosis. Using modern artificial intelligence tools, we aim to improve the algorithms used for the extraction of eye-movement features. Furthermore, we seek to explore the diverse and heterogeneous symptomatic manifestations of multiple sclerosis from a neuro-ophthalmological point of view.

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Faculty Supervisor:

Bratislav Misic

Student:

Partner:

Innodem Neurosciences

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Caractérisation non-destructive d’un matériau composite bio-sourcé

Il existe peu de données publiées sur les propriétés des matériaux composites, notamment à cause de la complexité des essais à réaliser pour les caractériser, ce qui rend difficile la modélisation de leur comportement mécanique. Dans ce contexte, une méthode d’essai non destructive pourrait s’avérer particulièrement intéressante afin de caractériser les matériaux composites et d’en apprendre plus sur leur comportement complexe. Le projet proposé s’intéressera spécifiquement à utiliser l’essai de résonance par impact sur un matériau composite. Une modélisation numérique sera réalisée à partir des résultats des essais réalisés en laboratoire et dans l’objectif de simuler d’autres types de chargements. Enfin, des outils informatiques seront développés pour améliorer l’acquisition et le traitement des signaux expérimentaux ainsi que l’analyse de ceux-ci.

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Faculty Supervisor:

Jean-Claude Carret

Student:

Partner:

Universidade Federal do Ceará

Discipline:

Engineering

Sector:

Education

University:

École de technologie supérieure

Program:

Globalink Research Award

Automated Neurotoxicity Validation using MRI Protocols on a Cloud-Based Architecture

The proposed research project is aimed at developing an automated MR-processing pipeline for pre-clinical neuroimaging. This pipeline will address some of the existing issues associated with current methodologies, and has the potential to re-define the world of early drug development, particularly relating to the assessment of neurotoxicity.

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Faculty Supervisor:

Chris Joslin

Student:

Partner:

Tessellis Ltd.

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Carleton University

Program:

Accelerate

Conception d’une trousse d’analyse d’opportunités pour l’implantation d’une solution enrichissant les systèmes de GMAO existants

Les actifs, qu’ils soient des machines industrielles, les équipements médicaux, des bâtiments, des équipements informatiques, des infrastructures de transport, etc., ont une durée de vie. Malgré la variabilité de leur performance au cours de leur cycle de vie, les gestionnaires souhaitent que ces actifs conservent leur valeur marchande au maximum tout en minimisant les coûts dus à leur entretien. Les logiciels de GMAO (Gestion de la Maintenance Assistée par Ordinateur) sont des exemples d’applications spécialisées conçues pour améliorer la gestion de la maintenance des actifs. Mais, une fois implantés, ces logiciels assez coûteux deviennent rigides. Alors que leur remplacement est peu souhaitable, de nouvelles opportunités technologiques (matériel et logiciel) de nos jours aident à concevoir des interfaces simples d’utilisation introduisant la maintenance prédictive plus efficace et plus économique que les autres formes de maintenance et qui peut améliorer significativement les logiciels de GMAO et ainsi la gestion des actifs. Le présent projet vise, entre autres, à démontrer l’amélioration significative apportée à la fonction maintenance et à la gestion des actifs avec les nombreux avantages en termes de coût-efficacité et coûtbénéfice, lorsqu’une politique de maintenance prédictive pour les actifs critiques est adoptée.

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Faculty Supervisor:

Michel Rioux

Student:

Partner:

Matricis Informatique Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

La justice épistémique en contexte de coconstruction : enjeux, défis et implications pratiques

Ce stage porte sur le concept de justice épistémique et ses applications concrètes dans le travail d’un organisme communautaire. Cet organisme développe des projets collectifs à partir de la parole et de l’action des citoyenNEs dans le but de lutter contre la pauvreté et l’exclusion sociale. Le concept de justice épistémique, de la juste valorisation et l’équilibre entre les savoirs des différentes personnes impliquées dans l’organisme, est au cœur de sa posture de travail. Néanmoins, l’organisme décèle certains enjeux opérationnels dans la mise en pratique de la justice épistémique. La stagiaire aura pour rôle de formuler une définition de la justice épistémique et de cocréer des recommandations afin de répondre aux enjeux terrains de l’organisme.

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Faculty Supervisor:

Juan-Luis Klein

Student:

Partner:

Parole d’excluEs

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

Université du Québec à Montréal

Program:

Accelerate

GWUT for Gas Diversion Detection on PE Pipes with a Steel Riser

Detection of natural gas diversion in residential pipelines is important for public safety. Detection of such diversion in a nonintrusive manner is important for customer satisfaction and the companies’ reputation. This project aims to develop non-intrusive guided-wave ultrasonic testing methods combined with machine learning to detect and locate diversions in residential gas pipes. These pipes are commonly polyethylene pipes connected to a steel riser, and are deployed below ground. Thus, the envisioned testing solution should be able to handle the effects introduced by the pipe’s material and the surrounding medium.

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Faculty Supervisor:

Anas Chaaban

Student:

Partner:

FortisBC Energy Inc

Discipline:

Engineering

Sector:

Utilities

University:

The University of British Columbia - Okanagan

Program:

Accelerate

Assessing Executive Function Through Eye Movements in Concussed Individuals

When a concussion occurs individuals can also experience several different subtle changes to eye movements and performance that is difficult to recognize. To understand how these eye-movement problems affect the recovery process the goal of the study is to investigate if these eye-movement problems are a result of executive functioning issues in the frontal lobe due to anatomical visual projections. Assessing how the eyes function in response to injury is imperative to further understanding symptoms of concussions and informing rehabilitation plans. By working in collaboration with HeadsupCAN, this type of research will reach the audience interested in learning more about concussions, work to inform, and advance the field.

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Faculty Supervisor:

Maureen Connolly;Liana Brown

Student:

Partner:

HeadsupCAN

Discipline:

Physics

Sector:

Health and Related Sciences & Technology

University:

Trent University

Program:

Accelerate