Innovative Projects Realized

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

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

Improving feature extraction from medical documents with structured information

We are building a machine learning algorithm to be able to better understand the unstructured clinical notes. This will help the medical coder and auditor to quickly navigate the clinical notes and locate the text that corresponding to the codes. Reduce the chance of missing labels and mis-labeling in the coding review process.

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Faculty Supervisor:

Michael Brudno

Student:

Partner:

Semantic Health Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Investigating the potential to enhance post-stroke physical rehabilitation via functional near-infrared spectroscopy (fNIRS)

This project involves work towards the development of a medical device meant to help people recover their movement abilities after a stroke. The device measures the part of the brain that controls movement, in order to provide feedback during rehabilitation exercises, as well as to help clinicians better understand the rehabilitation needs of patients. Specifically, in this project several researchers will collect and analyze data (1) to help better understand how such a device can be built so that it is usable by stroke survivors; (2) to understand the use of providing brain activity feedback during rehabilitation, as well as (3) help better understand how the data being collected from this device during the course of stroke recovery might be used to improve rehabilitation.

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Faculty Supervisor:

Shaun Boe

Student:

Partner:

Axem Neurotechnology

Discipline:

Life Sciences

Sector:

Manufacturing

University:

Dalhousie University

Program:

Accelerate

Contrôle intelligent pour conduite autonome dans conditions routières nordiques

Ce projet vise à développer une commande intelligente robuste pour la conduite autonome des véhicules dans des conditions nordiques. En général, les véhicules autonomes naviguent dans leur environnement en planifiant d’abord, puis en suivant une trajectoire sûre. Ils doivent en fin de compte effectuer ces tâches aussi bien ou mieux que les conducteurs humains dans un large éventail de conditions et dans des situations critiques. Pour cela, ce projet vise à améliorer la conduite du véhicule dans des conditions variées de route allant d’une chaussée sèche à une chaussée de neige. Un contrôle intelligent sera développé pour assurer la robustesse de la conduite dans les différentes conditions routières. Une structure basée sur les réseaux de neurones sera développée pour surmonter certaines limites du modèle physique du véhicule. Les approches de commande
développées seront implémentées sur un véhicule Chevrolet Volt et des tests sur la route seront effectués pour évaluer la performance de l’approche proposée.

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Faculty Supervisor:

Maarouf Saad

Student:

Partner:

Institut du véhicule innovant

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

Development of Novel Gripper and Lifting Mechanisms for Automated Test Water Systems

This project involves developing novel gripper mechanisms for Mantech that has faced issues with their robots. The first challenge is the need for having grippers (not pneumatic) that are robust and light. To solve this, we will develop (model, design, fabricate) a novel electromagnetic gripper that is equipped with tactile sensors to ensure perfect grasping. The electromagnets are solenoid-driven, lightweight, have good speeds, and can preserve the throughput of the bottle inspection. Another challenge is the required modifications for bottle lifting mechanisms for which we develop mechanical model of the mechanism and add a feedback sensor, touch or tactile, to guarantee not missing any caps. Extensive experiments for both gripper and mechanism for different robot speeds will be performed to ensure reliability and repeatability. The novel proposed solutions will help Mantech remain competitive in the market. This project also trains a graduate student to acquire training in advanced mechatronics, control.

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Faculty Supervisor:

Mohammad Biglarbegian

Student:

Partner:

Mantech

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Guelph

Program:

Accelerate

Improving Conductivity and Waterproof Ability of Solar Tile Connectors

The project is to enhance the stability of the detachable solar tile panel connector in terms of conductivity and waterproof ability. The student will investigate other applications such as solar tiles for roof mounted applications and the current designs and prototypes developed by Square Solar. They will also develop a set of design requirements that the connectors must meet taking into account requirements from applicable Canadian standards. The research will also develop designs to meet the optimum size, thickness, and materials for the solar tile connectors for practical production.

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Faculty Supervisor:

Stephen O'Leary

Student:

Partner:

Square Solar Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

British Columbia Institute of Technology; The University of British Columbia - Okanagan

Program:

Accelerate

Parallel Computing Solutions for Modelling Large Volume Geoelectrical Data Utilizing Unstructured Meshes

This project will develop computer modelling methods for geoelectrical data that are collected in geophysical surveys. Such data can be used to infer information about electrical properties in the Earth’s subsurface, and subsequently provide information about mineralization, groundwater pollution pathways, water intrusion through flood barriers, and various other important processes. It is ever more common that large volume geoelectrical datasets are collected. Although these have the potential to provide improved information about the subsurface, they pose particular challenges for computer modelling. The general objective of this project is to develop new computationally feasible computer modelling approaches for working with large volume geoelectrical data. To reach that objective, we will investigate use of unstructured meshes, parallel programming and data sampling/compression methods, among others. This project will develop powerful and sophisticated geoelectrical modelling software that will have the potential to benefit Canada though its use in resource exploration and many other applications.

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Faculty Supervisor:

Peter Lelièvre;Colin Farquharson

Student:

Partner:

DIAS Geophysical

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

Mount Allison University

Program:

Accelerate

Living Lab Lanaudière étude de cas et analyse des retombées

Le Living Lab Lanaudière (LLL) a vu le jour après que la Corporation de développement de la MRC de Joliette (CDÉJ) ait lancé en 2017 une vaste réflexion afin de mettre sur pied un projet novateur pour mieux outiller les entreprises et les milieux lanaudois à faire face aux enjeux d’accès aux percées technologiques, d’automatisation, mais aussi d’adaptation des travailleurs et des consommateurs dans un environnement en constant changement. Après près de deux ans de réflexion, d’élaboration, de consultations, et de projets pilotes, le concept du LLL a été sélectionné et implanté dans la région.

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Faculty Supervisor:

Fabiano Armellini;Catherine Beaudry;Laurence Solar-Pelletier

Student:

Partner:

Corporation de développement économique de la MRC de Joliette

Discipline:

Engineering

Sector:

Public administration

University:

Polytechnique Montréal

Program:

Accelerate

Additive Manufacturing of Functionally Graded Materials and Shape Memory Alloys with Biomedical Applications

Functionally graded materials (FGM) offer a better alternative than the conventional coating techniques since it eliminates the sudden change in composition between different materials. This project proposes to print FGM biomedical implants using a combination of titanium (Ti) powder and hydroxyapatite (HA) powder. Titanium will offer the required mechanical strength for load-bearing implants, while HA will enhance the biological properties of the implant surface to enhance bone cell attachment. The project will follow a comprehensive approach to cover the gaps in the literature. Firstly, powder mixing of Ti and HA process will be optimized to choose the best mixing parameters and weight percentage of each material. Then more focus will be directed to the laser powder bed fusion (LPBF) process to study the process-structure property relationship, thus choosing the preferred process parameter window. Afterward, the Ti-HA FGM concept will be applied to lattice structures and print novel radial FGM parts that mimic bone geometry and composition. Finally, the static and fatigue properties of the printed FGM parts will be characterized to check if they will withstand the requirements for bone implants.

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Faculty Supervisor:

Seshasai Srinivasan

Student:

Partner:

Additive Manufacturing International

Discipline:

Engineering

Sector:

Manufacturing

University:

McMaster University

Program:

Accelerate

Impact de l’alimentation de précision et de la stratégie « bump feeding » en gestation sur les performances, la productivité et la longévité des truies et sur les performances de la progéniture

L’alimentation de precision, soit le melange en proportions variables de deux aliments, l’un riche et l’autre pauvre en nutriments, permettrait de mieux alimenter les truies selon leur caracteristiques individuelles en comparaison avec l’alimentation conventionnelle n’impliquant qu’un seul aliment. L’objectif de ce projet est de valider !’impact du “bump feeding” et l’alimentation de precision en fonction du stade de gestation et de la parite, sur les performances et la longevite de truies suivies des leur premiere parite ainsi que sur les performances de leur progeniture. Au total, 4 bandes de 120 cochettes seront suivies pendant 3 cycles de gestation et lactation.

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Faculty Supervisor:

Frédéric Guay

Student:

Partner:

Centre de développement du porc du Québec

Discipline:

Life Sciences

Sector:

Agriculture; Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Intelligent Autonomous Mobile Robots with Safe Navigation in Dynamic Environment

With the global pandemic effect, the market is experiencing a significant transformation, with robotics to adopt the roles of delivery vehicles and personal assistants. Atlantic Business Express is looking at bring the service robots to Canada, starting in Nova Scotia through working with Dalhousie University. The project is to develop intelligent path planner for mobile robots with safe navigation through obstacles in indoor dynamic environment. The interns will develop an intelligent motion planner as well as efficient collision and obstacle avoidance modules. The company will benefit from having well-tested autonomous robots which can safely and smoothly navigate without interventions. The results will help the company to improve their competitiveness and have larger share of the market in service robots. The Canadian community will benefit from the state-of-the-art research project. Autonomous service robots offer improved capability in freeing up people from unsafe tasks and allowing people to handle more complex workload.

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Faculty Supervisor:

Ya-Jun Pan

Student:

Partner:

Atlantic Business Express

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Development of Load Case Model for the Design of Butt & Top Grapples

The sponsor company, Tigercat specializes in the design and manufacturing of premium quality forestry equipment and specialized off-road industrial equipment. This four months internship project will provide the company a set of load cases validated on a new design, optimized detail 3D and 2D models, selected material lists, and FEA simulation results of a tracked material handling machine attachment called a “Butt and Top Grapple”. These deliverables will help the company reduce costs, increase product performance, and be competitive in the forestry equipment industry. This project will develop a load case model that can be used to evaluate stresses on key components on any grapple design to determine possible design changes to improve the grapple’s durability and performance by reducing its weight and incorporating a stop mechanism into the grapple design. In order to achieve these goals, computer-aided design and finite element analysis methodologies and software will be used.

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Faculty Supervisor:

Robert Fleisig

Student:

Partner:

Tigercat Industries

Discipline:

Engineering

Sector:

Manufacturing

University:

McMaster University

Program:

Accelerate

Self-supervised Noise Modeling for Smartphone Cameras

Humans possess the ability to see objects as having the same color even when viewed under different illuminations. Cameras inherently lack this capability. A process called auto white balance (AWB) has to be applied by the camera to mimic this behavior of the human visual system. AWB is one of the first steps in a series of operations performed on-board the camera as the raw image recorded by the sensor is processed. It plays a crucial role in ensuring that the colors in the final image that is output to the user are correctly represented. In recent years, AI algorithms for AWB have demonstrated superior performance over conventional methods. However, existing AI solutions are too computationally expensive for use on smartphones and mobile cameras. The goal of this project is to devise an AI algorithm that is light-weight and capable of running in real time on-device. This project will help Samsung Electronics Canada develop an improved and more practical auto white balance AI algorithm applicable to modern smartphone camera images.

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Faculty Supervisor:

Marcus Brubaker

Student:

Partner:

Samsung Electronics Canada

Discipline:

Computer science

Sector:

Manufacturing

University:

York University

Program:

Accelerate

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