Projets novateurs réalisés

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

31 620 projets complétés

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856
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696
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899
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9419
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Projets par catégorie

In-Kind Student Edition: Skills and Services Impact Study

To date, there is a gap in the research determining how in-kind giving can be used to motivate student engagement. In tandem with Algonquin College, this project seeks to understand how in-kind giving can help students get involved in achieving the United Nations Sustainable Development Goals. Through a mixed-methods approach involving interviews, focus groups, and surveys, the research will create a student handbook. This handbook will guide student engagement toward in-kind giving and illustrate how this engagement will deliver on the UN-SDGs. With the data gathered through the creation of the handbook, a report will be generated with practical considerations for campuses and students on how to integrate the SDGs.

Voir la description complète du projet
Superviseur du corps professoral :

Paloma Raggo

Étudiant :

Partenaire :

Project K(IN)D

Discipline :

Sociology

Secteur :

Other services (except public administration)

Université :

Carleton University

Programme :

Accelerate

Next Generation candidate screening and assessment platform featuring psychological profiling though gamification

This project is the first step to providing Thinking North’s Purple Squirrel recruitment platform to go beyond traditional matching with a novel, data-backed holistic candidate matching process. To provide a robust system, Thinking North is collaborating with Seneca’s School of Software Design and Data Science to use advanced artificial intelligence and gamification techniques to combine “psychology” and “gamification,” known as “psychification,” to enhance the screening aspect for a recruitment process. Psychification builds on the data at Thinking North to create a gamified, interactive way to assess how motivated candidates are for open positions within select technology industries. This psychification and screening platform will benefit companies that are challenged by the need for speed and accuracy in recruiting. Specifically, we are addressing the emerging gig economy where staffing for projects and shorter commitments calls for an even more effective process than we have seen before.

Voir la description complète du projet
Superviseur du corps professoral :

Mark Buchner

Étudiant :

Partenaire :

Thinking North

Discipline :

Computer science

Secteur :

Finance and Insurance

Université :

Seneca College of Applied Arts and Technology

Programme :

Accelerate

Development of Lightweight Thermally Conductive Products Reinforced with Graphene Nanoplatelets for Automotive Industry

The focus of this project is replacing some of the current automotive parts by a stronger and lighter thermally-conductive polymer nanocomposite. This project takes advantage of the exceptional mechanical and thermal properties of graphene as a commercially viable and environmentally friendly nanomaterial, through an industrial scale process, i.e. injection molding. Therefore, the outcome of this research would technologically benefit our industrial partner, i.e. Axiom Group Inc., to sustain itself and/or to grow in the competitive market. Bearing in mind the global scope of our industrial partner, as a leading developer and manufacturer in the plastic injection molding industry, the products and technologies developed as a result of this project’s findings are expected to be commercialized and introduced to both Canadian and world markets.

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Superviseur du corps professoral :

Patrick C Lee

Étudiant :

Partenaire :

Axiom Plastics Inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Evaluating Latency in Virtual Production Pipelines with Integrated Prediction Model for Motion Capture Data

Virtual Production (VP) is seeing a dramatic spike in interest and adaptation as the global film industry, particularly Hollywood, has been shutdown due to Covid-19. Virtual production is a broad term referring to a spectrum of computer-aided production and visualization filmmaking methods, and is also being used for broader applications from animation to industrial visualization. Of particular interest is the novel application of virtual production for live theatrical performance where machine learning is driving digital puppeteering from real-time motion capture for innovative and compelling storytelling. Machine learning for real-time motion mapping predictions is a key component of the live performance virtual production pipeline. However, serving predictions from trained machine learning models is emerging as a dominant challenge in production machine learning. These computationally intensive prediction pipelines must run continuously with a tight latency budget and in response to stochastic and often bursty query arrival processes. In this proposal research project, the intern(s) will review the latest applications and research related to latency issues in virtual production pipelines, with a focus on machine learning prediction.

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Superviseur du corps professoral :

Jiannan Wang

Étudiant :

Partenaire :

AMPD;Shocap Entertainment

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

Simon Fraser University

Programme :

Accelerate

Using Bayesian Learning paradigms to enhance the clinical utility of an AI decision support tool for mental illness.

The Machine Learning team at Aifred Health is aiming to improve the performance of their core decision support models and the intern will assist in the development of a system that will intelligently iterate across dozens of unique model configurations to find the best performing one by leveraging previous configurations and their performance outcomes. The intern will also work on building a prototype of a model that takes advantage of longitudinal data to assess patient response trajectories so that a doctor can have a higher resolution view into whether the patient is getting better or rapidly degrading and needs to take action, thereby increasing the chances of remission. This work will ultimately help accelerate us in our mission to bring better mental healthcare to all.

Voir la description complète du projet
Superviseur du corps professoral :

Jean-Jules Brault

Étudiant :

Partenaire :

Aifred Health Inc

Discipline :

Computer science

Secteur :

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

Université :

Polytechnique Montréal

Programme :

Accelerate

Continuous Identity Verification using Blockchain Technology

With physical interactions greatly restricted due to the COVID-19 pandemic, the world is forced to rapidly adapt and embrace digital transformation. There is an urgent need for a digital identity infrastructure to authenticate users who rely on online services. The system must accurately validate physical identities, provide each user the ability to control access to its personal data, and support usage auditing. Furthermore, the infrastructure must operate at a large scale, maintain security and confidentiality while being practical and convenient to use for the average user. To address this important challenge, we propose a multi-disciplinary approach which combines biometrics, artificial intelligence, and blockchain technologies. Our objective is to explore relevant use cases, particularly those related to COVID-19, and develop a working prototype.

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Superviseur du corps professoral :

Chamseddine Talhi;Kaiwen Zhang;Jean-Philippe Roberge;Vincent Levesque

Étudiant :

Partenaire :

IPtoki Inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

École de technologie supérieure

Programme :

Accelerate

Development of a flexible and breathable PLA-based film as an eco-friendly alternative to animal leather

Leather manufacturing is a by-product of the meat and dairy industries, and leather can come from any animal. More than a billion animals are slaughtered every year for their skins. But, the most popular type of skin used is coming from cow, calf and buffalo, and accounts for 64% of leather. Turning skin into leather requires many steps, chemicals and generate a significant amount of waste. It is not surprising that the leather industry is consider as a cruel, inhuman and polluting business. Fortunately, leather can be obtained using different animal-free sources of material (e.g. plastics, apple fibers, pineapple, tree bark and cork). Most of the time those animal-free leathers are referred to as artificial, synthetic, faux or vegan leather. Among plastic-based leather, polyurethane (PU) and Polyvinyl Chloride (PVC) are the most used ones. However, those plastics are still oil-based ones and, overall, the artificial leather still represents one-third of the footprint of whole animal leather industry. This project aims at developing new fully bio-composite derived from renewable resource with comparable flexibility, breathability and feeling to genuine leather.

Voir la description complète du projet
Superviseur du corps professoral :

Saïd Elkoun

Étudiant :

Partenaire :

Gestion Dryad Inc

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Université de Sherbrooke

Programme :

Accelerate

Development of a data processing and machine learning pipeline using non-invasive diffuse reflectance spectroscopy eye imaging for Alzheimer disease screening

Alzheimer’s disease (AD) is a progressive neurodegenerative disease and is currently the most common cause of dementia, affecting approximately 50 million individuals worldwide. RetiSpec has developed a non-invasive, label-free retinal imager that can uniquely detect and quantify AD biomarkers – namely, signatures of A? aggregates. The combination of hyperspectral imaging and machine learning may be a quick, simple, and cost-effective method that can be used to identify AD retinal biomarkers years before the emergence of clinical symptoms. In this project novel tissue spectroscopy methods will be developed to detect the presence of amyloid plaque and soluble oligomers, and to quantify changes in microvasculature. To this end machine learning methods will be applied to data acquired in more than 100 patients to develop predictive models able to automatically screen patients for AD as part of regular eye exams.

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Superviseur du corps professoral :

Frédéric Leblond

Étudiant :

Partenaire :

Retispec

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Polytechnique Montréal

Programme :

Accelerate

IoT-based Rental Item Location Tracking System

The purpose of this project is to add a feature to Rentrax so that business owners can track the physical location of their rental items. Device should be small enough to be hidden in rental items such as bikes. Battery usage of device should be as low as possible so that it doesn’t need frequent re-charge Location of device can be sent in real time or by receiving a signal or SMS and sending the location The fix and operating cost of device should be reasonable (fix cost below $30 and operating cost below $5 a month)

Voir la description complète du projet
Superviseur du corps professoral :

Waleed Ejaz

Étudiant :

Partenaire :

Rentrax

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Lakehead University

Programme :

Accelerate

Design and prototype of a robotic system to avoid food security risk inCOVID-19 like situations

In the new reality of COVID-19 pandemic, contactless cooking and serving in food industry becomes a new
essential prospect to reduce virus transmission by reducing human labor and human-food interaction. The goal
of this project is to develop an intelligent robot system to manipulate tools and food items in a restaurant counter
and kitchen environment to automate preparation of some basic dishes to serve. The main design challenges are
(1) development of a reliable intelligent robot manipulator system for transportation of tools and food items in the
workplace, (2) intelligent perception and decision for localization and classification of key objects in the workplace,
(3) reliable efficient task execution planning, (4) integration of collision avoidance in the task environment, and (5)
integration of artificial intelligence to adapt the robotic system to new tasks and conditions. For the partner
organization, Business Innovation Labs, the project will produce intellectual property and products needed by
Canadians and the world market.

Voir la description complète du projet
Superviseur du corps professoral :

Baris Fidan;William Melek

Étudiant :

Partenaire :

Business Innovation Labs

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Waterloo

Programme :

Accelerate

“Missed Connections: Encouraging social encounter, connection, andengagement through time- and location-sensitive playful interactionand games among users/players of public space.”

In this research project, research on cross-reality urban games that foster social engagement and interaction among city-dwellers with themselves and the urban spaces they inhabit will be furthered. Special attention will be paid to the shared experience of time and memory, as these two interface in Urbanoid’s cross-reality urban game x-ode. The knowledge gained will be applied in the implementation and deployment of x-ode, an urban cross-reality game, in Montreal in the Fall of 2020. Urbanoid Inc. will benefit from the intern’s research skills, expertise, and sensitivities on urban-based socially-engaged interactive art projects—specifically in the form of a Literature Review (including a matrix of pertinent study cases and ‘best practices’) and a Study Case Report which will document the game x-ode’s development and implementation processes.

Voir la description complète du projet
Superviseur du corps professoral :

Rilla Khaled

Étudiant :

Partenaire :

Urbanoïd Inc.

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

Concordia University

Programme :

Accelerate

Development of a self-contained roadway powerharvesting system for energy recovery

Kinetic energy harvesting has become of a growing interest in recent years. Kinetic energy is
typically present in the form of vibrations that can be found in numerous environments
ranging from common household goods, industrial plant equipment, to various moving
st ructures. Kinetic energy harvesting is to capture minuscule quantities of kinetic energy in
these environments that would otherwise be dissipated. It is well known that vehicles of all
types travel daily along roads and highways throughout the world, and much kinetic energy
has been wasted as the vehicles have to slow down or stop when approaching toll booths,
t ruck inspection stations, or speed bumps. As a result, the Ottawa-based company, the BW
Services (BWS) Inc, initiated recently an ambitious plan for the development of a selfcontained
roadway power harvesting system (SRPHS) for scavenging the kinetic energy
dissipated from the vehicles. The generated electrical energy can be used to power the lights
and the equipment at the installation station….TOBECONT’D…

Voir la description complète du projet
Superviseur du corps professoral :

Jie Liu

Étudiant :

Partenaire :

BW Services

Discipline :

Engineering

Secteur :

Construction and infrastructure

Université :

Carleton University

Programme :

Accelerate

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Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.