Projets novateurs réalisés

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

31 620 projets complétés

2978
AB
5221
C.-B.
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projets par catégorie

Identifying Risk Factors for Hazardous Driving and Accident Propensity

Road safety affects everyone, Geotab has several years of driving and environmental data from over 2 million
connected vehicles providing the opportunity to make customers safer, as well as our communities and cities.
This project will leverage data and existing methods to build a model that can identify causal risk factors for
hazardous driving and accident propensity. The model will output a safety score representing the risk level of
fleets/drivers, which can facilitate high efficiency and safety management of light, medium and heavy duty
vehicles. With better understanding of environmental causality, safety concerns can be addressed proactively to
prevent accidents.

Voir la description complète du projet
Superviseur du corps professoral :

Andrei Badescu;Sheldon Lin

Étudiant :

Partenaire :

Geotab Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services; Transportation and warehousing

Université :

University of Toronto

Programme :

Accelerate

Automated code fix suggestions based on source code syntax tree analysis

AMD manages a very large code base that supports multiple graphics products, operating systems, and customers with multiple releases per year. With a high rate of innovation and corresponding code changes it is a daunting task to ensure a given change works correctly on all applicable configurations for every release. It is therefore imperative to detect potential issues as soon as possible in development lifecycle, and ideally as soon as developers make code changes and where possible also propose a fix for detected issues.

Voir la description complète du projet
Superviseur du corps professoral :

Shurui Zhou

Étudiant :

Partenaire :

AMD Canada

Discipline :

Computer science

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Autonomous Navigation for Small UAV in Indoor GPS-denied Environments

With the evolution of unmanned aerial vehicles (UAVs) in recent years, more and more researchers are setting their sights on the application research of the indoor environment. Indoor applications include industrial facility inspection, warehouse inventory management, health sector, search, and rescue, among others. However, the use of UAVs in these applications requires continuous high-accuracy positioning and pose information and the consequent efficient obstacle avoidance algorithm. To address the above problem, we want to design an algorithm that can:
1. Perceive the surrounding environment.
2. Control attitude and position of UAVs.
3. Navigate UAV through obstacles.
4. Account for the changes in the dynamic environment and remain stable.

Voir la description complète du projet
Superviseur du corps professoral :

Igor Gilitschenski

Étudiant :

Partenaire :

SOTI Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Real-time Bidding Using Contextual Targeting

Ads keep the internet free. But, to keep them from becoming spam and degrading the user’s online experience, they need to be relevant to them. The traditional way the industry does this is by collecting a lot of information about every user and creating profiles that can be used to target users based on their online journey. However, users have different tolerances for how much information they want collected about them by any website/app. In general, the problem the industry needs to solve is to make sure the ads shown to users are relevant even in the absence of any user profile. This is the problem the intern is going to tackle. In this research, an End-to-End project will be built to create a contextual targeting proof of concept for mobile and desktop websites. Industry standard metrics such as click-through rate will be used to get an understanding of whether contextual targeting works.

Voir la description complète du projet
Superviseur du corps professoral :

Annie Lee

Étudiant :

Partenaire :

Pelmorex

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Modeling and Optimization of roof based BIPV/T with air source heat pump

Incorporating the Air Source Heat Pump (ASHP) into Building Integrated Photovoltaic/Thermal (BIPV/T) system has the potential to reduce building heating and cooling costs and dependence on non-renewable heating fuels. ASHPs could boost the quality and quantity of heat output of a BIPV/T system by delivering a seasonal Coefficient of Performance (COP) of between 2.0 and 4.0, which means 2-4 times more energy output than the amount of energy (electricity) consumed.
When used in Canada’s cold climates, however, ASHPs alone have been found to underperform at low temperatures due to the scarcity of heat that may be pumped out of the atmosphere. One solution to this is ASHP which can provide a higher COP at very low winter outdoor temperatures. The incorporation of PV/T + ASHP into building integrated sloped roof, solutions in existing residential and commercial buildings will furthermore have the potential to lower overall costs of such systems, significantly reduce GHG emissions and provide significant economic and other benefits for Canada in general and for southern Ontario and the Greater Toronto Area (GTA) in particular.

Voir la description complète du projet
Superviseur du corps professoral :

Alan Fung

Étudiant :

Partenaire :

S2E Technologies Inc

Discipline :

Engineering

Secteur :

Construction and infrastructure; Finance and Insurance; Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

Hypatia-Learn: State of the Art Mathematics Learning and Tutoring System

The project revolves around reading and understanding students solution to various mathematical problems. We wish to analyse the work done by students and the solution to these problems and provide math checking capabilities to various types of problems. Furthermore, this project looks to construct a virtual tutor that can analyse students work and provide feedback and hints to help the student arrive at the correct solution. We wish to achieve all of this while using a simple mathematical editor to allow students to type up mathematical solution cleanly and easily.

Voir la description complète du projet
Superviseur du corps professoral :

Azadeh Farzan

Étudiant :

Partenaire :

Hypatia Systems Inc

Discipline :

Computer science

Secteur :

Education

Université :

University of Toronto

Programme :

Accelerate

Optimisation de l’aquaculture multitrophique en milieu tropical par l’intégration de la macroalgue Ulva lactuca dans la moulée du poisson marin Pompano de Floride (Trachinotus carolinus)

Les protéines dans les farines et huiles de poissons représentent l’élément le plus dispendieux des moulées commerciales. Son remplacement par une protéine végétale provenant de macroalgues produites dans les eaux de rejets piscicoles diminuerait les coûts associés à la production aquacole tout en réduisant les impacts environnementaux. Les Ulves, comme Ulva lactuca, ont été largement évaluées comme substitut alimentaire. Dans ce projet, nous remplacerons la farine de poissons par de l’Ulva (substitution de 25 %) et évaluerons les effets sur le rendement reproductif du Pompano de Floride, un poisson marin tropical commercialement prometteur. Les géniteurs seront nourris avec la moulée à base d’Ulva, produite dans le système AMTI (Aquaculture Multitrophique Intégrée), puis avec une moulée commerciale (Vitalis), pour comparer la qualité des œufs, à la base d’un bon développement larvaire, entre les 2 régimes. L’ajout d’Ulva dans la moulée du Pompano se refléterait par un rendement similaire ou supérieur à la moulée Vitalis.

Voir la description complète du projet
Superviseur du corps professoral :

Réjean Tremblay

Étudiant :

Partenaire :

Florida Atlantic University

Discipline :

Life Sciences

Secteur :

Technology; Aquaculture and Fishing; Sustainability & the Environment

Université :

Université du Québec à Rimouski

Programme :

Globalink Research Award

Performance of Fiber-Reinforced Lightweight Self-Consolidating Concrete Columns Reinforced with Glass Fiber-Reinforced Polymer Bars and Spirals under Axial and Eccentric Loads

One of the main interests of the construction industry is the use of innovative materials to facilitate construction, extend service life and minimize maintenance and rehabilitation costs. Lightweight aggregate self-consolidating concrete (LWSCC) can be of great interest for reducing dead loads, section dimensions and project costs, especially for precast elements. Integrating GFRP reinforcement into LWSCC would effectively contribute to producing lighter and more durable concrete members for precast applications. Lightweight concrete is more brittle than normal-weight concrete (NWC). Furthermore, the brittleness of concrete may affect not only the failure mode but also the axial capacity of concrete columns. Adding fiber into LWSCC is an effective way to solve the brittleness of concrete and improve the tensile strength and crack resistance of concrete. This research project aims to develop fiber-reinforced lightweight aggregate self-consolidating concrete (FR-LWSCC) mixes for precast applications
and to provide an experimental work as well as extensive theoretical analysis and design recommendations of RC columns reinforced with FRP bars. The experimental results will be discussed in terms of moment–deflection behavior, flexural capacity, mode of failure, crack patterns, and crack widths.

Voir la description complète du projet
Superviseur du corps professoral :

Brahim Benmokrane

Étudiant :

Partenaire :

Sym-Tech Béton Préfabriqué Inc.

Discipline :

Engineering

Secteur :

Manufacturing and Construction; Advanced Manufacturing; Sustainability & the Environment

Université :

Université de Sherbrooke

Programme :

Accelerate

Cloud platform of machine learning

Surgical Safety Technologies Inc. is expanding upon its existing OR Black Box® platform, which will allow users of the platform to build a personalized, user-created library of surgical videos in the cloud. There are many people and groups around the world who will use this video library to make sure that performance evaluations are fair and can be done quickly and easily. Among the methodologies used in this project are research on human-computer interaction, video relevance ranking, and business intelligence based on meta-data that comes from the cloud platform. The main goal of the project is to work with existing teams at SST to make prototypes and products that can be used on the cloud, and to make sure that the cloud solution can be used more widely.

Voir la description complète du projet
Superviseur du corps professoral :

Igor Jurisica

Étudiant :

Partenaire :

Surgical Safety Technologies Inc

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Neural Networks for Observable Market Data Validation

Observable Market Data is critical for effective valuation of trades for risk management purposes within the investment bank. The valuation process requires the existence of good quality data day by day, and dating back into the mid-2000’s. Not all assets have highly liquid data available either historically or at present, and there is significant interest within the industry in building models to both predict missing data and qualify available data. Historically this process has been highly manual, and due to the volume of data statistical methods are used to identify potentially suspect data. The use of these simplistic methods to gate incoming data results in known blind spots and false positives. This project seeks to use deep neural networks to tackle these two tasks : 1) flagging suspect data efficiently, 2) generating quality data that can be used to improve modeling where real data is unavailable.

Voir la description complète du projet
Superviseur du corps professoral :

Kirill Serkh;Vardan Papyan

Étudiant :

Partenaire :

CIBC

Discipline :

Computer science

Secteur :

Finance and Insurance

Université :

University of Toronto

Programme :

Accelerate

Assessment and modelling of salmon streams in western Newfoundland

The approach to assessing Atlantic salmon in Newfoundland is based on patterns of salmon production and habitat that were established for populations in rivers much further south. The physical and biological characteristics of watersheds and rivers in Newfoundland are different from the southern rivers and the bases for conservation decisions are likely inappropriate. Establishing relationships between stream physical and biological characteristics that are unique to Newfoundland is prudent for better management of Newfoundland salmon populations.

Voir la description complète du projet
Superviseur du corps professoral :

Robert Scott

Étudiant :

Partenaire :

Atlantic Salmon Conservation Foundation

Discipline :

Life Sciences

Secteur :

Other services (except public administration)

Université :

Memorial University of Newfoundland

Programme :

Accelerate

Advancing Gender Equality for Women in Venture Capital – Part 2

Women are vastly underrepresented in venture capital (VC) firms. There is also a lack of women entering the field of venture capital due to systemic barriers and a lack of momentum to shift existing barriers for women to enter the venture capital world. This research aims to understand the current status of women in VC firms, identify structural barriers facing them, and promote gender parity in VC firms and the investing community. The methods include a literature review, in-depth interviews with VC capitalists or senior leaders from VC firms, as well as the creation of an action plan for the partner organizations to drive changes in the investing community.

Voir la description complète du projet
Superviseur du corps professoral :

Wendy Cukier

Étudiant :

Partenaire :

Ethical Digital;National Angel Capital Organization

Discipline :

Sociology

Secteur :

Other services (except public administration); Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

Précédent
1...1,3681,3691,3701,3711,3721,3731,374...2,635
Suivant

Joignez-vous à un écosystème d’innovation florissant.

Abonnez-vous à notre infolettre dès maintenant!

S’inscrire

Mitacs — Retour sur innovation

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.