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

Assessment of Machine Learning–Based Medical Directives in Pediatric Emergency Medicine

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Superviseur du corps professoral :

Rahul G. Krishnan

Étudiant :

Partenaire :

The Hospital for Sick Children

Discipline :

Computer science

Secteur :

Health and Related Sciences & Technology; Public administration

Université :

University of Toronto

Programme :

Accelerate

Neural Network Model for Predicting NBA Shot Outcome

As the game of basketball evolved, analysis of the game has also grown from taking average of field goal percentage to more complex analytics. In the 2013-2014 season, the NBA has installed the SportVU Player Tracking technology in every NBA arena. SportVU collects 25 frames of data per second, each frame containing the (x,y) coordinates of each of the 10 players and the (x,y,z) coordinates of the basketball. The goal of this research is to understand how much better we can predict the outcome of shot given this massive amount of newly available information, and what the important factors are in contributing to a made shot. This understanding will assist the Toronto Raptors, and even the general basketball community, on many levels. For example, this could provide some guidance to players (shot location and time-of-game selection) and to coaches (which player/game situations tend to be most successful. The system could also help quantify the quality of performances of players by the shots that they took, instead of only looking at the outcome, which is inherently probabilistic.

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Superviseur du corps professoral :

Richard Zemel

Étudiant :

Partenaire :

Raptors

Discipline :

Computer science

Secteur :

Arts, entertainment and recreation

Université :

University of Toronto

Programme :

Accelerate

Conversational Problem Solving: generating multi-step actionable plans to build trustworthy dialogue agents

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Superviseur du corps professoral :

Irina Rish

Étudiant :

Partenaire :

ServiceNow Canada

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Université de Montréal

Programme :

Accelerate

Two-phase flow in industrial distributors – Optimizing bubble size to improve system efficiency

This project will be used to help develop tools for modelling how we control and optimize the size of bubbles that are needed in some industrial reactors. The current application is related to on-going work that is helping to reduce the energy needed to produce existing carbon-based fuels, but is also applicable to aquaculture, bioreactors, and a variety of emerging technologies that will need to be scaled up to meet the growing demand in Canada. This project is expected to increase collaborations between Dalhousie and the partner institution, Keio University (Japan), providing an opportunity for students at Dalhousie to learn more about some of the different research activities at Keio, while offering training in state of the art modelling techniques to participants from Keio that will help set a foundation for additional joint projects and research.

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Superviseur du corps professoral :

Adam Donaldson

Étudiant :

Partenaire :

Keio University

Discipline :

Engineering

Secteur :

Education

Université :

Dalhousie University

Programme :

Globalink Research Award

Development of bio-brick sequestering recycled aggregates and agricultural waste, for use in new construction projects

Bio-bricks are concrete bricks of recycled materials for use in low-cost structural applications. Natural aggregates will be replaced with recycled aggregates from construction and demolition waste to mitigate the carbon emissions and waste disposal. As a part of climate action plan against the climate crisis the Government of Canada has set its goal to achieve net zero emissions by 2050. The local construction industry along with the University of British Columbia (UBC) sees the value to the local construction industry to develop new affordable and sustainable building components. This work aims to develop cost-effective and environment friendly bio-bricks with adequate strength and durability. Th partner organization can utilize the research findings to develop green and durable bio-bricks as a sustainable solution to new building projects.

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Superviseur du corps professoral :

Shahria Alam

Étudiant :

Partenaire :

NetZero Enterprises Inc.;Westhills Aggregate

Discipline :

Engineering

Secteur :

Manufacturing

Université :

The University of British Columbia - Okanagan

Programme :

Accelerate

Attosecond control of exciton dynamics in quantum materials

The emergence of high-harmonic generation in solids has opened the door to countless new techniques for attosecond control in electronic devices. Simultaneously, quantum materials have become increasingly important for next-generation technologies that exploiting quantum mechanics for computation or sensing. Of particular interest is the family of 2D semiconductors, which are known to host an interesting atom-like quasiparticle called an exciton. The unique and diverse properties of these materials, combined with the inherently nanoscale features of 2D materials, provides a virtual playground for physicists and engineers. Nevertheless, while the merging of these two fields shows great promise for applications such as lightwave electronics, much of the fundamental physics governing the attosecond dynamics of excitons is not well understood. This leads to several interesting questions: 1) What are the excitonic siganture in the high-harmonic generation and how do we measure them? 2) To what extent can we control their properties using layers and heterostructures of 2D materials? And 3) can we exploit them to create novel devices harnessing the power of quantum mechanics? This Mitacs Globalink project, will begin exploring these questions, which tackle both the fundamental and applied aspects of attosecond science in quantum materials.

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Superviseur du corps professoral :

Giulio Vampa

Étudiant :

Partenaire :

Universidad Autonoma de Madrid

Discipline :

Physics

Secteur :

Quantum Science; Nanotechnology

Université :

University of Ottawa

Programme :

Globalink Research Award

Homeporter GPT

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Superviseur du corps professoral :

Dhanya Sridhar

Étudiant :

Partenaire :

HomePorter Inc.

Discipline :

Computer science

Secteur :

Real estate and rental and leasing

Université :

Université de Montréal

Programme :

Accelerate

Coalescence Free Surfaces

Water injection in the industrial gas turbines is frequently used to improve the turbine performance during hot days. Injected water evaporates in the compressor section providing effective cooling leading to increased gas density and improved performance. Water injection technology poses several technological challenges. The injection system needs to be optimized to provide a uniform droplet size distribution across the inlet cross section. Water droplet interaction with static components of a compressor, such as casings and vanes may create accumulation of a water film dynamically shedding off. Such behavior leads to a non-optimum water distribution decreasing the overall efficiency of the water injection system. The purpose of the project is to understand the dynamic interaction between the wet air stream and compressor components. The planned work will be realized through computer modeling and experimental validation.

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Superviseur du corps professoral :

Ali Dolatabadi

Étudiant :

Partenaire :

Rolls-Royce (Dorval, QC)

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Concordia University

Programme :

Accelerate

Manufacturing and supply chain optimization of a mobile plastics recycling plant for deployment in remote Indigenous communities

Plastics recycling remains a major challenge to global environmental sustainability, particularly for vulnerable populations such as remote Indigenous communities in which plastic waste is not viably captured by existing recycling networks. This research project aims to support the on-going work by NetZero Enterprises Inc., in the technical and business R&D for scaling-up the company’s mobile plastics processing plant, for deployment in processing waste PET in such remote communities. The processed PET will re-enter the plastics supply chain and provide income for the community leasing the mobile plant, such as re-bar used in construction, which will be upcycled and functionalized in targeted applications.

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Superviseur du corps professoral :

Babak Mohamadpour Tosarkani;Mohammad Arjmand;Abbas Sadeghzadeh Milani

Étudiant :

Partenaire :

NetZero Enterprises Inc.

Discipline :

Engineering

Secteur :

Manufacturing

Université :

The University of British Columbia - Okanagan

Programme :

Accelerate

Correction automatique de textes français avec Electra

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Superviseur du corps professoral :

Yoshua Bengio

Étudiant :

Partenaire :

Druide Informatique

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

Université de Montréal

Programme :

Accelerate

Detecting Intrusions Stemming from MSFT Co-Pilot in Windows 11

Living-off-the-land binaries (LOLBins) refer to legitimate executables pre-installed with the operating system, like powershell.exe and certutil.exe, exploited by attackers for sophisticated fileless attacks. These attacks, leveraging LOLBins, are often undetectable and pose challenges for detection, incident response, and threat hunting. Microsoft Copilot’s integration as a default tool in Windows 11 adds complexity to the threat landscape. This project aims to extract novel atomic indicators from incidents involving attacks utilizing Microsoft Copilot, contributing to threat intelligence. The extracted IOCs play a crucial role in enhancing security awareness without increasing the complexity of threat detection. This project can be divided into five steps: Data Collection, build a model for automated IOC extraction, testing and evaluation, fine-tuning and deployment and reporting and presentation. The initial stages focus on collection of data and identifying actionable intelligence by coordinating with the threat intelligence team. This data can be used to train, test, and deploy the developed automated IOC extraction model. On successful deployment of the model, it can be integrated with the Threat Intelligence feed to use the actionable intelligence in threat detection and incident response.

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Superviseur du corps professoral :

Ali Dehghantanha

Étudiant :

Partenaire :

eSentire

Discipline :

Computer science

Secteur :

Cyber Security; Information and Communications Technology; Technology

Université :

University of Guelph

Programme :

Accelerate

Developing domain specific deep learning models for phishing detection

Leverage machine learning to develop accurate and sophisticated malicious website detection tools

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Superviseur du corps professoral :

Ali Dehghantanha

Étudiant :

Partenaire :

Arctic Wolf Networks

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

University of Guelph

Programme :

Accelerate