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

Profinite Groups and Cohomology

In mathematics, a group is a set (an accumulation of items) together with a certain operation. For example: the integers with addition, the symmetries of an equilateral triangle. Being one of the simplest algebraic structures, groups are ubiquitous in mathematics and have applications in other disciplines. Informally, a group is called profinite if it can be assembled from finite groups in a certain manner. The above symmetries are a finite group: there are only three reflections along the axes and the rotations around 120, 240 and 360 degrees. On the other hand, cohomology is an algebraic tool that can discern different geometric objects by looking at their “holes”. For example, one can discern a ball from a donut using it. There is a counterpart for groups, so group cohomology is a tool that can discern different groups. This project forms a part in answering a question about group cohomology of profinite groups.

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Superviseur du corps professoral :

Alejandro Adem

Étudiant :

Partenaire :

University of Southampton

Discipline :

Mathematics

Secteur :

Education

Université :

The University of British Columbia

Programme :

Globalink Research Award

Estimation visuelle sécuritaire et explicable des conditions routières

Nous avons actuellement un prototype de systeme de vision artificielle base sur des reseau de neurones profonds entra1ne sur notre jeu de donnees proprietaire qui permet d’identifier les zones de construction et de detecter et lire les panneaux de limite de vitesse. Dans notre prochain de R&D, nous souhaitons tirer partie de notre reseau de detection d’objets afin d’identifier les conditions routieres dangereuses ( neige, blizzard, glace, pluie, aveuglement ) ainsi que le contexte de conduite ( autoroute, route rurale, zone urbaine, chemin de terre).

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Superviseur du corps professoral :

Ioannis Mitliagkas

Étudiant :

Partenaire :

E-SMART Control Inc.

Discipline :

Computer science

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Accelerate

Fabrication and measurement of 2D materials heterostructures

Two-dimentional (2D) materials made of few atomic layers, bring unprecedented quantum properties from their extreme thickness. The possibility to stack layers from different 2D materials into heterostructures is one of the most active areas of research in quantum materials, bringing a wide parameter space for creating previously inaccessible quantum states and device geometries. This project will advance the field of quantum devices based on 2D materials by focusing on heterostructures made from two atomically thin semiconductors WSe2 and MoS2 and insulating hexagonal boron nitride. The goal is to fabricate such ultrathin semiconductor heterostructures, optimize their electrical contacts in devices and understand their optical and electrical properties. To that end, we will combine the complementary expertise of the Canadian and French institutions on the fabrication and characterization sides. The outcome of this project are scientific advances in quantum technologies based on 2D materials, giving Canada a leading edge in this area.

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Superviseur du corps professoral :

Adina Luican-Mayer

Étudiant :

Partenaire :

Université Grenoble Alpes

Discipline :

Physics

Secteur :

Education

Université :

University of Ottawa

Programme :

Globalink Research Award

Test-based Fracture Criteria for Pipeline Steels

Steel pipelines as key Canadian infrastructure are often exposed to various geological and environmental conditions that cause defects such as cracks, dents, and gouges in the pipe wall, which can lead to pipe fracture in pipelines, compromising the entire pipeline’s functionality and resulting in significant economic losses, environmental issues or even fatalities. There are several methods to predict the fracture capacity, including experimental testing, analytical approaches, and advanced numerical methods. The use of fixed fracture strain criterion implemented in the computer programs may not appropriately predict the crack propagation path because of the concentration of large strains. Further, fracture criteria that ignore the crack tip constraints and depend on the type of the test specimens used to obtain fracture indices may lead to inconsistent predictions. There is a need to develop and implement more efficient and accurate fracture criteria specific to pipe steel as a function of crack tip constraints, independent of the type of specimens used and the size of pre-cracking. This research project aims at developing calibrated numerical-based fracture criteria for predicting the crack propagation in steel pipelines.

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Superviseur du corps professoral :

Ali Imanpour;Samer Adeeb;Samer Adeeb;Yong Li;Ali Imanpour

Étudiant :

Partenaire :

Enbridge Pipelines;C-FER Technologies

Discipline :

Engineering

Secteur :

Mining; Professional, scientific and technical services; Transportation and warehousing; Utilities

Université :

University of Alberta

Programme :

Accelerate

Study of Amaryllidaceae alkaloid pathway genes using comparative Omics analysis

Plant produce large number of the bioactive compounds, among them Amaryllidaceae alkaloids has such potential. Those Amaryllidaceae alkaloids are extracted from Amaryllidaceae plant family. Galantamine is one of the drug which is derived from the Amaryllidaceae alkaloid pathway; and is the only commercialized drug for the treatment of early symptoms of Alzheimer’s disease. Although many Amaryllidaeae alkaloid have potential pharmacological properties, its further research and application is restricted due to its low level of accumulation in plants. Emerging technology in genetic engineering have potential to produce plant derived compounds from heterologous microbial host. The knowledge on biosynthetic pathway of targeted compound is absolute necessity for reconstruction of biosynthetic route in microorganisms. Ongoing biological process can be captured using RNA sequencing technology, co-expression network analysis and computational studies. Hence, our project focus on the identification of biosynthetic pathway genes involved in Amaryllidaceae alkaloid metabolism by comparative transcriptomic analysis.

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Superviseur du corps professoral :

Isabel Desgagné-Penix

Étudiant :

Partenaire :

Nanyang Technological University

Discipline :

Life Sciences

Secteur :

Education

Université :

Université du Québec à Trois-Rivières

Programme :

Globalink Research Award

ALT TEX Circular Textile-grade Polymer Synthesis

Generating 10% of global greenhouse gas emissions the fashion industry’s heavy reliance on synthetic,
petroleum-derived, fabrics such as polyester, is projected to create over a quarter of the world’s carbon emissions
by 2050, according to the Ellen MacArthur foundation. Unlike its bio-based counterparts, such as cotton, wool or
silk, polyester does not biodegrade, and its synthetic production is estimated to consume 70 million barrels of oil
each year while it’s disposal creates 55 million annual tons of landfill waste globally.
This project proposes a green polymerization method to generate a circular biosynthetic polymer alternative that
can be manufactured into textiles, similar to the polyester counterpart. The resulting material alternative carries
potential to reduce fashion’s dependence on fossil fuels while the industrial biodegradability opens the door to
circular textile waste diversion.
This research will support ALT TEX in its materials science research on the path to developing commercially
viable, radically circular textiles for the fashion industry.

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Superviseur du corps professoral :

Parisa Mehrkhodavandi

Étudiant :

Partenaire :

ALT TEX

Discipline :

Engineering

Secteur :

Manufacturing

Université :

The University of British Columbia

Programme :

Accelerate

“The Space Where Everything Flows”: Room, Trauma and Myth in Youval Shimoni’s Work

My proposed internship is part of a larger research project, my thesis. In my research, I present the first critical, academic discourse on Youval Shimoni’s body of work through an examination of the concepts and aspects of space in his works, and their relation to Israeli reality. In my thesis, Shimoni’s work is mapped for the first time, revealing his unique poetic language, and the philosophical and political themes that reoccur throughout his body of work. I hope this internship will provide me a chance to make significant progress with my thesis while benefiting from the leading researchers that are part of the vital intellectual community at the University of Toronto. By working with the guidance of Professor Naomi Seidman I hope to deepen my knowledge of modern myths and rethink Jewish-Christian relations. I wish to participate in courses and the diverse community of the Department of Religion, the Center of Diaspora and Transnational Studies, and the Center for Jewish Studies at the University of Toronto. In the three months of the internship, I plan to work on my thesis chapter dealing with the myths in Shimoni’s work, while conducting a progress meeting with prof. Seidman, participating in seminars related

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Superviseur du corps professoral :

Naomi Seidman

Étudiant :

Partenaire :

Tel Aviv University

Discipline :

Sociology

Secteur :

Education; Other

Université :

University of Toronto

Programme :

Globalink Research Award

Arch-App

The intention of the Arch-App is to create a mobile app that utilizes geo-location and augmented reality technologies to access data (including imagery, videos, and text) on building projects throughout the city in real time. The infrastructure of the Arch-App effectively provides users a resources (ranging from historic imagery to notable interviews) and tour guides to any local landmark in the real world condensed into their smartphones. Currently, there is no such infrastructure which, supports said goals of Arch-App. The Arch-App strives to empower people with more information on any given landmark they may come across including touristic, academic, and recreational initiatives. The intern will be conducting interviews, gathering content from the firms and compiling and uploading information to the app. The app will expose the industry to cutting-edge technology and firms involved will gain exposure to the public, educational and professional level and will have the opportunity to leave a legacy through their work.

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Superviseur du corps professoral :

Vincent Hui

Étudiant :

Partenaire :

Ontario Association of Architects

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

Non-Destructive Evaluation of Irradiated Single walled carbon nanotube

Semiconductors have been used in electronics for decades and are an integral part of every circuit. Because of this, evaluating semiconductor performance and tolerance in different environments is crucial. For example, evaluating a semiconductor’s radiation tolerance can be quite useful such as for the radiation detectors in the Large Hadron Collider and for the solar panels on the international space station which are exposed to lots of radiation. Unfortunately, it is still unsure how radiation affects semiconductors, for this reason the student (Nicholas Dallaire) will study the tolerance of single walled carbon nanotube semiconductors. Nicholas will use transient grating spectroscopy (TGS) to evaluate the degradation of the semiconductors which have been exposed to radiation. TGS is a method used to characterize the surfaces of materials in a nondestructive way to determine a material’s elasticity, energy dissipation, thermal diffusivity. The research done will aid in figuring how semiconductors are affected by radiation and help innovate novel circuits which may need protection from radiation, such as satellites.

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Superviseur du corps professoral :

Benoit Lessard

Étudiant :

Partenaire :

Massachusetts Institute of Technology

Discipline :

Physics

Secteur :

Education

Université :

University of Ottawa

Programme :

Globalink Research Award

Federated Learning on Sensitive Mobile Data (Python/Java)

At Lerna IA, we are building a private federated learning platform for mobile applications. Our technology allows mobile-first companies to learn about their app users without violating their privacy. Our novel security architecture speeds up the federated learning process by at least 50x, rendering it practical for real-world mobile set-ups by running the whole ML process on thousands of mobile phones in a distributed fashion. We predict the user behavior based on their context, demographics, mood, etc. in order to identify best timing for out-reach, without retrieving any data!
For the purpose of this internship, the core research portion constitutes the selection and tuning of ML algorithms that are suitable for our application – both useful and with an efficient Federated Learning version.

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Superviseur du corps professoral :

Laurent Charlin

Étudiant :

Partenaire :

Lerna

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

HEC Montréal

Programme :

Accelerate

High-frequency financial forecasting

Berkindale Analytics is a cloud-based company and wants to create a next-generation platform to provide both market data and packaged analytics to financial clients via direct download, interface, and dashboards accessible from a web portal. It is distinguished by its service arm that engages in data discovery, new analytics design, and ETL (“Extract, Transform, and Load”) configuration with client data.
The student will develop supervised and unsupervised machine learning tools adapted to capture stylized facts of a market or a trading platform, such as liquidity and volatility indicators. Berkindale is looking to develop a short-term (intraday) liquidity and volatility forecasting model for market indices and individual stocks. This model should use machine learning to combine forecasts obtained from different econometric models, depending on the situation (market conditions for related stocks, forecast events such as earnings announcements or macroeconomics, intensity of media coverage, etc.). This model will allow Berkindale’s clients to better manage their execution and volatility risk, thereby reducing their costs and improving their investment performance.

Voir la description complète du projet
Superviseur du corps professoral :

Ioannis Mitliagkas

Étudiant :

Partenaire :

Berkindale Analytics Inc

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Université de Montréal

Programme :

Accelerate

Crevettiers : enjeux de santé et sécurité au travail

Le milieu des pêches commerciales est reconnu comme l’un des secteurs de travail les plus dangereux au Canada (Grant, 2017). Le Comité permanent sur la sécurité des bateaux de pêche du Québec (CPSBPQ) est un organisme à but non lucratif qui œuvre dans ce milieu afin d’améliorer la culture de sécurité et diminuer les risques et les enjeux auxquels sont exposés les pêcheurs professionnels. Le projet de recherche intitulé «?Les crevettiers : Enjeux de santé et de sécurité au travail?» vise à mieux comprendre la relation entre la fatigue, l’ergonomie et les risques dans les pêches commerciales au Québec. Grâce à une étude réalisée à bord des crevettiers du Québec, le CPSBPQ et les stagiaires pourront cibler les sources de risques prioritaires afin de proposer des solutions innovantes pour les réduire ou les éliminer.

Voir la description complète du projet
Superviseur du corps professoral :

Dany Rondeau;Claude Rioux;Anne Fauré

Étudiant :

Partenaire :

Comité permanent sur la sécurité des bateaux de pêche du Québec

Discipline :

Sociology

Secteur :

Other services (except public administration)

Université :

Université du Québec à Rimouski

Programme :

Accelerate

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