Projets novateurs réalisés

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

29 670 projets achevés

2811
AB
4990
C.-B.
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projets par catégorie

Thermal Management System for High-Temperature Thermal Energy Storage Applications

This proposal focuses on enhancing renewable energy utilization by developing efficient thermal energy storage systems. By leveraging technologies like microscale flow channels that are reported to provide high heat transfer coefficients, the project aims to improve heat extraction rates, enabling better integration of renewable power generation systems with thermal storage. The collaboration between the University of Alberta in Canada and NUST in Pakistan will not only advance research in sustainable energy solutions but also contribute to addressing global challenges related to industrial heat demand and climate change. Through systematic investigation, the project seeks to overcome technical hurdles and establish reliable, compact, and cost-effective coupling systems, benefiting both research institutions and the wider community striving for cleaner energy alternatives.

Voir la description complète du projet
Superviseur du corps professoral :

Muhammad Taha Manzoor

Étudiant :

Partenaire :

National University of Sciences and Technology

Discipline :

Engineering

Secteur :

Clean Technology; Energy and Utilities; Sustainability & the Environment

Université :

University of Alberta

Programme :

Globalink Research Award

Development of a computational pipeline to mine phage endolysin sequences from metagenomic datasets

The resistance of bacteria to antibiotics is a growing problem that we need to address, for example, through the development of alternative treatments. Bacteriophages, or phages, the viruses of bacteria, have been proposed as a potential avenue for the treatment of recurring bacterial infections or against multi-resistant bacteria. Even more promising, are proteins encoded by phages, called lysins, that attach to the bacterial cell wall and degrade it, eventually leading to the death of a target bacterium. Their natural diversity, matching the diversity of bacteria, only adds to their potential as a source to develop treatments. The goal of this project is to develop a computational tool to mine phage lysins from phage protein datasets. Such powerful computational tools for the discovery of new phage lysins could lead to the development of new alternative treatments to antibiotics targeting harmful bacteria. This project will combine the expertise of the host institution on lysins and that of the home institution in informatics for the development of a tool that will benefit the research conducted on phages in both institutions, and even more broadly to the research field interested in the development of alternative treatments to antibiotics.

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Superviseur du corps professoral :

Elsa Rousseau

Étudiant :

Partenaire :

Ghent University

Discipline :

Computer science

Secteur :

Education

Université :

Université Laval

Programme :

Globalink Research Award

“Improving Flexural Strength Predictions in Composite Materials using Image Processing and Machine Learning”

This project aims to improve the way we assess the strength of short fiber reinforced composites, focusing on sustainability. By exploiting the distinct visibility traits of PEEK and carbon fibers in CT scans, the study will utilize non-destructive testing and computer algorithms to analyze and measure factors critical to the material’s strength directly from scan images. Through a combination of 2D and 3D imaging techniques and machine learning, the research intends to streamline the analysis of large data sets and develop a predictive model linking scan images to the composite’s mechanical properties.
The collaboration between York University and Prof. Gupta at New York University aims to leverage intern’s skills in micro-CT scanning and image processing to advance research in composite materials. The joint work will not only contribute to the lab’s research objectives but also enhance the intern’s understanding of machine learning and the relationship between imaging techniques and material properties. With the intern’s expertise in material charactersation, CT scanning and image processing, this partnership is expected to yield innovations in sustainable material testing and development, benefiting both institutions by fostering academic growth and opening new research avenues in materials science.

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Superviseur du corps professoral :

Reza Rizvi;Garrett Melenka

Étudiant :

Partenaire :

New York University Polytechnic School of Engineering

Discipline :

Engineering

Secteur :

Artificial Intelligence; Technology; Advanced Manufacturing

Université :

York University

Programme :

Globalink Research Award

Development of an economical organic Rankine cycle (ORC) modular rig using low-temperature geothermal heat sources

This proposal aims to address the urgent need for clean energy solutions in Canada, particularly focusing on harnessing geothermal energy to meet electricity demands. By utilizing an Organic Rankine Cycle (ORC) system, which efficiently converts geothermal heat into electricity, the project seeks to develop a modular rig integrated with parallel turboexpanders for enhanced performance. This initiative not only aligns with Canada’s goal of achieving net-zero emissions by 2050 but also offers practical solutions for sustainable energy production. The participating institutions, including the University of Alberta in Canada and NUST in Pakistan, will benefit from collaborative research, innovation, and the training of interns in cutting-edge energy technologies, thereby contributing to global efforts in combating climate change.

Voir la description complète du projet
Superviseur du corps professoral :

Muhammad Taha Manzoor

Étudiant :

Partenaire :

National University of Sciences and Technology

Discipline :

Engineering

Secteur :

Energy and Utilities; Green/Alternative Energy; Sustainability & the Environment

Université :

University of Alberta

Programme :

Globalink Research Award

Impact assessment of delineated management zones and variable nitrogen application rates in potato production using artificial intelligence techniques

Prince Edward Island (PEI) potato production represents 23% of the total production in Canada, contributes 6.6% in the local provincial economy, therefore maintaining higher potato yield is the main goal of local farmers. This can be achieved through proper management practices including nutrients supply such as nitrogen. Nitrogen (N) is the one of the most limiting nutrient in potato (Solanum tuberosum L.) growth and plays a significant role in yield attributing factors such as plant emergence, plant height and weight of tuber per plant. However, uniform application of N fertilizer without considering spatial variability in terms of soil physicochemical properties and other environmental factors, leads to overuse of N fertilizer. The excess N supply leads to premature leaf senescence, low starch content, reduction in tuber yield and promotes nitrate loss through leaching, causing environmental pollution. To our knowledge, few studies have been carried out to reduce within field spatial variability using combined approach of integrating soil proximal sensor data with previous years tuber yield along with the artificial intelligence techniques to monitor in season N dynamics and tuber yield. Therefore the goal is to explore the optimization of N application in potato production to improve yield and minimizing N loss.

Voir la description complète du projet
Superviseur du corps professoral :

Antoine Karam

Étudiant :

Partenaire :

Walloon Agricultural Research Centre

Discipline :

Earth science

Secteur :

Agriculture and Food; Artificial Intelligence; Environmental Science and Technology

Université :

Université Laval

Programme :

Globalink Research Award

Studying the process-properties relationship of a new thermoplastic lignocellulose

Canada stands well positioned to becoming a commercial leader in sustainable materials, especially when based on the waste of our natural resources like forestry pulp. A flowable bioplastic being developed at Agapyo, came out of the research at McMaster University and promises to replace petroleum-based plastics meant for structural applications. Agapyo and McMaster are working together to rapidly bring this new material to market while simultaneously learning more about how the chemistry and extrusion processing environment interact on a fundamental level. The post doctoral fellow will study the interactions of chemistry and process, and translate the results into useable guidance for Agapyo’s manufacturing group.

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Superviseur du corps professoral :

Michael Thompson

Étudiant :

Partenaire :

Agapyo

Discipline :

Engineering

Secteur :

Manufacturing

Université :

McMaster University

Programme :

Accelerate

Rogers “Innovation Pitch”

To take an innovative look at issues facing Rogers hockey coverage, community outreach and engagement and opportunities for value creation by reaching new hockey audiences. The goal will be to connect with and develop students across the country who are interested in sports media and business. At the same time, to also develop important thought leadership on the challenges and opportunities facing Rogers as it enters into the groundbreaking hockey media rights deal starting in 2014.

Voir la description complète du projet
Superviseur du corps professoral :

Cheri Bradish

Étudiant :

Partenaire :

Rogers Communications Inc (Toronto, ON) - to merge

Discipline :

Business

Secteur :

New and Digital Media; Entertainment and Media

Université :

Toronto Metropolitan University

Programme :

Accelerate

Using Multiomics To Understand Spatial Heterogeneity in Alzheimer’s Disease

Single-cell -Omics analysis methods are having a transformational impact on research in the life sciences. Specifically, the capacity to assess genomes, transcriptomes, or proteomes of individual cells in place of (or in addition to) measuring the average signals from populations of cells allows researchers to ask and answer questions that have never been accessible until now. We recognize this transformation and propose to push it further, developing the world’s first system capable of capturing transcriptome, proteome, and epigenome sequences from a single, spatially resolved cell, and applying it to unraveling a hot question in neuroscience, the relationship between glial cell behavior and Alzheimer’s disease. In sum, in this work, we will explore and expand the unique selectivity of DISCO to obtain exceptionally high-content catalogs of individual glial cells to ask important questions about glial cell behavior as related to Alzheimer’s disease. Importantly, the DISCO platform is highly versatile and reconfigurable, and is cell-type-agnostic in such way that it can evaluate nearly any biological question of interest.

Voir la description complète du projet
Superviseur du corps professoral :

Aaron Wheeler

Étudiant :

Partenaire :

Max Planck Institute for Multidisciplinary Sciences

Discipline :

Life Sciences

Secteur :

Biotechnology; Health and Related Sciences & Technology

Université :

University of Toronto

Programme :

Globalink Research Award

Recherche participative sur la domestication d’espèces arctiques afin d’accroître la sécurité alimentaire et l’autonomie alimentaire des communautés inuites.

Dans le cadre du projet VertBerry du Défi Cultiver l’Innovation d’ici de la Weston Family Foundation et en complémentarité
avec le projet Sentinelle Nord sur la sécurité alimentaire des communautés inuites du Kitikmeot, ce stage de recherche vise à
concevoir des protocoles de domestication pour des espèces arctiques comestibles, notamment les petits fruits, permettant
ainsi une récolte allongée ou continue de plantes. Les baies traditionnelles et les plantes comestibles/médicinales font partie
intégrante du système alimentaire, de la culture et de l’identité inuites. Cependant, le climat arctique rigoureux et les
changements climatiques restreignent les opportunités de récolte, affectant l’accessibilité aux petits fruits et autres espèces.
Par ailleurs, la domestication de nouvelles espèces comestibles, dont des petits fruits, permettrait pour les régions plus au sud
de diversifier l’offre pour des produits nordiques à haute valeur nutritive et culinaire.

Voir la description complète du projet
Superviseur du corps professoral :

Martine Dorais

Étudiant :

Partenaire :

Viventem Science support agency;Weston Family Foundation

Discipline :

Earth science

Secteur :

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

Université :

Université Laval

Programme :

Accelerate

Co-designing a physical activity behavior change toolkit to promote effective rheumatoid arthritis self-management

In rheumatoid arthritis care, patients face long waits and frequent appointments. Using a patient-initiated follow-up model can help patients avoid unnecessary appointments and reduce wait times, but this only works if patients have enough support to manage their disease. Physical activity is essential for managing RA, but many people with RA do not have enough support to become and stay physically active. We want to change that. Our plan has three parts: first, we’ll figure out what physical activity support patients need. Next, we’ll work with patients and healthcare partners to design tailored support tools for physical activity. Finally, we’ll check if patients and healthcare providers find these tools helpful. Our goal is to empower Canadians to better manage their RA and use what we learn to create more self-management tools (to manage fatigue and other challenges) for RA and other chronic diseases.

Voir la description complète du projet
Superviseur du corps professoral :

Claire Barber

Étudiant :

Partenaire :

The Bone and Joint Health Strategic Clinical Network (AHS)

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology

Université :

University of Calgary

Programme :

Accelerate

Utilisation de l’apprentissage machine dans les pompes à chaleur à hautes températures pour la prévision et l’optimisation des coûts énergétiques, de la performance et de l’efficacité exergétique

Les pompes à chaleur à haute température (PACHT) peuvent répondre à la demande thermique de diverses applications. Elles peuvent être utilisées pour des applications résidentielles, commerciales et industrielles et fournir à la fois le chauffage et l’eau chaude. Selon le site officiel du gouvernement du Canada, les thermopompes sont une technologie éprouvée et fiable au Canada qui permet de contrôler le confort des maison en utilisant des sources d’énergie renouvelables telles la géothermie, la biomasse et les rejets thermiques. Les (PACHT) sont capables de réduire les émissions carboniques de 35 à 65% lorsqu’elles remplacent une chaudière à gaz et de plus de 80% lorsqu’elles remplacent une chaudière à charbon ou à fioul. L’objectif général du projet est d’utiliser des outils d’apprentissage automatique (machine) tels que les réseaux neuronaux artificiels pour prédire les performances des systèmes (PACHT) dans différentes conditions opérationnelles et d’optimiser leurs performances en termes de coût énergétique, de performance et d’efficacité exergétique. L’objectif spécifique est de fournir des moyens numériques prédictifs et une évaluation quantitative aux entreprises canadiennes d’énergie et aux utilisateurs individuels afin d’améliorer les procédés de fabrication et de faciliter l’adoption de ces systèmes efficaces avec les moindres coûts.

Voir la description complète du projet
Superviseur du corps professoral :

Mohammed Khennich

Étudiant :

Partenaire :

IMT Mines Albi

Discipline :

Engineering

Secteur :

Green/Alternative Energy; Artificial Intelligence; Technology

Université :

Université de Moncton

Programme :

Globalink Research Award

Interpretable AI for Seamless Robot Navigation Among People

This project aims to make advancements in mobile robot navigation in crowded environments, which will alleviate one of the key bottlenecks to wider utilization of mobile robotic systems and bring these systems into sectors such as entertainment, travel, health care, and logistics. To achieve this aim, the project proposes to develop robust, interpretable AI for human navigational intent prediction that, given input from a stereo camera, will output the probability distribution over where a person may be positioned the near future. Such predictions can be integrated with trajectory planning algorithms to allow robots to navigate much more quickly and smoothly around people without sacrificing safety. These planning algorithms will also be able to account for human reactions to potential robot actions. The efficacy of the proposed robot navigation system will be demonstrated in a real-world robotic system navigating among crowds.

Voir la description complète du projet
Superviseur du corps professoral :

Mo Chen

Étudiant :

Partenaire :

Ma Robot

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

Simon Fraser University

Programme :

Accelerate

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