Projets novateurs réalisés

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

31 914 projets complétés

3006
AB
5256
C.-B.
878
MB
703
NL
913
SK
9488
ON
9949
QC
98
PE
629
NB
1215
NS

Projets par catégorie

Methane Assisted Catalytic Upgrading of Extra Heavy Crudes under Moderate Conditions

Vacuum residue (VR) is the heaviest part of crude oil accounting for a large proportion in modern refineries, while its utilization routes are generally of low efficiency and high energy intensity, and thus economically and environmentally unfavorable. Similarly, bitumen recovered from Steam-assisted gravity drainage (SAGD) process experiences high viscosity and density as well as high content of impurities and thus diluent is often needed for its transportation with additional cost and environmental concerns. Both the diluent containing naphtha fraction recovered SAGD crude and VR are considered as extra heavy crude which are required to be further processed before end use. The goal of the current project is to develop a cost-effective upgrading technology to greatly enhance the quality of extra heavy crudes for the potential productions of clean light fuel and high-value added petrochemicals. This will be done using a technology based on the directly catalytic incorporation of natural gas into the heavy oil at mild temperatures and pressures, leading to enhanced productivity and reduced production cost and thus improved profitability. Furthermore, the incorporation of natural gas into the transportable oil product will minimize greenhouse gas emission from upgrading process, making it more environmentally friendly.

Voir la description complète du projet
Superviseur du corps professoral :

Hua Song

Étudiant :

Partenaire :

Kara Technologies Inc

Discipline :

Engineering

Secteur :

Health and Related Sciences & Technology; Manufacturing; Professional, scientific and technical services

Université :

University of Calgary

Programme :

Accelerate

Two-Step super-resolution method to enhance orbital imagery of celestial bodies using ground truth from rovers and drones.

Exploration of other planetary bodies poses multiple challenges. Notably, how can we obtain the most information about a planet or a moon while avoiding risky and costly crewed or robotic missions to the surface? Satellite imagery can partly solve this problematic by providing a relatively cheap alternative to cover massive areas of a planet. Sounds great, what’s the catch? Well, these satellite images have a limited resolution and therefore, limited information can be extracted from them. That being said, recent advances in artificial intelligence could offer us a way to enhance the resolution of satellite imagery. This projects consequently aims to test various artificial intelligence algorithms to help enhance the resolution of Martian orbital imagery. In term, this method could help the Canadian Space Agency and private partners such as Mission Control Space Services select region of particular interest for further investigation.

Voir la description complète du projet
Superviseur du corps professoral :

Myriam Lemelin

Étudiant :

Partenaire :

Mission Control

Discipline :

Earth science

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Université de Sherbrooke

Programme :

Accelerate

Feasibility of a pressure retarded osmosis process for Quebec electricity generation

Osmotic power or salinity gradient energy is one type of the renewable energies which is produced by mixing fresh water with salt water. This new environmental friendly energy based on the advantages such as carbon dioxide free and generating power continuously seems to be a good option in which to invest as it will be highly beneficial to Quebec. This project looks to develop expertise related to osmotic power. A pressure retarded osmosis (PRO) power test unit will be designed and installed in Quebec. This will be the first osmotic power system in North America. The project will consist of evaluation and selection of sites for potential pilot testing, determination of pretreatment and cleaning requirements for the membranes, and subsequent design of the test unit. This will provide hands on experience related to the design and operation of a PRO power system in Quebec and enable the evaluation of the viability of this technology for future development for the interns.

Voir la description complète du projet
Superviseur du corps professoral :

Catherine Mulligan

Étudiant :

Partenaire :

Hydro-Quebec (Shawinigan, QC);H2O Innovation;Concordia University

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Utilities

Université :

Concordia University

Programme :

Accelerate

Traceability Systems of the Next Generation: Towards Transparency, Agility and Sustainability in Quebec’s Seafood Supply Chain (SSC)

This project brings together university researchers, a Collegial Center for Technology Transfer – CCTT (Merinov), two young companies working in the sector of IT management tools (EOS Nation and reelyActive) and a Non-For-Profit Organization (Cercle-i) in order to address important research and development challenges facing the Seafood Supply Chain of the Gaspésie and Magdalen Islands region. The research team will study the possibility of adopting emerging technologies (including Blockchain, Internet of Things and Analytics) to improve the traceability of seafood, thus increasing the transparency of information, supply chain security and agility. Ultimately, this project may also have a positive impact on the sound management of the natural resources of the seafood industry in Quebec. To face this complex, multidimensional and multidisciplinary issues, the objective of this project is to develop a simulation platform integrating business aspects (supply chain management and data management) and technical aspects (integration of different emerging technologies) in order to be able to assess the potential gains and risks of an innovative traceability system.

Voir la description complète du projet
Superviseur du corps professoral :

Luis Antonio de Santa-Eulalia;Elaine Mosconi

Étudiant :

Partenaire :

EOS Nation;9266-5777 Québec Inc;Merinov (Gaspé, QC);Cercle-i

Discipline :

Business

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Université de Sherbrooke

Programme :

Accelerate

Machine Learning Based Classification of Atomization from a Rotating Bell Nozzle

Spray painting in the automotive manufacturing industry is a tough technical challenge. Due to a poor paint job, approximately 25% of cars coming off the assembly line must be reworked or scrapped. Previous research has shown that the droplet size distribution of the paint applied to the vehicle is important for the final coating finish and colour. Paint droplets are formed in an atomization process, and changes to this process can cause considerable differences in the coating finish and quality. In this project, experiments using an automotive paint spray robot will be done to collect atomization data of the paint as it leaves the nozzle. A machine learning based model will be developed to detect when the atomization changes, which can be used to flag defects on the assembly line. This project will further validate Mazlite’s technology in optimizing the automotive paint spray process and accelerate the commercialization of its product line.

Voir la description complète du projet
Superviseur du corps professoral :

Zheng Liu

Étudiant :

Partenaire :

Mazlite Inc.

Discipline :

Engineering

Secteur :

Manufacturing

Université :

The University of British Columbia - Okanagan

Programme :

Accelerate

Developing a Data Science Tool for Open Government Datasets

In an effort to build public trust, the Government of Canada has made a commitment to move toward an Open Government, where government data will be easily accessible and shared broadly. For the public to benefit from Open Government sources, they will need tools that will allow them to analyze and interpret the data accurately.
Dacture is an alpha-released platform where users can find openly accessible datasets, compute statistical analyses, and build engaging visualizations without needing any expertise in coding or statistics. As a byproduct of giving people the power to conduct data science themselves accurately and reliably, we hope that our platform will contribute to the public’s statistical literacy and trust in data from government sources

Voir la description complète du projet
Superviseur du corps professoral :

Alison Chasteen

Étudiant :

Partenaire :

Dacture

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Development of AI-assisted tools for enhanced clinical lymphoma PET/CT imaging

There are over 225,000 new cancer cases in Canada every year. Positron emission tomography/computed tomography (PET/CT) is the primary imaging modality for a range of cancer types. Various studies have established that determining size/volume, shape, and texture features of tumors from PET/CT images can help identify patients at high-risk of cancer relapse, or for whom standard treatments might fail. Nevertheless, the process of image-reading in clinics remains largely qualitative, since manual tumor delineation by radiologists can significantly reduce patient throughput and increase scan wait times. We aim to develop artificial intelligence based tools to assist radiologists in the detection/delineation of tumors in PET/CT images. In collaboration with Microsoft, we will help deploy such tools in the cloud, making them available to practicing physicians and researchers at BC Cancer. The expected benefits of this project include faster diagnosis, improved treatment outcomes, and reduced cancer-related healthcare costs in Canada.

Voir la description complète du projet
Superviseur du corps professoral :

Arman Rahmim

Étudiant :

Partenaire :

Microsoft Canada Development Centre

Discipline :

Life Sciences

Secteur :

Artificial Intelligence; Health and Related Sciences & Technology; Technology

Université :

The University of British Columbia

Programme :

Accelerate

Élaboration d’un protocole d’échantillonnage à long terme des bois de Laval

Les milieux naturels urbains sont d’importants acteurs à la préservation de la biodiversité en ville et à
l’augmentation de la qualité de vie des résidents. Par les nombreux services qu’ils procurent à la population, ils
contribuent à réduire de nombreux coûts du secteur publique, dont ceux des soins de santé par exemple.
Toutefois, l’environnement urbain ajoute des stress supplémentaires que subissent les milieux naturels qui s’y
trouvent et il devient alors important d’assurer un suivi de ces milieux afin d’en assurer la conservation. C’est dans
cette optique que s’inscrit ce projet visant à développer un guide de meilleures techniques d’échantillonnage des
forêts urbaines. Un protocole adapté aux contraintes budgétaires de CANOPÉE sera mis sur pied pour que
l’organisme soit en mesure d’implanter un suivi de qualité des bois sous sa gestion.

Voir la description complète du projet
Superviseur du corps professoral :

Alain Paquette

Étudiant :

Partenaire :

CANOPÉE

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

Université du Québec à Montréal

Programme :

Accelerate

Improving the Properties of Biopolymers through Chemical Functionalization; Adding Value to an Industrial Side Product for Cascades

This project, in partnership with Cascades, will develop novel functional materials prepared from a biopolymer generated at Cascades. The development of these novel materials and composites will help to fine-tune the properties of the final paper sheet produced at Cascades and access high performance materials for many of their core business activities. The new polymer additives will also be crucial for the valorization of industrial side-products and will lead to a new generation of biopolymers for the paper industry. Overall, the proposed research will be highly beneficial to various areas of application through development of innovative advanced biomaterials and will have broad and significant impact for Cascades and the scientific community through the advancement of current knowledge. This research will significantly influence the commercial direction of the paper industry and will have an even broader impact on the general population through increased environmental consideration.

Voir la description complète du projet
Superviseur du corps professoral :

Simon Rondeau-Gagné

Étudiant :

Partenaire :

Cascades Services et Achats

Discipline :

Physics

Secteur :

Advanced Manufacturing; Forestry; Natural Resources

Université :

University of Windsor

Programme :

Accelerate

Understanding the high-temperature behavior of alloys designed for additive manufacturing

The proposed project aims to determine the mechanical behavior of new commercial iron-based alloys, M789 and Corrax stainless steels, designed for additive manufacturing. The additively manufactured steel samples, known to possess an excellent combination of tensile strength and corrosion resistance, will be supplied by voestalpine Additive Manufacturing Center. After extensive high-temperature experiments (using Gleeble and SHPB machines) to acquire data, a custom-built data analysis application (Simu-Mat 1.0) will be employed to determine the recommended empirical, semi-empirical, and machine learning constitutive models. Once the suitable models have been established, these will be incorporated in finite element analysis using ANSYS/ABAQUS to accurately simulate the alloys’ mechanical response at various temperatures and strain rates. Therefore, based on the combined experimental and simulation work, it is expected that material issues associated with in-service AM components can be avoided, additional industry applications can be identified, and the component certification process will be more achievable.

Voir la description complète du projet
Superviseur du corps professoral :

Clodualdo Aranas Jr.

Étudiant :

Partenaire :

Voestalpine Additive Manufacturing Centre Ltd.

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of New Brunswick

Programme :

Accelerate

Nuclear Decommissioning Management using Building Information Modeling and Augmented Reality

Integrating augmented reality (AR) technology with decommissioning workflows will open new avenues to remotely visualize and interact with Building Information Models (BIMs), enabling safe and cost-effective decommissioning processes of nuclear power plant (NPP) structures. Research is proposed here to advance new NPP decommissioning workflows through novel sensing, computing, and artificial intelligence (AI) methods within the framework of BIMs, AR, and data fusion. BIM stores digital information of the current state of assets and structures, as well as physical systems, and services such as maintenance operations and safety inspections. AR technology can overlay digital information on BIM into the physical environments. In this project, the intern will focus on enabling automated digitization of assets and the development of three-dimensional, semantically enriched BIMs and explore how engineers augment and interact with BIMs using AR to streamline and improve existing NPP decommissioning workflows.

Voir la description complète du projet
Superviseur du corps professoral :

Chul Min Yeum;Carl Haas

Étudiant :

Partenaire :

MacDonald, Dettwiler and Associates Inc (Brampton, ON)

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Waterloo

Programme :

Accelerate

Clinical utility evaluation of a NGS based assay for the detection of genetic modifiers in families with reduced penetrance or uncertain copy number variants

There is increasing evidence that multiple genetic variants within a patient can compound their effects, resulting in a more severe clinical phenotype in comparison with the clinical manifestations in individuals with single genetic variation. In this study, we aim to examine the clinical utility of a massively parallel sequencing technique to identify clinically relevant secondary variants in patients with neurodevelopmental disorders by examining over 700 neurodevelopment disorder-associated genes in the patient and his/her parent with the primary genetic variation.

Voir la description complète du projet
Superviseur du corps professoral :

Elizabeth McCready

Étudiant :

Partenaire :

Sysmex Canada Inc

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

McMaster University

Programme :

Accelerate

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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.