Projets novateurs réalisés

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

29 670 projets achevés

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Projets par catégorie

DEI Intern via Mitacs/Queens Program

The internship will be to develop a hiring framework for Liberty Mutual Canada, grounded in academic research and best practices to mitigate implicit bias.

Voir la description complète du projet
Superviseur du corps professoral :

Sandy Staples

Étudiant :

Partenaire :

Liberty Mutual Canada

Discipline :

Business

Secteur :

Finance and Insurance

Université :

Queen's University

Programme :

Business Strategy Internship

L2M MITACS – Improving the Storage Stability of Research Grade Proteins using Super- Hydrophilic Sponges

The proposed research project seeks to explore the application of foam-like inserts to improve the shelf life of commonly used proteins. Many commercial proteins are used in a variety of applications such as food production, pharmaceuticals, and scientific research. These proteins must be stored at sub-zero temperatures as they are prone to degradation at higher temperatures. Protein degradation during storage and transportation results in significant losses to the industries where these proteins are used. Our solution is to use foam-like inserts to stabilize these commercially-relevant proteins. We propose to develop a variety of prototypes and to test them on proteins used in academic research labs. The benefits to the partner organization would be in kickstarting the successful launch of a potentially profitable technology.

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Superviseur du corps professoral :

Marya Ahmed

Étudiant :

Partenaire :

Springboard Atlantic Inc.

Discipline :

Life Sciences

Secteur :

Life Sciences (not health); Nanotechnology; Biotechnology

Université :

University of Prince Edward Island

Programme :

Accelerate

Modelling wind farm induction using high/low fidelity tools

Today’s wind energy prediction procedures ignore the flow deceleration, also known as blockage, caused by the wind farm on the
approaching wind, resulting in a power overprediction bias that pervades the entire farm. Numerical large eddy simulations (LES)
of wind farms immersed in atmospheric boundary layers (ABL) will be used to study the phenomenon and derive a fastengineering
blockage model, capable of estimating blockage effects as a function of wind farm properties, ABL thermal stability
and complex terrain morphology. Such model will be coupled with a reduced order turbine wake model to predict the entire wind
farm flow. Besides, accurately capturing gravity waves using LES is not straightforward, as gravity waves physics involves spatial
scales much greater than the size of the wind farm or of the turbulence scales. Consequently, the project also aims at defining
standards and producing benchmarks for such computationally intense simulations.

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Superviseur du corps professoral :

Joshua Brinkerhoff

Étudiant :

Partenaire :

Delft University of Technology

Discipline :

Engineering

Secteur :

Education

Université :

The University of British Columbia - Okanagan

Programme :

Globalink Research Award

Creating AR computer vision applications for children’s toys

The objective of this project is to explore the uses of Augmented Reality (AR), a technology that superimposes computer-generated animations, on a mobile user’s view of the real world, in the context of children’s gaming applications. These applications will allow children to experience a game as being directly tied to reality. Specifically, using for example an electronic tablet such as the iPad, children will interact with real world toys through the addition of virtual layers presenting various digital contents such as images or animations. It is therefore required to create a computer vision application that can detect in real-time 3D objects in a reliable way, from any point of view and at different scales. Once detected, the system will estimate the position of the camera with respect to the object and then will be able to place virtual content attached to the detected object.

Voir la description complète du projet
Superviseur du corps professoral :

Robert Laganiere

Étudiant :

Partenaire :

HabitatSeven Inc

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Ottawa

Programme :

Accelerate

Sound insulation performance of an innovative mass timber floor system

Acoustic comfort in all types of buildings is essential to our daily life and work. Mass timber buildings provide us
the solution to construct green buildings with much less carbon footprints compared with concrete and steel
buildings. This project will investigate the sound insulation performance of an innovative mass timber floor system
through experimental testing. The outcomes from this research will provide data to assist designers both
sustainable and quiet wood buildings that everyone can enjoy living and working in.

Voir la description complète du projet
Superviseur du corps professoral :

Jianhui Zhou

Étudiant :

Partenaire :

Intelligent City, Inc

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Northern British Columbia

Programme :

Accelerate

Slope Movement Prediction of Open-pit Mine Using Machine Learning and Field Data

In BC open pit porphyry mines, pit wall deformation rate has been closely monitored to evaluate the stability of open pits and determine proper operational response. This research aims to improve our understanding towards the deformation behaviours of pit walls considering both the slope characteristics and external influence factors. The project will collect a large dataset of pit wall displacements measured by robotic total stations and slope stability radars in Gibraltar mine as well as targeted pit walls’ geological conditions (e.g. rock type/strength) and operation parameters (e.g. blasting parameters, mining equipment/rate, and groundwater). By incorporating a machine learning method with a slope deformation function, a prediction model will be developed to predict the displacement of open pit walls subjected to external factors, and mostly importantly, identify their deformation stage for proper mine operation responses.

Voir la description complète du projet
Superviseur du corps professoral :

Wenbo Zheng

Étudiant :

Partenaire :

Taseko | Gibraltar Mines Ltd

Discipline :

Engineering

Secteur :

Mining

Université :

University of Northern British Columbia

Programme :

Accelerate

Testing, modeling, and simulation of a clean technology for converting forest residues to syngas and renewable natural gas

This proposed project will support our ongoing efforts in developing a novel two-stage fluidized bed gasifier for converting low-cost biomass residues to renewable natural gas in British Columbia to help the BC industry to meet the 2030 decarbonization target. Specifically, we will test and validate a new design of gasification reactor for producing low-tar syngas, verify a bauxite residue (f.k.a., red mud) derived catalyst for the removal of tar from gasification syngas to yield clean syngas, and evaluate and improve the commercial methanation catalyst for converting clean syngas to biomethane. The clean syngas can be directly used for displacing natural gas for industrial lime kiln operations, and the biomethane can be blended into the existing natural gas lines to lower the natural gas carbon content. Over the past 4 years, we have commissioned a pilot plant at UBC. In the proposed project we will carry out extensive tests to validate the new technology by generate performance data and develop a model to assist the scale-up, design and demonstration/commercialization of this new renewable energy technology using abundantly available forest residues in BC.

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Superviseur du corps professoral :

Xiaotao Tony Bi;Naoko Ellis;Kevin Smith

Étudiant :

Partenaire :

FortisBC Energy Inc

Discipline :

Earth science

Secteur :

Utilities

Université :

The University of British Columbia

Programme :

Accelerate

Acceleration of improvement in health and production of mink through genomics and machine learning

The project will examine of population genomics, application of genomic selection, and identification of genes underlying economically important traits which are vital steps for the development of selection program. Consequently, this will have an impact on the economic viability of mink producers due to targeted genomic breeding strategies and the use of biomarker-assisted selection. Such a selection over a period will significantly lower the cost of pelt production and hence increase efficiency. The selection for disease resistance (such as Aleutian Diseases) will also create the mink with better resilience. The project will generate results that can be directly implemented in the breeding programs of North American mink industry. These tools will enable the mink breeders to more effectively incorporate feed efficiency, health and reproduction traits as breeding objectives in their programs. Farmers will save money, while the international competitiveness of North America’s mink industry will increase. The environmental footprint of the mink industry will also be reduced because lower manure waste will be produced by more feed efficient or higher prolific animals.

Voir la description complète du projet
Superviseur du corps professoral :

Younes Miar

Étudiant :

Partenaire :

Canada Mink Breeders Association

Discipline :

Life Sciences

Secteur :

Agriculture

Université :

Dalhousie University

Programme :

Accelerate

An Automated Manhole Extraction Algorithm from 3D Point Cloud Utilizing a New LiDAR-based Mobile Mapping System

Traditional surveying procedures are labor and cost intensive. Mapping features like manholes require traffic disturbance, add risk to the field crew personal and the community members. The proposed project utilize a newly developed unique LiDAR-based mapping system. The developed 3D mapping system has a substantial cost reduction compared to the commercially available, which also tend to be bulky, expensive and out of the reach of many end-users. The newly developed system generate three-dimensional (3D) maps which are essential in traditional and new applications, such as smart cities, autonomous vehicles and augmented reality. This project proposes and validate an automated manhole extraction algorithm that allow mapping of manholes using the new LiDAR-system and quantify the advantages of this research compared to the traditional surveying procedures.

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Superviseur du corps professoral :

Ahmed Shaker Abdelrahman

Étudiant :

Partenaire :

IBW Surveyors Ltd.

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

Evaluation of Online Urban Futures Survey for Metro Vancouver

This project will expand upon the underlying research conducted with the 2012 Urban Futures Survey of Greater Vancouver. The intern will evaluate a survey that was the third similar survey approximately 20 years apart to inform planning policies in the Metro Vancouver region. The last survey, in 2012, used an online consultation platform instead of the previous face-to-face and/or telephone methods. This technology utilized was the PlaceSpeak public participation GIS, which authenticated respondents online to their physical address. The resulted survey produced a large amount of data that needs to be analyzed and interpreted. The intern will draw conclusions and possibly find new groups that might find the gathered data useful. Also, the intern will examine the survey methodology and in particular the sample size and confidence levels required for contemporary online survey techniques. At the end of the internship, a bulletin is to be produced and publicized, summarizing the findings of the survey and also generate an OpEd essay and other materials for publication in local newspapers and professional journals.

Voir la description complète du projet
Superviseur du corps professoral :

Meg Holden

Étudiant :

Partenaire :

PlaceSpeak Inc

Discipline :

Sociology

Secteur :

Information and cultural industries

Université :

Simon Fraser University

Programme :

Accelerate

Understanding the Bighorn Sheep Decline in Southern Interior BC: An Investigation of Grassland Health and Secwépemc Traditional Ecological Knowledge.

This project focuses on a herd of wild bighorn sheep on Kamloops Lake in the Secwépemc Territory of southern interior BC. The first goal of the project is to monitor lamb survival and assess habitat conditions for the Kamloops Lake herd over two years. The second goal of the project is to document Secwépemc Traditional Ecological Knowledge about the Kamloops Lake herd to strengthen our understanding of the herd’s history and ecology. The results of our study will help our partners to develop strategies on how to protect bighorn sheep and their habitat. To carry out the study, we will monitor the Kamloops Lake herd and determine the proportion of lambs that survive to the age at which they are independent from their mothers. We will also assess the health of the grasslands within the home range and identify impacts and ways to restore habitat.

Voir la description complète du projet
Superviseur du corps professoral :

Kara Lefevre

Étudiant :

Partenaire :

Wild Sheep Society of BC

Discipline :

Earth science

Secteur :

Agriculture

Université :

Thompson Rivers University

Programme :

Accelerate

Shaping AI-Driven Digital Transformation Strategy in HealthCare: The Case of Organ Donation and Transplant Digital Ecosystem Development

BI Expertise is developing a solution that leverages artificial intelligence technologies to improve organ donation. Due to the devolution of powers in Canada, organ donation is managed at the provincial level. In addition, information systems for organ donation are heterogenous between provinces. There is hence relatively little cooperation currently between provinces for interprovincial organ donation. The solution will open the way to providing donated organs in one province to potential recipients in different jurisdictions. But before this is possible, there are technical, legal, regulatory, cultural and ethical challenges that need to be addressed.
The current project will focus on the provinces of Quebec and Ontario and has the following objectives:
– Cartography the major stakeholders who would be involved in the development of an organ donation ecosystem between Quebec and Ontario, and map the regulatory framework(s) pertaining to the coordination of organ donation in and between the two provinces;
– Identify and describe the key regulatory, legal, ethical, and cultural challenges that can impede the development of the AI-based ecosystem for organ donation between Quebec and Ontario provinces;

Voir la description complète du projet
Superviseur du corps professoral :

Emmanuelle Vaast;Amir Taherizadeh

Étudiant :

Partenaire :

BI Expertise

Discipline :

Business

Secteur :

Professional, scientific and technical services

Université :

McGill University

Programme :

Business Strategy Internship

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