Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
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825
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8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

The Labour Market and Economic Impacts of Mental Health in Huron and Perth Counties

The goal of the project is to contribute to knowledge generation about mental health and addiction in rural Ontario by exploring the impacts of COVID-19 on the supply (employees) and demand (employers) of the labour market.
In partnership with Gateway Rural Health this project will examine Huron and Perth Counties as case studies to explore The Labour Market and Economic Impacts of Mental Health on rural areas since the beginning of Covid-19. This project has three objectives:
1) To identify existing information and resources about both supply (employees) and demand (employees) related to rural labour markets. Particular attention will be given to information from rural Australia, Western Europe, and the United States.
2) To investigate local labour market experiences from across Perth-Huron (survey/interviews).
3) To develop recommendations for relevant organizations related to market experiences, labour decisions, and impact of disruption.
Outcomes from this project will support rural communities to develop effective local policies and planning strategies to respond to the coronavirus pandemic and future disruptive events.

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Faculty Supervisor:

Leith Deacon

Student:

Partner:

Gateway Centre of Excellence in Rural Health

Discipline:

Sociology

Sector:

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

University:

University of Guelph

Program:

Accelerate

Hypothesis transfer in medical image analysis

Recent years have seen a wealth of clinical evidence accumulate in favor of the radiomics hypothesis, wherein standard-issue oncological medical images, such as CTs, PET-CTs and MRIs, exhibit reliable fingerprints of cancer tumor genetic makeup, enabling predictions of patient prognosis, treatment resistance and side effects to be made directly from an analysis of imaging data. However, these techniques require a large number of detailed hand-labeled data and annotations and so far have relied on hand-engineered features, limiting their scope and practical impact. This project aims at leveraging labels obtained from different datasets using novel domain adaptation techniques.
In vision applications, Hypothesis Transfer Learning (HTL) has emerged as a learning strategy to adapt the knowledge learned from one dataset (source domain) to a query dataset (target domain) and has shown superior performance to more conventional domain adaptation methods [1]. HTL has only been experimented with covariate shift (domain shift) and assumes similar class distributions between source and target domains. However, class distribution shifts and feature distribution shifts between datasets are common phenomena in medical imaging. With this incentive, an experimental study on the effectiveness of HTL in the medical domain and how it contrasts with other domain adaptation applications will be conducted.

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Faculty Supervisor:

Thomas Fevens

Student:

Partner:

Imagia

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Business-Oriented User Persona Construction and Preference Prediction: A Big Data-Based Machine Learning Approach

In this project, a group of scholars in computer science and business proposes using state-of-the-art machine learning methods for secondary-data-based persona construction and preference prediction. Specifically, the researchers will use recent data dimension reduction methods to process the raw data, use new machine learning models to achieve better learning results, and use self-supervised technology and unsupervised clustering technology to achieve efficiency in model training and learning.

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Faculty Supervisor:

Yimin Yang;Will Zhao

Student:

Partner:

PTPA Media Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Lakehead University

Program:

Accelerate

Efficacy of Harm Reduction Approaches to Hoarding in Social Housing

Hoarding involves keeping so many objects that the home becomes unsafe or unhealthy. Due to fire risks and other issues, hoarding can also be unsafe for neighbours – risks that housing providers must manage. A common strategy in social housing settings is to evict the tenant or forcibly clean out the unit, traumatic practices that can leave tenants at risk of homelessness. Lookout Housing and Health Society is partnering with UBC researchers to document the effectiveness of their harm reduction program to address health and safety issues in hoarded units. The key question is: Does the harm reduction approach achieve health and safety goals and support tenant wellness? We will use fire and building inspection reports, staff members’ reports, and tenants’ self-report measures to fill an important knowledge gap about interventions for hoarding and to help Lookout justify permanent funding for this program and inspire practice change among other housing providers.

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Faculty Supervisor:

Sheila Woody;Christiana Bratiotis

Student:

Partner:

Lookout Housing and Health Society

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

The University of British Columbia

Program:

Accelerate

Cable Simulation Methods Using Nonlinear Finite Elements

Cable systems play an important role in many large scale simulation applications. Examples include marine systems, mining machinery, and cranes. The high fidelity and efficient modelling and simulation of these systems can enhance the applications and usability dynamic modelling environments. In this project we particularly target to develop models and efficient algorithms based on nonlinear finite element representation of the cables in largescale multibody simulation models. We will investigate core modeling and implementation aspects that are directly related to practical applications. The partner organization, CMLabs will greatly benefit from this project. The proposed work is of direct relevance to their current work, can have applications in many projects, and will also open up possibilities to broaden the applications of CMLabs’ software platform Vortex.

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Faculty Supervisor:

Jozsef Kovecses

Student:

Partner:

CMLabs

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Using AI to Increase Diversity in the Talent Pool

Canada is having a youth unemployment crisis that has only worsened post-COVID. At the same time, an untapped pool of young, diverse talent exists to fill entry-level positions. However, difficulties arise when trying to match youth with employers. In particular, youth have indicated that job postings can be unfamiliar or intimidating and ask for unrealistic experience or credentials, which can deter them from applying. This project aims to help solve this problem by testing whether an AI tool that helps employers identify areas of the job posting that can become more youth-inclusive while also providing suggested changes can create change by increasing the diversity of hiring in entry level positions. This project will help CivicAction in their mandate to help solve the youth unemployment crisis.

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Faculty Supervisor:

Elizabeth Dhuey

Student:

Partner:

CivicAction Leadership Foundation

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Advancing Controlled Environment Agriculture (CEA) Through 3D Printing Construction

A new process to create greenhouse glazing using 3D Printing is prototyped and tested. Using the principle of layer height fusion of plastic, new glazing will be created to provide shading and diffused light. The 3D Printed glazing will also be changed through the 3D Printer to change the amount of shading and diffused light, a benefit in hot climates.

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Faculty Supervisor:

Rupp Carriveau

Student:

Partner:

I-INC Foundation for Business Development

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Windsor

Program:

Accelerate

Non-contact blood oxygenation measurement in human subjects using advanced multispectral imaging techniques

A low oxygen level can be life-threatening if not identified early. Many lung diseases, including the COVID-19 virus, can lead to oxygen deficiency. Currently, only a contact biomedical device is capable of measuring oxygen levels in the human body. This makes the measurement limited to people who can wear the device. Our goal is to design, develop, and test a system that can measure blood oxygenation in the human body remotely, which can then be implemented in various environments for monitoring health. To achieve this, we will use a special camera, similar to thermal cameras, capable of detecting the blood oxygen levels without touching the person.

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Faculty Supervisor:

Mamadou Diop

Student:

Partner:

Spectral Devices Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of Western Ontario

Program:

Accelerate

Temporary Migrant Farmworkers in Essex County: Building Community Inclusion in a Post-COVID-19 Context

Temporary migrant farm workers make essential contributions to our national food supplies as evidenced during COVID-19. Their exclusion from rights to labour mobility, family unity and the absence of systemic supports, however, undermines workers’ wellbeing and belonging, and the inclusions to which migrant workers are entitled. There is less attention to how communities support their access to service and enhance their inclusion and wellbeing. The project will examine how community-based initiatives advanced during COVID-19 through the Windsor Essex Immigration Partnership Council supports the inclusion of migrant workers. The project will employ a qualitative community-based research methodology, and conduct interviews with community stakeholders and temporary migrant farm workers to identify workers’ needs, how workers live in, make use of, and identify the barriers to inclusion they experience in Windsor-Essex. The project will benefit community efforts to identify migrant workers needs, gaps in service and recommendations that include migrant workers experiences.

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Faculty Supervisor:

Glynis George

Student:

Partner:

Workforce WindsorEssex/Windsor Essex Immigration Partnership Counsil

Discipline:

Sociology

Sector:

Information and cultural industries

University:

University of Windsor

Program:

Accelerate

Identifier son profil financier et ses tendances en matière de décisions financières, vers une formation à distance favorisant le bien-être financier

Ce projet propose la création d’un questionnaire qui permettra de fournir une rétroaction par rapport au profil d’habitudes financières des répondants. Considérant les impacts des finances personnelles sur la vie quotidienne et le bien-être individuel, un outil qui pourrait aiguiller les gens quant à leurs tendances et au contexte dans lequel ils prennent des décisions plus éclairées en matière de finance pourrait favoriser leur bien-être et leur satisfaction de vie. Il s’agirait pour un syndic autorisé en insolvabilité d’un outil novateur qui pourrait mener à des interventions et services se démarquant de l’offre existant présentement en matière de conseil financier. Le questionnaire pourrait également servir comme indicateur justifiant une consultation préventive, car trop souvent, les gens vont chercher des conseils en lien avec leurs finances seulement lorsque leur situation est désespérée, laissant peu d’options autres que la faillite.

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Faculty Supervisor:

France Lafleur

Student:

Partner:

Groupe Leblanc Syndic Inc

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

Université du Québec à Trois-Rivières

Program:

Accelerate

A data-driven approach for network-wide modelling and control of urban network

This research aims to model a large-scale urban network, consisted of thousands of short links and traffic signals, using a limited set of data collected from a combination of fixed and mobile traffic sensors. The required data for this study will be provided by the AMA Eco-drive trajectory data and Edmonton citywide Dynameq model. A general framework for describing a large traffic network will be developed using machine learning/artificial intelligence tools. Based on the developed traffic model, a congestion pricing scheme to optimize tolling prices and zones will be developed. Finally, a scenario analysis of the different tolling and congestion levels will be conducted. This study enhances computational efficiency and realism aspects of traffic modelling by describing large traffic networks using a limited set of links and vehicle trajectories.

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Faculty Supervisor:

Lina Kattan

Student:

Partner:

Alberta Motor Association

Discipline:

Engineering

Sector:

Administrative and support, waste management and remediation services; Finance and Insurance; Other services (except public administration)

University:

University of Calgary

Program:

Elevate

Cooperative ramp control in mixed traffic environment – Year two

This research will develop a novel freeway control approach for the era of co-existence of connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs). Fully connected and autonomous vehicles can navigate roads without a human driver and connect and interact with other vehicles, roadside infrastructure, and their environment. It is anticipated that the technology will be made available to consumers in the very near future. However, generic market adaption and phasing out of the current vehicle fleet is likely to take years or even decades. Meanwhile, CAVs, with various levels of automation, should co-exist and interact with HDVs. The current congestion control measures might become ineffective since they are mainly formulated based on humans’ driving behaviors and models. Recent research focused on developing control solutions for a fully automated driving environment. In this research, a multi-level freeway control approach will be developed for a mixed traffic environment that leverages the automation and connectivity features of CAVs to optimize their path while regulating the freeway corridor inflow traffic to optimize the system performance. The achieved insights would be valuable to prepare transportation experts at the City of Calgary, other municipalities, and the transportation industry for the era of co-existence of CAVs and HDVs to face the potential challenges in the future intelligent transportation systems.

View Full Project Description
Faculty Supervisor:

Lina Kattan

Student:

Partner:

City of Calgary

Discipline:

Engineering

Sector:

Public administration; Utilities

University:

University of Calgary

Program:

Elevate

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