Innovative Projects Realized

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

31620 Completed Projects

2978
AB
5221
BC
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projects by Category

Bacillus amyloliquefaciens KA32 role in Plant growth promotion and early transcriptomic changes in tomato seedlings

Many soil microbes present around the plant roots, these microbes are termed as plant growth promoting rhizobacteria (PGPR). Bacillus amyloliquefaciens KA-32 is a novel strain of PGPR’s that promotes plant growth, improve yields in some tested crops. The mode of action of this strain is still unknown. One of the possible action might be by altering the gene expression in treated plants, the microbe is providing the benefits to plants. The main objectives of the current project will be 1: To optimize the concentration of microbial inoculum for tomato seedling growth promotion. 2: Evaluation of best mode of application of the formulation. 3: Evaluate the formulation on plant growth promotion in tomatoes under greenhouse conditions. 4: Study the effect of microbial formulation on gene expression profiles in response to the rhizobacteria by RNASeq.

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Faculty Supervisor:

Lord Abbey

Student:

Partner:

Karyotica Analytics

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Climate Policies to Accelerate Soil Carbon Capture and Farm Health

Climate change is affecting BC farmers, with associated impacts to food security, community economic development, business risk management programs, and trade and innovation. With some of the oldest farmers in Canada, BC’s farmers also experience some of the lowest incomes in Canada. The Province has an urgent need to encourage both new entrants and existing producers to transition to climate adaptive approaches that support their economic viability in the face of a range of changing conditions.
This project will determine if farmers that adopt agricultural practices that capture carbon in the soil experience better health and relationships than their conventional counterparts, and will identify how provincial and national policies can be more attentive to practices that support soil quality and farmer health overall.

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Faculty Supervisor:

John Volpe

Student:

Partner:

Terramera Inc

Discipline:

Earth science

Sector:

Agriculture; Manufacturing; Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Réorganisation du cerveau: récupération de la fonction visuelle suivant une déficience visuelle cérébrale

a déficience visuelle cérébrale (DVC) se caractérise par une perte des fonctions visuelles associée à un dommage au cerveau et non une atteinte aux yeux. Bien que la majorité des individus ne regagnent pas une vision normale, dans certains cas une amélioration peut être notée avec le temps en raison de la capacité du cerveau à se réorganiser. La perte visuelle peut s’accompagner du blindsight, un phénomène permettant de traiter l’information visuelle tout en n’ayant pas conscience de l’avoir vue. L’objectif général de ce projet de recherche consiste à évaluer les conséquences d’une DVC sur la réorganisation cérébrale d’une large cohorte d’individus comparée à des individus neurotypiques par des techniques d’analyses de données d’imagerie par résonance magnétique. Comprendre le contexte neurologique précis, pouvant expliquer pourquoi cette réorganisation est parfois bénéfique permettrait de conceptualiser des outils (i.e., neurostimulation) pour guider ces changements adaptatifs et potentialiser la récupération de la fonction visuelle.

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Faculty Supervisor:

Franco Leporé

Student:

Partner:

Université Catholique de Louvain

Discipline:

Life Sciences

Sector:

Education

University:

Université de Montréal

Program:

Globalink Research Award

Hybrid Quantum-Classical Algorithms for Fuel Cell Optimization

Hydrogen fuel cells represent one of the most exciting technologies available for producing clean energy for onsite combined heat and power delivery, portable electronics, and electric vehicles. In the transportation sector specifically, several commercial vehicles powered by hydrogen have hit the market in the last several years, on top of a growing number of city buses and cargo trucks running on fuel cells. However, high cost due to the use of the precious metal platinum remains a barrier to their widespread adoption. In an effort to design materials that could replace this expensive platinum, we will investigate a combination of classical and quantum computing methods to model fuel cells at the atomic level. This modeling is an exciting application of quantum computers, which in theory can model the electronic structure of materials with much greater fidelity and efficiency than classical computers. In practice, quantum computers are still too small and noisy to simulate chemistry at meaningful scale.

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Faculty Supervisor:

Irina Paci

Student:

Partner:

Quantum Algorithms Institute;OTI Lumionics Inc.

Discipline:

Physics

Sector:

Education; Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Application of spatial regression models in general insurance

Desjardins General Insurance proposes different types of P&C (property and casualty) coverage to its clients. Properly rating an insurance premium to cover for P&C losses requires complex modelling that uses variables that are both at the individual and at the spatial level. In general, including a spatial component in the modelling is challenging. At Desjardins, the current approach generally produces good results, but they have shown inconsistencies over time. With a goal of constant improvement, we aim to question and revisit this approach, like it is regularly done with the various approaches in use at Desjardins. In particular, we aim to effectively include a spatial component in a way that ensures a smoothly varying rating over the territory (for similar individuals), the latter being a quality that the current approach lacks. While achieving this, we will make sure that the resulting approach is easy to implement on Desjardins’ platform. Our strategy to achieve those goals is to revisit the current model and explore different solutions, from robust estimation to highly flexible spatial models. Properly rating insurance premiums is beneficial for Desjardins as it positively affects its financial results.

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Faculty Supervisor:

Philippe Gagnon

Student:

Partner:

Desjardins Assurances Générales

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

Université de Montréal

Program:

Accelerate

An integrated study of CO2-based CSI process and CO2 saline aquifers geo-sequestration

CO2 geo-sequestration is an efficient approach to reduce CO2 emission and achieve zero carbon emission with minimum impact on economic growth and people’s wellbeing. This project focus on optimizing carbon utilization in heavy oil reservoirs and CO2 geo-sequestration in the underline saline aquaifer with three key objectives: optimizing CO2 injection in heavy oil reservoir to enhance oil recovery, understanding the behavior of injected CO2 interacting with formation brine and aquifer rock, and modeling the non-isothermal behavior during CO2 injection process. The findings from this study will provide solid foundations for further CCUS study.

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Faculty Supervisor:

Fanhua Bill Zeng

Student:

Partner:

Petroleum Technology Research Centre

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

University of Regina

Program:

Accelerate

Socially and physically based surf warning system to improve beach safety

Surf-related drowning fatalities represent a significant economic burden to the Province of Ontario but many public beaches in Ontario do not have lifeguard programs and there is also a lack of active monitoring of surf conditions to provide real-time warnings. Improving beach safety is complicated by the fact that rescues and drowning fatalities do not depend on the wave and current conditions alone, but also depend on the behavior of the beach user individually and as part of a group. The study uses a combination of wave and current measurement and modeling, beach user surveys and workshops to develop a dynamic surf hazard warning system for the Municipality of Kincardine in Bruce County, Ontario. Results of this research will lead to an adaptable and scalable approach to improved beach safety in the Great Lakes through real-time monitoring and direct and indirect changes in beach user activity.

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Faculty Supervisor:

Christopher Houser;Dana Menard

Student:

Partner:

Bruce County

Discipline:

Earth science

Sector:

Public administration

University:

University of Windsor

Program:

Accelerate

Implementing a Zinnia TV program for people with dementia in hospitals and long term care homes

This project work with stakeholders, residents, family members, and care staff, in an older adult hospital unit and a long-term care home to analyze use of smart TV catered for peoples with dementia (Zinnia TV). Zinnia TV is a TV program that TV program provides video experiences that offer joy and engagement for people with dementia (e.g., handwashing, eating, and holiday celebration). Research will be conducted over 2 years. We will include a diverse group with various sex and gender, age range, ethnic and racial backgrounds, etc. The sample will include
20 people with various types and stages of dementia, 20 family members, and 20 frontline interdisciplinary staff. This project intends to explore effects of assistive technologies and smart TV programs on mood, quality of life, and reduce responsive (aggressive) behaviours resulting from unmet needs in patients and residents with dementia The findings of this projectwill provide helpful insight into specific needs and preferences of LTC residents living with dementia. This project expands current knowledge about implementation science by adding a better understanding of userexperiences about technology adoption in complex care environments such as hospitals and long-term care.

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Faculty Supervisor:

Lillian Hung

Student:

Partner:

Vancouver General Hospital;Zinnia Technologies LLC

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

The University of British Columbia

Program:

Accelerate

Renewable Natural Gas Opportunities and Advancement

Anessa is developing software that assesses the feasibility of an anaerobic digestion facility at the earliest stages when trying to determine if a facility should be constructed. The challenge is that little information is fully known and there are a lot of factors that can affect the outcome to be positive or negative in the investment to construct and operate a facility. Some of these factors are based on the organic waste materials quantity and quality that are available, but some of it is also based on the legislative policies and incentives for clean energy. This research proposes 3 aspects that are vital to advance our research into this domain. First, to improve and refine our algorithms for predicting the quantity and quality of biogas that can be attained from waste via anaerobic digestion. Second, to complete market research into the various policies and incentives in place worldwide and the effects of these policies for anaerobic digestion uptake in constructing facilities. Third, to identify and implement a rigorous and automated quality assurance engineering practice on our software solution to ensure correctness.

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Faculty Supervisor:

David Bremner

Student:

Partner:

Anessa

Discipline:

Computer science

Sector:

Information and Communications Technology; Clean Technology

University:

University of New Brunswick

Program:

Accelerate

Development of a subject-centered social media – Phase 2

Developing subject-based social media requires proper interaction with the users by learning and analyzing their profile and dynamically incorporating their opinion. In this project, a crowd-based profiling of users with respect to their peers will be developed and confidence factor calculated based on the collective opinion of the crowd will be assigned to the individuals’ opinion. There is a prototype system already developed as a proof of idea. The intern will enhance the prototype by adding new functions and modules to it.

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Faculty Supervisor:

Behrouz Far

Student:

Partner:

Crowd Act Inc

Discipline:

Computer science

Sector:

Technology; Information and Communications Technology

University:

University of Calgary

Program:

Accelerate

Hydrogen Gas – Carbon Microsphere and Graphene Oxide Adsorption/Desorption Analysis for solid state hydrogen storage

Climate Change (CC) mitigation and reduction requires a strong effort to develop and put into use clean energy options that significantly reduce anthropogenic CO2 emissions. In Canada, the transportation sector accounts for 25% of all emissions. Hydrogen fueled vehicles is one option that has a great potential to reduce Canadian and global CO2 fuel emissions. This research project investigates methods to analyse required traits of storage materials, including surface area and pore volume, to develop methods and materials to increase hydrogen gas storage capacity to ensure the successful transition for decarbonization in the transportation sector.

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Faculty Supervisor:

Onita Basu

Student:

Partner:

Hydrogen in Motion

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

Carleton University

Program:

Accelerate

Development of a clinical decision support system to augment multi-disciplinary tumor board decision-making

We propose to develop and evaluate a clinical decision support systems (CDSS) for the Princess Margaret Cancer Centre (PMCC) lung metastases multidisciplinary tumor board (MDT) to improve the consistency and quality of MDT decision-making. We will develop and train a machine learning-based (ML) classifier, using historical decisions data from lung cancer MDTs to model the decision-making process. Clinical parameters and lesion characteristics parameterized from CT imaging will be used as inputs to the ML-based classifier. The ML classifier will be one of several components in the CDSS Application, called Janus, including auto-segmentation of normal anatomy and lesions and contour parametrization tools. The proposed CDSS application will impact health care delivery at the partner institution in several ways including 1) improving lung metastases MDT efficiency, 2) providing quality assurance to ensure consistent, evidence-based decision making and 3) enable knowledge sharing by deploying the CDSS in other partner-institutions without similar MDTs.

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Faculty Supervisor:

Dionne Aleman

Student:

Partner:

Princess Margaret Cancer Centre

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

University of Toronto

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.