Projets novateurs réalisés

Evaluating the Association of Intermediate Social Determinants of Health, Dementia Modifiable Risk Factors, and Cognitive Health for On-Reserve First Nations Peoples

The incidence of dementia, a clinical syndrome marked by progressive cognitive decline, is rising more steadily among Indigenous populations in Canada, mainly due to modifiable risk factors, such as diabetes and physical inactivity. Previous research has found that cultural and social connection and access to healthcare impact the incidence of many of the modifiable risk factors of dementia among the general populations and global Indigenous peoples. However, little research has investigated the association between these factors, the modifiable risk factors of dementia, and cognitive health among Indigenous peoples. Our study investigates the relationship between connection to culture, social support, and access to healthcare, the modifiable risk factors of dementia, and cognitive health among on-reserve First Nations peoples in Canada. Results will inform future community programming, research to develop interventions and public policy.

Establishing the Molecular Weight and the Length of Grafted Chains of PDMS Brushes Using the Ellipsometry Method

The field of research exploring slippery covalently attached liquid surfaces (SCALS), formed with Polydimethylsiloxane (PDMS) brushes, is fairly new and is proving pivotal in creating economically feasible and non-toxic solutions to resist fouling and prevent ice adhesion. These solutions will contribute to a more sustainable future by lowering the energy expenditure required for optimal efficiency of systems such as solar panels, wind turbines and aircraft wings.

The research aims to develop a simple method to establish the molecular weight and length of grafted chains, through performing a series of in-situ ellipsometry measurements of PDMS brushes in different solvents. A series of values and swelling ratios will be compiled and compared with current polymer theory to characterize the molecular weight and length of the grafted chains of the PDMS brushes. The proposed methodology could prove to be faster, more accessible and potentially just as accurate as current methods, including AFM force measurements and neutron reflectometry. If it is found that using this expeditious process to understand the brushes’ properties is possible and accurate, designs can be created with a high degree of assurance and knowledge about how the SCALS will behave.

Integrated organic opto-bioelectronics sensors

We are now in Polytechnique Montreal studying organic electrochemical transistors (OECT), which can be used to detect the analyte ion concentration in the liquid environment. The nature of an OECT is to convert ion concentration signal to electron signal. In this short-term cooperation, we aim to integrate OECT with an organic light-emitting diode (OLED), so that the obtained electrical signal by OECT can be further converted to photon signal. This renders it possible to convert ion signal directly to photon signal. Since both OECT and OLED are flexible, printable and wearable, so, this project may pave the way to bioactive, flexible and printable organic light emission sensors.

Temporal and spatially consistent inpainting with deep diffusion models

Most current brain imaging software is designed to work with images that have a consistent anatomy. However, this can be a problem when there are changes in the brain, like the appearance or disappearance of lesions, between two scans taken at different times. While we could develop complex new software for these situations, many researchers prefer to use existing, well-known tools, especially for studies over time. One suggested solution is to use a technique called image inpainting. In image inpainting, we fill in certain parts of an image based on a special pattern, making these parts look like they naturally belong there. This is really useful in brain scans, for example, when we need to add in images of lesions from multiple sclerosis (MS) in a way that looks real and fits with the rest of the brain image. Current inpainting methods usually practice on specific patterns, which means they might not work well on new or different types of patterns. Plus, these methods often struggle with handling lesions of various sizes and locations because they’re used to working with the same types of patterns, which limits how well they can work on different or new ones.

Building Mindset and Partnerships for Innovation in Canada: Business Strategy Internships with the Cansbridge Fellowship

This project enables interns to enable Market Innovation in Canada, related to their field of study or industry of interest. This will contribute significantly to the Cansbridge Fellowship’s mission of empowering entrepreneurially-minded students and promoting innovation in Canada. Under the guidance of the academic supervisor, the intern will focus on identifying innovative organizations for potential strategic partnerships with Canada. The intern’s multidisciplinary market research project will explore diverse technological and business opportunities, with a primary goal of aligning these opportunities with Canadian policy objectives and commercial needs. The academic supervisor will provide valuable insights into strategy and strategic partnerships, while the Cansbridge Fellowship, as a key partner organization, will offer mentorship and access to an extensive professional network. This collaborative program aims not only to equip interns with a wealth of knowledge but also to advance the partner organization’s mission of fostering collaboration and attracting forward-thinking Canadian youth. The outcomes of the market research will be made accessible to all interested stakeholders, ensuring that the research contributes to Canada’s broader innovation goals and strategic partnerships.

Archiving Groups and Athletes – Dylan Froh

Provide some background on the partner organization and their challenges or opportunities. How will this project help the partner organization address those challenges? Feel free to provide links to articles, reports or other useful information.

SkillShark Software is a SaaS model company leading the industry in making youth athlete evaluations easy. Current sport organizations do evaluations on pen and paper and spend countless hours re-entering the data onto a spreadsheet and are even then unable to provide report cards to athletes and parents. SkillShark has signed contracts with the largest youth sport orgs in the world (USSSA) as well as MLB
This project involves data life cycle. There is information which our customers (sport orgs and sport academies) want to remove from their primary view for multiple reasons. E.g. The athlete could be no longer attending their program but may return some day in which case they will want to retain historical data.

Optimal Coverage and Path Planning of Indoor Service Robots

The proposed project will study some essential tasks regarding motion planning of autonomous indoor service robots, focusing particularly on reliable coverage-planning of arbitrary and irregular-shaped indoor regions. The tools to be used in devising solutions for these problems include geometric and graph theoretical optimal path planning algorithms, various sensor data fusion techniques, and artificial intelligence and machine learning approaches. The goal is to produce methodologies and algorithms as solutions to these robot motion planning problems and to apply these solutions to provide reliable autonomous motion of Avidbots robots cleaning semi-structured indoor areas, with precise on-line monitoring, maximal area and quality of the cleaning, guaranteed collision avoidance, without requiring frequent calibration and fine-tuning.

Everly Product Iteration and Customer Retention

With this project, we aim to understand better what we can do to improve our product and customer experience to drive higher customer loyalty.

Phase 1 of this project will be to survey existing and churned customers to understand what they like, what they dislike, and what they would improve about our product. We will use tools such as Iterate (Consumer Insights Manager), and Hotjar (Behavior analytics platform) to collect customer feedback.
Phase 2 of this project will be to improve our product and website experience based on customer feedback.
Phase 3 of this project will be to test our product with existing clients and see if their feedback has improved based on product innovation. This phase will require sending samples to the consumer’s home and getting new feedback through iterate.

R&D Software Developer

The purpose of this project is to leverage Open AI fine-tuned models to enhance the speed in which consulting firms can respond to government issued RFPs. The benefit to the partner organization is enhanced speed and ability to match requirements with consultants.

CAN intrusion dataset for IDS development and digital twin simulation

In-vehicle networks of modern automobiles, particularly Controller Area Networks (CAN), are vulnerable to cyberattacks which can cause dangerous accidents. There are many CAN intrusion detection systems (IDS) that use different techniques and features. While there are several CAN datasets available from real vehicles and CAN testbeds, we identify a lack of datasets containing signals decoded from raw CAN messages, which hinders the development and evaluation of signal-based CAN IDS and prevents their comparison with other types of CAN IDS. We aim to address this gap by using open-source CAN databases to create a decoded signal dataset from raw CAN data and identify the physical values represented by the signals. Such a dataset can be used to create digital twin simulations that allow the evaluation of CAN IDS in a realistic and safe test environment and the generation of advanced attack scenarios that are lacking in current datasets. This collaborative project shall facilitate the sharing of knowledge, expertise, and insights into industry trends and best practices, as well as resources such as specialised tools and facilities, between the participating institutions. It will also enable participating researchers to expand their networks, leading to further opportunities and contributions to the area of cybersecurity.

Virtual Reality Design of a Mineral Processing Plant

This project is a collaboration between Queen’s University and BBA Engineering Consultants. With a shortage of mining and mineral processing engineers across the country, BBA is looking for way to attract more students to study mining engineering and for ways to expose their EITs from other engineering disciplines to topics in mining and mineral processing. This project will address these challenges by expanding the functionality of a Queen’s University developed Virtual Reality Concentrator that can be used as:
1. An innovative education tool at Queen’s University that will help attract high school and first year engineering students to the field of mining and mineral processing engineers, and
2. An internal training tool to give EITs at BBA exposure to mineral processing operating environments, particularly if there engineering degrees was in an other area (chemical engineering, mechanical engineering, civil engineering, etc.)

Mobile PO and Requisition Approval

Purchase Orders and Requisitions must all flow through an approval process based on an individual’s Delegation of Authority Guideline Grade (DOAG). When an approval is needed a user must be logged into the internal network, then logged into the ERP System (JD Edwards) and then search for the PO or Requisition and approve it. The goal of this project is to implement a solution that will improve efficiency by allowing individuals to use a mobile app to approve the PO or Requisition from anywhere.