Novel Ovulation Research-Recruitment Methods for an App (NORMA) Study

One purpose of the proposed research project is to contribute to the My Normative (MyN) app development by increasing the number of users on the app and maintaining long-term app usage. The second purpose is to verify the accuracy of the app’s menstrual cycle prediction in female persons of varying cycles less than or greater than 28-days, with or without ovulation. The project and MyN will initially target female persons in their reproductive years (18-35 years) with the bigger picture of representing all female persons of diverse backgrounds.

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.

Facilitating Canadian NGOs’ participation in Knowledge Mobilization: A Key to Enhancing the Societal Contribution of Academic Research

Annually, governments worldwide invest a lot of money from public budgets on research projects to solve societal challenges. Still, there is a huge gap between research-produced knowledge in universities and policies and practices in society. One challenge to increasing societal impact is aligning research projects with the needs and challenges of local communities. This project investigates the potential role of NGOs in informing research projects about the local challenges by using an online web-based platform.

Scaling of IoT Simulation for Verification and Testing

Simulation is a critically important enabler for the scalable verification and testing of Internet-of-Things (IoT) systems. There has been considerable research in recent years on developing IoT simulators. The existing research nevertheless does not adequately address the optimization of simulators for the competing objectives that one typically has to contend with, e.g., in terms of costs and resources.

Developing Efficient Machine Learning Models for Price Bidding

Curate Mobile operates a demand site platform (DSP), which is an advertising platform responsible for bidding in real time ad placements from various publishers. This process is a blind auction, happening over 50,000 times a second, and during this bidding process we have less then 100ms to determine which of our clients should bid for this ad placement, how much it might be worth to them, and what price we believe we can win this auction for.

Point-of-Purchase Barriers Impacting Canadian Consumers’ Decision to Purchase Sustainably Packaged Food

Nearly three quarters of Canadian consumers support banning single-use plastic food packaging in favour of more sustainable packaging options according (Walker et al., 2021). Barriers at the point-of-purchase, including a lack of availability, limit the purchase of sustainably packaged food in Canada. Due to the COVID-19 pandemic, Canadian consumers are facing additional barriers to purchasing sustainably packaged food products, including increased price sensitivity and safety fears (Scaraboto et al., 2020; Walker et al., 2021).

Testing, Validation and QA of Computer Vision Models Data Sets in a Novel SAAS Environment

The project is focused on advancing the capabilities in testing and validating computer vision models used in the field of artificial intelligence ( The project will focus o n researching current best practices in testing and evaluation of complex computer vision solutions used in AI.

Testing, Validation and QA of Computer Vision Models & Data Sets in a Novel SAAS Environment (2)

Test and expand the capabilities of the Zetane software for application in complex artificial intelligence industrial (AI) projects with the objective of augmenting the users’ ability to gain new insights in model performance and gain more trust on how the data influences the AI models to arrive at the AI’s recommendations.

Public deployment and prospective testing of a remote intake, triage, individualized ED wait time and site-specific clinical direction system

The goal of this study is to pilot the remote intake, triage, site-specific clinical direction and individualized wait time system we have developed as a local pilot project, for a short duration of time, which we believe will lead to both improved patient satisfaction and increased ED efficiency. Testing and validation goals include evaluating feasibility, efficacy, safety, adverse events, and improvements to the system and study design prior to performing a full-scale research project.

Dynamic actor tracking for Augmented Reality-based filmmaking guidance

Augmented Reality can help in simplifying the filmmaking process by intelligently suggesting shot composition angles for amateur filmmakers to take better shots. In partnership with Rubber Match Productions, researchers will investigate how actors within an AR filmmaking environment can be dynamically tracked to provide real-time guidance to the filmmaker for shot composition. The project will utilize latest advances in artificial intelligence and computer vision to track actors in real-time through videos.