Increasing demand for more reliable electric power requires advanced monitoring systems that prevent equipment failure and outages. The existing technologies used for monitoring the voltage and the electric field in the vicinity of the high voltage devices are bulky and expensive. On the other hand, maintenance of the monitoring devices requires specific safety precautions. In […]

Solar-driven dry-reforming is an ideal solution for recycling greenhouse gasses (GHGs) while producing valuable chemical feedstock. These anthropogenic emissions of the GHGs are the leading cause of global climate change. Furthermore, these emissions are related to the manufacture of fuels and carbon-based products. Solar fuels technology addresses both of these issues. Solistra is developing photocatalyst […]

Cannabis legalization creates a pressing need to improve existing screening methods. Currently, the two devices approved by the office other the attorney general of Canada (i.e. the Drager 5000 and SoToxa) have not been embraced by the vast majority of police forces who deemed both options unaffordable, difficult to use and inaccurate. The present project […]

There is a lack of “diversity” in Canada’s tech industry and this is what the research is based on. The lack of research considering racial diversity in the tech industry in Canada leaves a significant gap in understanding issues that would be critical in addressing such a lack of diversity. This research will explore how, […]

As a major contributor to Canadian industrial carbon emissions, miners are placing more emphasis on decarbonization efforts by developing greener strategies and sourcing cleaner energy for their mining operations. Despite some progress, decarbonization attempts by mining companies have been underwhelming mainly due to the financial challenges of renewable system implementations. This study aims to perceive […]

In the era of digitization, the success of an SME significantly depends on the active engagement with other actors (e.g., brand consumers, suppliers, influencers) in their business ecosystem. In this research project, we propose to develop an engagement model based on the business ecosystem network. These models will predict the customer engagement community association and […]

Schedulability analysis aims at determining whether task executions complete before their specified deadlines. It is an important activity in developing real-time systems. However, in practice, engineers have had difficulties applying existing techniques mainly because the working assumptions of existing methods are often not valid in their systems. Specifically, uncertainties in real-time systems and hybrid scheduling […]

Shape memory alloys are materials which, when cooled are easily stretched, but when heated, return to its previously “remembered” shape with a high force. This allows for a simple heat engine to be made, which can use hot and cold sources to create motion and do work. The amount of work that can be done […]

When utilizing and implementing ML for prediction using administrative health data, two key issues are ML algorithm evaluation and generalizability21. Current approaches evaluate model performance by quantifying how closely the prediction made by the model matches known health outcomes. Evaluation metrics include sensitivity, specificity, and positive predictive value, as well as measures such as the […]

In the last decade optimization is expanded in many applications from food production to sophisticated applications such as engine fuel efficiency. In the proposed package, it is tried to apply optimization techniques along with physics based analytical and semi-analytical methodologies to create a compelling framework which can help thermal-process based oil industry to reduce their […]

As Building Automation Systems (BAS) are becoming a standard in commercial buildings, and additional 3rd party applications can help buildings owners gain insights from their BAS, structured metadata management becomes the key to success. However, as converting traditional sensors naming convention to structured tagging systems is an expensive and time-consuming process, this project aims at […]

In AI safety, compliance ensures that a model adheres to operational specifications at runtime to avoid adverse events for the end user. This proposal looks at obtaining model compliance in two ways: (i) applying corrective measures to a non-compliant Machine Learning (ML) model and (ii) ensuring compliance throughout the model’s training process. We aim to […]