As a high-value crop, apples are intensively managed with much of this management being associated with yield estimates. Currently, estimates are done manually by experience farmers and by Scotian Gold experts. Unfortunately, this results in costly estimates that vary in their quality from farm to farm and between apple varieties. A system that can provide […]

Front-line clinicians have reported that different respiratory stiffness results in different COVID-19 patient conditions on ventilators. In this project, we test and improve NovaResp’s monitoring hardware and analyze the collected data for development of algorithms with focus on respiratory stiffness of patients with COVID-19. The resulting algorithms and monitoring device could lead to determine whether […]

Communities and regions throughout Canada have just been hit with a bomb that is a major threat multiplier: Covid 19. Across the country, rural municipalities that were already struggling economically are now struggling even more with how they should move forward, and support economic recovery and stabilization. This research project will focus on how to […]

This proposal seeks to identify the most promising lead candidate for a COVID-19 vaccine that could be rapidly and inexpensively scaled-up to meet Canada’s COVID-19 vaccine needs. In collaboration with a Canadian biotech company, Entos Pharmaceuticals, we will determine the safety and efficacy of several vaccine candidates to identify the most promising candidate to move […]

We are building a machine learning system to help clinical experts accurately label medical notes with diagnosis codes. This will make it faster and cheaper to train machine learning models to identify important codes, including those related to infectious diseases and COVID, in large amounts of medical notes.

This project will evaluate whether an innovative approach to looking at consciousness allows for the diagnosis and management of concussion. The device, cali-ed the Halifax Consciousness Scanner (HCS), reads the brain waves of a person while listening to a special sound recording, and uses this information to determine a score for their level of consciousness. […]

As the COVID-19 pandemic complete eradication will at least take 2-3 years, putting the country under complete lockdown is an impractical solution. Hence, Computing and Data Analytics research group at Saint Mary’s University (SMU-CDA) proposes a collaboration with Agyle Intelligence to develop a complete framework using Data Analytics and Machine Learning that can help citizen, […]

Micro-algae, which are being used to derive biofuels from, are typically grown in large volumes of water in systems which either expose the algae to, or protect it from, the natural environment. There are two key problems associated with large-scale commercial biofuel production: the identification of high yield and high lipid producing algal species, and […]

When blood-vessels in the brain are damaged, substances can leak from the blood into the brain. Such leakage can affect cognition and mental health, however there are currently no clinically-available tests for detecting such leakage. In this project we are developing a method for diagnosing blood-vessel leakage using MRI. We believe that this technology may […]

Aquaculture feed has historically relied on fish-based protein sources to satisfy nutritional requirements for optimal growth. While plant-based proteins are increasing throughout the aquaculture industry, the need for fish protein is still present to ensure the “natural fish” taste that consumers want. Black Soldier Fly Larvae (BSFL) have been proposed as a solution to this […]

The aim of this 2-year project is to do research to inform the development of, and fully test and develop a mobile application designed to improve the experience of (particularly at-risk) post-secondary (PSE) students in addressing COVID-19-related issues. Our key concern is that COVID-19 has not only disrupted important and significant developmental experiences that improve […]

This project deals with the development of new mathematical models and solution methods to optimize naval surface ship refit operations. The Naval Surface Ship Work Period Problem (NSWPP) is a highly complex resource-constrained project scheduling problem (RCPSP) with many work orders that are equivalent to small projects. Planning, scheduling, and executing NSWPPs are very challenging, […]