This project aims to enhance the work with technical drawings in manufacturing is done by using advanced computer techniques to automatically identify and read text within these drawings. This means turning detailed plans and sketches into digital data quickly and accurately, without manual input. For the partner organization, this innovation promises to greatly speed up […]

Total recordable injury rates (TRIRs) have declined significantly over the past thirty years, yet serious injuries and fatalities (SIFs) have not. With the Alberta Mine Safety Association (AMSA) and member companies, we will summarize and evaluate the leading indicators for SIFs, use subject matter experts and integrative AIML to develop and assess SIF predictive measures, […]

Zika virus is an important mosquito-transmitted human pathogen endemic to tropical and subtropical parts of the world and was responsible for the pandemic in South America in 2016. In pregnant women, the virus can cross the placenta and infect the brain of developing fetus leading to congenital abnormalities and life-long sequelae in newborn babies. Currently […]

FirstHx wishes to validate the French component of its’ in-person patient facing digital medical interview solution, which could be offered to clinicians and practitioners as a means of empowering patients, reducing time of clinical documentation, improve efficiency while increasing quality of care. Researchers from the UMoncton have the expertise and resources to validate our AI […]

In response to the growing concerns about landfill gas emissions, particularly methane (CH4) and carbon dioxide (CO2), which significantly contribute to global climate change, the proposed research project aims to address this issue through the development of bio-based landfill covers. While many landfills currently have implemented gas collection systems for processes like flaring or energy […]

La pollution liée aux déversements d’hydrocarbures pose de grands problèmes environnementaux et de santé humaine. Les méthodes conventionnelles utilisent des méthodes chimiques et/ou physiques (via excavation) pour nettoyer les sites impactés. Ces méthodes sont souvent très coûteuses et peuvent endommager durablement les écosystèmes incluant les milieux humides. Il est donc important de développer des méthodes […]

By 2050 the global population is projected to reach 9.8 billion, and food supply must sustainably scale to keep up with the population’s growing nutritional demand. Insects are rich in protein and require substantially less environmental resources compared to the standard protein sources of today, making them a promising food of the future. To optimize […]

mRNA vaccine technologies came to the forefront of public health during the recent global pandemic and this technology also has great potential for other therapeutic approaches. These vaccine platforms require that the mRNA be encapsulated by fat molecules into structures called “lipid nanoparticles”, and the specific chemical formulations of the mRNA and fats determine the […]

Cyanobacteria, or blue-green algal bloom are becoming increasingly common. These blooms, when they reach significant magnitudes are referred to as Harmful Algal Blooms due to release of toxins such as microcystins which pose a threat to both humans and terrestrial fauna. These extensive blooms induce anoxic conditions within the lakes, resulting in impact son aquaculture […]

This project makes it possible for Canadian researchers to share secure and traceable datasets between large computing systems in Canada. These traceable datasets can be used to further reproducible science by allowing everyone in the scientific community to know where the dataset used for experiments is from and that it has not been altered. Traceable […]

Knowledge of corrosion products and radioactivity transport in nuclear reactors is necessary to minimize radiation dose to station workers during maintenance activities. Modelling radioactivity transport can also be used predictively to assess how changes to station chemistry affect radiation fields. The objective of this project is to develop a new code in Python, leveraging the […]

Total::Insight™ is a geospatial and time distribution Decision Support System (DSS) that includes a correlator capable of consuming many sporadic time domain signals and converting them into feature rich tracks. The problem here is how to create an AI/ML embedding that is domain relevant from the tracks.The project objective is to develop, refine and industrialize […]