Glioblastoma is the most common type of adult brain cancer. Glioblastoma tumors are very aggressive because these cells can rapidly invade deep into healthy tissue, which makes them particularly difficult to attack with current treatment options including surgery, radiotherapy, and chemotherapy.
The goal of the project is to assess the viability of current synthetic data generation systems. If the generated synthetic data is accurate enough without providing sensitive details it can be used to train machine learning models without needing to share sensitive information. The particular application of this project is to computer logs which can contain sensitive information about the computer systems themselves or the individuals using them.
When responding to any cybersecurity threat, it is important that a security analyst is able to respond to it as quickly as possible so that they can reduce or eliminate any damage that the threat may cause. However, the high amount of data that must be analyzed when investigating a security event can impact the speed of an investigation. By automating routine incident response processes and orchestrating fundamental investigative approaches, much of the burden of the investigation can be lifted from the analyst.
Modern organizations collect and process mass amounts of personal data. This data has the power to individually identify an individual and may be linked to some sensitive information about them. Because of this risk, policies and legislation have been implemented to ensure that personal data is handled in an organized and secure manner. As the scope of personal data collection advances, it is difficult for organizations to ensure compliance with these frameworks. The goal of this project is to investigate the current proposed structures for metadata management of personal information.
Plenty Canada has partnered with the University of Guelph to launch a biocultural knowledge and mapping project to begin restoring Indigenous knowledge, visibility, and character to the Greenbelt as an important Indigenous cultural landscape in Ontario. Our proposed work builds upon the success of a pilot project that we launched with the Canadian Commission for United Nations Educational, Scientific, and Cultural Organization (CCUNESCO) to document and safeguard important Indigenous heritage resources along the Niagara Escarpment.
In recent years we’ve seen evidence of youth activism related to important social causes. Although much has been written about Millennials and Generation Z, little is known about the generation of young people who are currently at the precipice of adolescence – Generation Alpha (born 2010 and later). This generation will inherit the post-COVID society and will be called upon to meet significant challenges including climate change, economic inequality, Indigenous equity, LGBTQ+ equity, human rights and balancing technological advances with ethical considerations.
This study will investigate the ability of an injectable vaccine to reduce illness and death due to pneumonia in lambs born and raised in a feedlot setting. If the vaccine is effective, it will improve the welfare of the lambs on the farm where the study is conducted, reduce antibiotic usage and costs, and improve profitability for the company that owns the farm. If proven to be effective the study will help to justify the use of this vaccine beyond this population (i.e. other Alberta and Canadian farms) and help to support the use of respiratory vaccines for the livestock industry in general.
This project will result in the generation of mathematical models that will predict the quality and sustainability of protein-based ingredients that are commonly used in dog diets. With the projected growth of human and pet populations, and increases in food production necessary to meet growing demands, providing Canadian pet food companies (such as our industry partner, Champion Petfoods) with the ability to rapidly identify ideal protein-based ingredients to select for dog diets based on environmental, financial, and biological sustainability is a top priority.
Understanding scenes representing real world environments is a challenging problem at the intersection of Computer Vision research and Deep Learning and a necessary pre-requisite for Embodied AI. Embodied AI is an emerging field within Machine Learning that focuses on the challenges that need to be addressed for successful deployment of edge devices such as drones and robots. In this setting estimating the semantics of an environment plays an essential role in addition to how it can be efficiently navigated to solve a variety of tasks that can involve other agents as well.
In Canada, about 1 in every 3 Canadians has a medical condition, or takes medication, that would be important
to know about in an emergency situation. That’s why, since 1961, Medic Alert Foundation Canada (MAFCA) has
helped to protect over 1 million Canadians by helping first responders and healthcare providers get access to
health information quickly. However, though the work of MAFCA is undoubtedly important, we do not yet
understand the full impact or value of this work.