Digital twin technology creates a digital replica of a physical object, such as a human, device, system, or process that mirrors the actual process with full knowledge of its historical performance. It has the advantage of enabling agility and convergence of understanding to support more effective decision-making and resource allocation optimization. Aleo Canada (noted as […]

These days, there is growing concern about the security of confidential data in organizations. There is no doubt that organizations with high-security measures will witness cyberattacks. Therefore, the question is how we can prepare our infrastructure and cybersecurity team to deal with these challenges. The incidents response playbook is a comprehensive plan which has been […]

Carbon, nitrogen, phosphorus and micropollutants are primary environmental stressors that pollute lakes, drinking water wells, and streams. They originate from human activities and come through point and non-point sources. In the case of point sources, wastewater treatment plants (WWTPs) must remove these stressors before discharge into water bodies. Driven by population increase and climate change, […]

Physical inactivity is associated with impaired removal of sugar from the blood after a meal, or insulin-resistance and a reduced muscle mass and fitness. While exercise is well-established to prevent these impairments, it may not be feasible in some clinical conditions. Therefore, passive interventions that mimick the stressors and elicit the benefits of exercise may […]

This work will examine a novel “smart” insole that allows for the quantification of specialized running metrics and will compare the outputs with the gold-standard measure of metabolic work. The insoles work by collecting pressure data from many sensors embedded in the insole, and sending this to an phone app. We are comparing the insoles […]

When Indigenous rights and leadership are prioritized, Natural Climate Solutions (NCS) like forest carbon management present an opportunity to advance reconciliation while combatting climate change and biodiversity loss. Wahkohtowin Development GP Inc. is taking steps to drive NCS in the Missinaibi Forest toward Indigenous-led climate action and social-ecological benefits for its owner First Nations (the […]

KnowMeQ Inc, a future of work online skills assessment is working with the University of Guelph to establish a candidate recommender tool which reduces bias. This is the first phase of deliverables of the relationship, wherein the groups are building towards an ethical AI algorithm and an Adaptability Quotient (AQ) composite measure.

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 […]

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 […]

Wild boars (Sus scrofa) are a highly invasive species which causes destructive damages to property and crops and poses a major threat to the Canadian pork industry because wild boars are also reservoirs for infectious diseases, including African swine virus (ASF). Current control and management of the wild boar populations have been ineffective because these […]

Fertility improvement is important in both human being and livestock industry. Increasing the oocyte competence is one of the most critical measures for fertility improvement. miRNAs are small non-coding RNAs which can regulate the estrogen production in the ovarian follicles which in turn affecting the oocyte development and competence. However, its underlying mechanism remains unknown. […]

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 […]