Kanonhkwa’tsheranákere, Where the Medicines Are: Creating an Indigenous biocultural atlas and ethnobotanical field guide grounded in decolonial methodologies

This landmark project was built by Dr. Jessica Dolan with leadership at the Indigenous organization Plenty Canada, and the Conservation Through Reconciliation Partnership team at University of Guelph. Working closely in collaboration with Haudenosaunee and Anishinaabeg educators and culture-bearers, the team is combining plant biology surveys in the Greenbelt region of Southern Ontario, with historical […]

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Assay development for point-of-care COVID-19 antibody detection

A key requirement for returning to societal and economic normality is the evaluation and surveillanceof SARS-CoV-2 infection and immunity. The proposed technologies described herein, enable a safe and effectivediagnostic test that can quickly provide an easily interpreted result for SARS-CoV-2 immunity, all without complicated equipment, expensive reagents, or high-level biosafety containment facilities. Such a system […]

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Applying Natural Language Processing to Explore the Development of Automated Scoring and Feedback Models for Multi-Speaker Science Discussions

Many components of education, including those to support teacher and student learning, are now online and fully digital. But to make productive use of these data sources, the field needs to have a better understanding of what teachers and students do and how they respond to online assessments designed to build and measure complex constructs. […]

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Optimizing Security Orchestration, Automation, and Response for Incident response

This research project aims to develop cost-effective solutions to aid organizations in defending against cyber-attacks. With limited resources, security operations centers are struggling to defend against the vast volume of cyber-attacks. The project proposes reducing the work effort and amount of labor needed to perform tasks such as manual inspection and incident responses. By enhancing […]

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Command and Control Automation and Reporting

A red team is a group of cybersecurity experts who are tasked with simulating real-world attacks on an organization’s systems and networks. They do this by using a variety of tools and techniques to identify vulnerabilities and weaknesses in an organization’s defenses. This project implements command-and-control infrastructure, which is critical for the red team or […]

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Application of Machine Learning and Data Science for classification of BDD (Behavior Driven Development) Test Development and Execution

Continuous integration (CI) and continuous delivery (CD) are practices that help software development teams deliver code changes more often and with fewer issues. To ensure that code changes are working as they should, developers use Behavior Driven Development (BDD) tests. But running all these tests against every code change can be time-consuming and costly. This […]

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Cloud Hosting Cost Optimization

The proposed research project will focus on analyzing and optimizing the cloud infrastructure used by SOTI to manage mobile devices globally. The intern will analyze the current cloud architecture and hosting costs, identify areas for improvement, and propose and implement optimizations to reduce system requirements and minimize costs. The expected benefit to SOTI is a […]

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Simulation of Remote Control on a Mobile Device

Mobile devices have become a crucial tool for businesses, and SOTI MobiControl is a leading mobile device management solution that provides remote control capabilities. However, to ensure proper product functionality and scalability of SOTI MobiControl, the company is looking to research the simulation of remote controlling a mobile device for automation testing. By testing the […]

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Smart Battery Research

The proposed project seeks to develop a Machine Learning-based software solution that accurately measures the capacity, State of Health (SoH), State of Charge (SoC), and cycle count of non-smart batteries utilized in mobile fleets. The project’s primary objective is to bridge the gap between smart and non-smart batteries by monitoring non-smart battery capacity and other […]

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Emerging Event Classification System

The goal is to develop a system that can rapidly detect and report emerging disease outbreaks worldwide by analyzing clusters of news articles using Large Language Models. The objective is to create an efficient and effective way of identifying “disease events” that can alert public health officials to take prompt action.

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