Distributed Learning over Edge Computing to Support Covid-19 Modelling

The proposed research will allow any device to contribute its computing capabilities to the general distributed computer. Combined, these devices become a super-computer — providing resources for researchers and scientists in their quest for discovery. This research focuses on the finely calibrated aspects of scheduling slices of computing on this computing network. The intern will […]

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Machine learning and the COVID Black Box: Safe monitoring of COVID-19 ICU beds, assessment centres, and surgeries

The project aims to optimize healthcare provider and patient safety and monitor PPE use, to optimize resource utilization during the COVID-19 pandemic. Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these […]

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Interpretable dimensionality reduction of multivariate time series data using LSTM based autoencoders

Data collection over time is a common practice in many large organizations- including financial institutions and health care providers- often with the goal of using this data to predict future challenges and opportunities. While this data may contain valuable information, it is often unstructured, coming from different sources and recorded at different times. This lack […]

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Next Generation Canadian Satellite-based Positioning Technology

Present navigation applications rely mostly on the integration of Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). However, GNSS signals are prone to interruption due to various disturbances, including signal interference and jamming. On the other hand, Low Earth Orbit (LEO) satellite constellations from several providers are becoming rapidly accessible. LEO-based communication systems […]

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The COVID-19 infodemic : Telling Facts from Fakes

The Internet has become a major source of information, with a single piece shared across different platforms potentially reaching millions in a short period of time. As Covid-19 spreads across the world, the misinformation and fake news around it also spread. For each fact about Covid-19 made public, a large body of misinformation grows and […]

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AI for delivering product recommendation in retail consumer categories

E-commerce has evolved rapidly in recent decades resulted from globalization and international trade. The demand of online shopping is increasing every day, which has opened business opportunities to attract more costumers locally and globally. However, achieving satisfactory user experience in online shopping remains challenging compared to in-person walk-in shopping. Currently, customers have to input static […]

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Smart Data Fusion for COVID-19 Patients

In response to the COVID-19 pandemic, tech industry is racing to develop apps as well as wearable devices to help people to trace contacts, to self-assess, and to self-monitor the development of COVID-19 cases. However, these apps and devices work independently of each other, which leave it to users to connect pieces of information to […]

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Hunt for the Super-Spreaders — A Complex Networks Approach

Contagious diseases, such as SARS and COVID-19, bring a large amount of damage to human’s life and world economy. Pathogens spread among individuals through the contact network. It is observed that most social networks show a power-law degree distribution, implying that hubs exist in these networks. Finding underlying super-spreaders (hubs) and isolating or immunizing them […]

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SOTI SNAP Widget SDK Front-end and User Interface Toolkit

SOTI has developed a software product called SOTI SNAP that allows anyone to create an app with no programming or technical knowledge. SOTI SNAP allows users to create apps by dragging and dropping widgets onto a canvas and connecting them together to create an app. With SOTI SNAP apps can be created in minutes and […]

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Intelligent Card Detection for Automatic Documentation & e-Commerce

The goal of this project is to develop a Card Detection for Automatic Documentation solution that will be able to detect all features of a collectible card from a scanned image. Given a large number of design variations in cards, simple OCR cannot provide all available information. We aim to deliver an AI-driven solution deploying […]

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