In 5G and beyond networks, softwarization of network functions, as well as disaggregation of software and hardware, are the recent moves pushing Radio Access Networks (RAN) to be ultra-agile, reconfigurable and flexible. This flexibility comes along with complexity that goes beyond traditional algorithms’ capabilities to optimize the RAN. In addition, in future RANs, multiple-players interacting […]

Elephant and rhino population in southern African countries has been drastically decreasing due to poaching. This project aims to use tethered aerostats (blimps) equipped with robust cameras for constant detection and monitoring of these animals to protect them from external threats. The chosen location for implementation in Nyika National Park in northern Zambia, mainly due […]

The proposed research aims to provide a comprehensive explanation of the residents’ perceptions of roles and responsibilities of their local municipalities involved in community recycling in North America. It also will investigate the effect of the modern digital communication solution to the residents’ recycling engagement and education of proper household waste sorting, and examine whether […]

While taking foreign language tests, people may record responses with different background noises. The contaminated audios can lead to unusual results in speech recognition and scoring by the scoring systems. Pearson would like to develop a more robust system for the automated speech recognition machine to work with clean and noisy records. Audio files are […]

One assumption that is commonly used in machine learning is that samples are statistically independent. In effect, each sample of data doesn’t tell you anything about any other sample in the dataset. This is not true for all types of data; there are some types of datasets where relationships between samples can be modeled as […]

Road safety affects everyone, and companies are looking for ways to identify the risk factors for their fleet drivers, and to reduce the chance of accidents. This project will build on Geotab’s existing methods for assessing driving risks, and develop new techniques to better identify risky drivers and risky behaviours. The project will focus on […]

Companies spend a large amount of money and time on mobile application development which requires knowledge of various native platform programming languages and the different characteristics of these platforms. However, demands for mobile applications are increasing and are becoming difficult to follow for the IT department. One solution seems to be no-code development platforms that […]

Road safety affects everyone, not just Geotab customers. With several years of driving and environmental data collected from over 2 million connected vehicles, there is a great opportunity to leverage big data and machine learning to establish a minor collision detection system. On top of driving data and environmental data, it also contains machine diagnostic […]

One of ten Canadians will experience trauma at least once in their lives and will develop post-traumatic stress disorder (PTSD). Many people cannot access PTSD care because of the high cost, long-waiting time, stigma and other barriers etc. Amygdala (deep brain) is important to traumatic emotions and memories. One way to access these memories is […]

Over the past few years, the abilities and performances of deep-learning natural language processing (NLP) have evolved dramatically. A main reason for those improvements is the scaling of the number of parameters in models to tens or hundreds of billions. However, it also becomes impractical to deploy those models in production as the computation cost […]

Machine learning has great potential in detecting cognitive, mental and functional health disorders from speech, as acoustic properties of speech and corresponding patterns in language are modified by a variety of health-related effects. Specifically, neural language models, have recently demonstrated impressive abilities in tasks involving linguistic knowledge. Their success in language understanding and classification tasks […]

Working in partnership, interdisciplinary professionals and the Registered Practical Nurses (RPNs) Association of Ontario (WeRPN) aim to understand what contributes to and detracts from personal, professional and institutional resiliency for RPNs during COVID-19. This is a rare opportunity to learn from front-line workers directly during historical social periods, such as COVID-19, and even less often […]