Application of time-frequency based techniques to assess Auditory Brainstem Responses in newborn hearing assessment

Automatic detection and classification of the Auditory Brainstem Responses (ABR) is used in newborn hearing screening. Improved detection algorithms will reduce test time, prevent infants with hearing loss from being missed while reducing the number of normal hearing babies referred to diagnostic testing. We have already improved the objectivity of ABR classification in neurological assessments by using Continuous Wavelet Transform (CWT) and Machine Learning (ML). In the proposed project, we seek to validate our findings further to improve the objectivity in the newborn hearing assessment.

Subsurface Mapping and 3D Reconstruction of Silurian Clinton-Medina Groups, Southwestern Ontario

The Silurian age Clinton-Medina Groups is a succession of sedimentary rocks found across Ontario, in outcrop and in the subsurface. The history of the stratigraphy is complex, and therefore confusion exists relating the stratigraphy regionally in the subsurface across Ontario. The Clinton-Medina Group formations are important for Ontario’s energy sector, providing petroleum resources from natural gas pools found in Eastern Lake Erie.

Multilingual Semantic Similarity of Unstructured Enterprise Content

To communicate with their end users, businesses regularly produce written documents such as letters, notices, statements, etc. in various languages. A set of rules are usually used to ensure that information in these documents is 'correct' and consistent across languages and communication channels. However, with the increasing volume and variety of information being sent out to clients, it becomes difficult to preserve the semantics of client messages across vocabulary and language variations.

Multilingual Semantic Search Engine using Multilingual Semantic Similarity

Multiple situations require cross-lingual searching: lawyers reviewing litigation documents; intelligence analysts data mining open source data; and patent attorneys investigating technical documents. To imitate cross-lingual search, people use online translation platforms to find the equivalent terms laboriously and then re-execute the query multiple times in various languages. The commercial search industry hasn’t seen much demand for crosslingual search. Search is always monolingual and very English-centric.

Technology for Assessing Neurocognitive Functioning; Validation of Mobile Cognitive Assessment Technology using fMRI

There is growing concern that COVID-19 has neuroinflammatory effects which can have acute or sustained impacts on cognition. Tablet-based games can be used to monitor cognition in medical settings but have not been validated as measures of brain function. The current project will administer a suite of tablet-based measures of cognition as images of the functioning brain are acquired using an MRI scanner.

Interfacial Engineering of High Energy Density and Safe Solid-State Li Metal Batteries for Electric Vehicle Applications - Year two

Lithium-ion batteries (LIBs) have become a key player in the growing need for electric vehicles (EVs). State-of-the-art LIBs, using liquid electrolytes, still have significant challenges in their safety, lifespan, and energy density. Accordingly, solid-state lithium metal batteries (SSLBs) have recently been attracting increasing research and industrial attention due to their ability to overcome intrinsic disadvantages of flammable liquid electrolytes used in current LIBs.

Machine-learning-based posture identification from dynamic seat sensors

Sitting for long periods of time has negative health effects that could be solved by changing posture throughout the day. The solution lies in the use of sit-stand desks, active seats, and automated reminders to change position. For this purpose, this project focuses on developing software that can intelligently determine a person’s posture using sensors located in a dynamic seat. Data will be collected from people using the Formid Dynamic Seat, which will then be used to develop and test machine learning algorithms.

Algorithmic and Interface Advances in Computer Algebra

Computer Algebra Systems (CAS), with their unique ability to analyze and solve mathematical problems, are gathering new communities of users, who challenge them with more and more complex tasks. It is necessary, therefore, that the core engines of CAS implement state-of-the-art algorithms. At the same time, CAS need to build new bridges to specialized software and to develop interfaces to emerging research areas.

Demand estimation in consumer-packaged goods market using BLP method

Leveraging the entirety of point of sale and loyalty data collected across a category, as well as additional socio-economic and other supporting data sources, apply statistical modelling to identify the own-price elasticity of demand and cross-price elasticity of demand at regular and promoted price points across Unilever’s portfolio within that category. Subsequently measuring the promotional cannibalization of Unilever’s temporary price reduction activities across the market to assess the promotional events with the highest return on investment and revenue optimization potential.

Pan-disability COVID-19 data leadership and coordination initiative

The Canadian Autism Spectrum Disorder Alliance (CASDA) was created to develop and implement a comprehensive National Autism Strategy (NAS) to addresses critical gaps in funding and policies which are preventing autistic individuals and their families from exercising their equal rights as Canadians. COVID-19 has created additional challenges for families across Canada that must be taken into account as we set policies moving forward.

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