A Sequential Model to Recognize Depression Acuity Using Social Media and Physical Activity

Over 350 million people worldwide suffer from depression. A key part in diagnosing depression is screening questionnaires, which rely on patient self-reports of the recent past. With the advent of social media and wearable devices, there is an opportunity for a novel approach to detecting when a patient diagnosed with chronic depression becomes acute. In this project, we use social media data and physical activity data to detect depression acuity. Social media is indicative of an individual’s mental state. Physical activity is an indicator of physical wellness.

Acoustics Modeling of ecoCUBE

Emissions control is an important part of any environmental policy. However, in dense urban environments and other locations, it is important to deal with sound as well. To ensure effective pollutant mitigation while also ensuring minimal acoustic disturbance, it is necessary to look at computer models that look at these factors simultaneously. This work will provide SPI with tools necessary for acoustic models while ensuring that their current products meet environmental requirements.

Leveraging data analytics in modern tax function

Investigating geographical footprints of income shifting by multinational enterprises. PwC owns a large data set across all industries in Canada from its tax consulting engagements and annual standard tax filings from clients. This growing data source is an opportunity for accurate tax benchmarking, trend analysis and gaining deeper insights by transforming them into market differentiating knowledge that can be dynamically shared and accessed by multiple teams.

Development of an Equity Risk Score System and Interest Rate Shock Modelling for Value-at-Risk Computation

The objective of this research is twofold: to improve existing risk management framework to assess interest rate shocks, and to develop a new risk factor model to create an equity risk score system to help guide investment decisions.
The first part of this research project involves the development of an equity risk score system to better evaluate the quality of an investment.

Optimization of parameters in Blade Element model for Helicopter Training Simulators

Helicopter training simulators are an important part of improving the safety of both civil and military helicopter operations. The most important part of helicopter training simulators is the model of the helicopter dynamics since it drives all the other simulator subsystems. This project aims to provide CAE with a more automated and accurate method for determining the parameters within their blade element helicopter model such that it matches the real helicopter behaviour.

Innovative design of a sound numerical model calibration process: from lab tests to input data

Geomechanica Inc. develops simulation software (Irazu) for rock engineering applications. This numerical software has been used in several peer-reviewed research publications in the rock mechanics field. A key challenge in the numerical modelling of rock masses is the selection of appropriate input parameters. The objective of this work is to develop a solution to streamline the laboratory testing and integration of the results into Irazu models. As a result, the time needed to build a model will be significantly reduced and the uncertainties in the model inputs will be mitigated.

Modelling transient flow in a hydropower station

Modelling the movement of water through a hydropower station is an important tool for understanding this very complex behaviour, where water is pushed and pulled through long tunnels and spinning turbines, resulting in a vast range of pressures and speeds. There are generally two types of models: 1-dimensional (1D) models, which are simple and cost-effective, but do not provide adequate detail for the more complex features in the power station. The second type is 3-dimensional (3D) models, which are very detailed but cost both time and money.

Evolved Radio Access for Wireless Cellular Communication Systems - Year Two

The continuously increasing demand for wireless access, driven by the increasing requirements of our connected society, is pushing current wireless cellular communication systems to the limits of their capacity. The objective of this project is to continue the successful collaboration with our industry partner (Telus Corporation) to further contribute to the evolution of current generation wireless cellular communication systems (4G LTE) along with the development of next generation wireless cellular communication systems (5G) to meet current and future requirements of our connected society.

The SAVI Smart Edge Deploying D2D with Massive Multiple In Multiple Out (MIMO) Antenna Architectures

The NSERC Strategic Network for Smart Applications on Virtual Infrastructures is a five-year partnership between Canadian industry, universities, researchers, research and education (R&E) networks, and high performance computing centres to investigate the design of future application platforms that will deliver software applications of greater capability and intelligence.

Stochastic Modelling of One Time Programmable Memory Bit Cell

Programming of long-term digital memory storage devices is currently not an optimised process. This is due to the fact that the exact physical mechanisms that allow for a data bit to be reliably stored and read are not well understood. As a result, in order to produce high quality, long-lasting, reliable memory cells, the manufacturer must perform extensive testing and
iterative modifications on each generation of products. Our project aims to develop a software model that simulates the physics and chemistry of memory device structures on an atomic level.

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