Diagnostic Software for Mapping Blood-Brain Barrier Pathology

When blood-vessels in the brain are damaged, substances can leak from the blood into the brain. This leakage can affect cognition and mental health, however there are currently no clinically-available tests for detecting such leakage.
In this project we are continuing the development of a method for diagnosing subtle leakages in the brain’s blood vessels using MRI. We have recently demonstrated that this technology may help explain why patients diagnosed with the same disease often have very different severities of outcome.

Solving the integration problem for loyalty programs

Paying with a mobile phone within brick and mortar retailers is becoming increasingly popular, as it adds convenience as well as security to the payment process. Many retailers that use interac terminals with tap technology allow mobile phone payments in this way but are unable to integrate loyalty points into the mobile payment process.

Speeding up Federated Learning Convergence using Transfer Learning

The recent advances in machine learning based on deep neural networks, coupled with the availability of phenomenal storage capacity, are transforming the industrial landscape. However, these novel machine learning approaches are known to be data hungry, as they need to tune a huge number of parameters in order to perform well. As more and more AI based applications are being deployed to learn from personal data, privacy concerns are rising, and more specifically on sensible domains like medicine, finance or mobile related data.

Opportunities for and impacts of community-scale biomass and waste heat district energy systems in Canada

Solid biomass, of which Canada has plenty, is the lowest cost, and greatest employment generating, renewable heat source available but to date but is not often considered as a low carbon heating option for deployment on a large scale in Canadian cities. For solid biomass to reach a high market share, a key enabling infrastructure is required: district energy systems (DES). While there are existing DES in Canada, they provide less than 2% of all building heat in the country.

Unsupervised Learning Based Approach for Insider Threat Analysis

Insider threat is one of the most damaging security threats to the safety of data, systems, and intellectual property of institutions. Typical threats caused by malicious insiders are trade secrets / intellectual property theft, disclosure of classified information, theft of personal information and system sabotage. Malicious actions of insider threats are performed by authorized personnel of organizations, which may be familiar with the organizational structure, valued properties, and security layers.

Development and Application of Marine Mammal Density Estimation Methods for Directional and Omnidirectional Hydrophones

Estimates of the population density of marine mammals in an area and the change in population over space and time are critical inputs for managing the interactions of human activity and mammal populations. Visual surveys from boats, shore stations, and aircraft have served as the basis for most population estimates currently used by managers. However, these survey methods are generally only performed in good weather conditions and require many trained observers. These factors make visual surveys expensive and reduce the temporal and spatial coverage of population estimates.

Public Transit Feasibility Study for the Town of Happy Valley-Goose Bay

The Town of Happy Valley – Goose Bay is located in the central part of Labrador on the coast of Lake Melville and Churchill River and as such it plays a significant role in the area as a place of employment, education sectors, healthcare facilities, shopping, municipal services and healthcare facilities. With a population of 8,109 in 2016, it observed a huge surge in population between 1971 and 1991 in particular. The community is growing day by day but there is no existence of public transit here.

Developing Sustainable Aquaculture by Intensifying Seawater Gas Transfer

Over the past few decades, aquaculture has assumed a leading role in providing food security and meeting the increasing worldwide demand for a nutritious diet. However, the ability to continue this important role is threatened by the climate-change driven increase in ocean temperature and by the adverse impact aquaculture operations can have on the environment.
The overall objective of the proposed R&D project is to develop innovative, simple, flexible and energy-efficient approaches for enhancing aquaculture aeration operations.

Autonomous deployment, operations and recovery of underwater sensors

Integrating a towed array (which consists of a very long tow cable and a line array of sensors) with an unmanned platform requires unattended operation of the array during deployment, operation and recovery. The objective of the proposed work is to create and demonstrate a towed array handling system on an unmanned platform which can operate without human intervention and ensure the towed array and cable can be deployed and retrieved unharmed.

Practical implementation of an anisotropic rock mass strength model for rock slope stability analysis

As mine pit slope become higher, the implications of accurately predicted slope angles becomes greater for worker safety, environmental impact and economics. Over the past decade, data analysis and computational methods have resulted in significant research developments in this area. Utilizing these some of thee methods requires a high level of field data and large computational resources. For many projects, this may not be warranted or available.