Grants and Contributions

The objective of this project is to model and test hydrokinetic turbines to determine local and time-variant turbine blade loads. This model will be applied to determine blade loading and turbine interaction to real-life cases, proving its usefulness as an engineering design tool. Ultimately, this validated numerical method will be used to study the load behaviour on turbine blades as a function of various parameters (type of tidal flow, turbine design, turbine arrangement in an array, etc.) to extract a body of knowledge useful for engineers. The knowledge of spatio-temporal load variations is the starting point of material fatigue studies which will narrow down the estimated lifetime of turbine blades while in operation. Such
knowledge will have a great impact on risk assessment and overall system operation cost.

The project aims to develop new machine learning models, analysis software, and best practices to detect and classify fish by species using combined video and acoustic data from hundreds of underwater cameras. The data is being collected to measure effects of seismic exploration on commercial fishing. This research will support a new research initiative between the National Research Council (NRC) and the Department of Fisheries and Oceans (DFO). DFO will provide data and domain expertise NRC will process video data and develop the necessary tools required to process these large and novel datasets. Dr. Whidden (MUN) and the PhD student (MUN) will provide expertise on machine learning applications to improve video and acoustic data analysis methods specifically tailored and optimized for the field campaign data collected by DFO.

The DealPoint platform provides efficient online investor onboarding and subscription document execution for private placements. This project will focus on developments in three areas: investor dashboard, enhanced e-signature capabilities, and managing subscription funds.

The purpose of this project is to explore the idea of an autonomous fleet of vessels which increase the availability of a channel of interest by pushing ice out of the way. The project involves the hiring of one PhD student. A reinforcement learning strategy for the vessel control algorithm to capture the complex interactions with ice on water is proposed. The model test basins at NRC are proposed to be used to collect data to enhance a simulation for algorithm development that will also be demonstrated with a model test. An existing ice simulation technology developed at NRC-OCRE in combination with model-free reinforcement learning will be used to arrive at a design for the vessel controllers that maint navigability.

Development of a farm crop insurance industry parametric product delivery platform.

Smart home-based aging care systems are reshaping the health services by introducing proactive monitoring, improving quality of life, and facilitating efficient management of health resources. However, these advances inevitably emphasize growing threats to the security and privacy of sensitive personal and health information. This project will develop a comprehensive security analytics framework entailing multi-level countermeasures (i.e., software systems) for attack detection and prevention in smart aging care systems. The framework will include advanced vulnerability assessment, machine learning, and monitoring techniques that will consider the behavior of not only connected electronic devices and applications but also user activities and usage patterns to detect and prevent common and unknown threats. The developed cutting-edge and comprehensive solutions will improve the security and privacy of smart home-based aging care systems.

EMS will design and validate a polymer-based probe capable of quantifying solid-state hydrocarbons in soils.

Development of TAGDit Data-as-a-Service Cloud software product designed for the coming age of user-owned data. The software enables users to aggregate data in their own secure private living data library located in virtual spaces called “data rooms” on the TAGDit webpage, market it and sell it in their own data storefront. It comes with advanced search features to search the data, which could be text,audio, video, multimedia, IoT data or executable files. A custom web search tool that is weighted with your own saved search history return more contextually meaningful results. Other types of search filters are also possible such as text, image, and other filters.

The quality of quantum photonic technologies, ranging from communication to computation to sensing, depends on the generation of high-quality quantum states photonic states: either single or entangled photons. The Project addresses this challenge, developing on-demand sources of indistinguishable single photons and entangled photon pairs, on-chip and at telecommunication wavelengths. These sources require the integration and electronic-gating of self-assembled quantum dots, whose sizes and material composition have been carefully engineered to provide telecom photons, with on-chip nanoscale systems, designed to control and optimize quantum light-matter interactions. Together, this combination will for the first time, provide high-quality quantum photonic states on chip that can leverage the full power of the telecommunication industry, providing a powerful new platform for the development of quantum sensing technologies.

Hiring to consolidate the local "Quality Control" team by adding an additional resource.