Grants and Contributions
About this information
In June 2016, as part of the Open Government Action Plan, the Treasury Board of Canada Secretariat (TBS) committed to increasing the transparency and usefulness of grants and contribution data and subsequently launched the Guidelines on the Reporting of Grants and Contributions Awards, effective April 1, 2018.
The rules and principles governing government grants and contributions are outlined in the Treasury Board Policy on Transfer Payments. Transfer payments are transfers of money, goods, services or assets made from an appropriation to individuals, organizations or other levels of government, without the federal government directly receiving goods or services in return, but which may require the recipient to provide a report or other information subsequent to receiving payment. These expenditures are reported in the Public Accounts of Canada. The major types of transfer payments are grants, contributions and \'other transfer payments\'.
Included in this category, but not to be reported under proactive disclosure of awards, are (1) transfers to other levels of government such as Equalization payments as well as Canada Health and Social Transfer payments. (2) Grants and contributions reallocated or otherwise redistributed by the recipient to third parties; and (3) information that would normally be withheld under the Access to Information Act and the Privacy Act.
$25,000.00
Aug 4, 2021
Aboriginal recipient
Building species at risk capacity and facilitating youth engagement within the Piikani Nation
$160,600.00
Aug 4, 2021
Academia
A new framework for secure predictive healthcare delivery through federated machine learning
976925
In the last decade, significant advances in artificial intelligence (AI) and machine learning (ML) techniques has created a growing interest in leveraging these techniques to achieve predictive healthcare delivery. It is expected that AI and ML will bring about a paradigm shift in the next generation healthcare systems. Such systems will utilize AI and take advantage of inexpensive high-performance and cloud computing environments. However, ML and AI are data-hungry and data-driven
technologies. This characteristic, in particular, could potentially limit the utilization of AI in healthcare systems. The goal of this Project is to address these challenges using federated learning (FL). The Project will develop a secure and scalable federated learning framework for healthcare systems. To demonstrate the application of the proposed framework for predictive healthcare, the project team will extend the precision care ML model developed in a previous project and also create a new predictive model for breast cancer detection. The proposed framework will focus on secure data discovery, data mapping and negotiation, privacy preservation while providing trusted and traceable data access, and a sharing environment for
ML-based healthcare systems.
$60,000.00
Aug 4, 2021
For-profit organization
LoadLink Youth Project 2021
977415
To employ youths in our organization that will provide them with on the job experience and the opportunity to learn and grow within the business gaining skills and access to leadership to build on their field of studies.
$247,280.00
Aug 4, 2021
Academia
A new framework for secure predictive healthcare delivery through federated machine learning
978160
In the last decade, significant advances in artificial intelligence (AI) and machine learning (ML) techniques has created a growing interest in leveraging these techniques to achieve predictive healthcare delivery. It is expected that AI and ML will bring about a paradigm shift in the next generation healthcare systems. Such systems will utilize AI and take advantage of inexpensive high-performance and cloud computing environments. However, ML and AI are data-hungry and data-driven technologies. This characteristic, in particular, could potentially limit the utilization of AI in healthcare systems. The goal of this Project is to address these challenges using federated learning (FL). The Project will develop a secure and scalable federated learning framework for healthcare systems. To demonstrate the application of the proposed framework for predictive healthcare, the project team will extend the precision care ML model developed in a previous project and also create a new predictive model for breast cancer detection. The proposed framework will focus on secure data discovery, data mapping and negotiation, privacy preservation while providing trusted and traceable data access, and a sharing environment for ML-based healthcare systems.
$15,900.00
Aug 4, 2021
For-profit organization
Emersewell Inc.-2021-2022-978336
978336
The purpose of this CanExport Innovation agreement is to support Canadian organizations to carry out activities related to pursuing opportunities that would lead to establishing new collaborative Research and Development (R&D) partnerships between the Recipient and foreign organizations in order to support R&D on the Recipient’s technology and advance its commercialization.
$97,247.00
Aug 4, 2021
218820
218820
Provide working capital assistance to alleviate the impacts of COVID-19
$96,229.00
Aug 4, 2021
218591
218591
Support for oyster hatchery expansion and grow-out operation
$2,625,000.00
Aug 4, 2021
217446
217446
Province of Nova Scotia ACAT Bilateral Project 2020-2023
$78,130.00
Aug 4, 2021
218433
218433
Install a mega inflatable park as an outdoor family activity
$65,000.00
Aug 4, 2021
218925
218925
Engage expertise in the area of digital adoption