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.
$75,000.00
Jan 2, 2025
For-profit organization
AI Assist: ARP AI Data Project evaluating data sources for training AI enabled flux leakage NDT
1026039
The project will compare cost, effectiveness and ethical implications of different sources and management policies of labeled data for training the AI enabled flux leakage NDT.
$100,000.00
Oct 1, 2023
For-profit organization
Electro-Magnetic Acoustic Transducers for Non-Destructive Inspection of Laser-Welded Inter-Cell Connectors in Li-Ion Battery Packs
1009044
InspecTech will develop in-house Electro-Magnetic Acoustic Transducer (EMAT) hardware and integrate machine learning data analysis, for inspecting laser-welded inter-cell connectors in Li-ion battery packs.
EMAT is an emerging Non-Destructive Testing (NDT) technology that enables Ultrasonic Testing (UT) without the need for couplant, such as water; hence, EMAT overcomes the main barrier to using UT on Li-ion battery packs. The machine learning algorithm will refine the EMAT’s resolution to bring it to par with traditional UT. The machine learning enabled EMAT technology will have wide applicability to InspecTech’s other product offerings.
$101,900.00
Sep 1, 2021
For-profit organization
Integrating Artificial Intelligence based Defect Characterization into Phased Array Non-destructive Testing Systems
979996
Artificial Intelligence and Machine learning software will be integrated into InspecTech’s phased Array Ultrasound Non-Destructive Testing Systems to improve the system’s capabilities to characterize and classify defects in aluminum welds.