Grants and Contributions

The core deliverable of this project is to select, test, train and deploy a working artificial intelligence natural language processing model that can be purpose fit for a variety of niche topics and related expertise. Current conversational AI models, although very powerful, are generalized and lack the specificity and voice of an expert or expert resources present in a given industry. A first step to recreating these expert voices is selecting a general model that can be purpose built and trained on corpus, vocabulary, and text related to a specific niche quickly.

This project involves hiring two Engineers, one as a student summer internship, and the other a more experienced Junior Engineer, to help further research and development on the CROSSFIRE product line. The CROSSFIRE product line reduces or eliminates Methane emissions from the oil and gas industry and the firm requires technical assistance to advance the development of this technology to new applications. Specifically, the vapour recovery unit (VRU) and a higher output pressure VRU, in addition to a suite of complimentary products. Additionally, the engineers will implement lean manufacturing principles into assembly work flow and complete value engineering analysis on suite of existing commercial technologies.

This project engages a recent graduate in studying vegetation types and their influence on wildfires, aiming to deepen their knowledge of ecological systems and develop their research capabilities.

The firm's radiotherapy system combines an MRI system with a linear accelerator to provide high quality patient images to ensure they are properly aligned prior to delivering radiation therapy. This project will improve the efficiency of the MRI imaging system and develop robust patient registration. The system currently generates a 3D image as a single acquisition, which takes about 4 minutes. This will enable generating the 3D image as a series of 2D images to allow the user to see the first image almost immediately. This enables the firm to implement an automated registration process that will do a 3D registration based on three orthogonal images. The registration will occur in less than 1 minute, which will significantly increase our our imaging efficiency.

The plastic industry is an important sector in Canada with $35B/yr sales, 1,932 establishments and 93,000 jobs. Its annual volume of plastic production in Canada was 4.7 MT in 2020. Unfortunately, only 9% of it is recycled. The NRC, in collaboration with the Applicant, is looking for technical pathways to enhance the sustainability of plastic products fabricated and sold in Canada and to support Canada’s Net-Zero Waste strategy and circular economy. The purpose of this project is therefore to develop different innovative solutions to address hard-to-recycle plastic wastes, such as plastic containers and packages, agricultural film, apparel textile, plastic-coated paper, by converting them into valuable carbon black products with different characteristics to be used in plastics, metals, absorbents, and cements applications.

Molecules derived from bark can be used in a number of sectors. Three specific applications have been targeted for which the potential sales volume would be very high. The project will validate that the molecules produced can be used effectively in these three applications. Experiments with generic recipes will be carried out to confirm this potential, which will then enable us to approach potential customers. It will then be possible to confirm the functionality of the molecules with the results obtained in the targeted application. There are currently no products incorporating these molecules as active ingredients, but the scientific literature suggests that there are.

Plan and continue development of online user help and multi-language capabilities for all new modules of the platform as well as function as lead developer to intern students through the summer and school term. Participate in development efforts with new capabilities as required and address system bugs and issues as they are identified through testing and/or users.

This project intends to provide automated segmentation of tumor burden from PET (Positron Emission Tomography) scans to the firm’s full-body image segmentation solution. The project will develop the protocols for lesion segmentation from PET scans, train the team in these protocols, and help develop a manually annotated library of tumor lesion burden for AI training.

Innotech Alberta CtO will provide one-on-one technical services to growth-oriented SMEs across Canada. Canadian SMEs have limited funds for commercializing innovation. Innotech Alberta CtO provides essential support for SMEs to de-risk cap-ex by providing 3Rd Party Validation.

This project aims to research and develop a non-repudiation solution which will enable third party, offline verification and validation of data.