Grants and Contributions

The optical transmitter is a critically important component in optical satellite communications, which includes a high-power high-bit-rate laser, a telescope, and a driving circuit. The current satellite communication based on visible and near-infrared (NIR) light does not work for all-weather (such as fog, rain and snow). Optical satellite communication at mid-IR atmospheric windows (3-5 mm and 8-12 mm) is essential for practical all-weather networks since absorption is much smaller for wavelengths in mid-IR atmospheric windows than for visible and NIR wavelengths. Unfortunately, mid-IR lasers with high optical power and high bit rate are not available on the market. This project will provide a practical Made-in-Canada approach to mid-IR sources for all-weather optical satellite communications based on novel materials. The developed mid-IR transmitters will be tested under various weather conditions, with system performance of the developed mid-IR transmitters, radiation hardness and real world (space) implementation conducted.

To assess the functionality of novel NRC-developed chimeric antigen receptors (CARs) targeting leukemia in primary NK cells and assessment of CAR-NK potential for therapeutic development, expanded primary NK cells will be transduced, and their anti-tumor response will be evaluated in vitro and in vivo.

This project aims to develop digital twin technologies for aircraft structural life-cycle management. The digital twin can mirror aircraft structural lifecycle by predicting its performance and long-term behaviors, and support the optimal maintenance decision making. Integrated with industrial Internet of Things, a digital twin ecosystem can reduce maintenance costs and downtime. The outcome of the research will enhance Canada’s global competitiveness in both the MRO and ISS sectors to face the challenges from emerging economies.

Precision medicine is an emerging approach for disease treatment and prevention by delivering personalized care to individual patients taking into consideration their personal circumstance in terms of genetic makeup, environment, and lifestyle. Advancement in precision healthcare is tied to technological advancements, such as big data storage and analysis, sensor technologies, the Internet of Things, etc. Despite the rapid advancement of precision medicine and the considerable promises that it entails, several underlying technological challenges have not yet received the attention they deserve. One such area of great importance is the security and privacy of precision health related data. Specifically, the security and privacy risks of introducing precision health related data, such as the human genome, in patient’s electronic health record (EHR), are not well understood.
The purpose of the current project is to develop an Artificial Intelligence-based framework that will take as input precision health related data, such as the human genomic sequence, and produce a different representation that is privacy-proven and can be appended safely to patient’s EHR. This new representation will provide enough information that can be used and analyzed by the different precision health professionals, while not being reversible. The new framework will leverage advances in deep neural network and homomorphic encryption techniques.

HCI research involving simulating (digital twinning) IoTenabled objects and how users may interact with them. In the context of field maintenance of complex IoT-enabled objects, the question arises of exactly how a technician would interact with the IoT-derived data and other maintenance information. The project will look at the data and information by having the technician interact with a digital twin of the object and related IoT data. To identify effective ways in which a technician would interact with this digital twin and its data, the project will implement 3D interaction and visualization techniques and conduct human experiments to assess the efficacy of those techniques. While the project will focus on aircraft engine maintenance use cases, the more general HCI research issue is how to best support technicians in their interaction with IoT-enabled devices. Consequently, the results of this project would apply to a variety of other domains as well.

The proposed project aims to provide security to remote healthcare delivery efforts in Canada for in-home patients and geographically remote Canadian regions.
Project Objectives:
1. Propose secure authentication protocols for IoT systems in remote healthcare systems
2. Validate the security of the proposed authentication protocols
3. Develop embedded processor arrays for fast and secure elliptic curve encryption
Enhance protocol security using data flow computing and activity obfuscation

Photonic generation of millimeter-wave frequencies (30 GHz–300 GHz) has recently attracted great interest from both academia and industry, particularly for applications in future seamless fiber-wireless integrated optical access networks (OAN), such as both front-haul and back-haul of 5G and beyond (6G) of mobile wireless networks. A wireless access network (WAN) at millimeter-wave bands has large bandwidth for high speed indoor/hotspot communications to be utilized to support the combination of small cells and millimeter-wave radio, and fiber-optic communications plays an important role in both the back-haul and front-haul networks. The objective of the project is to implement heterogeneous photonic integration to develop fully integrated microwave photonic systems for the generation and transmission of millimeter-wave signals be used in 5G and beyond wireless networks.

Autonomous mobile manipulators are a novel class of autonomous systems that can be used in many advanced automation and manufacturing processes. Due to the high complexity of unified trajectory planning and control, current industrial solutions often decouple the autonomous platform and the attached manipulator, treating them as isolated systems. This project will focus on the development and validation of a unified multi-objective control system and trajectory planner to improve the performance and robustness of autonomous mobile manipulators for tasks such as force or visual servoing. In addition, artificial intelligence techniques will be explored for the optimization of the forward and inverse kinematic models of the autonomous mobile platform. Successful completion of this project will deliver HQP and high impact publications providing transferable knowledge directly into the autonomous mobile robotic industry and their supporting end-users within Canada.

Robotic based processing is a very attractive option for manufacturers due to the flexibility and re-configurability of the systems as business and market demands change. Within the robotic space, collaborative robots further extend the flexibility of traditional robotized systems by incorporating highly sensitive internal sensors to better perceive the environment around it. These sensors can be used to provide a source of time-series signals representing the process. This project will look to develop a generalized semi-supervised machine learning based predictive framework to estimate the surface roughness of a machine finished component to better improve the efficiency of robotic finishing applications. With an accurate predictor of the surface roughness derived from the processing data provided by the collaborative robot, requirements for additional external inspection can be reduced or removed. A fundamental component of the project is to ensure generalization of the framework, allowing for extendibility into other collaborative robotic manufacturing processes.

This Project aims to strengthen our understanding of innovation in rural areas, recognizing that rural innovation looks and works differently from that which typically takes place in cities.