Optimizing Virtual Care Solutions Capabilities to Address Cognitive Impairment

Optimizing an integrated virtual care technology solution to expand capabilities to manage patients with cognitive impairment. These enhancements will improve remote monitoring and management of patients with Alzheimer’s and Dementia. The project will result in the development of additional tools and proprietary applications to enable comprehensive assessments in the areas of stroke and other neurological conditions.

Analysis of the potential application of the shortwave infrared and near-infrared cameras to the weld temperature measurements

Temperature is a critical parameter in welding and related processes such as metal additive manufacturing. The real-time temperature measurement systems based on infrared thermal cameras have a potential to significantly improve the existing process control systems and, consequently, the quality of the welds and additive manufactured products. Conventional thermal cameras work in midwave (MWIR) and longwave infrared (LWIR) part of the infrared spectrum. They require sophisticated sensor systems and special optics.

Vapor-phase metal additive manufacturing

Additive manufacturing (AM, or 3-D printing) with metals is a rapidly growing field catalyzing a revolution in modern manufacturing. The most common approach involves the use of metal powders as a feedstock material. The proposed research program will use metalorganic gaseous precursors such as Ni(CO)4 and Fe(CO)5 which facilitate low temperature (~200 C) deposition, forming solid metal deposits utilizing infrared light radiation-based heating.

On-board gaseous fuel compression for low greenhouse gas commercial vehicles

To reduce the greenhouse gas (GHG) emissions from goods transportation low-carbon fuels can be combined with high-efficiency engine systems. Gaseous fuels such renewable natural gas and hydrogen offer low net GHG emissions from efficient direct-injection engines. These engines use high fuel injection pressures that need to be supplied during operation by a compressor on the vehicle. This project will investigate the technical pathways that could provide the desired fuel pressures.

High-Precision Imitation Learning for Real-Time Robotic Control

In recent years, an increase in industrial robots in manufacturing has emerged. However, there are still possible safety issues and difficulty in specifying tasks for the robots to perform. The objective of this research project is to make a path planning system that uses demonstrations of how to perform a task to learn how to perform the task using techniques from the field of machine learning. These demonstrations will also show the robot how to move in the workspace safely and without entering collision with items in its surroundings.

Development of a rapid, point of care, COVID-19 detection system using proximity-based electrochemical principles

Rapidly detecting SARS-CoV-2 in infected individuals remains a critical problem in Canada. The current detection method is hindered by the need for highly trained personnel and expensive laboratory equipment. Such requirements cause long wait times and reduce the ability to manage the spread of COVID-19 in our communities. This Mitacs Accelerate project aims at addressing such problems, i.e., developing a rapid, easy-to-use, point of care (POC) detection system for hospitals, airports, long-term care facilities and working places.

Optimizing a food wastage stream at the consumer level of the Food Supply Chain through Machine Learning and the Internet-of-Things.

Across the world, one-third of all the food produced yearly—¬¬¬worth $400 billion—is wasted (Bharucha,2017). This project aims to research and develop the accuracy of a machine learning algorithm in order to assess its efficiency in reducing food wastage and making restaurants more profitable.

Investigation of Zebra Configuration in Light-Weight MagentoRheological Dampers

Commercial MagnetoRheological (MR) dampers are still bulky and consume relatively high power. Thus new designs to improve their energy consumption and total mass are required so that they can be used in applications such as prosthetics and small electric vehicles that are restricted by energy consumption and mass. To address the above issues, in this research we focus on the design of a MagnetoRheological damper to achieve small mass with low energy consumption for commercial use.

Optical Trapping of Nanoparticles in X-Ray Photodynamic Therapy

A radioluminescent material converts ionizing radiation, such as X-rays, into lower energy photons. The use of radioluminescent nanoparticles has been proposed to enhance the efficacy of photodynamic therapy (PDT) in cancer treatments. During a typical treatment, a molecular specie, called photosensitizer, absorbs visible energy to produce reactive oxygen species, which determine cellular death due to the resulting oxidative stress. The required visible energy has a low penetration depth through the tissues, which limits this approach to superficial treatments.

Broadening the vascular diagnostic service continuum of Koven Technology Canada through the development and validation of a novel in vitro diagnostic technology to diagnose peripheral arterial disease

Peripheral arterial disease (PAD) is caused by changes in the wall of the blood vessels of the legs that make them narrow and stiff. The main causes of PAD are atherosclerosis and smoking. Unlike many other diseases, there is no blood test that is capable of detecting PAD. Instead, persons have to be referred by their doctor and they must go to a specialized clinic where an expensive hour-long ankle-brachial (ABI) test is performed.

Koven wants to develop a simple, inexpensive and reliable blood test that can detect PAD.

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