The development of autonomous unmanned aerial vehicles (UAVs) is a growing area of interest. An important step in the creation of a fully autonomous flying vehicle is the ability to precisely and smoothly land on a target. The goal of this research is to develop a UAV landing system that is able to track and land on a moving platform. The project will involve developing a guidance and control system that can plan a descent trajectory and track it down to the platform. The proposed system will be robust to strong wind gusts and still provide a smooth touchdown to avoid damage.
The goal of the project is to understand how athletes have been affected by the COVID-19 pandemic. Through online surveys and interviews, the researchers hope to learn about the way
the pandemic. They also want to know what athletes are doing to cope and how their families and coaches are supporting them. Study findings will guide the partner organization in their development of holistic recommendations and automated tools optimized through artificial intelligence.
People with the autoimmune disease scleroderma are vulnerable in COVID-19 due to frailty, lung involvement, and immunosuppression; they are representative of vulnerable groups in terms of COVID-19 mental health ramifications. No previous randomized controlled trials have tested mental health interventions during infectious disease outbreaks. We leveraged our existing ongoing cohort of over 2,000 people with scleroderma and existing partnerships to launch a new cohort, the Scleroderma Patient-centered Intervention Network (SPIN)-COVID- 19 Cohort.
Cost-effective clean energy production is one of the most urgent economic and societal issues facing Canada today. Hydro-Québec is a world-leader in clean hydro-electric energy production – an essentially carbon-free source of energy.
This project is about using artificial intelligence to interpret agricultural remote sensing data. We will develop new means to integrate repeated imagery data of targeted agricultural fields to pinpoint agronomically significant anomalies (e.g., water or nutrient stress, crop pathology, weeds, etc.) and provide field managers easy to follow recommendations guiding development of the most cost effective plans to treat these anomalies.
Depression is a common and often devastating illness that contributes to suffering for patients and families and is also the number one cause of disability globally. Many patients do not respond to their
first trial of treatment, and managing depression according to best practices can be difficult for clinicians. Using the power of machine learning, a new tool has been developed that is intended to help match
patients to treatments using a simple questionnaire and to assist clinicians in improving the quality of depression treatment.
In Canada, alfalfa is a widely cultivated legume forage and the principal source of protein in the diets of ruminant animals. High quality alfalfa (i.e. nutrient composition and fiber digestibility) is vital for profitable dairy production because it can reduce requirements of high-cost concentrated feeds. High fiber digestibility is associated with higher cow's intake and milk production. Low-lignin alfalfa has recently been developed through technological progress.
To aid in active management of Snowy Owls and other raptors at airports, it is essential to understand the spatial distribution and movement behaviour of birds both on and off the airfield. The impact of airfields on birds may be particularly pronounced because airfields provide open, undeveloped land similar to early successional habitats that are perceived as high quality by many species. Airport collisions are a significant threat to Snowy Owls and humans, and preventative measures cost over $500 million dollars each in North America alone.
Transportation systems are evolving towards intelligent transportation systems and ISR Transit is a leading provider of these systems providing solutions in fleet management. In these systems, one of the enabling technologies is wireless sensor networks in which sensors are used to obtain information about the fleets. For example, sensors are deployed on motor, brake modules, doors, emergency buttons and passenger stop request.
Two fundamental pillars of communications/communications networks are trust and truth; in particular, we must ensure that the message (or data) that a sender wishes to transmit does indeed reach the intended receiver without being altered or eavesdropped by an unwanted party. This project focuses on demonstrating one concept of the quantum internet. The quantum internet is not based on quantum communications per se, but rather considers exploiting quantum principles for encoding and decoding data transmitted over existing fiber networks as a means for obtaining secure transmission.