Le projet proposé vise à développer un appareil portable, non invasif, sans fil et rentable pour la surveillance continue en temps réel de l’activité respiratoire et cardiaque. Cet appareil aidera à diagnostiquer et à surveiller les maladies en fournissant des mesures continues de la fréquence respiratoire avec une précision comparable aux normes médicales, ce qui […]

Carbon dioxide (CO2) atmospheric concentration has increased by 50% (from 280 ppm to 420 ppm) in the last century. Despite efforts to reduce emissions, industries vital to our economy, such as mining, marine transportation, and aviation, remain dependent on fossil fuels for their operations. These sectors are considered hard-to-decarbonize because they lack viable alternatives to […]

Telecom operators are demanding more flexible, scalable and energy efficient products. As a system integrator managing networks for operators, Ericsson realize that the benefits of using modern and improved systems is becoming even more critical, as they offer a reduced Operational and Capital Expenditure (i.e. OPEX and CAPEX) of Information and Communication Technology (ICT) systems. […]

Breast cancer remains a major global health concern, with high prevalence rates in new case diagnoses across the world. The primary challenge in breast cancer detection centers on achieving early and precise diagnosis as actual methods have limitations. The primary challenge in breast cancer detection lies in achieving early and accurate diagnosis. Current methods face […]

In recent years, factors like thermal comfort, indoor air quality, and energy consumption in school buildings have received increasing attention. Lecture theatres and chemistry labs pose significant challenges for HVAC design due to thermal stratification in lecture theatres and ineffective ventilation in chemistry labs, caused by large spaces and pollutant generation, respectively. Despite many studies […]

This proposal aims to develop a robust, low complexity infant cry deep learning classification based on various babies’ responses to physiological needs such as hunger or to discomfort and pain. The significance of this research lies in its potential to enhance early detection of needs and moods in newborns, contributing to improved infant care, early […]

This project aims to quantify defects in the probability framework for 2-dimensional (2D) materials with superior performance using optical techniques, primarily focusing on molybdenum disulfide (MoS2). Additionally, defects are an important factor influencing the performance of single-photon emitters (SPEs), a type of quantum device. This project will directly relate the SPE performance with defect concentration. […]

This project will create a first of its kind system to measure and validate the performance of conformally cooled tooling (CCT) for die casting and injection molding. CCT increases production efficiency and quality helping Canadian manufacturing to stay competitive with foreign manufacturers. Yet, many manufacturers are reluctant to adopt CCTs due to uncertainty around its […]

Graphene is a promising new nanomaterial, single layers of graphite, with superior physical and electrical properties making it an ideal candidate for electrical applications; however, current graphene production methods are expensive and complicated. As a result, new materials that have similar properties to graphene, but are more amenable to high-yield production are currently being investigated. […]

This project focuses on revolutionizing space communication through the design and optimization of customized conical horn antennas tailored specifically for space applications. Horn antennas are pivotal in facilitating efficient communication in space, offering unmatched versatility in controlling radiation patterns and providing high efficiency. This project aims to optimize horn antenna geometries and design metrics by […]

The proposed research project aims to address the challenge of accurately detecting and classifying complex driving maneuvers in real-world conditions. Partnering with Matt3r Technologies Inc. in Vancouver, BC, this research will develop a deep learning model that uses multiple types of data, such as dashboard video, to achieve maneuver detection for autonomous vehicles. This innovation […]

Video surveillance systems have rapidly expanded, driven by their critical roles in security and traffic monitoring. This expansion has produced vast data volumes, causing bottlenecks in communication systems due to the time-sensitive and bandwidth-intensive nature of surveillance data. To address these challenges, research has increasingly focused on developing algorithms to compress redundant data effectively, evolving […]