The proposed research project will focus on the development of novel techniques to improve the assessment of psychological functions. Current psychological tests are limited in their ability to provide quantitative information on an individual’s ability to move and interact with their environment. Many psychological tests are computer-based systems that have been developed to assess psychological […]

La recharge de batterie ou encore l’alimentation continue d’appareils/engins sans fils et éloignés de toute source électrique ou solaire, comme dans le cas d’applications dans le domaine spatial, sont de véritables défis. L’usage couplé d’un émetteur laser et d’un photo-transducteur (PPC) pour transférer de la puissance sur de longues distances est une solution potentielle intéressante. […]

The project determines the limitation boundaries of single sensor measurements by assessing the accuracy of a rocket’s kinematic parameters—such as speed, turn rate, and acceleration—based on the precision of individual sensor measurements. This involves evaluating whether these parameters can be accurately measured or estimated using each available sensor while considering the rocket’s dynamic behavior. Additionally, […]

The project relates to a key electro-optic component used in optical modems that route internet traffic between cities, countries, and continents. These high-bandwidth long-haul systems are also being evaluated to solve the problem of moving data between data centers and even within data centers for high-bandwidth applications such as cloud services and artificial intelligence. The […]

Dysfunction of mitochondria, the cellular powerhouses, plays an important role in a plethora human disorders, including rare genetic myopathies such as Duchenne Muscular Dystrophy (DMD). Mitochondrial dysfunction also causes stem cell abnormalities in several tissues including skeletal muscle. For this reason, modulation of mitochondrial quality is increasingly proposed as a therapeutic strategy to prevent/restore cellular […]

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 […]

The continued health disparities and the recent public health challenges including COVID-19 pandemic and epidemics have highlighted for the need of more resilient community-based health system in Africa and beyond. Robust evidence is crucial by examining the lessons learned during practice of community-based health programs to build locally led better community health systems in Africa. […]

THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW

The general objective of this research is to investigate the effectiveness of fine-tuning large language models (LLMs) for the purpose of enhancing patent generation and brainstorming processes across various domains. The project follows an agile project management approach, emphasizing continuous small releases. The project is important to XLSCOUT as it aims to enhance text clustering, […]

Software requirements play a critical role in safety-critical cyber-physical systems as they are the foundation for designing, implementing, and testing of the software systems. Due to limited budget and time constraints, software requirements in a commercial setting tend to have unsatisfactory quality, which complicates downstream development activities. Prior research identifies dozens of quality attributes of […]

Cardiac PET is a powerful tool to assess heart function. One measure from a Cardiac PET study is left ventricle ejection fraction. This is mainly estimated through gated reconstructions of relative perfusion imaging and segmentation of the left ventricle myocardium. However, direct estimations of left ventricle volume and thus ejection fraction can be obtained by […]

Training artificial intelligence and machine learning (AIML) models requires a large amount of data. However, access to data for AIML projects has been problematic in practice, largely due to privacy concerns. One approach to enable data sharing and data access is to anonymize the data. However, in the Canadian context, a national standard and a […]