AVN uses a sophisticated Distributed Control System (DCS) to monitor and control the process. The mill is equipped with a data historian system which captures continuous and discrete process data from the DCS and manual tests. The effectiveness of process monitoring and control has evolved over the years. But at many stages of the process, […]

The partner, PhyCo, is a marine biotechnology startup specializing in the development of sustainable, seaweed-based bioplastics for agricultural applications. The company collaborates with the Verschuren Centre for product development, including seaweed bioprocessing and extrusion methods for seaweed-derived biomaterials. The main activity of the partner involves exploring proprietary biorefinery (multi-step extraction) technologies, developing bioplastic formulations, and […]

Lorsqu’un nouveau traitement est évalué dans les études cliniques, des critères cliniques sont utilisés pour mesurer son efficacité en fonction de l’état du patient, notamment comment il se sent, fonctionne ou survit. Cependant, ces critères peuvent nécessiter un suivi prolongé avant de fournir des résultats concluants dans la recherche clinique en oncologie. Pour accélérer l’évaluation […]

Given advancements in medical and surgical technology, the number of children with medical complexity (CMC) is rising. These children, who experience multiple chronic medical conditions and require ongoing specialized therapies, are at higher risk of adverse outcomes from respiratory infections. However, most research on respiratory infections among CMC has been limited by small sample sizes. […]

The proposed project will be the largest ever study of RSV associated hospitalizations to Canadian tertiary pediatric hospitals. Cases are identified via our national active surveillance program for vaccine-preventable diseases, the Canadian Immunization Monitoring Program ACTive (IMPACT). IMPACT’s pediatric hospital-based active surveillance network provides a rich source of data with rigorous quality control processes and […]

La gestion de la santé physique et mentale des artistes de cirque est un défi, car les exigences varient beaucoup selon les disciplines de cirque. Actuellement, le suivi de la charge de travail, utilisé pour optimiser l’entraînement et prévenir les blessures dans d’autres sports, n’est pas encore appliqué aux arts du cirque. Ce projet vise […]

This project will explore how artificial intelligence (AI) can make safety reviews in industrial plants faster, smarter, and more reliable. The intern will help build a computer system that can read and understand technical drawings and documents used in engineering, then use that information to spot possible risks in how equipment is designed or operated. […]

Le « avant pandémie » et le « après pandémie » divergent sur plusieurs aspects, dont la communication environnementale. D’ailleurs, depuis la pandémie, la population semble davantage fermée aux discussions climatiques, en plus de faire preuve d’éco-anxiété et démontrer moins d’efforts dédiés à la crise climatique. Toutefois, qu’elles sont les solutions viables pour la population […]

This project focuses on understanding how hydration status affects the health and wellbeing of dogs, a topic that has long been overlooked. Dehydration in dogs can lead to serious health issues, but the specific water intake requirements for dogs are still unclear. The project will explore key areas such as identifying reliable markers to measure […]

Le projet consiste à la mise en place de dispositifs d’échantillonnage et de prélèvements sur des systèmes de biofiltres plantés, ainsi que le suivi des paramètres de traitement de ces systèmes.

This project aims to answer the research question “can existing AI/ML models from other domains be applied to help address marine bioacoustics challenges?” One of the key challenges is that marine bioacoustics lags behind terrestrial bioacoustics in the level of research attention and technical advancement. Additionally, bioacoustics as a field has been slower in leveraging […]

This project aims to enhance proficiency estimation in large-scale assessments by improving missing-data imputation techniques. Specifically, the study focuses on refining Multiple Imputation with Denoising Autoencoders (MIDAS)—a deep learning-based approach—by incorporating item response time as an additional contextual feature. Unlike traditional item response theory (IRT) or regression-based methods, which rely on strong assumptions, the proposed […]