Developing an Inflammation Intensity Score based on AI analysis of blood biomarkers

With chronic inflammatory diseases such as arthritis affecting the spine, a major clinical problem is that disease can advance over years with unrecognized persisting inflammation. Recently, we discovered that elevated concentration of certain substances in blood considered together, are highly associated with persisting local inflammation. This study will use data gathered from the blood chemistry analysis of 286 spinal arthritis patients followed for up to 12 years.

Multimodal Representation Learning from raw data to detect customers emotional state in the financial industry

Currently, call centres effort in this matter is largely reactive. Someone calls in, they are upset, and agents respond accordingly. However, this approach is not always most effective, especially with difficult customers. Therefore, knowing the customers current emotional state is very important for appropriate problem solving.

A Deep Learning approach to identify and localize room assets using handheld RGB-D sensors

With the availability of low-cost edge devices equipped with color and depth sensors, such as iPhone or iPad, 3D data capturing is becoming more accessible and convenient. Asset managers and building owners seek benefiting from this potential to accurately and automatically create 3D indoor models of buildings. In particular, having 3D indoor models containing objects of interest enables several applications, such as asset inventory and maintenance management.

Optimization of the tempering heat treatment cycle of large size forgings

Large size high strength steels parts used in transport and energy applications undergo several heating and cooling cycles during their manufacturing process (casting, forging, quench, tempering). Generally, in the tempering process the parts are heated in industrial furnaces and the impact of non-uniform heating on the subsequent steps is of critical importance. A non-uniform temperature distribution may result in property variation from one end to another of the part, changes in microstructure, or even cracking.

Identification of Cost-Effective Recycling Strategies for High-Performance Thermoplastic Prepreg Production Waste

The use of composites in transportation vehicles has been increasing for many years without a proportional response in the commercialization of recycling technologies to deal with this composites waste. Most of the waste generated during manufacturing and end-of-life is currently either landfilled or incinerated. Governments around the world recognize that such practices represent an obstacle in the effort to mitigate climate change and have, therefore, started implementing legislation such as the European Waste Framework Directive to promote waste reduction and recycling.

Realistic Few-Shot Learning

The main objective of this project is to investigate, develop and evaluate state-of-the-art deep-learning algorithms for joint few-shot classification and out-of-distribution (OOD) detection. Few-shot learning deals with the challenges of limited supervision, and OOD detection attempts to identify inputs that do not belong to the set of classes seen during training. The two research problems are in line with several applications that are of high interest to the industrial partner as they tackle realistic open-set and limited-supervision scenarios.

Adaptation de l’algorithme de Rainflow pour le calcul des cycles de chargement de manière incrémentale

Les éoliennes de taille industrielle sont conçues pour une durée de vie nominale de 25 ans. Plusieurs hypothèsessont retenues lors de la conception, notamment au niveau de l’estimation des conditions environnementales etd’opération. Il est pertinent d’utiliser les données opérationnelles pour avoir une estimation propre à une éoliennedans le but d’estimer sa vie résiduelle et optimiser ainsi les opérations de maintenance ou de remplacement. Unsignal clé est la vitesse du vent qui permet de calculer les contraintes sur le rotor et les pales.

Conception d'un chariot bitempérature sans gaz réfrigérant

Que ce soit en milieu hospitalier ou dans les centres d’hébergement de personnes âgées en perte d'autonomie, les services alimentaires en chambre sont effectués à l’aide de chariots de distribution qui permettent la remise en température et distribution de repas. Le système de refroidissement de ces chariots est basé sur l’utilisation d’un fluide caloporteur inflammable ou contribuant à l'effet de serre. De plus, la majorité fonctionne sous une tension électrique de 208 volts ce qui les rend inutilisables sans une refonte du système électrique.

Development of solutions for clothing consumption: reduction at the source and recycling of textile waste

It's very likely that shoppers have experienced many choices when browsing their favorite clothing store, more than they can keep up with. Whether these clothes end up being bought or not, they are likely to have a similar fate, ending up in landfills as waste and contributing to climate change. An alternative to face this undesirable scenario proposed in this research project is to increase the life cycle of clothes through recycling. And for that, these clothes will be shredded in their fibers to be studied for possible new applications.

Déterminer un modèle d'innovation pour une plateforme de gestion des réductions de GES et de leur conversion en crédits carbone

Cette recherche a pour objectif d’élaborer un modèle conceptuel de gestion de l’innovation pour une PME œuvrant dans le secteur de l’environnement afin de permettre d’innover rapidement dans le contexte de la monétisation des crédits de gaz à effet de serre (GES) au Canada et à l’international. En plus des caractéristiques inhérentes à la mesure de l’empreinte carbone et aux réductions de GES, le modèle doit prendre en compte les aspects d’adaptation rapide aux innovations technologiques.