This proposed project aims to develop a control model that can counteract gait asymmetries in human walking. Gait asymmetries can arise in two different scenarios. It can be introduced from the environment, such as uneven terrain or strong winds, that would cause the body to need to adjust its motion to stay balanced. It can […]

The proposed project aims to develop a method for three-dimensional reconstruction of manual work using multiple RGB-D cameras and a thermal camera. This innovative approach will enable the digital archiving of intangible cultural heritage, such as traditional craft techniques and dance performances, which are currently predominantly documented in 2D formats. By integrating rich information about […]

Les objectifs de ce projet sont de réaliser des mesures électrocatalytiques de la réaction de réduction de l’oxygène sur des substrats d’électrodes à base de graphène. La réduction de l’oxygène est une réaction fondamentale dans les piles à combustibles et les batteries air-métal. Les catalyseurs de pile à combustible de pointe utilisent des nanoparticules de […]

This project will investigate the feasibility of applying fixed-bed chemical looping as a technology for off-gas cleanup and heat recovery from a conventional steelmaking process. Investigation will consist of thermodynamic studies and material selection, numerical investigation of system dynamics using a specialized process model, and experimental investigation for a bench-scale proof of concept. Experimental results […]

The intern will travel to the University of Jyväskylä’s Department of Chemistry, where they will be hosted in the group of Prof. Heikki M. Tuononen. The principal investigator host is a computational chemist of international recognition, University of Calgary alumnus, and longtime collaborator of Prof. Roland Roesler, the host in University of Calgary’ Department of […]

Au cours des dernières années, la recherche en reconnaissance gestuelle a connu une forte effervescence, principalement appuyée sur la démocratisation de l’intelligence artificielle. Cependant, les approches actuelles rencontrent souvent des défis en termes de robustesse et demandent un grand effort de calibration. Pour remédier à ces limitations, ce projet propose d’employer la fusion de signaux […]

Le but ce travail est de mettre en place une platforme qui integrerait efficacement plusieurs algorithmes d’evaluation des produits derives sous differents modeles non-gaussiens. Cette platforme cherche a etre une calculatrice des prix des options integrant des modeles de pointe pou servir d’aide a la comparaison empirique des point de depart de l’etude. Cette famille, […]

Our project emphasizes the integration of advanced artificial intelligence techniques with traditional diagnostic methods, fostering a synergy that enhances the accuracy and efficiency of cardiac health assessments. By leveraging the power of Artificial intelligence, specifically through the utilization of a Convolutional Neural Network (CNN), we can discern subtle patterns and nuances in ECG data that […]

La physique des particules se concentre sur l’étude des éléments fondamentaux constitutifs de la matière et des forces qui régissent leurs interactions. Les recherches dans ce domaine sont menées à l’aide d’accélérateurs de particules. De plus, le Modèle Standard de la physique des particules est le cadre théorique principal décrivant les interactions entre ces particules […]

The proposed project explores the flow dynamics of Bingham fluids through channels with superhydrophobic (SH) grooved walls. The focus is on understanding how these special surfaces, which trap air in grooves, affect the flow behavior of fluids that exhibit both solid-like and fluid-like properties under different stress levels. The research aims to develop a semi-analytical […]

The central idea of this project is the observation that publications using systematic time series feature extraction from the Open Source machine learning library tsfresh, always need to visualize and explain the extracted features. Due to the fact that tsfresh uses 168 algorithms to compute up to 800 time series features, this process can be […]

The proposed project aims to enhance the interpretability of machine learning models, particularly in the context of time series data analysis. By extending the capabilities of the tsfresh library, a widely used tool for time series feature extraction, the project seeks to make complex models more transparent and understandable. This effort will improve confidence in […]