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 […]

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 […]

A multidisciplinary study for the utilization of artificial intelligence for sustainable energy production in Saskatchewan Province is proposed. In this research, the Artificial Intelligence for Energy Team of the University of Regina will use AI technology to various sustainable energy resources, which including to empower the field of nuclear energy by optimizing the reactor design […]

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 […]

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 […]

Dissolvable Fertilizers are an agricultural innovation with slow and controlled fertilizer release. This technology is posed to reduce application costs and lead to optimized nutrient uptake by plants. Furthermore, it promises to reduce the agricultural, carbon footprint, as the frequency and amount of fertilizer applied is decreased resulting in less environmental pollution from nutrient loss. […]

Depuis maintenant plus trois (3) ans, un projet a été initié par Rio Tinto et l’UQAC dans le but de réduire les résidus issus de la production de l’aluminium sachant que leur entreposage est de plus en plus problématique. Une des solutions proposées est d’utiliser ces différents résidus pour développer des géopolymères électriquement conducteurs (GEC). […]

The effective planning of resources when scheduling maintenance tasks and repair jobs is an enormous challenge, especially for heavy industries such as aerospace and transportation manufacturers. In such industries, because of the product complexity and variety, not to mention continuous technological improvements, a broad range of maintenance tasks and high-performance services should be done over […]

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 […]

This research project works to improve the industry partner’s customer engagement prediction by using advanced analytics. The project focuses on understanding which contacts are most likely to engage with a customer’s marketing campaign, such as opening emails, clicking links, or making transactions. By analyzing a large amount of data, the research team will develop models […]

The free-flow counter gradient focusing technology provides a solution to tackling the problem of separating and collecting large amounts of protein sample. This technology is to be high performance and scalable, and is meant to compete against current batch mode protein separation techniques. The intern will assist in developing the experimental set-up necessary to validate […]