Machine learning applied to drilling in open pit mines

The project involves identifying changes in mineralization during the drilling of the blast holes. During drilling, an experienced driller is able, to a certain extent, to detect signals that indicate that a zone change is occurring: vibration in the cabin, rotation rate, etc.

Cancer tissue classification using machine learning/deep learning algorithms

Raman spectroscopy is a non-destructive laser-based optical technique that provides information on the molecular composition of biological tissue. Using this technique, it is possible to distinguish different types of tissue and use this information to develop prognostic tests to evaluate, for example, how a patient will respond to a specific therapy.

Systematic Risk Mitigation Methodology Applied to the Bioénergie La Tuque (BELT) Biofuels Biorefinery - Year two

Bioénergie La Tuque (BELT) is promoting the development of a 200 million liter per year biofuels plant to be built by 2023 in La Tuque. The plant will use residues from forest harvesting as feedstock, which will be a first at that scale for a second-generation biomass biorefinery in Canada. It is critical for a project of that magnitude to achieve success, that risk associated with the biorefinery implementation are thoroughly identified and mitigated. In this project, technology and market risk factors are specifically targeted.

Automated Visual Inspection, Sentencing & Dressing

Within the aerospace sector, aftermarket services account for over 50% of revenue generated by aero engine manufacturers. Central to this is the ability to inspect and repair high unit cost components. Many processes are manual but given the ever-increasing quality, cost and delivery requirements, and the safety critical nature of these rotating parts, there is a strong drive towards process automation.

Deep Generative Modeling of Character Animation

The goal of this research project is to develop novel techniques to solve different tasks for character animation using deep neural networks and generative modeling. Namely, we wish propose a novel approach for transitions generation, in which clips of character animation can be linked together with a novel clip. This transition will be generated by a specifically designed recurrent neural network that should make use of recent advances in adversarial learning in order to produce realistic animations.

Study on the hydro-geotechnical properties and establishment of a numerical model for waste rocks

Mines produce large amount of waste rocks, mostly disposed on ground surface in form of pile. In underground mines, waste rocks are increasingly used to construct barricades to retain mining backfill in the stopes. Waste rocks can also be used as inclusions to accelerate the drainage and consolidation of tailings. To properly evaluate the stability of these infrastructures, numerical models are needed. However, the existing numerical models suffer from two major limitations.

Certifiable Fly-By-Wire Robust Control Laws for Flexible Civil Transport Aircraft : Structured H-Infinity Synthesis

New generation of civil transport aircraft can present aeroelastic coupling between flight mechanics and structural dynamics. The lower-frequency flexible dynamics can be perceptible by a fly-by-wire controller. This requires control law design that take into account the flexible dynamics. Robust control techniques have been investigated over the past 20 years for this purpose. They result in highly complex black box dynamical controller with a large number of states. It requires strong efforts to simplify the controller.

A green technology project: Development and production of eco-responsible, innovative biodegradable, recyclable and compostable food packaging materials based on natural fibers

Technological challenges in the pulping process of cellulosic fibers of different origins that can provide an optimal eco-responsible, biodegradable, recyclable and compostable alternative to polluting styrofoam packaging. AecopaQ stands out by using natural fibers grown and processed locally to the production of packaging trays for the food industry. AecopaQ is part of Canada's sustainable development agenda.