Projets novateurs réalisés

Impact Investing in Underserved Communities – University of British Columbia

This project will support Propel Impact in engaging and building relationships with organizations advancing impact investing in underserved communities.

Imitation learning based control for quadrupedal robots

This project aims to make quadruped robots smarter and more versatile by adding a 360-degree camera and a robot arm into a reinforcement learning control system. The quadruped robots will undergo training with these upgrades in a simulation environment before being deployed in real-world scenarios. These upgrades will help the robots better understand their surroundings and interact with objects, making them more useful in real-world situations like search and rescue missions or exploring rough terrain. By working on this project, participating institutions will gain valuable insights into advanced robotics technology, which can be applied to various fields such as healthcare, manufacturing, and disaster response, ultimately advancing scientific knowledge and societal well-being.

Fault zone reactivation and structural inheritance in accretionary orogens

The strength and behaviour of the Earth’s crust is largely controlled by the presence and nature of plate boundaries—the boundaries that separate Earth’s jigsaw puzzle of tectonic plates. When movement occurs between two rigid crustal blocks, the resulting deformed zone that forms along the boundary is referred to as a deformation zone. Recent research has focused on the physical manifestation of deformation zones at depth, however, despite their key role in controlling crustal strength over long geologic timescales, how deformation zones evolve over time and space remains poorly understood. The purpose of this project is to analyze previously collected samples from two different deformation zones and reconstruct the tectonic histories of each one. This will be accomplished through a combination of novel analytical techniques, including geochronology (dating rocks) and microstructural analysis. This research will contribute significantly to our broader understanding of how deformation zones evolve by providing a general framework for the structural and temporal evolution of these systems. These results will have direct implications on our understanding of how the strength and behaviour of the Earth’s crust can vary over long timescales and will improve seismic risk assessments of modern-day plate boundaries that pose a potential seismic hazard.

Lignin valorization for the production of high-value added materials for environmental applications

In recent years, lignin valorization has been given more attention by the scientific community, hoping to make breakthroughs in the field. Thus, this project aims to attribute value to lignin biomass (sugarcane bagasse and sugarcane straw from Brazil and kraft lignin from Canada), an industry by-product that is currently being discarded as industrial waste on a ton scale. Most of the lignin waste material is either disposed or burned as low-grade fuel, posing a severe environmental hazard. Thus, this project will be based on the conversion of lignin into biochar at different process conditions and to be evaluated as adsorbents for mining water treatment. The sorption capacity of lignin-adsorbent materials will be comparable to commercial activated carbons.

Boron nitride nanotubes and nanocellulose composites for aeronautical applications

In the last twenty years, many efforts have been made to study the incredible properties that boron nitride nanotubes (BNNTs) and nanosheets (BNNSs) have presented since their discovery, especially through their excellent performance in the aerospace industry. In parallel, bio-based materials such as nanocellulose have been considered a cheap and attractive material for developing nanocomposites together with BNNTs and BNNSs to reduce their overall cost. Thus, this research project aims to study the synthesis of BNNTs, BNNSs together with nanocellulose fibers (NFCs) formulations, varying the concentrations of each substrate, characterizing them through physicochemical analyses, and comparing their performance with any similar off-the-shelf products.

Harnessing Algorithms and Machine Learning for Sales Recruitment Platform through Artificial Intelligence Integration

Just Sales Jobs prioritizes quality candidates and collaborates with clients to positively impact their businesses. Sales recruiting is a challenging task due to its labor-intensive nature and reliance on recruiters’ experience and skills. Just Sales Jobs aims to enhance their recruiting process by integrating Artificial Intelligence (AI) and Machine Learning (ML) technologies through a partnership with Lambton College. The research objectives include assessing current sales recruiting challenges, defining optimal criteria for evaluating sales candidates, developing AI/ML models for candidate screening and assessment, and validating the effectiveness of the approach. Successful implementation will allow Just Sales Jobs to expand the technology into Canadian and U.S. territories, creating approximately 27 new job positions by 2026 and contributing the growth of the Canadian economy and advancement in the IT sector.

APS Sensor for Adaptive Driving Devices

Howell Ventures Ltd (HVL) is a world leader in the development, production, and sale of adapted driving aids. As OEM throttle systems the world over have shifted from mechanical to electronic over the past 20 years, the mobility industry has needed to adapt their products to interface with these systems. While this goal has been accomplished by a number of companies across the world, including HVL, they are all using Accelerator Position Sensors (APS) which are not fundamentally designed with adaptive products in mind. This project seeks to investigate an APS which is tailored for the functional and aesthetic needs specific to adaptive applications.

The intern will work closely with the various departments within HVL including electrical engineering, production, marketing and injection molding to achieve success. Availability of in-house production methods will pose a constraint that the intern will need to include in the research of design methods. Having an in-house APS will provide HVL, and potentially the larger Canadian accessibility market, with various advantages including product consistency, cost reductions, functional improvements and isolation from international supply chain disruptions.

Advancing the Downstream Hydrogen Supply Chain in Newfoundland and Labrador

Newfoundland and Labrador (NL) is embracing the global shift towards clean energy with a commitment to achieving net-zero emissions. Our research project, funded by Cenovus Centre for Sales and Supply Chain Management and Mitacs, focuses on optimizing NL’s Hydrogen Supply Chain (HSC) to harness its abundant renewable energy resources effectively.
Aligned with the goals of the Cenovus Centre for Sales and Supply Chain Management at Memorial University, our project aims to enhance the sustainability and competitiveness of NL’s hydrogen supply chain downstream.
This strategic investment in NL’s future not only drives innovation but also fosters economic growth and sustainability. By positioning NL as a global leader in clean energy technology, we are creating new opportunities for businesses and contributing to the well-being of our province and its residents.

Association Mapping of Phytochemical Composition and Antioxidant Properties in Whole Grain Rice (Oryza sativa L.)

Phytochemicals including vitamins, carotenoids and phenolic compounds have been widely accepted as the functional substances that make cereal grain health beneficial. Increasing evidence has shown the relation between these antioxidant phytochemicals and reduced risks of oxidative-stress related chronic diseases, such as cardiovascular disease, diabetes and some cancers. Among these cereal grains, rice is of critical importance in agriculture, because of its wide consumption over the world. To breed functional rice with elevated level of phytochemicals, understanding the genes that manipulate the expression of these traits is necessary. This study aims to investigate the genetic bases of phytochemical content in relation to antioxidant properties through the use of association mapping. In other words, the genes that control the levels of phytochemicals in whole rice grains will be identified and related to antioxidant activities. Samples investigated in this study will include yellow, red, purple and black rice, and white rice is used as a control. This study will provide genetic information to improve the health-beneficial properties of rice if marker-assisted selection of breeding is used.

Does the requirement to use DairyTrace ear tags in proAction affect the value of beef × dairy calves at the time of sale?

Does the requirement to use DairyTrace ear tags in proAction affect the value of beef × dairy calves at the time of sale, and how do factors such as calf management practices, marketing timing, and seasonal variations influence Holstein and Holstein × beef calf prices?

Analyse holistique des céramiques mésoaméricaines du Musée des Beaux Arts de Montréal

La majeure partie des collections précolombiennes possédées par les institutions muséales n’ont généralement pas de données sur l’origine et les artistes autochtones qui les ont créées sont inconnus. Puisque les œuvres d’art découlent de dons faits par des particuliers, la grande majorité des informations contenues dans les archives sur ces pièces céramiques concernent les donateurs des pièces aux musées durant le XXe siècle (Hubert and Pimentel 2013). Ce projet vise à découvrir davantage le côté autochtone des objets précolombiens du Musée des Beaux Arts de Montréal à travers (1) des analyses physicochimiques, (2) des recherches sur leur style les reliant à des communautés du passé archéologiquement identifiées (sites et régions antiques) ainsi que (3) leur documentation numérique. Plusieurs méthodes d’analyses chimiques permettent d‘identifier le lieu d’origine des artisans anciens, tel que l’utilisation de la fluorescence par rayons X. Notre recherche permettra ainsi de reconstruire une partie de la biographie de l’objet et permettra de remettre les mains de l’artiste sur sa création.

Audio Structural Analysis for Music Segmentation

This project aims to explore how state-of-the-art deep learning models can accurately identify and label musical sections like the “verse” and “chorus” across various musical genres. The research will begin by examining available datasets for music structural segmentation, as well as recent deep learning methods suitable for this data. Following the exploration of available data and models, the team will conduct experiments to assess the strengths and capabilities of the different models, proposing enhancements as needed. By training and testing these models, the goal is to simplify music production in digital audio workstations and music notation editors.

Ultimately, this research aims to streamline the creative process for musicians, sound engineers, and composers, making their workflows with audio software faster and smoother by automatically locating and labeling sections of musical compositions.