Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

29 670 projets achevés

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801
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568
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Projets par catégorie

Uptime Energy Control Procedure Using Machine Learning

In a time where energy use awareness is more and more prevalent due to its significance in global warming, all sectors of society are putting effort to participate in finding new ways to reduce energy consumption. The industrial sector in Canada consumes nearly 1/3 of total energy. A challenge for industrial organizations is to define improvement actions that will significantly reduce the energy consumption of their production facilities, resulting in significant energy savings, while maintaining an adequate level of production for its customers. However, in industrial processes, there are complex dynamics between energy and a large number of process variables that affect energy consumption. Recent advances in machine learning combined with the vast availability of process data thus make process industries ideal candidates for energy performance optimization. TO BE CONT’D

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Superviseur du corps professoral :

François Bouffard

Étudiant :

Partenaire :

Energy Performance Services (EPS) Inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

McGill University

Programme :

Accelerate

Quantification and characterization of food waste in Canadian households: case of Waterloo region

This research project is aimed at developing a food waste inventory at household level for the Region of Waterloo to assess the associated environmental impacts and to identify the potential for future reduction. Due to lack of similar research in Canada, there is only a limited knowledge on the methodological approaches for food waste audits at household level. Thus, the knowledge and experience from prior and ongoing food waste research in Denmark is used to enhance the strength of the above food waste inventory by working with the Danish experts. This research will provide the much needed primary data for food waste generation at households in Canada, enabling the local and provincial governments to design, implement and monitor the progress of food waste reduction programs.

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Superviseur du corps professoral :

Komal Habib

Étudiant :

Partenaire :

Technical University of Denmark

Discipline :

Life Sciences

Secteur :

Education

Université :

University of Waterloo

Programme :

Globalink Research Award

Probiotics for improved carotenoid bioavailability: A double-blind, randomized, controlled trial

There is a simple way to have great skin, be more attractive, and improve one’s health, but most of the global population refuses to do it. Worldwide fruit and vegetable (FV) intake is below recommendations reducing the intake of yellow-red plant pigments that have antioxidant, anti-inflammatory, anti-cancer, and anti-obesity properties. These plant pigments are called carotenoids and are largely stored in the skin. In fact, a yellow-red glow in the skin indicates FV intake, independent of race or tanning, and is correlated with improved attractiveness. Not everyone absorbs carotenoids in the same way, however, and the health and types of bacteria in the gut might account for a large portion of the differences in carotenoid absorption. This study was designed to determine whether the health of bacteria in the gut might have an influence on the absorption of carotenoids.

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Superviseur du corps professoral :

Stan Kubow

Étudiant :

Partenaire :

Lallemand Health Solutions Inc (Montreal, QC)

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

McGill University

Programme :

Accelerate

Manualization of occupational performance coaching for stroke survivors

Approximately 300,000 Canadians live with the effects of stroke. These effects include problems with mobility, cognition, speech and mood. Returning to personally valued activities following stroke can be quite difficult. In fact, the majority of stroke survivors, across all disability levels, report problems occupying their time in meaningful ways. This is particularly troubling as, while health providers tend to view stroke recovery in terms of changes in discreet aspects of disability, stroke survivors define recovery largely in terms of how well they have been able to return to their valued activities. Researchers have not yet developed an effective, efficient intervention for problems in this area that has long-lasting benefits. In our lab, we have begun to test a promising intervention called Occupational Performance Coaching (OPC). The goal of this project is to analyze pilot data from a first application of OPC with 5 patients and develop a manual for this……TBC

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Superviseur du corps professoral :

Mary Egan

Étudiant :

Partenaire :

Heart and Stroke Foundation of Canada (ON)

Discipline :

Life Sciences

Secteur :

Université :

University of Ottawa

Programme :

Accelerate

Develop a reliability-based robust shoring design system using Excel

The project is to develop a robust shoring design system using Excel software. A shoring system is a group of structural elements used to support/retain earth pressure during the construction of underground structures. Its design is influenced by many variables, such as the intended use of systems, earth pressure selection, performance of different systems, ground conditions, soil strength, and loading effects. Many of these variables cannot be easily interpreted, for example, accurate characterization of the highly variable glacial deposits covering the GTA. The risks are also extremely high for safe construction of a shoring system due to adjacent properties in densely populated urban settings. Due to these uncertainties and risks, it can easily lead to an inconsistent and unsafe design. This research is to develop an Excel-based design software by integrating the reliability-design concept for achieving cost-effective infrastructure development in Canada.

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Superviseur du corps professoral :

Jinyuan Liu

Étudiant :

Partenaire :

Groundbreaking Foundations Inc

Discipline :

Engineering

Secteur :

Construction and infrastructure

Université :

Toronto Metropolitan University

Programme :

Accelerate

Apprentissage profond semi-supervisé pour la segmentation et l’analyse d’images d’équipements de réseau électrique

La maintenance du réseau de distribution d’électricité d’Hydro-Québec exige d’exploiter une quantité astronomique d’information concernant la localisation et l’état des actifs. Ce projet propose de développer des approches efficaces à base d’intelligence artificielle pour l’inventaire et le diagnostic automatisé et en continu des équipements du réseau de distribution. De nouveaux algorithmes d’apprentissage automatique, utilisant peu de données d’entraînement, seront développés pour la détection et la segmentation d’objets d’intérêt dans les images. Ces algorithmes seront ensuite appliqués pour identifier et géo-localiser les poteaux électriques à partir d’images prises avec un appareil mobile, segmenter ces poteaux et leur transformateur dans les images, et prédire l’état de ces équipements afin de déterminer s’ils nécessitent de l’entretien ou un remplacement éventuel. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Christian Desrosiers

Étudiant :

Partenaire :

Institut de Recherche Hydro-Québec

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Utilities

Université :

École de technologie supérieure

Programme :

Accelerate

Increasing real-time video streaming performance over Wi-Fi networks

This project focuses on improving the performance of the real-time video streaming over Wi-Fi networks, in which losing packets is a serious concern. State-of-the-art methods try to improve the robustness of AL-FEC mechanisms by providing unequal protection to the packets. But such approaches are complex and increase even more the delays. In contrast, the proposed research will study how to dynamically select the packet size and the period of AL-FEC redundant data (number of rows and columns in AL-FEC), crucial parameters for real-time applications. The research will study how to adjust the packet size dynamically based on estimated communication conditions (e.g. the number of packets received without error versus damaged ones, etc.) by using machine learning approaches. Appropriate selection of packet size will optimize the effective throughput as the network conditions change. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Stéphane Coulombe

Étudiant :

Partenaire :

Summit Tech

Discipline :

Engineering

Secteur :

Information and Communications Technology; Entertainment and Media; Technology

Université :

École de technologie supérieure

Programme :

Accelerate

Structural and Hygrothermal Performance of Masonry Walls with Large Cavities

A veneer wythe protects the indoor environment and other building components against adverse outdoor effects, such as rain and physical impacts. Veneer walls are connected to a structural substrate (e.g. wood frame or masonry units) by ties. These are usually made of steel and therefore high in thermal conductance. The ties penetrate the thermal insulation layer between the veneer and structural substrate and hence act as uniformly distributed point thermal bridges. In conventional thermal analysis, their presence is usually neglected. However, with the advent of newer energy codes that require larger cavities to accommodate thicker insulation layers and performance-based thermal analysis, the structural and thermal performance of the ties must be carefully assessed. To enhance the durability and sustainability of Canadian infrastructure it is necessary to develop a new tie system for large cavity walls, and test its performance with full-scale experimentation.

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Superviseur du corps professoral :

Carlos Cruz Noguez

Étudiant :

Partenaire :

FERO Corporation

Discipline :

Engineering

Secteur :

Construction and infrastructure

Université :

University of Alberta

Programme :

Accelerate

Feasibility Study to Determine the Application of Unmanned Aerial Vehicle for Aircraft Inspection

This project assesses the feasibility of using drones to inspect aircraft for surface damage and defects such cracks, fractures or dents. The intern will first carryout a comprehensive literature review and environmental scan of the existing technology. He will then assist in developing and conducting a series of physical tests to determine the best camera parameters, drone flight pattern, image format and proximity sensor performance. The results of these tests will be used to program a commercially available drone to carryout an automated image acquisition flight. The images will then be used to generate an accurate 3D model of the surface condition of the aircraft which will be automatically analyzed for defects.
The overall goal of the project is to develop drone-based aircraft inspection standards of practice which will improve defect detection, safety and inspection efficiency.

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Superviseur du corps professoral :

Eric Saczuk;Sanja Boskovic

Étudiant :

Partenaire :

Spexi Geospatial

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

British Columbia Institute of Technology

Programme :

Accelerate

Automated Target Classification for Multi-Frequency Echosounders

The oceans cover the majority of our planet’s surface but much of their depths are still a mystery. Improvements in technology have allowed for the development of instruments on underwater platforms and autonomous gliders that are able to survey the world’s oceans. One instrument, called an AZFP (acoustic zooplankton fish profiler), emits high-frequency sonar pulses and listens for backscatter (reflections) to observe fish, zooplankton, suspended sediments, and other quantities in the water column. Backscatter data are complex and time consuming to process and interpret. This study seeks to use recent improvements in Machine Learning to automate the processing and interpretation of backscatter data to reduce the time and manual effort required. Some studies using Machine Learning have already been carried out, but these focused specifically on certain species of fish and plankton and ignore everything else. However, animals in the ocean are also affected by their environment. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Stan Dosso

Étudiant :

Partenaire :

ASL Environmental Sciences Inc

Discipline :

Earth science

Secteur :

Professional, scientific and technical services

Université :

University of Victoria

Programme :

Accelerate

DESIGN OF A NOVEL HEAT EXCHANGER TEST RIG

Heat exchangers, used in building heating, ventilation and air conditioning (HVAC) systems to transfer heat from hot to cold fluids, are designed to operate under ideal conditions. However, in practice operating conditions may vary with ambient temperature or humidity. HVAC system efficiency can be improved significantly if fluid flow rates are adjusted in response to such changes. Armstrong Fluid Technology is a Canadian firm that has developed control systems to adjust the flow through building heat exchangers to maximize their efficiency. This project is being undertaken to develop a heat exchanger test rig and to use it to determine heat exchanger efficiency as a function of fluid temperatures and flow rates. The feedback control system will reduce the energy required for operating an HVAC system by approximately 30% and have a significant impact on Canada’s energy usage and greenhouse gas emissions.

Voir la description complète du projet
Superviseur du corps professoral :

Sanjeev Chandra

Étudiant :

Partenaire :

Armstrong Fluid Technology

Discipline :

Business

Secteur :

Manufacturing

Université :

University of Toronto

Programme :

Accelerate

Removal of Micropollutants from Wastewater by Immobilized Laccase on Hollow Silica Embedded Plastic Packing Reactor

Micropollutants can be found in almost all water bodies due to their recalcitrant character. As conventional treatment plants are not efficient for many recalcitrant pollutants, oxidative methods and physical treatment methods have been widely applied for treatment of wastewater.
Green enzyme-Laccase has high ability to transform many kinds of micropollutants, such as recalcitrant contaminants, into oxidized products that are less bioavailable or even harmless, as well as stable water-insoluble polymer derivatives. This project aims to promote laccase catalyzed treatment for removal of pharmaceuticals in pilot scale systems by using immobilized laccase on silica embedded packing by using partially purified laccase from P. Dryinus strain. Particularly, this project aims tor emove of pharmaceuticals from real wastewater and to evaluate the system durability and cost efficiency.

Voir la description complète du projet
Superviseur du corps professoral :

Hubert Cabana

Étudiant :

Partenaire :

Materium

Discipline :

Engineering

Secteur :

Manufacturing; Utilities

Université :

Université de Sherbrooke

Programme :

Accelerate

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