Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

29670 Completed Projects

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Projects by Category

La gestion des revenus en restauration; la pratique en période de reprise après Covid-19 pour les établissements de restauration à service complet

Ce projet de recherche porte sur les pratiques de gestion des revenus en restauration en période de reprise à la suite de la pandémie Covid-19, plus particulièrement pour les restaurants qui offrent un service complet.
Les restaurateurs ont l’une des marges bénéficiaires les plus faibles de l’industrie hôtelière et en cette période de reprise, ils voient leur marge se réduire encore en raison de l’augmentation prévue des coûts de main-d’oeuvre et de nourriture. Ils sont encore soumis à des restrictions sanitaires qui font qu’ils ne peuvent pas opérer à pleine capacité. Les restaurateurs vont donc chercher des moyens de renouer avec les profits afin de rester en activité. Une façon d’augmenter les revenus est d’utiliser des stratégies dîtes de gestion des revenus. La question qui se pose est : comment et jusqu’à quel point ces stratégies sont-elles mises en oeuvre pendant et après la pandémie de la Covid-19?
Des entrevues avec des gestionnaires de restaurants indépendants et des gestionnaires des revenus d’hôtels permettront d’identifier les bonnes pratiques ainsi que de mieux comprendre la nature des difficultés rencontrées.

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Faculty Supervisor:

Riadh Ladhari;Marie-Claire Louillet

Student:

Partner:

Société des Casinos du Québec

Discipline:

Business

Sector:

Arts, entertainment and recreation

University:

Université Laval

Program:

Accelerate

Modeling and optimization for designing smart freight platform

This research is motivated by the need to coordinate matching and pricing decisions in resource sharing platforms. In general, matching decisions can be seen from different standpoints of shippers, carriers, and the platform. We are particularly interested in investigating the matching problem considering all standpoints simultaneously, which has not received much attention in the literature review. Furthermore, trending toward new freight procurement mechanisms managed by a third party increases the importance of applying dynamic pricing policies to respond to market fluctuations and satisfy all trading parties. This mechanism needs to valorize real-time data to provide the best price recommendation according to the market circumstances. The recommended price can facilitate the trading mechanisms and provide a balanced tradeoff between different sides of the market. This trade-off can, in turn, result in less need for negotiation in the market and more facilitated transportation service procurement mechanisms.

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Faculty Supervisor:

Samira Keivanpour;Maha Ben Ali

Student:

Partner:

ShipHaul Logistics Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Transportation and warehousing

University:

Polytechnique Montréal

Program:

Accelerate

Anomaly Detection in Highly Noisy Signals from Electrical Rotating Machines

Equipment failure is the primary source of unplanned downtime in industries working with rotating electrical machines. Fault detection at the early stages is an essential solution for reducing this downtime. Condition monitoring of machinery is the process of capturing and monitoring parameters such as vibrations to identify a developing fault. This project uses the data resulting from condition monitoring to develop anomaly detection algorithms for improving early-stage fault detection and diagnosis processes.

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Faculty Supervisor:

Faramarz Samavati

Student:

Partner:

AB Cognitive System Inc.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Développement de nouveaux algorithms pour accroître la precision, la robustesse et la reproductibilité d’instruments intelligents en réponse aux exigence de l’industrie

Le monitoring en temps réel des bioprocédés permet d’augmenter les performances et de réduire les pertes. La principale
difficulté provient de la quantité limitée d’information accessible en temps réel et des phénomènes complexes et fortement
non-linéaires en présence. Ainsi, les algorithmes statistiques conventionnels ne permettent pas d’interpréter adéquatement et
avec la précision requise en pharmaceutique les signaux mesurés par des sondes spectrales. L’objectif du projet est de
développer de nouveaux algorithmes non-linéaires complexes qui permettront de réaliser la transformation de signaux
spectraux bruts complexes en indicateurs de performances précis, robustes et reproductibles. Ce projet permettra de
développer un algorithme qui améliore les performances d’estimation en temps réel des concentrations de produits dans des
cultures cellulaires pharmaceutiques. Ces algorithmes utiliseront l’apprentissage profond pour modéliser les phénomènes nonlinéaires
et s’appuieront sur le transfert d’apprentissage pour permettre l’entraînement avec peu de données.

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Faculty Supervisor:

François Grondin

Student:

Partner:

BioIntelligence Technologies inc

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Are phenolic enrichments along with rewetting a necessary approach towards carbon sequestration, impeding decomposition, and optimized Sphagnum productivity?

Peatlands act as vast carbon (C) reservoirs by regulating decomposition over millennia. Considerable changes due to anthropogenic activities such as peat extraction have shifted long-term C sink to atmospheric C source. Previously, bioengineering tools as rewetting were used to reverse post-extracted peatland hydro-physical properties, and phenolic addition was used on small scale to test the enzymic latch process but ends up with contradictory results. Therefore, we aimed to combine rewetting with phenolic addition on large scale to strengthen enzymic latch and to test how it can suppress enzymes activities, reduce peat decomposition, promote Sphagnum productivity, and limit greenhouse gas emissions. For this, multiple measurements such as carbon flux, decomposition rate, Sphagnum biomass and productivity will be conducted in Quebec, while extracellular enzymes activities will be analyzed in Bangor University, Wales. It is expected that proposed technique will strengthen the enzymic latch and will help to formulate strategies for reducing C emissions in the peatland ecosystem.

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Faculty Supervisor:

Line Rochefort

Student:

Partner:

Bangor University

Discipline:

Life Sciences

Sector:

Education

University:

Université Laval

Program:

Globalink Research Award

From Hammers to Homes: a housing development report for Metro Vancouver

The From Hammers to Homes project seeks to engage one masters student intern for two semesters to work with the partners in order to design a new database and conduct a new annual survey to report on improving the quality and transparency of information on the residential development environment in regional Vancouver’s municipalities. The interns will conduct survey, interview, secondary and case study-based research, consultation across the spectrum of interests in housing policy and development issues in metropolitan Vancouver, and will construct and maintain a unique database. The Greater Vancouver Home Builders Association expects to benefit from this project that will help the hands holding the hammers to build the housing that our region needs, recognizing the vital role of a predictable and accountable municipal policy process, not for developers and municipalties to “hammer” each other with problems, but to move residential development in the direction of the public interest, affordability, innovation and sustainability.

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Faculty Supervisor:

Meg Holden

Student:

Partner:

Greater Vancouver Home Builders’ Association

Discipline:

Earth science

Sector:

Construction and infrastructure; Other services (except public administration)

University:

Simon Fraser University

Program:

Accelerate

A Deep Learning approach to identify and localize room assets using handheld RGB-D sensors

With the availability of low-cost edge devices equipped with color and depth sensors, such as iPhone or iPad, 3D data capturing is becoming more accessible and convenient. Asset managers and building owners seek benefiting from this potential to accurately and automatically create 3D indoor models of buildings. In particular, having 3D indoor models containing objects of interest enables several applications, such as asset inventory and maintenance management. However, the automatic and accurate generation of such 3D models introduced many challenges, and the current methods exposed several limitations. This research project aims to propose and implement a framework, which employs various state-of-the-art computer vision techniques, to overcome the current limitations.

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Faculty Supervisor:

Ali Motamedi;Érik Poirier

Student:

Partner:

Planifika

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

Interactions of mesoscale eddies and sea ice

Fundamental questions remain on how polar oceans will respond to climate change and how rapidly changes will occur. Based on observations made from satellite, there is growing evidence that ocean and sea ice interact at scales on the order of a few tens of kilometers, the mesoscale. However, it is not clear how exactly the ocean is shaping the sea ice cover and what is its subsequent impact on sea ice melt. This project makes use of numerical simulations of the ocean and its sea ice cover. With the help of these simulations, which aim at representing approximately the Southern Ocean, the direct and indirect effects of the mesoscale on sea ice in areas of high sea ice concentrations will be investigated. These impacts could be mechanical, induced by the motions of sea ice and water, or thermodynamical, driven by the heat stored in the ocean. Several simulations will be analyzed to account for different oceanic and atmospheric conditions in order to improve our understanding of the mesoscale’s influence on sea ice in a changing climate.

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Faculty Supervisor:

Carolina Dufour

Student:

Partner:

California Institute of Technology

Discipline:

Earth science

Sector:

Education

University:

McGill University

Program:

Globalink Research Award

Acquisition of an aviation safety taxonomy from incident reports and its evaluation

Ontology induction from unstructured text is a long standing goal of Natural Language Processing (NLP). An ontology can serve a number of tasks, such as question answering, Information Retrieval to name a few. In fact, practice communities are often relying on an ontology in their daily decision making process. This is the case of IATA, the partner in this proposal, which currently manually labels aviation incident reports into nodes of an in-house ontology. This time-consuming task is typically conducted by experts. One problem with relying with an ontology is the ontology itself which should evolve over time (e.g., new types of incidents) and is often fraud with inconsistencies. The ontology at IATA is no exception and the goal of the project is to evaluate existing extraction technologies in order to see how useful would an automatically extracted ontology be. One issue with such an endeavor is the evaluation of an ontology. This is typically conducted by asking experts to conduct a manual evaluation. This is at the very least a tedious exercise that definitely prevents the optimization of the acquisition process. Therefore, in this proposal, we also address the issue of automatically evaluating an ontology.

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Faculty Supervisor:

Philippe Langlais

Student:

Partner:

International Air Transport Association

Discipline:

Computer science

Sector:

Other services (except public administration); Professional, scientific and technical services; Transportation and warehousing

University:

Université de Montréal

Program:

Accelerate

Machine Learning and Stochastic Chemical Modelling: A Novel Synthesis for Emissions Mitigation

Combustion-generated particles called ‘soot’ are the second worst contributor to climate change and are carcinogenic to humans. The formation of soot in combustion devices, however, remains poorly understood. It is therefore essential to gain a better fundamental understanding of soot formation to help reduce soot emissions and mitigate its negative effects on humans and the planet. To facilitate this understanding, the proposed research will develop an Artificial Intelligence (AI) algorithm to predict the rate at which soot is nucleated in flames. Chemical modeling software developed at the University of Michigan will provide highly detailed information about thousands of chemical species in flames. An AI algorithm will learn to predict soot formation from this data pairing, and can then be applied to predict soot formation in other systems. The AI algorithm will improve our understanding of soot formation; how much forms and under what conditions. Improving our scientific understanding and creating a robust soot prediction algorithm will inform engine and other combustion device designers and enable them to select designs with minimal soot production.

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Faculty Supervisor:

Seth Dworkin

Student:

Partner:

University of Michigan

Discipline:

Engineering

Sector:

Education

University:

Toronto Metropolitan University

Program:

Globalink Research Award

Commodification of Traditional Musical Modalities and Cultural Identity (Re)constructions on Prince Edward Island,1980s to the Present

This project explores the commodification and marketing of traditional Prince Edward Island musical culture over the past forty years in light of the experiences and understandings of individuals who have been prominent players in the traditional music sector over the past four decades. This process will be explored by investigating the relationships that exist between major government/government-adjacent organizations (cultural and touristic funding organizations) and the traditional musicians who apply for and receive said funding. The researcher anticipates that the outcome of the study will demonstrate the subtle ways in which funding processes like cultural or tourism grants create incentive for artists to shape their artistic expression and their own conceptions of traditionalism, as well as the ways by which artists may offer resistance to these pressures.

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Faculty Supervisor:

Lisa Chilton

Student:

Partner:

Fédération culturelle de l’Île-du-Prince-Édouard

Discipline:

Sociology

Sector:

Information and cultural industries

University:

University of Prince Edward Island

Program:

Accelerate

Business Strategy Internship with Planetary Hydrogen

This 8-month project will help advance Planetary Hydrogen’s efforts to demonstrate and certify it’s SeaOH2 process by:
1. Explore the Canadian CDR policy landscape and developing a strategy to inform policy-makers of Ocean-based CDR methods;
2. Work with Ocean Scientist, regulators and other stakeholders (such as community groups, environmental non-governmental organizations and partner for-profit entities) to determine a certification pathway(s) for OAE, and other Ocean based CDR methods; and
3. Work with the PH Business Development and Engineering Teams to develop a full-project proposal for a first-of-it’s kind 1 ton per day carbon capture pilot plant to demonstrate not only the innovative technology, but an innovative circular business model that seeks to generate multiple revenue streams from waste products such as mine tailings, while leveraging existing processes such as waste water treatment for climate and ocean restoration.

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Faculty Supervisor:

Yuri Leonenko

Student:

Partner:

Planetary Hydrogen

Discipline:

Earth science

Sector:

Administrative and support, waste management and remediation services

University:

University of Waterloo

Program:

Business Strategy Internship

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