Innovative Projects Realized

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

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

Repenser le restaurant de demain : vers le développement d’un indice synthétique d’intégration des nouvelles tendances de consommation

Compte tenu du contexte unique actuel auquel le secteur de la restauration fait face, dû à la pandémie de la Covid-19 (modification de l’expérience de consommation, digitalisation des pratiques, inflation, pénurie de main-d’oeuvre) et à l’évolution des modes de consommation (progression de l’alimentation saine, du cuisiné maison, des boîtes de repas « prêts à cuisiner » et de la livraison à domicile), Benny & Co souhaite se doter d’un outil d’analyse de prospective des tendances de consommation afin d’adapter ses établissements.
Ce projet de recherche a pour objectif de développer une mesure fiable du « restaurant de demain » et de favoriser le transfert de connaissances en proposant un outil d’évaluation de la performance de la réponse aux nouvelles tendances sous la forme d’un indice synthétique. Il évalue pour chaque tendance son niveau d’importance (, son taux de pénétration, son niveau d’opinion et son niveau d’utilisation future par rapport à la clientèle.

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Faculty Supervisor:

Fabien Durif

Student:

Partner:

Benny & Frères Inc.

Discipline:

Business

Sector:

Accommodation and food services

University:

Université du Québec à Montréal

Program:

Accelerate

Vers une meilleure gestion de la sécurité avec la Fondation LOJIQ – Les Offices Jeunesse Internationaux du Québec: Gestion d’identités, classification des actifs informationnels, classification des incidents de sécurité.

La fondation Les Offices Jeunesse Internationaux du Québec (LOJIQ) explore de nouvelles approches de renforcement de la sécurité informatique et de la lutte contre les cybermenaces. LOJIQ travaille au quotidien avec plusieurs partenaires qui attendent d’elle une meilleure protection de leurs renseignements. Malheureusement les mécanismes actuels de sécurité connaissent des faiblesses relativement à la gestion des identités et des accès, à la classification des actifs informationnels et à la gestion des incidents. La présente demande de recherche vise donc plusieurs objectifs au premier rang desquels l’identification et l’évaluation des solutions existantes de gestion des identités et des accès, de classification des actifs informationnels et de gestion des incidents de sécurité. Il sera par la suite question de proposer une solution de gestion décentralisée des identités et des accès qui garantissent au mieux la protection des données sensibles et proposer une solution de classification automatique des actifs informationnels et des incidents de sécurité qui s’appuie sur l’intelligence artificielle explicable.

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Faculty Supervisor:

Mohamed Mejri

Student:

Partner:

Fondation des Offices jeunesse internationaux du Québec

Discipline:

Computer science

Sector:

Other services (except public administration)

University:

Université Laval

Program:

Accelerate

Searching for Mushroom Extracts and Fractions with Potential Antidepressant Activity

Mental illnesses, particularly depression, are one of the leading causes of global disease burden. In addition to reducing the quality of life of patients and their relatives, they costs billions of dollars annually to the Canadian economy. Unfortunately, current antidepressant drugs are barely satisfactory and have numerous side-effects. The goal of this project is to discover potential new extracts, fraction or compound(s) with potential antidepressant activity from wild mushrooms native to British Columbia. This is in line with the objective of Translational Life Sciences (TLS) Inc., a biotechnology company based in Vancouver. TLS will have the proprietary rights to any discovered extracts, fraction or compound(s) and is therefore expected to benefit financially in the near future.

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Faculty Supervisor:

Chow Lee

Student:

Partner:

Translational Life Sciences Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Northern British Columbia

Program:

Accelerate

Usage de récits mémoriels pour approfondir un dispositif intégratif lecture littéraire et pensée historienne

La lecture d’un témoignage d’un survivant de l’Holocauste humanise la découverte du passé et peut inviter tout lecteur à apprivoiser l’inconnu, lui permettre d’enrichir son bagage interprétatif en lui présentant d’autres perspectives, dont certaines demeurent encore dans l’ombre (ex. enfants, femmes). Or, à l’heure actuelle, peu de balises claires existent afin d’aider les enseignants, en formation comme en exercice, à explorer le potentiel heuristique et éducatif d’un récit mémoriel en contexte secondaire pour œuvrer à la formation de citoyens sensibles et critiques au moyen de la lecture.

En continuité et en cohérence avec la recherche doctorale en design que nous poursuivons, ce projet vise à approfondir un dispositif didactique, nommé travail d’enquête historico-littéraire, destiné à l’enseignement du français et de l’histoire. Ce dispositif a pour but d’atténuer certains défis d’ordre curriculaire, didactique et contextuel rencontrés par les enseignants pour renforcer le caractère significatif et vivant de l’enseignement-apprentissage de la lecture. La mise à disposition du travail d’enquête que nous proposons pourrait d’ailleurs contribuer à conduire les élèves à mieux comprendre le processus génocidaire et ce qu’il sous-tend (ex. manifestations, effets, mesures de prévention) à partir d’un témoignage écrit.

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Faculty Supervisor:

Sabrina Moisan;Sivane Hirsch

Student:

Partner:

La Fondation Azrieli

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

Université de Sherbrooke

Program:

Accelerate

Perception pipeline for automated compound sanding of gypsum plasterboard

Nowadays, many building contractors use modular construction, where various parts of a building are partially or
completely built on an assembly line and then put together on the delivery site. Building interior modules often
involve building and finishing plasterboard walls, including closing joints between panels and hiding fasteners or
defects. To do so, a gypsum-based compound is applied, let to dry, and sanded iteratively to achieve a regular
surface. This produces a considerable amount of fine dust, which can be a nuisance, especially in the closed
space of a manufacturing plant. In this project, we are investigating if various sensors (cameras, LIDAR, …) can
be used to detect and precisely locate the surfaces that need sanding, which is a crucial step in the automation
of the whole task.

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Faculty Supervisor:

François Ferland;Alexandre Girard

Student:

Partner:

RCM modulaire

Discipline:

Engineering

Sector:

Manufacturing

University:

Université de Sherbrooke

Program:

Accelerate

In vivo efficacy and safety of novel therapeutic host defense peptides

Biofilms are clusters of bacterial cells that grow together on a surface. Biofilms are often associated with infections (~65%) but they are exceedingly difficult to treat with conventional antibiotics and there are currently no biofilm-specific treatments available on the market. Some common biofilm-associated infections include skin and sinus infections as well as infections associated with implanted medical devices. There is an urgent need to develop alternative therapies that target biofilms and ABT Innovations has developed a series of synthetic peptides with potent antibiofilm activity that they intend to move towards clinical applications. The purpose of this project is to study the potential of these therapeutic peptides to cause local toxicity or inflammation at the site of administration, which is important information that will help inform ABT’s future clinical development. The novel antibiofilm peptide therapeutics will in turn benefit the Canadian community, providing a novel treatment option for biofilm-associated infections.

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Faculty Supervisor:

Robert Hancock

Student:

Partner:

ABT Innovations Inc.

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Remediation of orphaned sites inundated with wood preservatives (pentachlorophenol & creosote), and detailed environmental impact assessment of dichloro-octyl-isothiazolinone (DCOI) on soil core and groundwater

There is a pressing need for studies centered on the impact assessment of emerging wood preservatives and the remediation of orphaned sites. The present proposal describes a dual-purpose research project. The project aims to; (i) apply a modified in situ chemical oxidation technique for the removal of pentachlorophenol (Penta) and creosote compounds in orphaned sites and; (ii) conduct a comprehensive environmental impact assessment of the dichloro-octyl-isothiazolinone (DCOI)-formulated wood preservative on soil cores and groundwater. Penta and creosote can be referred to as legacy pollutants. They used to be the foremost wood preservatives until their restrictions due to the toxicity potential they pose to humans and aquatic organisms. Conversely, DCOI is one of the present-day’s choices approved for use as a wood preservative in the United States. Findings from this project may provide some basis for DCOI’s approval for use in Canada; and this will be advantageous to Stella-Jones Inc.

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Faculty Supervisor:

Chijioke Emenike

Student:

Partner:

Stella-Jones Inc.

Discipline:

Life Sciences

Sector:

Agriculture; Manufacturing; Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Photogrammétrie en conditions difficiles améliorée par des modèles d’intelligence artificielle

La photogrammétrie est une technique de modélisation où on utilise plusieurs images prises tout autour d’un sujet afin de le reconstituer en 3D. Parfois, les conditions de capture influencent la qualité de la reconstruction 3D : des obstacles obstruent certains points de vue, l’éclairage est mauvais, etc. De plus, quand le sujet est difficile d’accès, il n’est pas toujours possible ou économique de retourner prendre de meilleures images. Dans ces cas, les algorithmes qui analysent les images n’arrivent pas à calculer les paramètres des caméras pour les différents points de vue, nécessaires pour les assembler en 3D, et la reconstruction échoue ou comporte des défauts. Le CDRIN vise donc à développer, à l’aide de l’intelligence artificielle, un modèle capable d’améliorer le calcul des paramètres des caméras en photogrammétrie, plus robustes par rapport aux conditions de capture, et plus accessible au public parce que demandant moins d’ajustements et de configurations.

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Faculty Supervisor:

Jean-Francois Lalonde

Student:

Partner:

Centre de développement et de recherche en intelligence numérique

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Conception d’une bibliothèque d’outils logiciels permettant la calibration et l’amélioration de la radiométrie des caméras infrarouge

Ce projet consiste en la conception, réalisation et tests d’outils informatiques servant a facilité le travail de recherche et développement de nouvelles méthodes de correction d’images digitales thermiques. Les outils crée par l’étudiant servirons à supporter les opérations d’acquisition de donnée et de calibrations et correction d’images infrarouges dans le but de les rendre visuellement propres (sans défauts) et d’être en mesure d’estimer la température en dégrée Celsius des objets dans la scène. Les mêmes outils serviront également à l’évaluation des performances de différentes méthodes ainsi qu’a la validation et au déploiement en production de masses. Ses outils permettront d’accélérer le développement et de diminuer les risques relier a la mise en production de caméras infrarouges (dites « thermique »).

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Faculty Supervisor:

Tony Wong

Student:

Partner:

Teledyne DALSA Semiconducteur (Montreal, QC)

Discipline:

Engineering

Sector:

Technology; Information and Communications Technology; Advanced Manufacturing

University:

École de technologie supérieure

Program:

Accelerate

Advanced Adaptivity and Personalization in Learning Systems through Collaborative Recommendations Year Two

Learning Systems are among the most popular e-learning tools in today’s education and training. Most e-Learning systems do not take into account individual aspects of learners (e.g., their goal, experiences, existing knowledge, learning style etc.).The primary goal of the proposed research is to offer rich adaptivity by combining information from a learner’s profile (e.g. levels, goals, learning style, cognitive abilities etc) with the information from other learners sharing common interests. Based on this combined information, advanced personalized recommendations can be provided, increasing efficiency, performance and learner’s satisfaction. The proposed research will have numerous benefits to the company: (1) Training and learning would become more accessible, to the benefit of employees in small to large -scale enterprises as it will offer unique learning experiences that fully engage and support users (2) It will help in improving and increasing the basic skills of employees, providing the organization with a competitive advantage and hence, will be used to build workforce capability

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Faculty Supervisor:

Sabine Graf

Student:

Partner:

Athabasca University

Discipline:

Computer science

Sector:

Education

University:

Athabasca University

Program:

Elevate

Retrospective analysis of operational legacy restoration

Alberta’s natural resource sector has resulted in the continuous and persistent loss of forest productivity. Despite huge strides in reclamation practices within the last 40 years, there is still a sizeable legacy of industrial disturbed sites that represent a significant opportunity to enhance the sustainability of the forest industry in the province.

Forest companies have been engaged in varying levels of reforestation of these disturbed sites but success has been mixed because often, the success of the program is not consistently assessed. This program presents a unique opportunity to evaluate forest regeneration success (or lack thereof) to address this knowledge gap between implementation treatments and the relative success of these treatments. The project’s core objective is to provide a quantitative understanding of forest recovery following an operational scale restoration program and to extract patterns in ecological region, ecosite or other attributes that may be used to predict forest regeneration ‘success’.

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Faculty Supervisor:

Amanda Schoonmaker;Mark Baah-Acheamfour

Student:

Partner:

Weyerhaeuser

Discipline:

Earth science

Sector:

Agriculture; Manufacturing

University:

Northern Alberta Institute of Technology

Program:

Accelerate

Developing machine learning tools for routine clinical EEG

The proposed project is part of a large-scale collaboration between SFU’s Behavioral and Cognitive Neuroscience Institute (BCNI) and Fraser Health Authority (FHA) in the domain of AI applied to clinical electroencephalographic (EEG) scans recorded and evaluated in the process of diagnostic workup in FHA’s public hospitals (n = 40’000). The key goal of the SFU/FHA collaboration is to automate the process of EEG reporting by building a decision support system. Conventional review of EEG relies on neurologists to visually inspect complex, noisy, high-dimensional digital data. Such an approach is slow, not fully reliable, and suboptimal. There is considerable variability in EEG interpretation, and this variability is affected by specific reader characteristics. Given these challenges, clinical reporting of EEG is highly suitable for machine-driven automation. The focus of the proposed project at a smaller scale is on predicting diagnoses (codes for most responsible diagnosis, secondary diagnosis, etc, according to International Statistical Classification of Diseases ICD-10) from in-patient EEG scans. We aim to address the following question: what current deep learning approaches can be used to reach state-of-the-art performance for EEG classification based on diagnostic codes.

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Faculty Supervisor:

Vasily Vakorin

Student:

Partner:

Taras Shevchenko National University of Kyiv;Bogomolets National Medical University

Discipline:

Computer science

Sector:

Education

University:

Simon Fraser University

Program:

Globalink Research Award