Projets novateurs réalisés

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

31 620 projets complétés

2978
AB
5221
C.-B.
856
MB
696
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899
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9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projets par catégorie

Optimal and heuristic optimization methods for large-scale naval refit operations

This project deals with the development of new mathematical models and solution methods to optimize naval surface ship refit operations. The Naval Surface Ship Work Period Problem (NSWPP) is a highly complex resource-constrained project scheduling problem (RCPSP) with many work orders that are equivalent to small projects. Planning, scheduling, and executing NSWPPs are very challenging, and a large volume of planned and scheduled work is typically never achieved for a variety of reasons such as unexpected discovery of damages, high variability in work scope and duration, unavailability of human resources or equipment, logistical delays. The goal of NSWPP is to complete all important and critical activities within the time-window available, where uncompleted activities will not compromise the mission or can be reasonably mitigated.
This project will propose new models to deal with the optimization of the NSWPP and incorporate time-quality, capacity-cost, cost-risk trade-offs. Heuristic solution methods will also be developed.

Voir la description complète du projet
Superviseur du corps professoral :

Claver Diallo;Alireza Ghasemi

Étudiant :

Partenaire :

Thales Canada Inc

Discipline :

Engineering

Secteur :

Management of companies and enterprises; Manufacturing; Professional, scientific and technical services

Université :

Dalhousie University

Programme :

Accelerate

Moose browsing intensity and landscape structure of wintering habitat patches

Over the last decades, the moose population of New Brunswick has greatly increased, to a point where forest regeneration is locally compromised. Moose browsing can severely influence forest dynamics by altering stand structure and composition and favouring softwood species over hardwoods in mixedwood stands. Hence, it is important to understand the factors influencing moose browsing in order to reduce damage to regeneration and economic losses to the forest industry. Although the factors influencing the spatial distribution of moose browsing have been intensively studied, both in Europe and North America, the influence of landscape structure of wintering habitat patches has not been studied. Therefore, we decided to analyze the influence of the landscape structure of wintering habitat patches at the landscape level on moose browsing intensity.

Voir la description complète du projet
Superviseur du corps professoral :

Martin-Hugues St-Laurent

Étudiant :

Partenaire :

Northern Hardwoods Research Institute

Discipline :

Life Sciences

Secteur :

Forestry; Natural Resources; Sustainability & the Environment

Université :

Université du Québec à Rimouski

Programme :

Accelerate

Impacts on dairy management and acceptability of a law restricting use of Class 1 antimicrobial

In a recent study conducted in the province of Quebec it was determined that 34% of antimicrobials used on dairies are antimicrobials of very high importance for humans (AKA Category 1 antimicrobials; Lardé et al., personal communication). However, since February 2019, a new regulation restricts their use in food producing animals in Quebec’s province, Thus, the objectives of this project are to determine the impacts of the implementation of a new regulation aimed at restricting category I AMU on the sale of veterinary drugs on dairy farms in Quebec by measuring the change in Category 1 AMU on dairies following application of the new regulation, investigating factors that are associated with reducing Category 1 AMU and exploring the main barriers and facilitators to the implementation of this new regulation. In France a similar legislation was implemented in 2016. Thus, doing an internship at l’INRAE will be helpful to develop hypothesis in the study of factors that are associated with a decrease in category 1 antimicrobials (objective 2 of the research project) and to target themes to explore with the qualitative interviews (objective 3 of the research project).

Voir la description complète du projet
Superviseur du corps professoral :

Cécile Aenishaenslin;Simon Dufour

Étudiant :

Partenaire :

École nationale vétérinaire, agroalimentaire et de l'alimentation, Nantes-Atlantique

Discipline :

Life Sciences

Secteur :

Public Service, Policy, and Governance; Health and Related Sciences & Technology; Agriculture and Food

Université :

Université de Montréal

Programme :

Globalink Research Award

Do socio-demographic and parenting factors moderate the impact of the HIPPY program on children’s school readiness?

The purpose of this project is to assess the impact of a home-based education program for preschool-aged children called the Home Instruction Program for Preschool Youngsters (HIPPY). This program aims to increase school readiness of children deemed educationally “at-risk” by reason of family poverty, parent education levels, family isolation, settlement issues, and/or English language skills. 13% of HIPPY participants are refugees, 70% are newcomers to Canada, and 12% are Indigenous. A data set on school readiness will be analyzed, as measured by The Bracken Basic Concept Scale (2006), a well-known standardized school readiness instrument. Bracken data were collected at two time points one year apart on 311 preschool children at 6 HIPPY sites across Canada, serving a diverse population of families. Analyses of the data will address change over time in children’s age-adjusted Bracken standard scores. Bracken scores will also be examined in relation to a variety of socio-demographic (e.g., child sex, immigration status, place of birth, and mothers’ English language competency) and parent (e.g., frequency of reading to child, engagement in HIPPY) factors.

Voir la description complète du projet
Superviseur du corps professoral :

Lucy Le Mare

Étudiant :

Partenaire :

Mothers Matter Centre

Discipline :

Sociology

Secteur :

Education

Université :

Simon Fraser University

Programme :

Accelerate

Optimisation du processus de classification des initiatives 4.0

L’émergence de l’Industrie 4.0 amène les chefs d’entreprise à remettre en question leurs modèles d’affaires et à envisager de quelle façon ces technologies peuvent se combiner pour transformer les produits, les processus et les services offerts. Cette transformation numérique amène inévitablement les entreprises à identifier les fournisseurs de ces technologies et les experts qui peuvent les accompagner dans leur démarche. BRIDGR offre ce service d’accompagnement à partir de sa plate-forme web en offrant un service de jumelage entre les entreprises et les fournisseurs de service technologique. L’accompagnement des clients pour clarifier leurs besoins réels et les solutions potentielles exige toutefois un investissement en temps considérable. L’objectif de ce projet est de revoir le processus de jumelage en cherchant à faciliter l’identification des fournisseurs potentiels à partir de l’énoncé des besoins exprimés par les clients.

Voir la description complète du projet
Superviseur du corps professoral :

Robert Pellerin;Christophe Danjou

Étudiant :

Partenaire :

BRIDGR

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Polytechnique Montréal

Programme :

Accelerate

iStandardize: Recommendations for Healthcare Form Standardiz

iStandardize is an AI-powered machine learning solution that is designed to streamline the standardization of clinical order sets (i.e., forms) by using machine learning and natural language processing techniques. Currently, hospital networks use multiple versions of forms and order sets, many of them are similar in nature. The lack of standardization poses a challenge in integrating the data for sharing, adds additional documentation burden, and disrupts the workflow for clinicians. The solution applies Natural Language Processing and Machine Learning to identify similar order sets and their elements (attributes and responses), reduce the manual work required to compare the order sets, and expedite the decision making process for standardization.

Voir la description complète du projet
Superviseur du corps professoral :

Michael Brudno

Étudiant :

Partenaire :

Deloitte Consulting (Toronto, ON)

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Victoria Green Economy

The proposed research is a collaboration between Vancity, the City of Victoria, and the
University of Victoria to bring together the necessary information (financial, regulatory, and
knowledge, respectively) to build a plan that will initiate Victoria’s Green Economy. Interns will
be part of distinct interviewing panels that will research the needs, benefits, and obstacles of
the development of a green economy. With that necessary information the interns will
collaborate with the industry partners to devise strategic plans that would lead to a roadmap
of how a green economy can be developed in Victoria. The major work will be to identify the
drivers of a green economy and then how those drivers can be advanced in Victoria. This
research has yet to be done in Canada and will serve to complement sustainability work done
on the environment with a focus on the economic drivers.

Voir la description complète du projet
Superviseur du corps professoral :

Matt Murphy

Étudiant :

Partenaire :

Vancity;The Corporation of the City of Victoria

Discipline :

Business

Secteur :

Finance and Insurance

Université :

University of Victoria

Programme :

Accelerate

Investigating strategies for optimizing immunity to COVID-19: examining the impact of probiotic lactic acid bacteria-derived secretomes on epithelial cell and macrophage immune activity

Strategies to promote immune defences against COVID-19 infection are urgently needed. The gastrointestinal tract is a potentially important route for COVID-19 infection and for generating protective anti-viral immunity against this pathogen. Certain features of COVID-19 contribute to its ability to evade and subvert our immune defences. Type I interferon is a key immune protein that shuts down viral replication during virus infections. However, SARS-CoV-2 evades this defence by failing to induce these protective interferons, allowing the virus to replicate and cause symptoms of COVID-19 infection. Macrophages are another key host immune defence. Severe COVID 19 infections can result in acute respiratory distress syndrome (ARDS), an outcome linked to the disastrous effects of pro-inflammatory macrophage activity and “cytokine storm” production. In our research analyzing probiotic bacteria communication with the immune system, we found that Lactobacillus rhamnosus R0011 acts on intestinal epithelial cells and macrophages via secreted molecules (a secretome). This secretome-mediated communication induced Type I interferon production and drove macrophage differentiation into a regulatory phenotype, in contrast to the pro-inflammatory macrophages causing damage in severe COVID-19 cases.

Voir la description complète du projet
Superviseur du corps professoral :

Julia Green-Johnson

Étudiant :

Partenaire :

Lallemand Bio Ingredients

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

University of Ontario Institute of Technology

Programme :

Accelerate

Multilingual B2B Supplier Detection and Information Extraction

At Tealbook, we search the web to make the world’s business-to-business supplier websites readily accessible. We extract important sentences and keywords to create a searchable database that buyers can then use to find the right supplier for their needs. But right now, we are limited to servicing English-language organizations. Can we expand our services to French? To German? To Korean? To any of the other 7000 languages in the world? Doing so would not only allow Tealbook to reach a wider audience, but also help the world stay interconnected in any language.

Voir la description complète du projet
Superviseur du corps professoral :

Gerald Penn

Étudiant :

Partenaire :

Tealbook

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

A smart edge computing infrastructure to support workflows, communication and logistic in COVID-19 healthcare facilities

The ability of the health system to manage a massive influx of patients is based on the combination of four factors: the personnel, the equipment, the physical spaces and the system in place. A combination better known in jargon as the 4 “S” (staff, stuff, structure / space, system). A fifth factor that is often misunderstood is synchronicity. With great adaptation to the workspace and team structures, a newly trained staff with new equipment, and a system of critical processes that evolve according to the evolution of the environment and the healthcare system status, synchronicity is essential. This synchronicity requires real time data and automations to enable already pressured teams and a stressed healthcare organization to adapt to unforeseen requests and needs.
In the actual project, we present a real time management system designed to empower healthcare systems and workers in the logistical chain of operation under a turbulent environment. This project will significantly help our organization to timely develop a more efficient and scalable C4 solution, capable of offering a wider range of OTT-services to medical personnel and, ultimately, save lives.

Voir la description complète du projet
Superviseur du corps professoral :

Esma Aimeur;Gabriela Nicolescu;Sofiane Achiche;Maxime Raison;Maxime Raison;Sofiane Achiche;Gabriela Nicolescu

Étudiant :

Partenaire :

Humanitas Solutions

Discipline :

Computer science

Secteur :

Health and Related Sciences & Technology; Information and cultural industries; Professional, scientific and technical services

Université :

Polytechnique Montréal; Université de Montréal

Programme :

Accelerate

Using NLP models to fetch SQL data via voice command for SOTI SNAP Analytics (NL-to-SQL)

This project is focusing on creating an integration of a database and mathematical calculation, with the use of Alexa, Google home, Cortana, so that users can use Natural Language to aggregate meaningful data and answer questions from a given database. For example, suppose there is a database about car sales. If I asked Siri, “who is the best sales for BMW in Toronto?” Our designed algorithm should return the name of the top sales from this given database. The project also builds out an Analytics Engine that will perform mathematical calculations on the data submitted by the SNAP APP dynamically.

Voir la description complète du projet
Superviseur du corps professoral :

Gerald Penn

Étudiant :

Partenaire :

SOTI Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Designing ‘Zero credit touch’ (ZCT) pre-approved credit underwriting program for retail customers

ICICI Bank has developed various ‘Zero credit touch’ (ZCT) strategies where without any credit intervention and additional information taken from customers, credit facilities can be provided. But there are several challenges in the expansion of ZCT strategies, namely, (i) current credit models which are a combination of business rules, scorecards and machine learning models, do not qualify a significant proportion of existing ICICI Bank customers; (ii) wherever customers do not have a salary account with the Bank, estimated income is lower leading to the customer being offered an amount lower than his/her requirement; (iii) customers with fraudulent intentions can open accounts and over time, these profiles would qualify for ZCT. To tackle these problems, we propose a novel ZCT system incorporating several state-of-the-art methodologies to build one go-to product to reduce credit and operations cost of lending whilst providing a superior customer experience.

Voir la description complète du projet
Superviseur du corps professoral :

Sebastian Jaimungal

Étudiant :

Partenaire :

ICICI Bank Canada

Discipline :

Computer science

Secteur :

Finance and Insurance

Université :

University of Toronto

Programme :

Accelerate

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Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.