Projets novateurs réalisés

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

29 670 projets achevés

2811
AB
4990
C.-B.
801
MB
663
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825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
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Projets par catégorie

Analysis of the implementation of a Model-Based Systems Engineering approach for the conceptual design of advanced aircraft high-lift system architectures

Today, the development of complex products such as aircraft systems is still mainly based on a paper-based requirements and development process which leads to delays, cost overrun and sometimes failure to respond to customer needs. A structured, model-based design approach is considered promising to bring innovation and optimization in systems architectures. The project aims to demonstrate the value of a model-based systems engineering approach opposed to a traditional bottom-up approach for the example of advanced aircraft high-lift system architectures. The open-source framework Capella will be used to provide the partner organization a tailored new methodology, example process and models for the conceptual design phase that will enable subsequently a more efficient and effective development process.

Voir la description complète du projet
Superviseur du corps professoral :

Susan Liscouet-Hanke

Étudiant :

Partenaire :

Bombardier Aeronautic Inc (Saint-Laurent, QC)

Discipline :

Engineering

Secteur :

Manufacturing; Transportation and warehousing

Université :

Concordia University

Programme :

Accelerate

Early Childhood Education project

Early Learning is an impotant undertaking in Canadian society and supporting young children as they move from home to early learning centres onto kindergarten classes is of particular interest and value to educators, helping us to ensure we provide the right environments and supports for all young children. This research will help us to provide the most appropriate learning experiences to young children in new Brunswick and beyond.

Voir la description complète du projet
Superviseur du corps professoral :

Ann Sherman;Sherry Rose;Sherry Rose

Étudiant :

Partenaire :

Margaret and Wallace McCain Family Foundation;Origins Natural Learning Childcare

Discipline :

Sociology

Secteur :

Education

Université :

University of New Brunswick

Programme :

Accelerate

Voice Transformation for Interactive Digital Media

The main purpose of the research project is to have the student investigate and develop a voice transformation system that modifies waveforms of recorded speech segments to produce multiple different sounding voices for characters within a video game.

Voir la description complète du projet
Superviseur du corps professoral :

Frank Rudzicz

Étudiant :

Partenaire :

Ubisoft Toronto

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

University of Toronto

Programme :

Accelerate

Complex Continuing Care in a Rural Hospital: Optimizing community-based health care

Community hospitals in small towns or rural areas face challenges in delivering health care that will allow elderly members of their community to remain in the community that they helped to build. Using simulation modelling, this project will develop strategies for delivering complex continuing care in rural hospitals that is closely integrated with long-term care, residential care, and home care services. Small towns and rural communities have a tight-knit social fabric and the contributions that family support and community services provide to health care are important factors. This project will be carried out with the Listowel Memorial Hospital Foundation and will focus on the municipality of North Perth, Ontario.

Voir la description complète du projet
Superviseur du corps professoral :

Alexander Rutherford

Étudiant :

Partenaire :

Listowel Memorial Hospital Foundation

Discipline :

Mathematics

Secteur :

Health and Related Sciences & Technology

Université :

Simon Fraser University

Programme :

Accelerate

A study of the hydrogeotechnical behavior of in-pit tailings and their interaction with the contact structures – Year two

Mines wastes include tailings and waste rock. Tailings are crushed rock produced by mineral extraction and waste rock is coarse material excavated to create mine openings. These wastes are commonly disposed on the surface in tailings or waste rock piles, which could pose serious environmental and geotechnical issues. Backfilling the openings of underground mines with wastes has become a common practice. The disposal of wastes in open pits is less common, yet is a promising technique. Very little research has been performed on the behavior of tailings disposed of “in-pit” and on their interaction with contact structures. In-pit disposal of mine wastes is underway at the partner’s mine. This is an opportunity to study in-pit disposal that will lead to improvements in the technique and an understanding of its effects on the environment. ponds

Voir la description complète du projet
Superviseur du corps professoral :

Li Li

Étudiant :

Partenaire :

IAMGOLD Corporation Mine Westword (Rouyn-Noranda, QC)

Discipline :

Engineering

Secteur :

Mining; Environmental Science and Technology; Natural Resources

Université :

École Polytechnique de Montréal

Programme :

Elevate

A study of the hydrogeotechnical behavior of in-pit tailings and their interaction with the contact structures

Wastes produced by mines include tailings and waste rock. Tailings are crushed rock produced by mineral extraction and are typically disposed as slurry. Waste rock is coarse material excavated to create mine openings that have no economic value. These wastes are often stored on the surface in tailings impoundments or waste rock piles and they pose important environmental and geotechnical risks. Backfilling the openings of underground mines with treated wastes has become a common practice. The disposal of wastes in open pits is less common, yet is a promising approach for integrated mine wastes management. Very little research has been conducted on the behavior of tailings disposed of “in-pit” and on their interaction with contact structures. In-pit disposal of mine wastes is underway at the partner’s site, Doyon-Westwood Mine. This is an opportunity to study important aspects of in-pit disposal that will lead to improvements in the method and an understanding of its effects on the environment. For example, waste rock could be placed in the pits as inclusions that would improve drainage and stability. Where the pit lays above underground mine openings the effects of in-pit disposal on the stability of these openings should also be evaluated.

Voir la description complète du projet
Superviseur du corps professoral :

Li Li

Étudiant :

Partenaire :

IAMGOLD Corporation Mine Westword (Rouyn-Noranda, QC)

Discipline :

Engineering

Secteur :

Mining; Environmental Science and Technology; Natural Resources

Université :

École Polytechnique de Montréal

Programme :

Elevate

Recurrent Deep Architectures for Modeling Time Series Data

Deep learning is currently the dominant machine learning technique as a result of state of the art performance in vision (Russakovsky, et al., 2015), speech (Amodei, et al., 2015) and natural language processing (Vinyals et al., 2015). The improvement in performance of these models is attributed to the availability of large datasets for training the models as well as software & hardware improvements that help accelerate the training process. Recurrent Neural Networks (RNNs) are one of the most powerful and popular frameworks for modeling sequential data such as speech and text. We propose to create an open source implementation of scalable, “industrial-strength”, RNN models. These models can then be fine-tuned and trained to perform specific prediction tasks on time series datasets from finance and insurance sectors.

Voir la description complète du projet
Superviseur du corps professoral :

Graham Taylor

Étudiant :

Partenaire :

RBC Royal Bank (Toronto, ON)

Discipline :

Engineering

Secteur :

Finance and Insurance; Management of companies and enterprises

Université :

University of Guelph

Programme :

Accelerate

Ecosystem Value Accounts – Tools to Advance the Green Economy and Sustainability Agenda

The project will develop ecosystem value accounts of land owned by the forestry company Kenauk Canada ULC (Kenauk Canada) using a variety of ecological economic approaches. The emphasis is to capture the broader value of ecosystem goods and services as opposed to equating value with the price of standing timber. Approaches under consideration include: net primary productivity, development of biocapacity accounts, and development of ecosystem service indicators. The project will also contribute to economic and sustainability discourse by exploring the normative underpinnings of how we assign and determine ecosystem value.
Kenauk Canada recently took on the mandate of transforming from a traditional forestry business into a sustainable conservation operation. Kenauk Canada will use the accounts to communicate the ecological importance of land they own and inform the new strategic direction of the company. Communicating the ecological significance is further regarded as a key strategy to leverage partnerships with conservation groups and economic development agencies. In addition, the ecosystem value accounts will include a carbon inventory which will be used to explore participation in carbon trade. Kenauk Canada understands that environmental risks and climate induced changes require forestry companies to create new business models based on principles of integrity and sustainability.

Voir la description complète du projet
Superviseur du corps professoral :

Raymond Paquin

Étudiant :

Partenaire :

Kenauk Canada ULC

Discipline :

Sociology

Secteur :

Agriculture

Université :

Concordia University

Programme :

Elevate

Development and commercialization of novel reference material for food allergen and gluten proficiency testing – Year two

The planned research program aims to address an existing gap: the lack of commercial availability of reference materials for food allergens to be used in the context of analytical method development, validation and performance testing. In particular, naturally incurred samples representing food matrices where priority allergens are likely to occur, in a controlled and calibrated fashion are not available. Allergens targeted include egg, milk as well as wheat gluten (targeting both wheat allergen and Gluten testing). Selected food carriers (food matrices where the allergen will be incorporated in a controlled and calibrated fashion) will be identified based on needs and priorities for allergen testing as well as market research.
The research envisaged will include the development of conditions of production, quality control and use of such reference materials. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Samuel Godefroy

Étudiant :

Partenaire :

r-Biopharm Canada inc

Discipline :

Life Sciences

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Université Laval

Programme :

Elevate

Development and commercialization of novel reference material for food allergen and gluten proficiency testing

The planned research program aims to address an existing gap: the lack of commercial availability of reference materials for food allergens to be used in the context of analytical method development, validation and performance testing. In particular, naturally incurred samples representing food matrices where priority allergens are likely to occur, in a controlled and calibrated fashion are not available. Allergens targeted include egg, milk as well as wheat gluten (targeting both wheat allergen and Gluten testing). Selected food carriers (food matrices where the allergen will be incorporated in a controlled and calibrated fashion) will be identified based on needs and priorities for allergen testing as well as market research.
The research envisaged will include the development of conditions of production, quality control and use of such reference materials. Support will be sought from the food allergen analytical community established under the auspices of the Association of Official Analytical Communities (AOAC International) as well MONIQA (international non-for profit network gathering analytical scientists: moniqa.org).
This initiative will also include some market research to study opportunities of commercialization of the developed materials in North-America, Europe and the Asia-Pacific region.

Voir la description complète du projet
Superviseur du corps professoral :

Samuel Godefroy

Étudiant :

Partenaire :

r-Biopharm Canada inc

Discipline :

Life Sciences

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Université Laval

Programme :

Elevate

Using multivariate deep-learning algorithms for automatic quality control of high-resolution MRI – Year two

NeuroRx is an imaging contract research organization (CRO) specialized in the central nervous system (CNS) that utilizes state-of-the-art digital image processing techniques to produce accurate and precise outcome measures for clinical trials of drugs in development. Prior to analysis, all scans must pass Quality Control (QC). The goal of this project will be to incorporate advanced computer algorithms to automatically classify the quality of high-resolution structural brain Magnetic Resonance Images. The advanced computer algorithms will include deep learning algorithms. Developing an automated algorithm to realize this time-consuming procedure can help companies save time and increase efficiency. NeuroRx will provide thousands of QC’d scans for algorithm training, and benefit from the most technologically advanced concepts and resources developed at a world-renowned institution, the Neuro at McGill.

Voir la description complète du projet
Superviseur du corps professoral :

Amir Shmuel

Étudiant :

Partenaire :

NeuroRx Solutions Inc

Discipline :

Engineering

Secteur :

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

Université :

McGill University

Programme :

Elevate

Using multivariate deep-learning algorithms for automatic quality control of high-resolution MRI

NeuroRx is an imaging contract research organization (CRO) specialized in the central nervous system (CNS) that utilizes state-of-the-art digital image processing techniques to produce accurate and precise outcome measures for clinical trials of drugs in development. Prior to analysis, all scans must pass Quality Control (QC). The goal of this project will be to incorporate advanced computer algorithms to automatically classify the quality of high-resolution structural brain Magnetic Resonance Images. The advanced computer algorithms will include deep learning algorithms. Developing an automated algorithm to realize this time-consuming procedure can help companies save time and increase efficiency. NeuroRx will provide thousands of QC’d scans for algorithm training, and benefit from the most technologically advanced concepts and resources developed at a world-renowned institution, the Neuro at McGill.

Voir la description complète du projet
Superviseur du corps professoral :

Amir Shmuel

Étudiant :

Partenaire :

NeuroRx Solutions Inc

Discipline :

Engineering

Secteur :

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

Université :

McGill University

Programme :

Elevate

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