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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4990
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801
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663
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825
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8841
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9197
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95
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568
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Projets par catégorie

Sensitivity Analysis of Gas and Particulate Matter Emissions from Future Power Generation in the Province of Alberta

The Province of Alberta (AB) has decided to phase out coal power generation by 2030 and increase renewable electricity production to 30% of total power generation, also by 2030 with the remaining 70% of the power generation being dependent on natural gas. It has been conjectured that part of generation portfolio could be diversified to include nuclear power generation. The current proposal aims at studying available power generation (seasonally) in Alberta and create a model to predict their gas (CO2, CH4, and NOx: mainly N2O, but also NO and NO2) and PM1 (particulate matter) emissions in time using different generation portfolios. Once this model is verified against gas emission data obtained from the literature, future seasonal emissions will be predicted after varying the generation portfolio to include a certain amount of nuclear power generation (from 0 to 25% of the total output). An uncertainty analysis of the prediction will also be performed.

Voir la description complète du projet
Superviseur du corps professoral :

Edgar Matida

Étudiant :

Partenaire :

Canadian Nuclear Association;Emission Trak

Discipline :

Engineering

Secteur :

Utilities

Université :

Carleton University

Programme :

Accelerate

Investigating polysaccharide-protein conjugation: characterization and effects of glycation conditions

Pneumonia remains the single leading cause of childhood death under age 5 worldwide. The price per dose of current vaccines is high and supply is limited due to a complex manufacturing process and low yield, significantly reducing its distribution in developing nations.1 A newly patented vacuo dry-glycation process promises much higher efficacy than the conjugation chemistry used currently, paving the way towards a much lower dosage cost. and its vaccine is a kind of polysaccharide-protein conjugate system. However, the process conditions required for activation of the polysaccharide by vacuo dry-glycation have not been optimized, and the characteristics of distinct serotype polysaccharides and the corresponding activated polysaccharides and conjugate products are not fully reported and studied. This research addresses these deficiencies, enabling PnuVax Inc. to further the development of a more affordable vaccine that can be used in Canada and around the world to reduce childhood death due to pneumonia.

Voir la description complète du projet
Superviseur du corps professoral :

Robin Hutchinson

Étudiant :

Partenaire :

PnuVax Inc (Kingston, ON)

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Queen's University

Programme :

Accelerate

Analyse structurale des formations de fer au nord-est du réservoir Manicouagan

Champion Iron Mines est une société de développement et d’exploration québécoise effectuant de l’exploration régionale dans la plus importante région de production de minerai de fer du Canada. Le minerai se trouve dans des formations de fer plissées en une géométrie complexe lors de la formation de la chaîne de montagne « Grenville » il y a un milliard d’années. Le projet proposé vise à faire une analyse structurale de deux projets minier situés près entre le réservoir Manicouagan et Fermont. Les résultats permettront de tester des modèles conceptuels proposés récemment pour expliquer des structures d’orientations perpendiculaire à celle attendue pour une chaîne de montagne. Déterminer la géométrie 3D des gisements améliorera l’estimation des réserves et la localisation d’autres gîtes de fer potentiels. Enfin, ce projet contribuera à la formation d’un étudiant spécialisé en géologie de terrain, une expertise rare, mais cruciale pour le milieu d’exploration minière du Canada

Voir la description complète du projet
Superviseur du corps professoral :

Félix Gervais

Étudiant :

Partenaire :

Champion Iron

Discipline :

Engineering

Secteur :

Natural Resources; Mining

Université :

Polytechnique Montréal

Programme :

Accelerate

Pattern Recognition: The Exploration of Machine Learning Algorithms in Archaeological Site Prediction, Fraser River Valley, British Columbia

Golder Associates Ltd., teaming with the Seyem’ Qwantlen Business Group (Kwantlen First Nation), was retained by the Township of Langley to develop a model to predict the location of unrecorded archaeological sites on a 10,000 year-old landscape located in the Fraser River Valley, British Columbia. Conventional predictive modelling techniques are common practice however with the increased availability of more powerful computers and software there is a growing potential for using machine learning algorithms to predict a wider variety of archaeological site types with greater accuracy. For this Pattern Recognition Project (PRP) the intern will complete a machine learning literature review and an examination of the local archaeology to identify potential machine learning methodologies and algorithms to predict site locations as well as the best environmental, physiographic and cultural variables to input into the model. This research will be used to create a report which describes the PRP, its results, and recommendations. The results generated by the PRP will be used to pilot a new approach for archaeological predictive modelling using machine learning algorithms and will ultimately be used to assist the Township in responsibly managing local archaeological sites.

Voir la description complète du projet
Superviseur du corps professoral :

Andrew Martindale

Étudiant :

Partenaire :

Golder (Vancouver, BC)

Discipline :

Sociology

Secteur :

Environmental Science and Technology; Aboriginal Affairs; Sustainability & the Environment

Université :

The University of British Columbia

Programme :

Accelerate

Ultra-thin graphene oxide membranes for efficient humidity harvesting

The main goal of the proposed work is to develop an ultra-thin and selective GO membrane capable of separating water vapor or steam from air. For this purpose, a suitable membrane supports required to hold the GO sheets. Therefore, the GO sheets will be deposited on various membrane supports and their performance in terms of selectivity, permeability, and mechanical strength will be evaluated. Then, the effect of GO layer number on the selectivity and permeation rate will be investigated. Once the best performing membranes have been determined, the impact of feed humidity and temperature on the permeation rate and selectivity of water vapor transport through the membranes will be evaluated. Evercloak will supervise the intern and support out of lab research activities on their premise. Evercloak will benefit as the results of this project will inform key decisions within their technology development roadmap in addition to talent acquisition/training.

Voir la description complète du projet
Superviseur du corps professoral :

Michael KC Tam

Étudiant :

Partenaire :

Evercloak

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Waterloo

Programme :

Accelerate

Using Machine Learning for audio analysis and synthesize

Voices.com, the largest online marketplace for voice talent, have identified Machine Learning as an enabler for
future growth. In particular, incorporating Natural Language Processing (NLP) into structured queries and
automatic classification of sample recordings. The first phase of this research involving NLP is in the process of
being integrated into production. The second phase will be to automatically classify sound samples. This has been
historically difficult resulting in low levels of accuracy, but we will take advantage of new ML techniques, and one
of the world’s largest databased of tagged audio. This classification will cover areas of current research, such as
gender and age detection, but extend to new areas including style and emotion. Having completed this
classification, we will be able to incorporate emotion into voice synthesis, increasing the acceptance and usability
of Voice AI.

Voir la description complète du projet
Superviseur du corps professoral :

Christopher Anand

Étudiant :

Partenaire :

Voices

Discipline :

Computer science

Secteur :

Information and Communications Technology; Technology; New and Digital Media

Université :

McMaster University

Programme :

Accelerate

Passivity Guaranteed Frequency Selective Time Domain Simulation of Very Large Linear Electric Power Systems

In this research, a new approach to efficiently simulate large RLC represent power systems will be introduced and implemented in RTDS. The new approach utilize principle component analysis to search the subspace of state space vectors corresponding to a customer designed frequency band excitations and using projection method to form the reduced order system. Unlike other frequency dependent network equivalent methods, the proposed method reserves all internal information of original system and also inherently guarantees the passivity of the equivalent network. The results of this study will provide a new module in RTDS. It can be used for efficiently modeling large RLC represented network. So, ultimately will enhance this part of the RTDS simulator.

Voir la description complète du projet
Superviseur du corps professoral :

Aniruddha (Ani) Gole

Étudiant :

Partenaire :

RTDS Technologies

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Manitoba

Programme :

Accelerate

Delegation of Trust to Consumer Devices in Banking Applications

Trust lies at the very foundations of computer and information security, and is the basis for real-world schemes that require security properties, such as those that underlie consumer banking. Under this research project, we will investigate models for delegation of trust that meet desirable properties, for example, that guarantee that no security compromises occur unless certain trust assumptions are violated. We will also build a software prototype that integrates an appropriate delegation model that we devise with features on a consumer device, such as a fingerprint sensor on a mobile phone. The intent is to demonstrate, in practice, that such features in consumer devices can be securely leveraged in banking applications. This, in turn, gives new capabilities for our industry partner, BMO, to provide Canadian consumers with superior banking services, while maintaining security properties.

Voir la description complète du projet
Superviseur du corps professoral :

Mahesh Tripunitara

Étudiant :

Partenaire :

Bank of Montreal

Discipline :

Engineering

Secteur :

Information and Communications Technology; Finance and Insurance

Université :

University of Waterloo

Programme :

Accelerate

Extraction et purification durable du lithium à partir du spodumène : étude de la variabilité du spodumène du gisement de lithium Whabouchi

Afin de réduire son empreinte environnementale, l’entreprise Nemaska Lithium souhaite revaloriser les résidus produits par le traitement de leur minerai de spodumène, un minéral riche en lithium, afin d’éviter leur entassement. Dans cet optique, différentes voies de valorisation ont été envisagées, incluant, entre autres, la fabrication de verre et vitrocéramique lithié, l’utilisation dans le ciment et la synthèse de zéolites. La présente recherche vise la caractérisation du minerai de spodumène afin de déterminer comment la variabilité chimique du spodumène influencera la qualité du résidu produit. Les résultats de cette caractérisation permettront d’établir les meilleures voies de valorisation selon les variations observées dans le minerai. En plus de positionner l’entreprise comme chef de file dans le domaine de l’exploitation minière écoresponsable, cette recherche permettra de contribuer à l’avancement de la science et de la technologie pour la valorisation de résidus miniers.

Voir la description complète du projet
Superviseur du corps professoral :

Jean-François Blais

Étudiant :

Partenaire :

Nemaska Lithium

Discipline :

Earth science

Secteur :

Mining; Professional, scientific and technical services

Université :

Université du Québec : Institut national de la recherche scientifique

Programme :

Accelerate

The enemy of my enemy is my friend: fear responses in mussels exposed to apex and meso-predators

Top-down control in ecosystems helps maintain ecosystem stability and resilience; however, anthropogenic stressors, such as commercial fishing, have led to the global decline of apex predators. There is a growing recognition that the indirect effects of predators on prey (eg. fear-mediated behavioural responses) could be just as important as direct consumption. For instance, apex predators play an important role in regulating meso-predators by evoking fear and stress responses (eg. retreating and hiding) that limit meso-predator activity. Likewise, meso-predators drive similar fear responses in their own prey items, but few students have explored how meso-predator prey responses are modified by the presence of an apex partner. Apex predators suppress meso-predator feeding an in turn, could indirectly reduce the stress response of meso-predator prey. We propose to measure the effects of an important marine meso-predator (crabs) on the feeding responses of mussels when in the presence of an apex predator (sharks).

Voir la description complète du projet
Superviseur du corps professoral :

Paul Mensink

Étudiant :

Partenaire :

Queen’s University Belfast

Discipline :

Life Sciences

Secteur :

Education

Université :

Western University

Programme :

Globalink Research Award

Integer Factorization

This project lies in an area of mathematics called computational number theory. Specifically, we will be studying the topic of integer factorization. The idea is that all non-prime integers can be factored into a product of smaller integers. While this seems simple, it is computationally difficult and although various factoring algorithms attempt to solve the integer factorization problem, it remains very difficult for large integers. This problem has applications in modern cryptography. In particular, it impacts the security of RSA, which is one of the most widely used public-key cryptosystems. The objective of this project is to learn the underlying theoretical concepts of specific algorithms used for integer factorization. We will focus on general purpose algorithms, with the end goal of gaining a comprehensive understanding of the general number field sieve, which is currently the most efficient algorithm for factoring large integers. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Mark Bauer

Étudiant :

Partenaire :

University of Hawai'i at M?noa

Discipline :

Mathematics

Secteur :

Education

Université :

University of Calgary

Programme :

Globalink Research Award

Penser la solidarité multiculturelle : un défi néo-républicain ?

Le but du séjour est double. Premièrement, encadrer la rédaction de mon projet de thèse en me permettant d’accéder à un environnement de recherche attentif à une des thématiques centrales de mon travail : la solidarité sociale. Deuxièmement, développer mes compétences en méthodes d’analyse de contenu et d’analyse de discours afin de rédiger le volet méthodologique de ma thèse.

Voir la description complète du projet
Superviseur du corps professoral :

Charles Blattberg

Étudiant :

Partenaire :

Université Catholique de Louvain

Discipline :

Sociology

Secteur :

Education

Université :

Université de Montréal

Programme :

Globalink Research Award

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