Projets novateurs réalisés

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

30 508 projets complétés

2882
AB
5105
C.-B.
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projets par catégorie

Risk of Confusion for Trademarks

An important legal task for which natural language processing has a use-case is for assessing the risk of confusion for trademarks. By means of a thorough understanding of factors which are used by legal professionals to make decisions in this domain, we replicate the process by using state-of-the-art deep learning models for natural language processing. Furthermore, we promote access to justice by enabling members of the general public to utilize this framework, with much simpler input requirements. In other words, our system has a strong foundation in trademark law, and is able to provide useful information to people looking to protect their intellectual property.

Voir la description complète du projet
Superviseur du corps professoral :

Xiaodan Zhu;Samuel Dahan

Étudiant :

Partenaire :

I-INC Foundation for Business Development

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Queen's University

Programme :

Accelerate

Development of deep neural networks for analyzing the prospectivity of Nova Scotia offshore basins

Unlocking the energy potential of offshore basins is key to fully evaluate Canada’s ability to satisfy its future energy demand while respecting UN Sustainable Development Goal 7, Affordable and Clean Energy. In frontier basins, including offshore Nova Scotia, deep-water exploration entails various risks due to uncertain geological settings, thus requiring comprehensive prospect analyses and risk assessments. One of the major sources of hazard is mass transport deposits (MTDs), which commonly host over-pressured subsurface zones. MTDs constitute a considerable volume of sediments in deep-water environments, and understanding their distribution is crucial in assessing drilling hazards and development planning. Here, we propose designing and implementing the first artificial intelligence platform to automatically identify MTDs in over 10,000 square kilometres of offshore Nova Scotia. Further, we apply state-of-the-art processing and interpretation techniques on multiple geophysical and well datasets to determine the distribution and reservoir potential of identified MTDs and associated sediments. We will explore how submarine sediment failures control the formation of new deep-water channel systems, thus delivering new insight on sediment transport and accumulation mechanisms. The proposed project will contribute to understanding Nova Scotia’s offshore energy resources.

Voir la description complète du projet
Superviseur du corps professoral :

Vittorio Maselli

Étudiant :

Partenaire :

Offshore Energy Research Association of Nova Scotia

Discipline :

Earth science

Secteur :

Mining; Professional, scientific and technical services

Université :

Dalhousie University

Programme :

Elevate

Nighttime Bed Occupancy Pilot Project

The care and safety of Persons Living with Dementia (PLWD) within assisted living and other communal living models is extremely important. One key symptom of dementia is disorientation for time and/or place and this can lead to wandering behaviours for residents. Overnight in care homes, the limited is focused on required resident care cannot watch all residents that are expected to be sleeping in their rooms. A resident that wanders is at risk for falls or may wander into the room of another resident disturbing them or worse. The result is that care homes need a solution that can monitor and alert staff for residents that have left their beds but do so in a way that does not disturb other residents. This project will assess the Tochtech SleepSense sensor within a specialized memory care facility to assess its performance and effects of staff workflow and efficiency.

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Superviseur du corps professoral :

Bruce Wallace;Mirou Jaana;Frank Knoefel

Étudiant :

Partenaire :

Elizabeth Bruyere Continuing Care Hospital;Tochtech Technologies Ltd.;All Seniors’ Care

Discipline :

Engineering

Secteur :

Information and cultural industries; Manufacturing; Professional, scientific and technical services

Université :

Carleton University

Programme :

Accelerate

Applications Of Data-Driven Analytics and Decision-Making Optimization for Solar-powered Energy Hubs Integrated With Electrical Vehicles

The worldwide urge to seek solutions for global warming and its negative environmental impacts, has driven the increased adoption of renewable energy resources and electric vehicles (EVs). This increase in the share of renewable energy generation and EV users has widened the implementation of distributed energy resources (DERs) systems and encouraged the move towards developing and modeling smart energy hubs. Boxbrite Technologies is a leading cleantech company in the region of Waterloo and develops software solutions for the renewable energy industry that aims to optimize energy systems. The solar charging systems that are overseen by Boxbrite are examples of energy hub systems, which can be better optimized via the full utilization of available data. However, several challenges are imposed on the energy hub optimization that include EVs charging system due to high degree of uncertainties in renewable DERs power output, demand, and unavailability of accurate forecasting profiles for the renewable power generation and EV charging behaviour. This research will take the full advantage of recent advancements in big data tools by strategically integrating them within the energy system decision-making. The proposed project is designed to be a top-to-bottom comprehensive study to investigate how energy hubs powered by renewable energy and EV infrastructure can be utilized to enhance the profitability of all stakeholders involved. It is expected that this project will guide the deployment of renewable DER on a larger scale, providing deeper visibility into the performance of energy hubs as one of the potential solutions to Canada’s decarbonization goals.

Voir la description complète du projet
Superviseur du corps professoral :

Ali Elkamel

Étudiant :

Partenaire :

Boxbrite Technologies Inc.;Net Zero Atlantic

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Waterloo

Programme :

Elevate

« Optimisation des aspects mécaniques et électriques d’une plateforme de forage hybride en utilisant l’aluminium pour l’industrie pétrolière, minière et géothermique.».

Ce projet porte sur le développement d’une plateforme de forage de haute performance en aluminium, hybride électrique-diesel destiné aux secteurs pétrolier, minier et géothermique. Le projet prévoit principalement l’analyse d’un prototype en tenant compte des aspects de sécurité, la stabilité et la facilité d’entretien. Dans cette perspective, le groupe de recherche de l’Université du Québec à Rimouski (UQAR) et la compagnie Caron Technologie International (CTI) ont décidé d’unir leurs forces et de mettre en place un projet d’envergure dans le domaine de la fabrication de pointe. Cette grappe Mitacs comprend 6 stages. Elle permettra à CTI d’avoir un concept de qualité de foreuse hybride sécuritaire, de haute performance et ayant peu d’incertitude.

Voir la description complète du projet
Superviseur du corps professoral :

Noureddine Barka

Étudiant :

Partenaire :

Caron Technologies International Inc.

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Université du Québec à Rimouski

Programme :

Accelerate

Developing Customizable and Affordable Medical Simulation Solutions by Facilitating the Transfer of Research Driven Products into the Simulation Market.

The goal of the proposed research project is to design and develop an application called 3DCrowdGo that uses crowdsourcing to fill the COVID-19-induced gap in health professions simulation training via community-based 3D printing. Since COVID-19 has pushed simulation labs to be held virtually, learners are in need of affordable and portable simulators. 3DCrowdGo will connect this need with 3D printer owners and hobbyists within the local community who will be able to 3D print the necessary simulators so that learners can continue to practice technical skills outside of the classroom.

Voir la description complète du projet
Superviseur du corps professoral :

Adam Dubrowski

Étudiant :

Partenaire :

I-INC Foundation for Business Development

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

University of Ontario Institute of Technology

Programme :

Accelerate

The Mood Disorders Society of Canada (MDSC) Virtual Assistant: A machine learning and artificial intelligence chatbot to support the mental health of frontline healthcare workers

Mental disorders are the leading cause of disability in Canadaxiii. Unfortunately, there are significant gaps in care including a lack of support in navigating the mental health systemxivxvxvixvii. It is widely agreed by the medical community that there will be a wave of widespread need for mental health related services resulting from COVID-19xviii, which will only further exacerbate existing system issues.
With 91% of Canadians actively using the internetxix, new digital technologies that harness the internet can be leveraged to bridge gaps in services, increasing the ease and ways in which people can access mental health services, and in-turn improving their health outcomesxx.
This pilot study will develop, activate, and evaluate state-of-the-art artificial intelligence and machine learning, in the form of a chatbot (called the MDSC Virtual Assistant), to support the mental health of front-line health care workers and their families. Our goal is to examine whether the bot effectively helped people connect with the right services, if users were satisfied with their experience with the bot, and whether the bot supported their wellbeing.

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Superviseur du corps professoral :

Osmar Zaiane;Eleni Stroulia

Étudiant :

Partenaire :

Mood Disorders Society of Canada

Discipline :

Computer science

Secteur :

Other services (except public administration)

Université :

University of Alberta

Programme :

Accelerate

Toxic Disinformation: Credibility Attacks Against Journalists

Journalists around the world face attacks on their reputations and efforts to undermine the impact of their work. These “credibility attacks” can take the form of false allegations, insults about their character or professionalism, or denigration of their social identity. They often take place online, and in some cases involve disinformation tactics such as doctored images and accusations spread by actors using fake identities. Anecdotal cases of credibility attacks have received attention but there is no systematic study of their prevalence globally, the forms they take, or their impact on journalists. While there is growing recognition of online harassment of female journalists, much less attention is given to issues of ethnicity, race or religion. Working with PEN Canada, UBC researchers will address these knowledge gaps to improve understanding of this issue and propose measures to counteract it.

Voir la description complète du projet
Superviseur du corps professoral :

Peter Klein;Rithika Shenoy

Étudiant :

Partenaire :

PEN Canada

Discipline :

Sociology

Secteur :

Other services (except public administration)

Université :

The University of British Columbia

Programme :

Accelerate

Germicidal Robotic Systems

Coronavirus is highly contagious. It can remain active and infectious on cardboard, fabric, and paper for up to 24 hours, on plastic, stainless steel, and countertops for up to three days. Decontamination, sterilization, and disinfection are standard procedures to prevent and reduce the spreads of COVID-19. The conventional method of decontamination and disinfection is through manual cleaning, which is labor-intensive, error-prone, and ultimately unable to disinfect completely.
There is a wealth of evidence indicating the effectiveness of the ultraviolet germicidal irradiation, UVC, as a disinfection method for the prevention of various infectious diseases. This proposal presents a low-cost and automated approach to disinfect enclosed environments. We use UVC, robotics, and artificial intelligence to present efficient and affordable solutions. The proposed design not only is beneficial to the Canadian healthcare and public systems but also to other countries, particularly the countries with weaker healthcare systems.

Voir la description complète du projet
Superviseur du corps professoral :

Sajad Saeedi

Étudiant :

Partenaire :

I-INC Foundation for Business Development

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

AWE Technology Development Project – The Virtual History of Fort York

Divani’s AWE Augmented Reality product is expected to assist Fort York to create a more engaging experience for the attraction’s 100,000 annual visitors. By combining the historical value of Fort York with the immersive experience of AR, the organization will be able to increase revenue to assist with its financial goals. Divani Films is expected to benefit from a successful rollout by generating new revenue streams from the licensing of AWE technology and/or forming additional partnerships within the tourism industry as well as other industries (gaming, sports, etc.).
The intern will provide research services to assist Divani Films in the commercialization of results of current technology and products. With the Fort York project serving as proof of concept, the intern will assist Divani to develop a business and technology innovation strategy (focusing on use of current technology as a platform, identification of next steps in other AR application markets, assessment of investment needs to create a suite of products and services, and identification of business models to support commercialization), accompanied by an investment plan.

Voir la description complète du projet
Superviseur du corps professoral :

Charles Davis

Étudiant :

Partenaire :

Divani Films Inc

Discipline :

Business

Secteur :

Information and cultural industries

Université :

Toronto Metropolitan University

Programme :

Accelerate

Collision detection algorithms in Mandatory Entry-Level Training virtual reality truck simulator

The Mandatory Entry-Level Training (MELT) virtual reality (VR) truck simulator under development by Serious Labs Inc. offers a training solution for boom and scissor lifts. MELT in Alberta is a Class 1 training program in compliance with the National Safety Code Standard 16 Commercial Truck Driver Entry Level Training. The purpose of this research project is to create physics simulation software that is more accurate, functional, and optimized for the simulators, as opposed to typical physics simulation software used for games. Specifically, the collision contact detection algorithm requires more work to be able to satisfy the performance demands of the MELT VR Simulator. A tangible goal of this project is to extend the functionality of the contact detector and optimize its performance.

Voir la description complète du projet
Superviseur du corps professoral :

Raymond Spiteri

Étudiant :

Partenaire :

Serious Labs

Discipline :

Computer science

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Saskatchewan

Programme :

Accelerate

Évaluation de l’impact de l’historique de production de la crème sur les rendements en beurre et leur texture

La demande en beurre est en forte croissance au Canada ce qui nécessite de maximiser sa production. Toutefois, les différentes étapes de production de la crème en usine peuvent avoir un grand impact sur la texture du beurre. Il est donc primordial de développer des outils d’évaluation des crèmes afin de pouvoir proposer des stratégies pour optimiser leur comportement au barattage et la texture du beurre comme la fermeté et la tartinabilité. Ainsi l’effet des traitements thermiques, de l’âge de la crème sur l’état physique (solide versus liquide) et sur le profil de points de fusion de la matière grasse seront étudiés afin d’identifier des leviers permettant d’optimiser la production du beurre et sa texture. Ainsi, ce projet en collaboration avec Agropur permettra de proposer des stratégies d’optimisation des paramètres de production pour améliorer les rendements en beurre et la qualité du produit fini.

Voir la description complète du projet
Superviseur du corps professoral :

Guillaume Brisson

Étudiant :

Partenaire :

Agropur Coopérative

Discipline :

Earth science

Secteur :

Manufacturing

Université :

Université Laval

Programme :

Accelerate

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