Projets novateurs réalisés

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

31 620 projets complétés

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856
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696
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899
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9419
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9858
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98
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619
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Projets par catégorie

Analysis of the potential application of the shortwave infrared and near-infrared cameras to the weld temperature measurements

Temperature is a critical parameter in welding and related processes such as metal additive manufacturing. The real-time temperature measurement systems based on infrared thermal cameras have a potential to significantly improve the existing process control systems and, consequently, the quality of the welds and additive manufactured products. Conventional thermal cameras work in midwave (MWIR) and longwave infrared (LWIR) part of the infrared spectrum. They require sophisticated sensor systems and special optics. Cameras that work in the part of the infrared spectrum which is closer to visible light (shortwave infrared SWIR and near-infrared NIR) are less sensitive at lower temperatures, but potentially may be used for temperature measurements at temperatures typical in welding. They can use regular glass optics and their sensors do not require cooling to low temperatures and are made of less sophisticated materials which makes them significantly cheaper and easier to use. These features of the SWIR and NIR camera systems indicate their potential for the real-time welding and metal additive manufacturing temperature measurement systems. The objective of the project is to study the ability of the camera systems working in the SWIR and NIR spectrum ranges to capture the thermal emission during welding and provide temperature measurement.

Voir la description complète du projet
Superviseur du corps professoral :

Patricio F. Mendez

Étudiant :

Partenaire :

Xiris

Discipline :

Engineering

Secteur :

Manufacturing

Université :

University of Alberta

Programme :

Accelerate

Développement d’un algorithme d’apprentissage profond pour la modélisation 3D des bâtiments à partir de photographies aériennes et de données lidar

Le projet proposé vise à développer un système automatisé de modélisation 3D des bâtiments par intelligence artificielle, et plus particulièrement par l’utilisation des réseaux de neurones convolutifs. Ces derniers sont reconnus pour leur performance en vision par ordinateur, notamment dans la segmentation d’objets fournis à travers des exemples d’entrainement. Le système de modélisation 3D utilisera la combinaison de photographies aériennes et de données lidar afin d’améliorer la segmentation des bâtiments. Les algorithmes développés seront intégrés dans un système opérationnel qui permettra d’automatiser la reconstruction 3D des bâtiments, et ainsi de réduire le temps et les coûts de cette opération pour la compagnie.

Voir la description complète du projet
Superviseur du corps professoral :

Yacine Bouroubi;Richard Fournier;Mickael Germain

Étudiant :

Partenaire :

XEOS Imagerie

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Université de Sherbrooke

Programme :

Accelerate

Lithium titanate nanocomposites for hybrid supercapacitors

Rapidly diversifying technologies are driving demand for power supplies that can meet a wider range of and more intermittent power needs. Main drivers include transportation, renewable energy grid connections, energy storage, and consumer electronics. Tesla has recently purchased a top supercapacitor company, Maxwell Technologies, to streamline these advancements to product integration. Supercapacitors are an important technology used in the power supply industry, supplementing conventional batteries by offering higher power and longer lifetime. Hybrid supercapacitors are undergoing accelerated development and expected to surpass current market options due to their promise of high energy and power density, and long cycle life. In this project we investigate fabrication process variations to improve their performance. Our industry partner intends to scale up the processes to establish Canadian supercapacitor R&D and manufacturing that will position us as a global competitor in this expanding high tech market.

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Superviseur du corps professoral :

John Madden

Étudiant :

Partenaire :

Tycor UPS;Edison Power Corp

Discipline :

Engineering

Secteur :

Manufacturing

Université :

The University of British Columbia

Programme :

Accelerate

Ownership of Content in an Overlay Platform

The notion of ownership is fundamental and essential in a number of settings, including the setting that is the focus of this proposal: information over the Internet. Ownership of some content, in turn, endows the owner with certain rights over the content. The intent of this proposed research project is to (a) precisely enunciate what properties we associate with the notion of ownership in the software platform for structuring content over the Internet that our partner organization, Scrawlr Inc., is developing, and (2) incorporating into their software using sound software engineering principles elements of this notion of ownership. Our research will be of value to both our partner organization, and more broadly, to Canadians, as management and generation of new ways of presenting content over the Internet has now become a norm, and we seek to give owners of information meaningful control over it.

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Superviseur du corps professoral :

Mahesh Tripunitara

Étudiant :

Partenaire :

Scrawlr Development Inc.

Discipline :

Engineering

Secteur :

Information and Communications Technology

Université :

University of Waterloo

Programme :

Accelerate

Fault Diagnosis for Gas Turbine Engine Systems Using Model-Based Techniques

The ability to find fault in engine systems and proactively monitor their progression to remedy the root-cause before it fails is of paramount importance in today’s industry safety. An effecting change in current engine monitoring methods will require insight and understanding of the level of robustness and engineering rigour required to maintain safety and airworthiness standards. A model-based fault detection method compares the engine’s output data to that of a model running simultaneously. A suitable threshold should be selected to avoid false alarms due to measurement non-repeatability and current model uncertainty. Any difference beyond a threshold value signifies that a fault has occurred. This project aims to develop novel methods for fault diagnosis of gas turbines that require fewer data/parameters to work while maintaining or improving the detection and isolation schemes’ accuracy.

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Superviseur du corps professoral :

Afshin Rahimi

Étudiant :

Partenaire :

Reticom Solutions

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Windsor

Programme :

Accelerate

Luminescent Solar Concentrator Waveguide Encoded Lattice (LWELs)

The principal objective of this project is to design and fabricate optically functional, slim, flexible, dielectric coatings – luminescent wavelength encoded lattices (LWELs) – that enhance sunlight harvesting and therefore, within the short term, have a measurable, significant impact on the efficiency of commercially available solar cells. LWELs will combine two powerful approaches to incandescent light-collection: (i) lumophores that convert ultraviolet light – normally wasted as dissipated heat – into visible wavelengths that can activate the photovoltaic cell and (ii) dense, complex 3-D polymer waveguide architectures that impart near-hemispherical fields of view (FOV), enabling efficient light collection despite the diurnal solar trajectory. This is fundamentally different from typical solar cell configurations, which are efficient only when the Sun is incident along the surface normal and therefore must be physically rotated to track the Sun across the sky.

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Superviseur du corps professoral :

Kalaichelvi Saravanamuttu

Étudiant :

Partenaire :

University of Cambridge

Discipline :

Physics

Secteur :

Education

Université :

McMaster University

Programme :

Globalink Research Award

Investigation of the practicality and benefits ofintegrating photovoltaic (PV) arrays with greenroofs

Throughout Canada manufacturers and distributers of green roof and photovoltaic (PV) panels compete for installation projects on top of industrial, commercial and high-density residential rooftops.
These technologies are often viewed as direct competitors as both systems reduce the environmental impact of buildings, albeit through different mechanisms, and consequently, rooftop designs rarely, if
ever, apply both technologies. However, when integrated together, green roofs systems may improve the energy performance and lifetime of PV arrays through evapotranspirative cooling in combination with solar reflectance. Curently, there exists no published data on the practicality and benefits of integrating Solar PV with green roof systems in Canada. The research at the Green Roof Innovation Testing (GRIT) lab will deliver to our industrial partners Tremco and Bioroof: improved models, design tools and guidelines, and Canadian-based performance data which are essential to build consumer acceptance of new roof systems and to drive innovation.

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Superviseur du corps professoral :

Liat Margolis

Étudiant :

Partenaire :

Tremco;Bioroof Systems Inc

Discipline :

Earth science

Secteur :

Construction and infrastructure

Université :

University of Toronto

Programme :

Accelerate

AI-based Platform for Population-level Social Isolation Detection and Prediction

Social isolation is a serious public health issue which has many negative effects on quality of life and well-being of individuals. This research project aims to develop and test a Minimally Viable technology platform (MVP) to tackle population-level social isolation. This platform is designed to collect and analyze surveys from the users and detect socially isolated people and identify individuals at risk of isolation in a community using AI and social network analysis techniques. It is capable of analyzing real-time data obtained from the users through multiple channels such as web portal or mobile app. Our approach is to map the network to an attributed weighted multi-dimensional social graph and use graph theory, network science, and AI techniques.

Voir la description complète du projet
Superviseur du corps professoral :

Pooya Moradian Zadeh

Étudiant :

Partenaire :

Community Support Centre of Essex County

Discipline :

Computer science

Secteur :

Health and Related Sciences & Technology

Université :

University of Windsor

Programme :

Accelerate

The impact of social distancing on biological rhythms and mental health: a study of the effectiveness of interventions in biological rhythms and sleep

Under the conditions of social distancing during the COVID-19 pandemic, most individuals are experiencing a major shift in daily routines. For some, having a flexible work schedule may be beneficial to their natural bodily rhythms. For others, the lack of structure that was previously provided by an external schedule may impose misalignment on behavioural circadian cues, such as eating and sleeping schedules, physical activity, and social interactions. Therefore, there is a need to understand how social distancing has impacted circadian rhythmicity and mental health, and if adhering to recommendations focused on maintaining circadian organization improves mental health outcomes. These are the primary aims of the study. Specifically, the student will assess daily variability in affective, cognitive, and somatic symptoms and their relationships to scores of anxiety and depression. The current project examines the effects of social distancing one year after the emergence of COVID-19 restrictions, and is complementary to a similar project that was launched at the start of the pandemic.

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Superviseur du corps professoral :

Benicio N. Frey

Étudiant :

Partenaire :

Universidade Federal do Rio Grande do Sul

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology; Other

Université :

McMaster University

Programme :

Globalink Research Award

High-Throughput Linguistic Content Sentiment Analysis

Explosive growth of social media has transformed how people communicate, interact, and actively express their opinions about different topics. Scrawlr’s unique model for platform management allows extensive freedom for users to generate their content, creating a novel opportunity to evaluate user opinions and network structure. A popular method to analyze online content is sentiment analysis. While research on sentiment analysis is growing explosively, most methods rely on lexicon-based or machine learning approaches. The majority of research efforts are designed to work with only English content, while a significant share of information is available in other languages. In the proposed research, using machine learning algorithms, we develop an automated content sentiment analysis in multiple languages and take a different step into this field, which is providing the capacity to enable comparison of sentiment conclusions against the evaluation and classification of content by users. In other words, we train a set of data, then predict the labels for the rest based on the train set.

Voir la description complète du projet
Superviseur du corps professoral :

Ketra Schmitt

Étudiant :

Partenaire :

Scrawlr Development Inc.

Discipline :

Computer science

Secteur :

Information and Communications Technology; Artificial Intelligence; New and Digital Media

Université :

Concordia University

Programme :

Accelerate

Structuration d’un accélérateur d’entreprise spécialisée en intelligence artificielle : Thales AI@Centech – Suite

Thales vient de lancer son accélérateur AI@Centech. Situé à Montréal, l’accélérateur a pour objectif d’accompagner, sous forme de cohortes de 6 mois, des start-ups qui fournissent des solutions basées sur l’intelligence artificielle (AI). Cette grappe Mitacs, qui réunit des stagiaires de l’ÉTS et HEC, vient appuyer Thales dans la structuration de son accélérateur d’un point de vue de gestion de l’innovation. Les stagiaires auront notamment à cartographier l’écosystème d’innovation, identifier des partenariats potentiels, recenser les meilleures pratiques, créer des outils d’accompagnement pour les cohortes et soutenir les start-ups dans le développement de leurs solutions

Voir la description complète du projet
Superviseur du corps professoral :

Mickaël Gardoni;Patrick Cohendet;Patrick Cohendet

Étudiant :

Partenaire :

Thales Canada Inc (Montreal, QC)

Discipline :

Engineering

Secteur :

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

Université :

École de technologie supérieure; HEC Montréal

Programme :

Accelerate

The Effects of Release Size, Location and Timing on Chinook Salmon on the West Coast of Vancouver Island

Throughout Western North America with few exceptions all species of Pacific Salmon stocks have been in steady decline for over 50 years. On the West Coast of Vancouver Island, Chinook salmon stocks are of particular concern. These fish provide ecological, cultural and economic value to the region and current numbers are at an all-time low. This research will use PIT telemetry and capture-recapture techniques to study survival, growth and habitat use of Chinook salmon during outmigration and early marine life to identify habitat bottle necks or other limiting factors to production/survival as well as study success of hatchery released fish. It is important to study the early life history as egg-to-smolt life stages of salmonids experience high mortality rates and survival during this time is a key factor contributing to population growth for Pacific salmonids.

Voir la description complète du projet
Superviseur du corps professoral :

Eduardo Martins

Étudiant :

Partenaire :

Toquaht Management Ltd.

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

University of Northern British Columbia

Programme :

Accelerate

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Mitacs — Retour sur innovation

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.