Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

31132 Completed Projects

2940
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5159
BC
837
MB
685
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882
SK
9291
ON
9695
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97
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601
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1161
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Projects by Category

Travaux préliminaires à l’implantation du Learning Analytics Lab pour optimiser et monitorer l’engagement et l’apprentissage dans des environnements numériques

Si les TIC ont permis à la formation de devenir plus accessible et favoriseraient l’engagement et la motivation, les faibles taux de réussite en formation à distance (FAD) posent problème. Les environnements numériques (EN) utilisés dans les formations en ligne enregistrent systématiquement les traces informatiques des activités des apprenants, qui peuvent être combinés avec des données de questionnaire dans une approche de Learn Analytics. Le projet vise notamment à développer des systèmes et des interventions soutenant l’apprentissage, la collaboration et l’engagement des apprenants; à comprendre les stratégies d’apprentissage et de collaboration déployées par les apprenants ainsi que les usages qu’ils font des ressources d’apprentissage ; à mieux comprendre l’engagement et la motivation des apprenants; et enfin à développer et mettre en place un cadre d’évaluation de la qualité. Les résultats permettront d’évaluer les processus d’apprentissage en fournissant des éléments pour rendre optimaux l’engagement, l’apprentissage, et ultimement, la réussite.

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Faculty Supervisor:

Bruno Poellhuber

Student:

Partner:

Loto-Québec

Discipline:

Computer science

Sector:

Arts, entertainment and recreation

University:

Université de Montréal

Program:

Accelerate

Enhanced and Conformation Specific G protein-coupled receptors (GPCRs) Expression for Autoimmune Diagnostics

G protein-coupled receptors (GPCRs) are proteins present on the surface of a cell that are the targets of >30% prescription drugs. These GPCRs are involved in various diseases ranging from hypertension, airway diseases to taste disorders. Detection of antibodies for GPCRs in various disease states is a challenging task. The main goal of this project is to develop novel methods and improve existing methods to overexpress a couple of GPCRs for potential use in diagnostic assays. The industry partner, Acudex Inc. has a strong interest in the outcomes of the proposed research project and has the capacity to validate the assays and commercialize the findings.

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Faculty Supervisor:

Anthony Iacopino;Prashen Chelikani

Student:

Partner:

Acudex-Canada Inc

Discipline:

Life Sciences

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Deep learning for tooth wear monitoring of mining shovels

The main objective of this project is using deep learning algorithm to enhance the current state of the art tooth wear monitoring system used in mining shovels. Unlike the current approach, the proposed deep learning method operates by building a model from input images in order to make data-driven predictions. We use deep learning approach to identify the pixels that belong to the teeth-line in each video frame taken by camera located on the mining device. Consequently, the extracted teeth will be registered to a template in order to compute all the changes happened to the teeth length during time.

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Faculty Supervisor:

Parvin Mousavi;Purang Abolmaesumi

Student:

Partner:

Motion Metrics

Discipline:

Engineering

Sector:

Mining; Technology; Advanced Manufacturing

University:

Queen's University

Program:

Accelerate

Non-Stationary Time-Series Analysis based on Geometric Signal Modeling

High dimensional signals may arise in many fields of science. For example, biomedical signals such as EEG and EMG can be modeled by few latent processes measured by a large set of noisy sensors. In such applications the goal is to identify the latent intrinsic variables, which describe the true, intrinsic state of the system, e.g. disease state, sleep stage, performed action. Such real signals are commonly hard to analyze due to nonlinearities and rapid state changes in time (non-stationarity). In this project we plan to address these difficulties and construct a framework which is based on manifold learning techniques. These techniques provide a compact and reliable representation of the system by exploiting the structure and patterns in the data. This compact representation describes intrinsic properties of the analyzed system. We plan to develop new mathematical tools which will give rise to a new analysis framework for problems involving rapidly changing signals that existing tools fail to handle.

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Faculty Supervisor:

Hau-tieng Wu

Student:

Partner:

Technion – Israel Institute of Technology

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

Metal-free Carboxylation of Electron Rich Substrates with CO2

Carbon dioxide, a green-house gas that contributes to global warming. It is overabundant and therefore inexpensive. Nowadays, there are many attempts to use carbon dioxide as carbon source in variety of products, such as plastic, foams, fuel etc., which will reduce its amount in atmosphere. However, for now most of these methodologies are not efficient enough and usually very expensive due to use of very expensive compounds used in this processes. In this project we aim to develop new inexpensive and environmentally friendly methods for using carbon dioxide in a variety of different chemical processes and products. Therefore, the approach we aim to develop is of high environmental importance as well as have high industrial potential.

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Faculty Supervisor:

Douglas Stephan

Student:

Partner:

Tel Aviv University

Discipline:

Physics

Sector:

University:

University of Toronto

Program:

Globalink Research Award

Engineering human muscle tissue with PEGylated fibrinogen

Loss of skeletal muscle integrity arising from disease, injury, or genetic conditions is debilitating to human health and happiness. Efforts aimed at identifying drugs that improve skeletal muscle strength and form relies on assays of cells grown within two-dimensional culture dishes. While this format has served the community well for several decades, three-dimensional tissue models are emerging as more faithful models of human tissues. The Gilbert Lab (Canada) recently developed a 96-well custom built screening platform that supports the growth and maturation of miniature human skeletal muscle tissues. The Seliktar Lab (Israel) created a semi-synthetic polymer that is well suited to support muscle maturation. In this Student Mobility Innovation Initiative, the Gilbert lab will test the utility of the Seliktar Lab polymer to replace a costly component of their platform thereby overcoming cost and reproducibility issues that hinder widespread adoption of the system.

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Faculty Supervisor:

Penney Gilbert

Student:

Partner:

Technion – Israel Institute of Technology

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

Testing the response of sand samples to cyclic loading under different boundary conditions

Local site conditions can strongly influence the amplitude and duration of ground motion during an earthquake. Therefore, it is necessary to analyze and understand the mechanical properties of soils. By testing the same samples with similar conditions in different devices we can obtain more accurate results for dynamic loading tests and imitate the stress history that a soil might experience. The preparatory work will include a series of tests that will be held at Ben Gurion University under the supervision of Dr. Ronnie Kamai, followed by a test-series on a different testing device, held at University of Toronto under the supervision of Dr. Mohsen Ghafghazi. Such comparison will allow us to develop a more comprehensive understanding and quantification of the soil’s response to dynamic excitation. The mechanical properties of the soil can then be used to describe the behavior the soil during earthquake loading. With these parameters it will be possible to create an analysis that is more proper and accurate to the local conditions in Israel, contrary to what we think exists in the local building code today.

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Faculty Supervisor:

Mohsen Ghafghazi

Student:

Partner:

Ben-Gurion University of the Negev

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

Modélisation avancée des cuves d’électrolyse et l’efficacité énergétique

Les travaux qui seront entrepris par les stagiaires entrent dans le cadre de la Chaire de recherche industrielle CRSNG-Alcoa « Modélisation avancée des cuves d’électrolyse et l’efficacité énergétique (MACE3) » et de la subvention de Recherche et développement coopérative (RDC) « Amélioration de l’efficacité énergétique de l’électrolyse d’aluminium par l’optimisation du procédé de fabrication d’anodes, phase II ». Ces travaux permettront de développer les connaissances et les techniques requises pour contribuer à améliorer la performance énergétique des cuves Hall-Héroult, afin de réduire la consommation d’énergie et l’émission de CO2. Le développement de l’expertise pour la modélisation et l’amélioration de cuves d’électrolyse nécessite ainsi le développement de modèles numériques de pointe, la maîtrise du comportement multi physiques des matériaux utilisés et l’augmentation du rendement énergétique des anodes de carbone.

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Faculty Supervisor:

Mario Fafard;Seyed Taghavi;Louis Gosselin;Houshang Alamdari;Mario Fafard

Student:

Partner:

Alcoa Canada

Discipline:

Engineering

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

Thermo-economic assessment and experimental investigation of renewable energy based NH3 production options for clean energy communities

Production and utilization of ammonia in the transportation and power generation sector brings numerous advantages by introducing environmentally friendly, sustainable and efficient systems. Ammonia (NH3) is the only carbon-free chemical energy carrier together with hydrogen suitable for use as a transportation fuel. In this project, renewable energy based NH3 production methods are investigated for power generation, transportation and energy utilities. Specifically, concentrated solar energy based electrochemical ammonia synthesis is experimentally investigated. Furthermore, comparative thermodynamic, thermo-economic and life cycle analyses related to wind, hydro and solar energy based ammonia production and utilization are undertaken together with hydrocarbon decomposition based ammonia synthesis.

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Faculty Supervisor:

Ibrahim Dincer

Student:

Partner:

Hydrofuel Inc.

Discipline:

Engineering

Sector:

Green/Alternative Energy; Sustainability & the Environment; Transportation (excluding aerospace)

University:

University of Ontario Institute of Technology

Program:

Accelerate

Generation Z: Understanding Canada’s Newest Youth Generation

The differences among today’s multiple generations of workers, such as Baby Boomers, Generation X and Millennials have received a great amount of attention from the media, business best-sellers and academic researchers. Much of the recent existing research has documented perceived and observed characteristics of the millennial generation (those born in the 1908s and after), who are said to differ from preceding generations in their perspectives on work and life in general. There is little agreement on the end date of the millennial generation, raising speculation about the generation that follows them (tentatively referred to as “Generation Z”): When did this generation begin? How are they different from Millennials? How will they approach their careers and working lives?. This study will investigate trends in the characteristics, expectations, values, attitudes and behaviors of Canada’s youngest adults to determine if and how they differ from Millennials. This will establish generational trends for the future and an appropriate cut-off point between them and Millennials. The information we gather will help educators, employers and governments better understand and react to emerging generational trends.

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Faculty Supervisor:

Sean Lyons

Student:

Partner:

Lovell Corporation

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

University of Guelph

Program:

Accelerate

External Cavity Laser Integrated with Silicon Photonic Systems

The project aims to develop a novel optical device for use in high-bandwidth data-communications. Such applications feed the insatiable desire for data transfer fuelled by the ever-expanding demand for social networking, video-over-internet and the emerging internet-of-things. The intern will gain invaluable industrial experience in a rapidly growing area, while the company will obtain an insight into the potential expansion of its product line into new applications.

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Faculty Supervisor:

Andrew Knights

Student:

Partner:

RANOVUS Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

McMaster University

Program:

Accelerate

The use of assistive technology in school-aged children with learning disorders

Assistive Technology (AT) allows children with Specific Learning Disabilities (LDs) to adequately access school curriculum. There is a paucity of literature addressing perception of use and training for teachers to support use. Studies suggest that children with AT like their devices and find them useful. The proposed study will examine the ages of children provided AT devices, the types of AT hardware and software being used by children with various learning limitations in a school environment, and children’s perception of their AT devices. Archival data collected from school-aged children referred to the Learning Disability Association of Windsor-Essex County (LDAWE) will be statistically analyzed. The proposed research will increase the understanding of current practices of the distribution and utilization of AT.

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Faculty Supervisor:

Joseph Casey

Student:

Partner:

Learning Disabilities Association of Windsor - Essex County

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology

University:

University of Windsor

Program:

Accelerate

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.