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

Real-time COVID-19 detection in wastewater from long-term care homes

The goal of the partnership between Mantech and Waterloo is to develop a technology to manufacture smart hybrid water sensors for current and future disease prediction and detection. This technology will have an invaluable impact on human health research efforts to contain the COVID-19 and possible future pandemic spread, and put Ontario and Canada far ahead of similar efforts worldwide.

Voir la description complète du projet
Superviseur du corps professoral :

Mustafa Yavuz

Étudiant :

Partenaire :

Mantech

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Waterloo

Programme :

Accelerate

Quini Machine Learning Wine Recommendation Engine

Quini is developing a revolutionary system that allows wine producers to predict with a high level of accuracy how much acceptance and sales they will be able to generate from a wine product, over time, in which major cities and selling to whom as the primary buyers. The system will also give consumers exacting wine recommendations that suit their personal taste and that are likey to be available for purchase in their area.

Voir la description complète du projet
Superviseur du corps professoral :

Jiguo Cao

Étudiant :

Partenaire :

Quini

Discipline :

Mathematics

Secteur :

Information and cultural industries

Université :

Simon Fraser University

Programme :

Accelerate

Photoelectrochemical biosensing for COVID-19: virus and antibodies

This project aims to develop a Photoelectrochemical (PEC) biosensor based on photoactive nanoparticles such as Quantum Dots (QDs) for the detection of COVID19 and related antibodies. Highly efficient QDs based on engineered core/multi-shelled structures will be developed and their interaction with a molecular recognition element (MRE) layer will be investigated. A consistent structure-property picture of virus and antibody detection will be developed by studying the relationship between QD-ligands structures and detection performance, to realize a new PEC biosensor that can be used in different conditions, under specific types of lighting. This research will be conducted in close collaboration between the Solstar Pharma R&D team and the INRS Intern for the whole duration of the project. The expected impacts will result in advancing knowledge regarding the biosensing mechanism of the virus, with the realization of a PEC biosensor for detecting COVID antibodies.

Voir la description complète du projet
Superviseur du corps professoral :

Federico Rosei

Étudiant :

Partenaire :

Solstar Pharma

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Université du Québec : Institut national de la recherche scientifique

Programme :

Accelerate

Adapting Maxwellian’s surface plasmon resonance optical sensor platform for COVID detection

To control and thwart the COVID19 pandemic, significant efforts are being deployed to adapt existing diagnostic tests, including those that use the standard reverse transcription polymerase chain reaction (RT-PCR) method, to detect the SARS-COV-2 virus. Despite its high sensitivity and ability to detect small virus amounts in samples, RT-PCR is time consuming and subject to diagnostic errors (false positives and false negatives). Capitalizing on their respective complementary expertise, Prof. Rosei’s team at INRS and Maxwellian decided to join efforts to develop a technology for antimicrobial sensing and specifically SARS-COV-2 detection. In particular, the MITACS intern will play a crucial role in adapting Maxwellian’s existing sensing technology for this purpose. Maxwellian brings its core expertise in optical fiber sensors and its technology based on photonic-plasmonic resonators to synergistically combine it with nanomaterials and processes developed in Prof. Rosei’s team. This multidisciplinary project will provide advanced training in the areas of nanomaterial-based devices, optical sensors and data analysis which are relevant in the high-tech photonics sector.

Voir la description complète du projet
Superviseur du corps professoral :

Federico Rosei

Étudiant :

Partenaire :

Maxwellian

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Université du Québec : Institut national de la recherche scientifique

Programme :

Accelerate

From pipeline inspection data to insight

To ensure oil and gas pipelines operate safely, instrumented inspections and assessments are completed on a recurring frequency. A common and valuable inspection method is In-line inspection (ILI). This form of inspection uses a measurement device (ILI tool) that is propelled through the pipeline by product flow and the tool identifies and sizes anomalous conditions along the inside and outside walls of the pipeline that could affect the pipes ability to contain the product. Anomalous conditions can include metal loss corrosion, deformations, cracking, weld defects, and other defects on pipe welds. The results of an ILI survey are used in the determination of repair and replacement locations for a pipeline. The purpose of this project is to study the data from multiple historical ILI surveys, subsequent corresponding non-destructive examinations (NDE) reports, and basic pipe attribute and operating data to assess if any trends, patterns, or commonalities can be determined.

Voir la description complète du projet
Superviseur du corps professoral :

ZhangXing John Chen

Étudiant :

Partenaire :

Dynamic Risk

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Calgary

Programme :

Accelerate

Antioxidants render silicone elastomer surfaces antiviral

Viruses are susceptible to antioxidants. COVID-19, to which the grant is directed, is also affected by surface active species, like soap. These two vulnerabilities of the virus will be combined to create silicone coatings that will render relevant surfaces anti-viral (e.g., doorknobs, facemasks and shields). Antioxidants will be modified with entities that allow them to be dispersed in silicone elastomers, from which they can be released, or to which they are chemically tethered. In either case, the surface active and antioxidant active ingredients will present at the interface, leading to COVID-19 death on contact. The research project involves small molecule and polymer synthesis, physical characterization, and biological assessment using, initially, a safe virus bacteriophage as a surrogate for COVID-19. Our partner, Siltech, is a world leader in surface active silicones. They will scale up and test promising surface formulations. 1 PDF will be involved in the project.

Voir la description complète du projet
Superviseur du corps professoral :

Michael Brook

Étudiant :

Partenaire :

Siltech

Discipline :

Physics

Secteur :

Manufacturing

Université :

McMaster University

Programme :

Accelerate

Monolithic microwave integrated circuit front-end module for satellite communication and next generation wireless communication applications – Year two

Front-end Module is key component in satellite and wireless telecommunication systems. It contains sub-modules like power amplifier, duplexer, antenna, low noise amplifier and etc. Advanced semiconductor technology enables the integration of these sub-modules. Compared to conventional bulky communication systems, this integration features compact size, lower cost, and higher performance. In 2019, the MMIC market reaches 7.7 Billion and increase to 10 Billion in 2022. The proposed project will use Gallium Nitride, the latest semiconductor technology, to design high performance MMIC chips. The target of this project is increasing the efficiency and bandwidth of the power amplifier, lower the noise of low noise amplifier and the switch, and integrate these parts in a compact area. The outcome of project will provide competitive products to the communication market which helps the partner company to gain a larger market share in the near future.

Voir la description complète du projet
Superviseur du corps professoral :

Ammar Kouki

Étudiant :

Partenaire :

AGILEMMIC INC

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

École de technologie supérieure

Programme :

Elevate

Monolithic microwave integrated circuit front-end module for satellite communication and next generation wireless communication applications

Front-end Module is key component in satellite and wireless telecommunication systems. It contains sub-modules like power amplifier, duplexer, antenna, low noise amplifier and etc. Advanced semiconductor technology enables the integration of these sub-modules. Compared to conventional bulky communication systems, this integration features compact size, lower cost, and higher performance. In 2019, the MMIC market reaches 7.7 Billion and increase to 10 Billion in 2022. The proposed project will use Gallium Nitride, the latest semiconductor technology, to design high performance MMIC chips. The target of this project is increasing the efficiency and bandwidth of the power amplifier, lower the noise of low noise amplifier and the switch, and integrate these parts in a compact area. The outcome of project will provide competitive products to the communication market which helps the partner company to gain a larger market share in the near future.

Voir la description complète du projet
Superviseur du corps professoral :

Ammar Kouki

Étudiant :

Partenaire :

AGILEMMIC INC

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

École de technologie supérieure

Programme :

Elevate

Spatio-Temporal Models for the Analysis of GPS Traces: Application to Road Safety

The goal of this research is to leverage the telematics data collected in the context of the usage-based insurance program at Intact for road safety improvement. Specifically, we aim to tackle issues on the identification of risky driver behaviors through the characterization of unsafe events and to identify sites on the road network with high probability of collision. The objectives of this research project are defined around three research themes: 1) Automated detection and characterization of unsafe events at the driver level using unsupervised, semi- supervised and supervised machine learning models; 2) Computation of contextual variables at the network level (traffic and congestion measures); and 3) Network screening and validation of the measures defined in themes 1) and 2). This project will revolve around the third theme which will involve the development of spatio-temporal point process models for network screening using historical crash database. This project is part of a larger research project carried at HEC Montreal on road safety in collaboration with several researchers from McGill, Polytechnique and HEC Montreal. By developing a better framework and better tools for GPS and motion sensor data analysis, Intact Insurance will gain a competitive edge over its competitors, both nationally and internationally.

Voir la description complète du projet
Superviseur du corps professoral :

Aurélie Labbe

Étudiant :

Partenaire :

Intact

Discipline :

Mathematics

Secteur :

Transportation (excluding aerospace); Finance and Insurance; Health and Related Sciences & Technology

Université :

HEC Montréal

Programme :

Elevate

Trunk task-oriented training combined with functional electrical stimulation to improve functional independence in spinal cord injured individuals

Following a spinal cord injury (SCI), sensory and motor impairments affect the ability to perform daily life tasks independently, such as transferring or grabbing an object. Intuitively to accomplish these tasks, the use of the upper and lower limbs is obvious, but the trunk is equally essential. Trunk control alterations generate deficits in the functional independence (FI), even in sitting position. However, alteration processes and clear treatment guidelines have not been issued.
Trunk task-oriented training (T-TOT) combined with function electrical stimulation (FES) is a novel rehabilitation approach using the capacity of the central nervous system to reorganize (neuroplasticity) to increase trunk motor control and therefore possibly improve FI.
The objectives are to 1) evaluate FES/T-TOT efficacy on sitting balance and FI, and 2) understand the mechanisms of neuroplasticity that would improve FI following FES/T-TOT in individuals with SCI.
Improving FI of individuals with SCI will reduce healthcare costs for the individuals themselves and the health system. Private clinics are increasingly becoming key players in the healthcare system for the recovery and health of Canadians.

Voir la description complète du projet
Superviseur du corps professoral :

Dorothy Barthélemy

Étudiant :

Partenaire :

Neuro-Concept Inc

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology

Université :

Université de Montréal

Programme :

Elevate

Elaboration of a high-throughput toolbox for analysis and visualization of mesoscale longitudinal cortical imaging dataset – Year two

In recent years, a dramatic increase in computer processing power and storage allowed the exploration of new frontiers in science by analyzing large, complex datasets. The field of neuroscience is evolving towards larger and more complex studies creating a huge amount of data that is hard to understand using classical analyses. Thus, the development of tools able to process voluminous datasets is necessary to advance our understanding of brain function. Although some efforts have been made to solve this issue, most of the software is created “in-house” with limited applications, discouraging their use by other groups. In this project, a new open-source software will be designed to process large amounts of data from brain optical imaging experiments. This will be done with the collaboration of LabeoTech, a Canadian SME specialized in the development of technological tools applied to biomedical research. The toolbox will be published online where web-based tools will be created to build a community of researchers and engineers/programmers to encourage discussions on analytical problems on optical imaging. This will give LabeoTech a greater reach to more potential clients worldwide, and consequently it will contribute to the establishment of a Canadian expertise on this niche of biomedical research industry.

Voir la description complète du projet
Superviseur du corps professoral :

Matthieu Vanni

Étudiant :

Partenaire :

LabeoTech

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Elevate

Elaboration of a high-throughput toolbox for analysis and visualization of mesoscale longitudinal cortical imaging dataset

In recent years, a dramatic increase in computer processing power and storage allowed the exploration of new frontiers in science by analyzing large, complex datasets. The field of neuroscience is evolving towards larger and more complex studies creating a huge amount of data that is hard to understand using classical analyses. Thus, the development of tools able to process voluminous datasets is necessary to advance our understanding of brain function. Although some efforts have been made to solve this issue, most of the software is created “in-house” with limited applications, discouraging their use by other groups. In this project, a new open-source software will be designed to process large amounts of data from brain optical imaging experiments. This will be done with the collaboration of LabeoTech, a Canadian SME specialized in the development of technological tools applied to biomedical research. The toolbox will be published online where web-based tools will be created to build a community of researchers and engineers/programmers to encourage discussions on analytical problems on optical imaging. This will give LabeoTech a greater reach to more potential clients worldwide, and consequently it will contribute to the establishment of a Canadian expertise on this niche of biomedical research industry.

Voir la description complète du projet
Superviseur du corps professoral :

Matthieu Vanni

Étudiant :

Partenaire :

LabeoTech

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Elevate

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