Innovative Projects Realized

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

31620 Completed Projects

2978
AB
5221
BC
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projects by Category

Thermodynamic Modeling and Optimization of Pressurized Liquefied Natural Gas in the Presence of Solvent

The current research project aims to assess the PLNG storage condition for obtaining higher methane density. The liquified natural gas/methane is supposed to be shipped into the PLNG terminals. The PLNG market demands high methane density with a trace ethane. To make this happen, the solvent (e.g., C5, C6, and C7) are added to the natural gas for C2+ absorption purpose. Finding optimal pressure, temperature, and solvent composition avoid energy and money loss over the PLNG process. energy consumption minimization in the LNG and PLNG plants is of primary importance as several compression and liquefaction facilities are involved. Thus, toward the optimized operation, the partner organization will be benefit from energy efficient operation as well as achieving high methane density.

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Faculty Supervisor:

Sohrab Zendehboudi

Student:

Partner:

CanaGas Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Named Entity Recognition (NER) autodetection and Adverse Events (AEs) prediction from Social Media and scientific journals using a Deep Learning approach

Social medias data bases are important for continuous and automated Adverse Drug Reactions (ADRs) surveillance. Predicting ADRs can reduce the related mortality. A systematic review of the medical scientific literature is required for tracking and identifying the risk/benefit ratio of drugs and safety issues.
The implementation of means of standardizing patient’s language used in social media such as Twitter will improve the precision of ADR detection and continuous surveillance at post-marketing phase of drugs (off-label drug uses included). The required processing flow will be improved with labeling mechanisms enhancing machine learning algorithms that can make them more accurate.

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Faculty Supervisor:

Sylvie PERREAULT;Chahé Nerguizian

Student:

Partner:

Medvalgo Group

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program:

Accelerate

Suivi expérimental qualitatif et quantitatif d’unjardin de pluie en climat nordique

Cette étude vise à déterminer le niveau de performance du jardin de pluie aménagé dans les conditions
du climat nordique. Les résultats du suivi expérimental qui seront obtenus devront permettre de mettre
en évidence les points forts et faibles du système implanté à Longueuil, afin d’en améliorer le
fonctionnement en climat froid aussi bien en termes quantitatif que qualitatif. Le potentiel de
réutilisation domestique des eaux pluviales capturées par cet ouvrage sera aussi étudié.

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Faculty Supervisor:

Musandji Fuamba

Student:

Partner:

Vinci Consultants

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

École Polytechnique de Montréal

Program:

Accelerate

Large Scale Simulations of Photonic Quantum Computers

Current quantum computers are in the “NISQ”, or Noisy-Intermediate-Scale-Quantum regime. The true potential of quantum computing will only be realized when noise levels are reduced or controlled, and large scale is achieved. Xanadu’s approach is to use photonic technology as the building blocks of their machines. This project addresses two related questions concerning the future development of these machines: A – In which conditions does a photonic quantum computer reach quantum advantage (demonstrating large speedups compared to today’s most powerful conventional computers)? B – What are the resources required to build a scalable, fault-tolerant photonic quantum computer? This project will provide the team with a better understanding of the requirements and tradeoffs involved in the future, much larger-scale generations of quantum photonic hardware that must be built in order to fully realize the potential of quantum computing.

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Faculty Supervisor:

Hoi-Kwong Lo;John Sipe;Henry Yuen

Student:

Partner:

Xanadu

Discipline:

Computer science

Sector:

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

University:

University of Toronto

Program:

Accelerate

Digital Transformation of Automotive Industry: Action Design Researchand Startup for Last Price Recommendation Engines

The Automotive Industry is one of the most mature and has undergone several waves of digital transformation. We focus on one segment of the value chain where IT adoption has not yet had the expected impact, namely dealer-prospect relationship management. While Customer Relationship Management (CRM) solutions and methods have been widely adopted, there remains several issues as to how to properly match the right prospect with the most appropriate dealer. The channeling of prospects is relatively mature and well structured, but there remain significant issues to raise mutual satisfaction of both parties who must, on both sides, find their respective “best deal” more rapidly and efficiently. To shed new light on this challenge, as it requires more hands-on empirical analysis, we propose an Action Design Research (ADR) methodology helping a new startup in developing an innovative Last Price Recommendation Engine. The purpose of these internships will be to systematically analyze where process innovations may be possible, and to successfully implement these requirements into a new recommendation engine hosted on the domain name http://lastprice.ca

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Faculty Supervisor:

Stéphane Gagnon

Student:

Partner:

eSano Communications Inc.;Centre de recherche en technologies langagières

Discipline:

Business

Sector:

Professional, scientific and technical services

University:

Université du Québec en Outaouais

Program:

Accelerate

Performance mapping, modelling, and development of membrane-based energy recovery ventilation exchangers

Membrane based energy recovery ventilation (ERV) is now a key component of most energy efficient modern buildings. ERVs improve the indoor air quality of buildings through ventilation and reduce the energy cost of ventilation by using building exhaust air to pre-condition fresh building supply air. In cooling conditions heat and humidity are removed from the incoming air and in heating condition heat and moisture are added to the incoming air. The membrane in the device allows the transport heat and moisture without transport of other gases and contaminants from the exhaust air to the supply air. Better models are required for predicting performance of exchangers of different geometry, materials, and assembly methods. In this project students will assist in testing, prototype assembly, and analysis of exchangers and develop improved performance models for membrane-based ERVs.

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Faculty Supervisor:

Steven Rogak

Student:

Partner:

CORE Energy Recovery Solutions

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Innovation in Expanded Pharmacy Care Health and Wellness Approaches in the Grocery Retail Environment

Health care systems in Canada and countries around the world are challenged by increasing
demands for services, while providing those services within fixed health agency budgets. To address
these challenges, the Ivey International Centre for Health Innovation, Loblaw Company Limited and
Green Shield Canada has formed a collaborative partnership. The proposed research will engage
academic and industry researchers, key decision-makers, pharmacists and dietitians in examining
and exploring the impact of new, expanded models of pharmacy care in retail grocery store settings
that focus on achieving health and wellness outcomes for communities. In addition, the impact of
expanded pharmacy practice roles will be examined for potential program development opportunities
for employee health products designed to enhance employee health and wellness outcomes in
workplace settings.

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Faculty Supervisor:

Anne Snowdon

Student:

Partner:

Loblaws Inc;Western University

Discipline:

Business

Sector:

Health and Related Sciences & Technology

University:

Western University

Program:

Accelerate

Machine Learning Solutions for Detecting Suspicious and Abnormal User Access Roles and Entitlements

The latest cybersecurity incidents (e.g., Desjardinds, CapitalOne) have shown that the current cybersecurity solutions are not always effective in capturing and preventing attacks, especially when it comes to insider attacks that originate from within the targeted organization. In this project which will be conducted in collaboration with Xpertics, we aim to build a new solution for extracting and analyzing users’ access and entitlement data within a cloud environment, in order to detect suspicious and abnormal access activities and permissions. We will capitalize on the strength of deep learning to build strong prediction models with high accuracy. At the end of this project, the company will have an effective cybersecurity solution that could be used to prevent unauthorized access to its resources and identify the suspicious access attempts that try to manipulate the internal security measures of the company.

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Faculty Supervisor:

Jamal Bentahar;Omar Abdul Wahab

Student:

Partner:

Xpertics Solutions Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Anatomy Detection of Cats and Dogs using Localization

The proposed work is an application of artificial intelligence and medical imaging. When positioning a dog to have an X-ray image taken of its paw, a neural network trained in canine anatomy can be configured to inform radiologists if the patient’s paw is improperly placed or even drive motorized hardware to automatically center the patient’s anatomy with respect to the imaging hardware. Diagnostic X-ray images like DICOMs contain header information about the subject including species, anatomy imaged, and the orientation of the image. This information is filled out manually, but the aforementioned neural network could be configured to automatically populate this DICOM tag information. The methods developed in this research will be immediately applicable to the partner organization; these tools will be integrated within iMi’s x-ray imaging system for use in veterinary clinics. Additionally, automatic anatomy detection will allow iMi to develop new hardware informed by this technology.

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Faculty Supervisor:

Alex Thomo

Student:

Partner:

Innotech Medical Industries Corp

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Inclusion of Genetic Information to Better Inform Coffee Choices

Coffee is one of the world’s most popular beverages due to the delivery of caffeine and diverse flavours. The genetics of how caffeine is processed in the human body is fairly well understood. With the decrease in cost and increase in popularity of consumer genetics, we are interested in learning how modern genetic analysis techniques can benefit the choice of caffeine and flavour for coffee consumers. We plan to look at candidate genes that relate to caffeine clearance rates within volunteers, then deliver blends of coffee customized to individual volunteers’ caffeine tolerances and preferences. Additionally, the genetics of flavour perception, and taste associated genes are fairly well known. Based on candidate taste genes, will also test which blends of coffee are preferred based on flavour perception with respect to bitter taste genes.

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Faculty Supervisor:

Marc Ekker

Student:

Partner:

Beverage Genetics

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Ottawa

Program:

Accelerate

Analyzing a Large User Community using theSocial Network Analysis Framework

In this project we will conduct Social network analysis (SNA) of MyCA user network, in order to
assess the interplay between social influence and the diffusion of information within the MyCA
platform. SNA offers a convenient method to represent and analyze interactions among the
components of a system. SNA can thus provide an abstract representation of the MyCA a system,
and allow us to study its function and organization. We will work with CA to determine ways to use our
insights to increase participation of MyCA members such that their connections and contributions will
bring overall value to the community. The results of this analysis will help us determine how to
structure the platform and support community users such that greater value can be realized by
community users, CA employees, and CA product owners.

View Full Project Description
Faculty Supervisor:

Kelly Lyons

Student:

Partner:

CA Technologies

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program:

Accelerate

Microemulsion technologies for the extraction and delivery of herbal oils and oleoresins

Herbal oils and oleoresins are components extracted from flowers, bark, leaves, roots, or fruits. These extracts are used as fragrances, flavoring agents, antimicrobials, and therapeutic agents with a market value of more than USD 8.5 billion and 7% annual growth. Steam and solvents are used to extract oils and oleoresins (respectively), but they have limited extraction efficiency, are energy-intensive, and emit greenhouse gases (GHG). Solvent extraction can also emit volatile organic components (VOCs) and produce flammable environments. This project seeks to develop aqueous extraction and delivery systems for herbal oils and oleoresins using food-grade surfactants and emulsified solvents. The example herbal oil, clove oil, and oleoresin, capsaicin, are both used as flavoring agents, as antimicrobials, and as medicinal compounds. Micellae delivery systems (partner organization) will use the findings from this work to develop a safe aqueous extraction process and delivery systems for cannabinoids.

View Full Project Description
Faculty Supervisor:

Edgar Acosta

Student:

Partner:

Micellae Delivery Systems

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Toronto

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.