Projets novateurs réalisés

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

31 133 projets complétés

2940
AB
5159
C.-B.
837
MB
685
NL
882
SK
9292
ON
9695
QC
97
PE
601
NB
1161
NS

Projets par catégorie

GRID: Geo-Registry Integrated Datachain

This project will conduct business model validation research for a blockchain prototype developed by Arrowhead Development Company Ltd for the real estate industry. The student intern will collect market research from potential stakeholders of this industry to help the partner organization assess business opportunities and revenue streams as well as informing the launch decision.

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Superviseur du corps professoral :

Neil Maltby;Jane Fraser

Étudiant :

Partenaire :

Arrowhead Development

Discipline :

Business

Secteur :

Real estate and rental and leasing

Université :

St. Francis Xavier University

Programme :

Business Strategy Internship

Predicting Reactions with Controlled Errors

Given a group of molecules and a specification of reaction conditions, do chemical reactions occur? If so, what products are produced, and what is their relative abundance? This problem pervades chemistry, with applications in environmental science (e.g., the degradation of pollutants), molecular sensing (e.g., interpreting the results of tandem mass spectrometry), chemical synthesis (e.g., finding efficient ways to synthesize drug molecules), and energy-efficiency (characterizing molecular combustion). Such problems are usually addressed by nearly exhaustive experimental and/or computational characterization techniques, both of which are extremely costly in terms of time, money, and human resources. We aim to use a data-science approach, so that these previous experimental/computational works can be leveraged to make predictions of likely chemical reactive pathways. One important innovation is to make these predictions in a controlled way, with error estimates so that future experimental/computational studies can be focused towards reactions where the model is highly uncertain, and redundant work can be avoided. Other innovations include using reactivity indicators to construct rich molecular representations and representing chemical reaction networks as hypergraphs.

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Superviseur du corps professoral :

Paul Ayers

Étudiant :

Partenaire :

Sorbonne Université

Discipline :

Physics

Secteur :

Artificial Intelligence; Quantum Science

Université :

McMaster University

Programme :

Globalink Research Award

Chemical and biological conversion of mussel processing by-products into new value streams in agriculture

Atlantic Canada’s fishery industries have been identified as key sectors where market demand is expected to increase. PEI mussel and shellfish production employ over a thousand employees, and contributes in excess of CAD$60 million to PEI’s coastal and rural communities. Production of Atlantic Canadian shellfish has tripled since 1995 and is expected to continue growing rapidly. Prince Edward Aqua Farms Inc., is one of the largest mussel and oyster producers in North America, generating 9,072 tonnes of mussels annually which results in 2,770 tonnes of solid waste by-products. Waste disposal is a serious economic and environmental burden that can cost the industry upwards of $888,410 each year. Landfill disposal of these by-products may also result in higher greenhouse gas emissions and represent a loss of valuable natural resources. Dalhousie University’s Innovative Waste Management Group aims to work with PE Aqua Farms to identify economically and technically viable pathways to create value from mussel by-product solid waste streams, including composts, biochar, and alternative agricultural liming amendments.

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Superviseur du corps professoral :

Gordon Price

Étudiant :

Partenaire :

Prince Edward Aqua Farms Ltd.

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Dalhousie University

Programme :

Accelerate

Modeling Strong Electron Correlation with AC-ERPA

In order to understand how chemical bonds fracture and form, and to predict how electrons rearrange in photoactive materials, one must describe the electron structure of the substances. This requires evaluating a quantum-mechanical model for the system. Unfortunately, accurate quantum-mechanical models require enormous computational resources, and can only be applied for tiny systems. For systems of chemical importance and technological relevance, “single-reference” quantum-mechanical models are used, but these standard methods are often unreliable, and frequently fail catastrophically for important classes of systems, including molecules containing unpaired or weakly-paired electrons and materials containing delocalized electron pairs or strongly localized unpaired electrons. Solving this problem requires extending single-reference methods: the host group (Katarzyna Pernal) has pioneered extensions of the random phase approximation and the adiabatic connection beyond their normal domain (single-reference Kohn-Sham density functional theory). The aim of this visit is to generalize the host group’s techniques to treat strong electron-pairing phenomena (e.g., for describing high-temperature superconductors and chemical catalysis).

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Superviseur du corps professoral :

Paul Ayers

Étudiant :

Partenaire :

Lodz University of Technology

Discipline :

Physics

Secteur :

Quantum Science; Other

Université :

McMaster University

Programme :

Globalink Research Award

Advance Generalizability of Graph-based Machine Learning Models for Applications Automotive Metal Forming and Impact

In modern automotive engineering, vehicles are primarily designed in the virtual space to enable a rapid vehicle design process. However, this process is heavily constrained by the time and computational requirements necessary to generate the vast number of simulations needed for vehicle design. Fortunately, modern machine learning (ML) techniques may be used to dramatically accelerate the generation of new simulation results. In this project, several recently developed ML frameworks will be applied to industrially applicable metal forming and impact problems to speed up the vehicle design process. The ML models developed will maintain high accuracy in key performance indicators over a range of geometries, material parameters, and process parameters. The technology developed in this project will underpin the simulation framework that Impact AI is developing to provide its customers with the ability to significantly accelerate impact and stamping simulations as used in the automotive industry.

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Superviseur du corps professoral :

Cliff Butcher;Kaan Inal

Étudiant :

Partenaire :

Impact AI

Discipline :

Engineering

Secteur :

Information and cultural industries

Université :

University of Waterloo

Programme :

Accelerate

Advanced Adaptivity and Personalization in Learning Systems through Collaborative Recommendations

Learning Systems are among the most popular e-learning tools in today’s education and training. Most e-Learning systems do not take into account individual aspects of learners (e.g., their goal, experiences, existing knowledge, learning style etc.).The primary goal of the proposed research is to offer rich adaptivity by combining information from a learner’s profile (e.g. levels, goals, learning style, cognitive abilities etc) with the information from other learners sharing common interests. Based on this combined information, advanced personalized recommendations can be provided, increasing efficiency, performance and learner’s satisfaction. The proposed research will have numerous benefits to the company: (1) Training and learning would become more accessible, to the benefit of employees in small to large -scale enterprises as it will offer unique learning experiences that fully engage and support users (2) It will help in improving and increasing the basic skills of employees, providing the organization with a competitive advantage and hence, will be used to build workforce capability

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Superviseur du corps professoral :

Sabine Graf

Étudiant :

Partenaire :

Athabasca University

Discipline :

Computer science

Secteur :

Education

Université :

Athabasca University

Programme :

Elevate

Structural performance of Glass Fibre-Reinforced Polymer (GFRP) reinforced concrete tilt-up wall panels under out-of-plane loads

Glass Fibre-Reinforced Polymer (GFRP) materials have emerged as a promising material in civil engineering applications due to their superior characteristics such as light weight, high strength, durability, and resistance to corrosion. Thanks to these features, GFRP bars have been used in many civil infrastructure applications. However, there are still opportunities to benefit from this innovative material. Using tilt-up wall panel method in construction of houses, and commercial and industrial buildings is a popular alternative to cast-in-place, precast, or masonry construction methods. Tilt-up wall panels are conventionally reinforced with steel bars, which are susceptible to corrosion. Thus, GFRP bars have great potential to be a sustainable alternative reinforcement. The superior characteristics of GFRP materials would extend the life cycle of tilt-up walls and reduce the related construction and repair costs. Despite these advantages, there are no relevant design equations and recommendations in FRP reinforced concrete design codes and guidelines. Thus, this study will provide a unique set of data and will introduce new design formulations and recommendations for GFRP reinforced concrete tilt-up wall panels. The results would allow owners, engineers and contractors to benefit from GFRP bars as internal reinforcement in tilt-up walls to be safe under vertical and lateral loads.

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Superviseur du corps professoral :

Khaled Galal

Étudiant :

Partenaire :

MST Rebar Inc.

Discipline :

Engineering

Secteur :

Construction and infrastructure; Manufacturing

Université :

Concordia University

Programme :

Elevate

Optimization of Low-Cost, Low-Power Irrigation Control System Design

The project will be done in the context of a collaborative project between Prof. Jorg Liebeherr (UofT) and Prof. Maryam Shojaei Baghini (IIT Bombay) on designing a low-cost, low-power irrigation control system, which seeks to address poverty and rural development in India. IIT Bombay has developed a sensor system, called Soilsens, for measuring soil conditions on farms. The current Soilsens stations use cellular networks for data transmissions, which incur high recurring cost and high energy consumption. The joint project seeks to develop a low-cost low-power communication system for Soilsens, which adopts LoRa based wireless radios for data transmissions. The communication system is based on a self-organizing communication protocol, which is developed at UofT using LoRa technology. The system will reduce power requirements by having only one cellular station for 10-20 Soilsens stations. The Globalink project seeks to optimize parameters of the CottonCandy protocol for a deployment in large-scale irrigation systems.

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Superviseur du corps professoral :

Jorg Liebeherr

Étudiant :

Partenaire :

Indian Institute of Technology Bombay

Discipline :

Engineering

Secteur :

Education

Université :

University of Toronto

Programme :

Globalink Research Award

Financial Analyst

The main goal of the project is to design and implement a new and improved financial and technical analysis strategy that would use historical trading protocols of the past 20 years. This would be done by researching how the knowledge of the operators can be codefide, automated, and integrated into the current technology platforms being used. Strategies and applications will be tested in a live environment where the outcome of the research and work will be assessed. The technology that will be used for the codification of the analysis and trading methodologies are APIs (Application Programming Interfaces).

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Superviseur du corps professoral :

Charles Scott

Étudiant :

Partenaire :

Fieldhouse Capital Management

Discipline :

Business

Secteur :

Finance and Insurance

Université :

University of Northern British Columbia

Programme :

Business Strategy Internship

Opikihiwawin

New Directions, Opikihiwawin mission is to provide cultural education, support and advocacy to indigenous adoptees, and people. The pandemic as well as a fire in their building has caused engagement to decrease. I think that this project will help Opikihiwawin by increasing their attendance, getting more people engaged and bringing back cultural support. The organization’s participants would benefit from the assistance with the virtual venue development and the student’s development of a follow-up/engagement strategy that can be used regularly in the future by staff or volunteers.

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Superviseur du corps professoral :

Shauna MacKinnon

Étudiant :

Partenaire :

New Directions

Discipline :

Business

Secteur :

Education; Health and Related Sciences & Technology

Université :

University of Winnipeg

Programme :

Business Strategy Internship

A Supply Chain Traceability System for Seafood Distribution

In this project, we are going to design blockchain networks and design an interaction between IoT devices. In this way, we can update the location of tokenized asset which is our food product in this project. Blockchain network can provide traceability and transparency, so we decided to use blockchain because of these features. The partner organization goal is to provide the seafood customers with a suitable source by which they can check whether the product is mislabeled. This project will help the organization to get close to its goal which can increase the Canadians’ awareness about healthy and authenticated seafood products.

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Superviseur du corps professoral :

Victoria Lemieux;Ahmad Al-Dabbagh

Étudiant :

Partenaire :

Traxe Technologies Inc

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

The University of British Columbia

Programme :

Accelerate

Regulation of T-type calcium channel activity by targeting channel trafficking – a novel approach for pain management

Current therapies to manage pain either result in side effects or are insufficient and the associated medical costs and loss of work days come pose a tremendous socioeconomic burden. We recently showed that T-type channel activity is aberrantly regulated in inflammatory and neuropathic pain by the deubiquitinase USP5, and we have begun to explore this mechanism as a new therapeutic avenue based on interfering TAT peptides. We now plan to test our TATpeptides in diabetic neuropathy and inflammatory bowel pain. We also plan to generate additional TAT peptides to enhance efficacy in vivo and validate them at the cellular and whole animal level. Compared with ion channel blockers which often lack specificity, our approach specifically targets a process that is involved in aberrant upregulation of channel activity, while sparing normal channel function, thus reducing the risk of adverse side effects.

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Superviseur du corps professoral :

Gerald Werner Zamponi

Étudiant :

Partenaire :

Innovate Calgary

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology

Université :

University of Calgary

Programme :

Elevate

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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.