Innovative Projects Realized

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

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Service Life Predictions for Machined Components of Nickel-based Superalloys

Nowadays in aerospace industry, the main concern is to reach an optimum, reliable, and reproducible manufacturing process with a high predictability of the components’ service life and the lowest production cost. Machining is one of the main manufacturing processes for industrial parts which can change the surface characteristics of materials. The main aspects of these alterations are metallurgical, topographical, mechanical, and thermal which could affect microstructure, roughness, and residual stresses at the surface and near the surface of machined components, respectively. Since the fatigue behaviour of materials is sensitive to the local changes at their surface, developing a predictive model for fatigue life of machined components influenced by these surface characteristics is necessary to quantify their correlation. In this project different aspects of machining-induced surface integrity and their effect on fatigue behaviour of a Nickel-based superalloy used by Pratt & Whitney Canada in turning process will be investigated. For some applications testing real parts up to targeted fatigue life, sometimes over millions of cycles, is too expensive and time-consuming to be practical. The present project will also develop a predictive model for the functional performance of machined components by monitoring short crack propagations in the vicinity of machining affected layer.

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Faculty Supervisor:

Philippe Bocher

Student:

Hamid Javadi

Partner:

Pratt & Whitney Canada

Discipline:

Engineering - mechanical

Sector:

Aerospace and defense

University:

Program:

Elevate

A nanoscale electrochemical sensor for measuring changes in blood-glucose levels

The proposed work main goal is to improve the overall human health quality through providing an online monitoring device acting as a data platform that represents a gateway to simple solutions that allow consumers and patients to better manage their health and disease risk. The broader mission includes leveraging the data platform to improve diagnostics
The technology is to be inserted in the human body under the skin layers without the need of any advance operational procedures. In addition, the work aims on the development of an interactive phone and web application that provides users with a proprietary health score based on the nutrition and lifestyle data they input on their own terms according to a preset schedule.

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Faculty Supervisor:

Jeongwon Park

Student:

Huthaifa Abderahman

Partner:

HealthWorks

Discipline:

Engineering - computer / electrical

Sector:

Nanotechnologies

University:

Program:

Accelerate

Refinement of a leadership development impact assessment toolkit

CHLNet identified the need for valid, reliable tools to determine the impact of these health leadership development programs. This project will develop a practical, easy to use toolkit to facilitate the measurement of program outcomes and impacts. The toolkit will be pilot tested and evaluated across the country according to defined selection criteria. The finalized toolkit will be electronic and other knowledge produced during the project will be broadly disseminated. The immediate outcome of this research will be a collection of usable tools to determine impact of leadership development programs on key organizational measures.

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Faculty Supervisor:

Ivy Bourgeault

Student:

Mehri Karimi-Dehkordi

Partner:

Canadian Health Leadership Network

Discipline:

Business

Sector:

Medical devices

University:

Program:

Accelerate

CCREST: Cold Cracking by Resonance Energy for Sustainable Technologies

The project is a demonstration of Advanced Energy Technologies (AET)’s patented refining process for upgrading heavy oil products without diluent or extreme heat treatments. This produces lighter, higher value oil that is easier to work with throughout the process stream, with greater efficiency and less cost. AET will be conducting demonstration runs of the Hydrogen Activator Technology (HAT) on Albertan feedstock, partnering with local oil companies to secure heavy oils, bitumen and refinery residues. The initial objective is to have a final, robust technology package, consisting of the HAT device and the resonance cold-cracking mechanism, that is validated, certified, demonstrated and ready for commercialization by the end of December 2018. The company also intends to improve its knowledge of the science behind the HAT technology by refining the testing process to achieve consistent, reproducible results under local conditions with local Alberta feedstock. Such results will help provide reliable, quantifiable benefits to support commercialization efforts. Successful demonstration of the HAT with a variety of feedstock and the subsequent deeper grasp of the basic science behind the process will lay the groundwork for further development efforts with a Sulfur Activator Technology (SAT) and a Carbon Activator Technology (CAT) , currently in development.

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Faculty Supervisor:

M. Yaman Boluk

Student:

Hafez Balavi

Partner:

Advanced Energy Technologies

Discipline:

Engineering - civil

Sector:

Oil and gas

University:

Program:

Elevate

A Customized CAD Tool for Automated CNC Program Code Generation

To develop parts from an initial design to the final product is a very tedious process in the mold manufacturing industry. Computer Numerical Control (CNC) plays a major role in the mold manufacturing industry to create products in a fast and efficient manner. The goal of this project is to automate the CAD to CNC program code generation. A customized CAD tool will be developed that reads a three-dimensional (3D) CAD file specification for a part, and automatically synthesize optimized G-code that will be used to program the CNC machine to manufacture the given part. There will be no manual intervention involved in G-code generation. The generated automated system will speed up the G-code generation task which is currently being done manually. TO BE CONT’D

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Faculty Supervisor:

Mohammed Khalid

Student:

Jenita Priya Rajamanickam Manokaran

Partner:

Concours Mold Inc

Discipline:

Engineering - computer / electrical

Sector:

Advanced manufacturing

University:

Program:

Accelerate

An Artificial Intelligence algorithm for creating personalized learning journeys for students

With the fast growing information available on the web, students are often greeted with countless learning materials. As such, personalization is an essential strategy for facilitating relevant learning materials to satisfy students’ needs. The scope of this project is to design a recommendation system by using a deep learning process for personalized learning based on a quiz module. At the end of the project, we would be able to determine how students like to learn and to evolve the learning path based on strengths to enhance the learning experiences. Moreover, based on the obtained model, we will provide recommendation and dialogue to support learning. The proposed recommender system is based on hybrid filtering that considers both content-based and collaborative filtering properly. Indeed, the students’ historical data and the information of learning resources are taken into account to design a learning path to the students based on their needs.

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Faculty Supervisor:

Michael Chen

Student:

Mohammad Reza Peyghami

Partner:

Stem Minds Corp

Discipline:

Mathematics

Sector:

Education

University:

Program:

Accelerate

Hydrorefined fuels – computational insight into the mechanism

Improving the quality of fuels, increasing the efficiency and also producing lower emissions is one of the main challenges of the 21st century. A Calgary company, Katal, is working on a hydrorefining process in order to produce diesel fuel with superior quality compared with the traditional fuel. The company, however, has limited scientific understanding of the current process and also needs to possess further insights to make the process more efficient. This project will help to better understand the hydrorefining process and improve the properties of diesel fuel. Numerical simulations will be performed in order to elucidate the reaction mechanisms and provide atomistic insight into the process. A series of computational modelling tools including molecular dynamics and quantum mechanics will be used to perform the theoretical study. The collaboration will first enable Katal to gain a better understanding of the chemical reactions happening in the refining process. TO BE CONT’D

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Faculty Supervisor:

Dennis Salahub

Student:

Morteza Chehel Amirani

Partner:

Katal Energy Inc

Discipline:

Chemistry

Sector:

Energy

University:

Program:

Accelerate

Pharmacological inhibition of USP19 deubiquitinating enzyme as a novel therapy for muscle wasting

Muscle wasting is a common complication of many diseases such as cancer, chronic heart and lung disease and results in weakness, impaired quality of life and shortened survival. There are no drugs for the treatment of muscle wasting. We have identified a gene, USP19, in the ubiquitin pathway which is the major pathway of protein breakdown in cells. USP19 is activated in rodents in skeletal muscle wasting from many catabolic conditions. Mice lacking USP19 lose less muscle mass and strength in several conditions of muscle wasting. Therefore, inhibiting USP19 is an attractive new approach to the treatment of muscle wasting. We propose here to test whether a new inhibitor of USP19 discovered by Almac Discovery prevents muscle wasting in mice. We will also perform studies to understand how this inhibitor works. These studies may lead to the development of this inhibitor into a drug for the treatment of muscle wasting.

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Faculty Supervisor:

Simon Wing

Student:

Erin Coyne

Partner:

Almac Discovery

Discipline:

Medicine

Sector:

Medical devices

University:

Program:

Accelerate

A comparative analysis of glycan variation and its effects on therapeutic protein function

There are many exciting therapeutic applications for proteins. Many diseases are caused by faulty enzymes, which can sometimes be replaced. Antibodies and antibody-like molecules are being developed to specifically target cancers and other diseases. However, in order to administer these products, they must be made in a way that has minimal effect on the patient’s immune system. To make them viable commercially, they also have to be made in a robust, cost-effective process. This MITACS intern will compare two enzymes, each with important roles in human physiology, produced in two different systems. The goal is to determine whether the system for production matters in making a potential protein for therapeutic purposes. The intern will work closely with a commercial partner, PlantForm, a company that specializes in making therapeutic proteins in plants. PlantForm will benefit from the results by verifying that their plant-made proteins have the best possible qualities for therapeutic use. The project will also provide PlantForm with basic information that could suggest improvements to their system.

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Faculty Supervisor:

David Rose

Student:

Nicole Fraser

Partner:

PlantForm Corporation

Discipline:

Biology

Sector:

Pharmaceuticals

University:

Program:

Accelerate

Spatiotemporal travel behavior modeling and analysis for better public transport systems

The public transportation system is crucial in alleviating urban congestion. The widespread of smart card automated fare collection (AFC) system produces massive data recording passengers’ day-to-day transport dynamic, which provides unprecedented opportunities to researchers and practitioners to understand and improve transit services. This project aims to make full use of the transit operational data (mainly smart card data) to enhance transit services. The main body of the research project is spatiotemporal behavior patterns mining. The project collaborates with the transit operator exo and will be accomplished by a series of methodological and practical contributions. Data fusion technique will be used to make up incomplete data and contextualize trips’ and passengers’ attributes. We will construct features to profile passengers’ behavior at different time scales and utilize statistical learning methods to extract meaningful latent representations to help to understand passenger behavior patterns. TO BE CONT’D

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Faculty Supervisor:

Lijun Sun

Student:

Zhanhong Cheng

Partner:

Exo-s inc

Discipline:

Engineering - civil

Sector:

Automotive and transportation

University:

Program:

Accelerate

An investigation of Canadian companies’ orientations towards modern slavery and extreme human exploitation in global supply chains

Slave labour continues to be used in business settings around the world and is often linked to society through the supply chains for consumer goods. Yet, the issue of slavery in modern society (“modern slavery”), despite its ties to business settings, has received very little attention in societies around the around. While countries such as the UK have introduced legislation (Modern Slavery Act) and others such as Australia have introduced proposed legislation (Modern Slavery Bill) targeting the issue of modern slavery, Canada is in the early stages of discussing similar legislation, that in part targets transparency in the supply chain of Canadian companies. Through a collaboration with World Vision Canada, a not-profit organization dedicated to protection of human rights around the world, this project will examine how companies in Canada view and approach modern slavery and human exploitation in their global supply chains.TO BE CONT’D

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Faculty Supervisor:

Mike Valente

Student:

Kam Phung

Partner:

World Vision Canada

Discipline:

Business

Sector:

Management of companies and enterprises

University:

Program:

Accelerate

Design and development of an intelligent measurement flight mode

Testing industrial facilities including pipelines and tanks are key to optimize operation and maintenance costs in heavy industries such as oil and gas. Hazardous industrial spaces (e.g. confined spaces) are of the most challenging and costly areas to inspect. WorksafeBC has reported about 18 people have been annually killed in confined spaces in BC, in the last decade. Avestec is focused on development and commercialization of a novel flying robot (Robotic UAV) for inspection of hazardous spaces such as interior of tanks for various industries. This task is currently performed manually using scaffolding or rope accessing, solely relying on skills of operators. TO BE CONT’D

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Faculty Supervisor:

Shahriar Mirabbasi

Student:

Mahdi Yousefi

Partner:

Avestec Technologies Inc

Discipline:

Engineering - computer / electrical

Sector:

Alternative energy

University:

Program:

Accelerate

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