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

Detection, characterization and analysis of unsafe video content on YouTube

A safe video platform can provide a healthy and suitable environment for users in general and children in particular. This project aims to utilize machine learning and deep learning techniques to identify and flag sensitive and questionable content (e.g., content related to violence, sexuality, etc.). The algorithm will leverage video frames extracted from the database for training and building a 3D Convolutional Neural Network (CNN) model. This model can detect and classify videos just like a human being. With this technology, BBTV can provide a more appropriate channel management solution to content creators that leverage its services.

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Faculty Supervisor:

Fengjun Yan

Student:

Yangliu Dou

Partner:

BroadbandTV Corp.

Discipline:

Engineering - mechanical

Sector:

Information and communications technologies

University:

Program:

Accelerate

Developing statistical methods to discover genetic variants underlying longitudinal decline in lung function

COPD is a common inflammatory lung condition that is characterized by airflow limitation and symptoms of cough and shortness of breath. Globally, it affects 384 million people and is responsible for ~4-7% of all deaths. Longitudinal genome-wide association studies (GWAS) are needed to unravel the molecular determinants of dynamic quantitative traits underlying COPD, such as decline in lung function over time.
Analysis of longitudinal GWAS to find biomarker of lung function decline was unsuccessful in the past. None of the discovered biomarkers were replicable. A novel statistical methods is needed to address challenges faced by current methods, to more powerfully and precisely discover biomarkers from longitudinal GWAS.
We will develop a novel statistical method based on Bayesian hierarchical model improve biomarker discovery from longitudinal GWAS. This novel method will be applied to unique data owned by our collaboration team, and try to find novel biomarkers for dynamic traits underlying COPD.

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Faculty Supervisor:

Xuekui Zhang

Student:

Yan Xu

Partner:

Providence Health Care

Discipline:

Mathematics

Sector:

Medical devices

University:

Program:

Accelerate

Low cost micro dispenser for general analytical or synthetic applications

The micro-dispenser serves to accurately and precisely dispense a variety of fluids in droplets with volumes in the microliter range. The micro dispensing is quite valuable as it reduces the required volume of reagents and subsequently reducing cost. Here we propose a novel micro dispensing technology based on electrowetting on dielectric (EWOD) digital microfluidic (DMF) technique. Not like the existing dispensing systems which incorporate bulky pumps, valves, needles, or syringes, fluid manipulation of the present technology is carried out using electrical control of the surface tension and its various geometry effects, which reduces the complexity of the system while saving considerable amount of manufacturing cost. This project will advance pharmaceutical industry and personalized medicine through fundamental studies of micro dispensing technologies in printable medicinal products in order to effectively transfer fluid formulations and enable high density multi well platform in which miniaturized assays are constructed.

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Faculty Supervisor:

Andrew Smith

Student:

Jagath Nikapitiya

Partner:

81292 NEWFOUNDLAND & LABRADOR INCORPORATED

Discipline:

Medicine

Sector:

Nanotechnologies

University:

Program:

Accelerate

Grassland butterfly conservation and headstarting program

Grasslands are one of the most endangered habitat in North America. In Manitoba, over 90% has been lost in the last 100 years and with it a suite of prairie adapted species. The Poweshiek skipperling is one such species which in recent years has plummeted in abundance for unknown reasons. Less than 500 individuals remain in the wild and the grasslands of southeastern Manitoba represent one of the species’ last strongholds. The Assiniboine Park Zoo is partnering with other organizations to establish a headstart program for this endangered butterfly in hope to stabilize its population in the province. This project will develop the needed expertise and novel methodologies to raise and release this butterfly back into suitable grasslands.

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Faculty Supervisor:

Richard Westwood

Student:

Conner Savage-Watson

Partner:

Assiniboine Park Zoo

Discipline:

Environmental sciences

Sector:

Environmental industry

University:

Program:

Accelerate

Study of biomechanics during equine rehabilitation: development of harness system and rehabilitation protocol

The aim of the internship program is to develop a rehabilitation harness for horses and study its use together with a computerized lift system designed for rehabilitation of injured horses. Measurements used to direct harness design and rehabilitation protocols include movement analysis of the horses, physiological measurements and analysis of behaviour. The lift system was developed by the partner organization RMD Engineering, Inc. RMD has a material interest in the success of the rehabilitation harness proposed in this project. The desired project outcome is that this rehabilitation harness will be integrated with RMD’s lift system to enable a complete solution to the equine rehabilitation challenges.

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Faculty Supervisor:

Julia Montgomery

Student:

Samantha Steinke

Partner:

RMD Engineering Ltd.

Discipline:

Engineering - biomedical

Sector:

Life sciences

University:

Program:

Research into the Design and Development of Inclusive Digital Media Technologies

This project, a collaboration between Ryerson University and Pear Square, will be researching what would enable businesses and organizations to provide resources efficiently to students with disabilities. The outstanding issue is mainly a lack of standardized work flow methodologies that promote accessible development from the beginning stages of any project for large institutions. The research proposed for this project will be to formulate, test, and acquire feedback on experimental workflows that accommodate a variety of accessible digital media systems. The research conducted for this project will provide Pear Square with a comprehensive insight of how accessible systems can be used as a resource for assisting students with disabilities to reach their goals.

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Faculty Supervisor:

Alex Ferworn

Student:

Samuel Legros

Partner:

Pear Square

Discipline:

Medicine

Sector:

Information and communications technologies

University:

Program:

Accelerate

Solar Heat Energy Storage and Solar Roof De-Icing Technology for BIPV Living Lab Pro

The first part of the project will be to determine the best material to store heat energy produced by the OM solar system. This project will look into the solar energy and heat capacities of various materials. CRE will befit by being able to choose the best material for heat storage in there home. The intern will benefit because they will get first hand experience in sustainable construction, heating and cooling of a sustainable home.

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Faculty Supervisor:

Shahria Alam

Student:

Arman Chowdhury

Partner:

CRE Green Consulting Ltd

Discipline:

Engineering

Sector:

Alternative energy

University:

Program:

Accelerate

Aboveground Storage Tank (AST) tightness testing using statistical approach

The industry partner, Cantest is establishing a new leak detection procedure for analyzing data sources in aboveground storage tanks and statistical learning models to monitor AST shell dynamics and product activity over time. This is an important problem as identifying leak detection is usually associated with various environmental data and records collected from sensitive sensors attached to the ASTs. Current testing procedure for leak detection uses simple statistical rules and thresholds to detect anomalies. These methods are failing for preventing AST related environmental incidents. Incorporating data records from upgraded evaluation equipment, this research internship will help to identify and create appropriate leak detection procedures for the ASTs and extend and improve the functionality of Cantest’s current leak detection systems.

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Faculty Supervisor:

Jingjing Wu

Student:

Wenyan Zhong

Partner:

Cantest Solutions

Discipline:

Mathematics

Sector:

Oil and gas

University:

Program:

Accelerate

Data Poverty Project

In many developing countries, it is very difficult to survey vulnerable groups in a way that provides reliable research findings. These surveys also only give limited insights into the experiences of these populations. This project will develop a software program that can be used to model the probability of events occurring given the estimated probability of other events. These models can be developed with a small group of individuals and can give a better insight Into the network of events underlying the experiences of vulnerable groups. This software can also help organizations make better decisions by providing quick predictions based on their expert opinions or data analysis.

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Faculty Supervisor:

Bruce Frayne

Student:

Jamie Sgro

Partner:

Accelyst Technologies Limited

Discipline:

Environmental sciences

Sector:

Information and communications technologies

University:

Program:

Accelerate

Computational and machine learning approaches to improve design and screening of high bioactivity peptides for drug discovery

The cost of developing new drugs is now widely acknowledged by industry leaders as prohibitive, with some estimates now in excess of $ 5B per drug. It is imperative that new approaches are developed to mitigate the cost and time required to bring new drugs to market. To help achieve this, we contend that new techniques in machine learning must be brought to bear on the drug development process. We plan to use machine learning approach to help in building better drugs by improving the process of finding molecular structure using the building blocks of proteins, the amino acids, which could one day serve as models to create drugs against microbes. The process could be extended to other fields (cancerology, neurology, infectious and immunological diseases, among many others) since the methods developed can be adapted easily.

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Faculty Supervisor:

Sylvain Moineau

Student:

Francis Brochu

Partner:

Consortium québécois sur la découverte du médicament

Discipline:

Biochemistry / Molecular biology

Sector:

Medical devices

University:

Université Laval

Program:

Accelerate

Simulation of Transient Over-Voltages for Overhead Transmission Lines via Electromagnetic Transients Programs

The candidate will utilize his knowledge and experience in transmission line modelling to implement test cases required for the Transient Over-Voltage studies. The simulations will be performed using well-known computer packages available at BC Hydro and Power labs at UBC as well as programs written by the candidate to implement the recently developed line model in his PhD work. Simulation results will be compared with the simulations previously performed by BC Hydro. In case of agreement between these results, BC Hydro will be able to use the confirmed data and standards to design and set protective devises to moderate the effect of transient over-voltages on the overhead transmission lines existing in the province of British Columbia.

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Faculty Supervisor:

Student:

Partner:

British Columbia Hydro and Power Authority

Discipline:

Engineering - computer / electrical

Sector:

Energy

University:

University of British Columbia

Program:

Accelerate

Securitized Tokens as a Service (STaaS)

This research study aims to investigate the potential and performance of a novel Securitized Tokens as a Service platform. Blockchain is the distributed ledger of verified transactions, and smart contract is the programmable part of the blockchain which can automate more complex transactions. We can define the tokens on top of the blockchain platform; and actually, these tokens can stand for anything in real business world which can be transferred. In addition, smart contract is used to define the required rules of the business market through the blockchain. Using our suggested platform, companies can define their own tokens and use them for variety of purposes. These tokens, for example, can be used as a utility tokens, or as a tool for share management, asset management, and fund raising.

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Faculty Supervisor:

Student:

Partner:

Trioova

Discipline:

Computer science

Sector:

Finance, insurance and business

University:

University of Saskatchewan

Program:

Accelerate

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