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

Evaluation of Cycling Education Programs

Fewer children are walking or bicycling to school than ever before. Programs promoting active transport to school may increase physical activity in children’s lives and allow opportunities for independent mobility. Programs may be funded by municipal and provincial governments, or other stakeholders, but on the whole typically lack evaluation. In this project we focus on evaluation activities for cycling promotion programs in elementary schools in two Metro Vancouver municipalities – Surrey and New Westminster. The evaluation seeks to understand how well the program succeeded in encouraging students and families to change their school travel, and how this varies across schools and settings. This internship will provide the partner organization with resources to justify to potential funders and partners the importance of supporting cycling education program across diverse settings. TO BE CONT’D

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Faculty Supervisor:

Meghan Winters

Student:

Theresa Yuha

Partner:

HUB Cycling

Discipline:

Kinesiology

Sector:

Medical devices

University:

Program:

Accelerate

Material Point Method Modeling of Soil Liquefaction in Cyclic Loading

Large deformation problems represent a new issue in the current Canadian engineering practice since the current numerical methods cannot adequately address these problems. Material point method (MPM) is a modern numerical technique with many potentials for applications in large deformation problems in geotechnical engineering. The main benefit of addressing large deformation problems is the estimation of risk since as an example this methodology provides the opportunity to know the run-out distance in dam failures. Also, such method gives a better knowledge to understand the failure mechanisms. The objective of this research project is to implement an advanced soil constitutive model in an MPM platform to reproduce large strains and deformation resulting from liquefaction in seismic loadings. The developed tool will then be used for analysis of a tailings dam facility, the run-out distance (consequences), and evaluation of a mitigation technique.

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Faculty Supervisor:

Mahdi Taiebat

Student:

Erick Lino

Partner:

SRK Consulting (Canada) Inc.

Discipline:

Engineering - civil

Sector:

Mining and quarrying

University:

Program:

Accelerate

3D Printable conductive nanocomposite sensors for CRFID moisture, strain, and temperature sensing in composite pipes

Transportation of oil and gas through pipeline networks remain a crucial infrastructure for sustainable economic growth in Canada. Pipeline wear and damage will remain a major concern as it can lead to catastrophic failures causing environmental and economic damage if undetected. For easier detection of damage on a large network of pipelines, an array of wireless radio frequency identification tags was developed for steel pipes. However, the material used for the tags were not suitable for pipes made with polymer composites as the stiffness of the copper could damage it. The main objective of this project is to create a conductive polymer material which is softer than copper but will achieve similar results as the wireless tags. Furthermore, the material needs to be 3D printable, which would facilitate in large scale implementation of the tags during the manufacturing of the pipes. The project will benefit the company as the wireless detection system can be used for Shawcor’s composite pipes.

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Faculty Supervisor:

Hani Naguib

Student:

Marco Chu

Partner:

Shawcor

Discipline:

Engineering - other

Sector:

Oil and gas

University:

Program:

Accelerate

Faith-Based Discrimination and Mental Health: Gaps in Service for Muslim Women Seeking Mental Health Care Services

Members of Canada’s Muslim communities face unique mental health care needs as their racial and religious background informs identify and experience. Researchers, advocates and service providers are starting to understand the unique mental health needs of Muslim communities, but we are still learning about how the mental health care system can provide the most appropriate supports and services. This community-based study draws on the personal experiences of Muslim women and mental health workers to understand what is working well for this community and what needs to be improved.

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Faculty Supervisor:

Wendy Cukier

Student:

Ruby Latif

Partner:

Canadian Mental Health Association

Discipline:

Business

Sector:

Other

University:

Program:

Accelerate

The effects of a step-wise exercise regime and dietary soluble fiber intake on behaviour and welfare, gut health, and metabolism in mid-distance training sled dogs

Regular exercise has also been associated with positive effects on the health and mood of dogs, although extreme exertion, such as that experienced by sporting dogs, can lead to activity-related injuries and a reduction in welfare. Sporting dogs commonly experience gastrointestinal upset, but trainers tend to not recognize the importance of dietary fiber to support gut health. Moreover, while physical activity is viewed as an essential part of a dog’s physiological and psychological welfare, research on basic topic of how behavior and welfare may be influenced by the amount or intensity or exercise is sparse. Our primary objective is to evaluate the effects of a carefully controlled step-wise exercise regime and a specially designed bled of dietary fibers on the behaviour, welfare, exercise performance, gut health, and metabolism of client owned sled dogs preparing for their competitive racing seasons.

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Faculty Supervisor:

Anna Kate Shoveller

Student:

James Templeman

Partner:

Champion Petfoods LP

Discipline:

Animal science

Sector:

Agriculture

University:

Program:

Accelerate

The Contribution of Invertebrates to the Seasonal Diets of Walleye in Lake St. Joseph – year 2

The aim of this project is to better understand the onshore and offshore feeding habits and movement of walleye on Lake St. Joseph. There is special emphasis on answering the question: if, when and how much do Walleye rely on invertebrates in general, and Mayflies in particular. Walleye are an economically and ecologically significant sport fish and Mayflies are an important bioindicator of ecosystem health and potentially have an intricate predator prey relationship. To better understand these interactions, we will reconstruct the seasonal diet of walleye, across many age classes and determine their foraging habits both onshore and offshore. Biological information will be collected from the walleye to determine any specific foodweb interactions and transient movements that may exist. To conserve and protect ecological processes in an everchanging world understanding natural interactions has never been more important.

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Faculty Supervisor:

David Beresford

Student:

Ayden Ricker-Held

Partner:

Old Post Lodge

Discipline:

Environmental sciences

Sector:

Natural resources

University:

Program:

Accelerate

The use of machine learning tools to identify organisms and contaminants in lake ecosystems

The ultimate objective of this research project is to use a form of artificial intelligence to be able to classify and identify images of microscopic particles. Machine Learning is the term applied to this type of process, in which an algorithm is created by the computer software itself (i.e. mostly hidden from human intervention) to complete the task. The intern will complete a Masters of Science degree at the University of Toronto, and work with EcoVision Consulting Group, to develop a framework for testing machine learning packages and to parameterize some machine learning tools to identify microscopic organisms called zooplankton and classify inorganic contaminants (example, plastic fibres) in lake water samples. This work will benefit academic and government environmental monitors by providing an automated process for identifying microscopic species within lakes, and benefits EcoVision (and private industry in general) in automating contaminant monitoring in environmental effects monitoring projects.

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Faculty Supervisor:

Dak de Kerckhove

Student:

Corey Ramkissoon

Partner:

EcoVision Consulting Group

Discipline:

Biology

Sector:

Environmental industry

University:

Program:

Accelerate

An information-theoretic framework for understanding generalization in neural networks

Deep neural network (DNN) is a class of machine learning algorithms which is inspired by biological neural networks. DNNs are themselves general function approximations, which is the reason they can be applied to almost any machine learning problem. Their applications can be found in visual object recognition in computer vision, translating texts in unsupervised learning, etc. DNNs are prone to overfitting because DNNs usually have many more parameters than the available training data. However, they usually have a low error on the test data. This surprising fact has motivated the scientific community to study the generalization performance of DNNs. Nevertheless, the previous attempts do not lead to a satisfying answer to the aforementioned question. In this project, we aim to introduce an information-theoretic framework which let us find a promising answer to the question of why DNNs generalize well in practice.

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Faculty Supervisor:

Daniel Roy

Student:

Mahdi Haghifam

Partner:

Element AI

Discipline:

Visual arts

Sector:

Information and communications technologies

University:

Program:

Accelerate

Evaluating dining improvements in Schlegel Villages

This project is focused on evaluating dining improvements being implemented by the partner organization, Schlegel Villages (SV). The first study involves one SV where the CHOICE+ Program is currently being piloted. CHOICE+ is a team-based approach to making physical and psychosocial improvement. The team is guided by Champions to make these changes over time; changes include small physical improvements (e.g. music), as well as education and training to support relationship-centred principles for dining. Interviews and questionnaires with residents, families and staff will be completed to determine their perceptions of these improvements. A second study will be conducted to compare the impact of blue and white dishware on resident food intake (the primary outcome). It is hypothesized that the darker colour dishes will provide greater contrast and will thus improve intake. Evaluation is timely for these initiatives as the partner organization and will support its scale and spread across 19 homes.

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Faculty Supervisor:

Heather Keller

Student:

Rachael Donnelly

Partner:

Schlegel Villages Inc

Discipline:

Kinesiology

Sector:

Medical devices

University:

Program:

Accelerate

Applying Low-Field, Bench-Top NMR Technology for the Rapid, On-Site Analysis of Critical Metrics in Wine Grapes and Wine

Vineyards, as with many other agriculture-based industries, often deal with time-sensitive decisions regarding how to manage their grapes to ensure the production of high-quality crops. Similarly, wineries need information quickly during fermentation to help guide winemaker interventions. Existing methods of obtaining the information needed by grape growers and winemakers is often time-intensive to collect. This research project seeks to apply new analytical technology to develop methods that can be used in the field so that critical information can be relayed to grape growers and winemakers quickly. Supra Research and Development hopes to build a stronger connection with the wine industry in the Okanagan valley of British Columbia, to not only grow our business, but also to provide the wine industry with the analytical tools they need to compete in the global marketplace.

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Faculty Supervisor:

Wesley Zandberg

Student:

James Favell

Partner:

Supra Research and Development

Discipline:

Chemistry

Sector:

Other

University:

Program:

Accelerate

NLP Sales Assistant

The goal of this project that will be conducted in collaboration with Heyday is to create a technology that uses a given messaging platform (e.g. Facebook Messenger, web chat widget) that allows users to communicate easily and smoothly with their preferred brands or retailers. This technology should allow the automation of answers and interaction between users and retailers. The technology that we would like to develop will be based on advanced Natural Language Processing (NLP) and machine learning techniques. These techniques shall allow the performance of the existing approaches which have a small success rate especially when dealing with complex situations that involve for instance users asking their questions simultaneously in two different languages (e.g. English and French) or using regionalized languages. The project will have unique benefits for both Heyday and the intern. For Heyday, it will allow the improvement of their success rate which is now around 60%. Concerning the intern, this project will help him to improve his knowledge about recent advanced NLP and machine learning techniques as well as working with real data in a real-life challenging problem.

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Faculty Supervisor:

Nizar Bouguila

Student:

Francisco Toral

Partner:

Heyday Technologies Inc.

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Program:

Accelerate

Advanced Signal Processing and Machine Learning for BLE-based Indoor Localization

The Internet of Things (IoT) is a new emerging paradigm and is rapidly gaining ground in different applications of significant engineering importance including but not limited to smart buildings, and smart public environments. The main enabling factor of this promising paradigm is integration of identification, localization, and navigation technologies with smart hand-held devices equipped with sensing, processing, and communication capabilities. Stringent accuracy requirements along with lower cost, energy efficiency, and high security standards make indoor localization a challenging problem, which in turn calls for in-depth research on alternative and innovative multi-sensor solutions. In particular, the main objective of this research program is development of advanced signal processing and machine learning solutions to micro-locate and track a person within a delimited physical space (e.g. building) using the industrial partner’s Smart Bluetooth locating infrastructure installed within this space.

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Faculty Supervisor:

Arash Mohammadi

Student:

Parvin Malekzadeh

Partner:

dormakaba Canada Inc

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

Program:

Accelerate

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