Innovative Projects Realized

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

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

Design and Innovation: Academic-In-Residence Project

This project builds upon two previous Mitacs Accelerate projects with Creative BC (CrBC). CrBC leads the economic development and promotion of BC’s creative industries. Recently CrBC and UBC PhD candidate, Angèle Beausoleil co-designed and delivered an innovative strategic plan involving 80 industry stakeholders. Angèle facilitated design sessions, observed the process, and proposed a new strategic framework for CrBC. From this framework, Angèle and CrBC seek to pilot an ‘academic in residence’ as her post-doctorate fellowship project. The two-year fellowship will support the implementation of key action plans focused on creating a culture of innovation required to grow BC’s creative industries. She will support the CEO’s vision to cultivate a new generation of creative and strategic thinkers. The PDF objectives include: leading applied research on new program and service development; teaching the strategic design method to staff and stakeholders; and, generating academic research publications on the innovation process within university-industry collaborations.

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Faculty Supervisor:

Moura Quayle

Student:

Partner:

Creative BC

Discipline:

Business

Sector:

Information and cultural industries

University:

The University of British Columbia

Program:

Elevate

Development of Indicators and Benchmarks of Sustainability for a Standardized Municipal Sustainability Index

Municipal sustainability in Canada has been gaining importance in recent years. In order to ensure real progress is made, sustainability assessment must be conducted. Indicators are the recommended measures for sustainability assessment. This research project will create a core set of indicators for use in a sustainable cities index. A set of sustainability best practices will also be compiled to assist in developing benchmarks for use in a ranking of sustainable cities. These objectives will be completed by conducting both academic and practitioner literature reviews and a comparison of the two. Further depth will be gained through selected interviews with relevant city officials and/or staff. The research gained through this project will benefit the private sector partner (MMM Group) by providing the indicator and benchmark bases for their ‘successful cities audit’.

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Faculty Supervisor:

Amelia Clarke

Student:

Partner:

Discipline:

Earth science

Sector:

University:

University of Waterloo

Program:

Accelerate

Gearbox fault detection and failure prediction

The objective of the project is to develop an automated monitoring system to accurately and reliably detect deterioration within gearboxes operating on an industrial forming line. This will involve reviewing, developing and testing one or more methodologies based on vibration signal measurement and analysis. In particular the work will focus on exploring existing potential methods, defining the capabilities of different sensors that could be used in the given environment and developing appropriate vibration signal analysis algorithms for gearbox deterioration detection and decision making. The final result of the work will be a system suitable for implementation on an actual forming line.
The participating sponsor anticipates to benefit from the project through participation and guidance of an investigation into the possibility of developing a new automated, accurate and reliable gearbox deterioration detection system. A successful system could be used in a wide range of applications where machinery condition inspection is done manually or not at all. Reliable detection of gearbox deterioration will result in improved efficiency and therefore lower costs.

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Faculty Supervisor:

Chris Mechefske

Student:

Partner:

Co-Ex-Tec

Discipline:

Engineering

Sector:

Manufacturing

University:

Queen's University

Program:

Accelerate

Improving usage pattern quality by comparing different sequential pattern mining methods and the effect of considering additional user information

Frequent usage patterns generated can provide valuable information for several applications such as platform restructuring and recommendation. In this project, we aim to compare different practical methods, and to investigate the effect of user identity and user intention information on them. To that end, a technique and a framework need to be developed, in which frequent patterns are composed of more refined analysis result instead of simple frequent sequences of basic operations over all users’ behavior. The outcome of this project is expected to improve the user experience for the partner organization’s product and such methods can be also used in various relevant applications.

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Faculty Supervisor:

Fred Popowich

Student:

Partner:

Kinematicsoup Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

Development and application of molecular tools to assess the acute and chronic impacts of petroleum hydrocarbons on birds

The Northern Gateway Pipeline and similar projects propose to transport oil from Alberta to tidewater terminals in British Columbia and eastern Canada. Accidental release of petroleum distillates and related by-products would have consequences on the marine ecosystem. To evaluate spill implications for seabirds, we propose to develop and apply molecular tools to assess toxicological and health endpoints in selected seabird monitoring species, using a combination of laboratory and field research. This study will inform regulators about baseline molecular responses in seabirds to current levels of petroleum hydrocarbons in proposed shipping channels and to those anticipated in the unlikelihood of a spill. Results from this study will provide insight into the toxicology of oil in seabirds, will advance our ability to evaluate a change in the health of seabirds due to a spill and will enable our partner organization as they conduct risk assessments for proposed oil transportation.

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Faculty Supervisor:

John Edward Elliott

Student:

Partner:

Northern Gateway Pipelines

Discipline:

Life Sciences

Sector:

Mining

University:

Simon Fraser University

Program:

Elevate

A systems biology approach to investigate chemoresistance in urothelial carcinoma of the bladder.

To perform a complete molecular analysis of muscle invasive bladder cancer (MIBC) before and after pre-operative chemotherapy to find changes responsible for resistance to treatment. Analysis will include a combination of DNA sequencing, RNA expression analysis and quantification of protein. Together this information will reveal the molecular landscape for these tumors. We will use these complex datasets to address two specific comparisons: 1) chemotherapy responders versus chemotherapy non-responders (defined by extent of tumor remaining in bladder after chemotherapy); and, 2) tissue before and after pre-operative chemotherapy in non-responders, in order to assess for enriched molecular pathways that are indicative of resistance. Specific computer tools will be used to test the biologic functional of the changes described. The proposed methods include protein-protein interactions, gene-regulatory network and pathway-enrichment analysis. Novel analytic algorithms will also be developed to benefit the partner organization for day-to-day processing of clinical data.

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Faculty Supervisor:

Peter Black

Student:

Partner:

GenomeDx Biosciences Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Elevate

MiX – Motion Capture in XNA

XNA (Xbox New Architecture) allows independent game/digital-media content developers to build, deploy, and publish games on the Xbox360 and PC platforms. The technical objective of this project is to bridge Vicon MOCAP technology with XNA to allow for Real Time Visualization of Motion Capture data on the PC and Xbox360 platforms using XNA.The Vicon Real-time Engine processes motion capture data in real-time allowing you to stream to your preferred viewing software. Directors can then, with the help of MiX (Motion Capture in XNA) map the motion capture data to the character(s) or objects producing a real-time visualization of the motion capture session. Real-time motion capture visualizations, increase Director efficiency, provide immediate Actor feedback, and reduce expensive pick-ups or recapture sessions.

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Faculty Supervisor:

Maria Lantin

Student:

Partner:

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Emily Carr University of Art + Design - Main Campus

Program:

Accelerate

Ciena Environment for Network Innovation (CENI)

The NSERC Strategic Network for Smart Applications on Virtual Infrastructures is a five-year partnership between Canadian industry, universities, researchers, research and education (R&E) networks, and high performance computing centres to investigate the design of future application platforms that will deliver software applications of greater capability and intelligence. These application platforms will be supported by an extended computing cloud, encompassing a virtual converged infrastructure and control software that also serves as a live testbed for exploring novel concepts in application-oriented networking, cloud computing, integrated wired/wireless access, and smart applications. Novel software applications will build on advanced services provided by the platform, including context, mobility, location, identity, social network, media recognition, and intelligence. The SAVI network will involve the academic community in the creation of new content and novel applications.
This MITACS proposal is to support a SAVI internship program that will strengthen the Canadian industrial base in information and communications technology through the preparation of highly qualified manpower with expertise in the design and operation of globally competitive ICT infrastructure and the creation of innovative and disruptive products, services, and applications. TO BE CONT’D

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Faculty Supervisor:

Alberto Leon-Garcia

Student:

Partner:

Ciena Corporation (Ottawa, ON)

Discipline:

Engineering

Sector:

Information and Communications Technology; Technology

University:

University of Toronto

Program:

Accelerate

Genetic evaluation of sow efficiency traits using single step genomic evaluation methods – Year 2

Most economically important traits associated with lactation and reproduction in pigs are either less heritable, sex-limited, expressed later in life, or difficult to measure on a routine basis. Genomic predictions using single step best linear unbiased prediction (SSBLUP) methodologies, which utilizes information on phenotypes, pedigree and markers from genotyped and non-genotyped animals simultaneously, is an alternative to phenotype and pedigree based (BLUP) methods. The goal of this project is to develop genome enhanced estimated breeding values (EBVs) for sow reproductive traits using single step methodologies. The objectives are to 1) develop single step EBVs for sow traits associated with lactation and reproduction 2) to estimate the accuracies of prediction using SSBLUP and compare it with the pedigree based estimates and 3) to incorporate single step methodologies into routine genetic evaluations. The overall outcome is to demonstrate and integrate SSBLUP genomic selection methodologies to improve key economic reproductive traits.

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Faculty Supervisor:

Graham Plastow

Student:

Partner:

Genesus Genetic Technology Inc.

Discipline:

Life Sciences

Sector:

Agriculture and Food; Biotechnology; Life Sciences (not health)

University:

University of Alberta

Program:

Elevate

Genetic evaluation of sow efficiency traits using single step genomic evaluation methods

Most economically important traits associated with lactation and reproduction in pigs are either less heritable, sex-limited, expressed later in life, or difficult to measure on a routine basis. Genomic predictions using single step best linear unbiased prediction (SSBLUP) methodologies, which utilizes information on phenotypes, pedigree and markers from genotyped and non-genotyped animals simultaneously, is an alternative to phenotype and pedigree based (BLUP) methods. The goal of this project is to develop genome enhanced estimated breeding values (EBVs) for sow reproductive traits using single step methodologies. The objectives are to 1) develop single step EBVs for sow traits associated with lactation and reproduction 2) to estimate the accuracies of prediction using SSBLUP and compare it with the pedigree based estimates and 3) to incorporate single step methodologies into routine genetic evaluations. The overall outcome is to demonstrate and integrate SSBLUP genomic selection methodologies to improve key economic reproductive traits.

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Faculty Supervisor:

Graham Plastow

Student:

Partner:

Genesus Genetic Technology Inc.

Discipline:

Life Sciences

Sector:

Agriculture and Food; Biotechnology; Life Sciences (not health)

University:

University of Alberta

Program:

Elevate

Fast and robust real-time precise point positioning – Year 2

The main outcome of this Mitacs-sponsored project will be a robust navigation software capable of providing accurate navigation solutions for commercial Unmanned Aerial Vehicles (UAVs). Such a software will further elevate the industrial competitiveness for the partner corporation, the Profound Positioning Inc. (PPI). After finishing this project, PPI will be able to offer more comprehensive embedded integrated UAV navigation products. Furthermore, Canada will benefit from the established knowledge and expertise in technologies of growing demand worldwide, thus making the Canadian academia and industry sectors leaders in commercial UAVs operation and navigation.

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Faculty Supervisor:

Xin Wang

Student:

Partner:

Profound Positioning Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Calgary

Program:

Elevate

Fast and robust real-time precise point positioning

Current real-time precise point positioning (PPP) systems still suffer significant challenges. One is its long position convergence time necessary before precise position solutions become obtainable. Another is its sensitivity to the loss/latency of high-frequency precise orbit and clock corrections, resulting in degraded performance. Those challenges have limited PPP’s adoption in many applications. This project aims to develop a fast and robust real-time PPP system. A positioning model based on uncombined observables will developed to facilitate ambiguity resolution (AR) and ionosphere-aiding which will help significantly reduce the position convergence time. A new real-time orbit and clock generation method will be developed to improve the robustness of PPP by reducing the system’s sensitivity to the loss/latency of precise orbit and clock corrections. A prototype system will be developed to assess the performance of the system for product development.

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Faculty Supervisor:

Xin Wang

Student:

Partner:

Profound Positioning Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Calgary

Program:

Elevate

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