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

Automatic Genre Detection for Intelligent Audio Tools

MixGenius works on automated musical production by real-time musical genre detection. High accuracy of genre detection for a variety of sub-genres is required for quality production and has yet to be achieved. The project involves researching available real-time high-accuracy musical genre detection methods and improving upon them, extracting each genre’s audio features, calibrating the algorithm with a database of songs of different genres, testing them with other songs of the same genres and repeating the process as needed to improve detection accuracy. The partner organization will benefit from insight into academia and access to state of the art genre detection research, new software modeled and created, superior results from music engine product gained by knowledge of genre, and implementation that is reusable and expandable for future development.

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Faculty Supervisor:

Paul Charbonneau

Student:

Kim Thibault

Partner:

Mixgenius

Discipline:

Physics / Astronomy

Sector:

Information and communications technologies

University:

Université de Montréal

Program:

Accelerate

Scalable Training of Classification Systems Using Heterogeneous Input Data

Effective monitoring is an important component in safety and security related applications. Equipment failure, trespassing, theft and vandalism are all regular occurrences that the companies must deal with. These kinds of problems emphasize the importance of designing a state-of-the-art system for monitoring. In this project a system will be devised and trained to detect different moving-objects (pedestrians at the first step) and classify them into different groups. The system will be trained steadily by adding missing targets to the initial database. This intelligent classification will make monitoring systems to be capable of producing reports (It can be about number of people, vehicles in the site) and setting an alarms when it is necessary (For instance in case of animal detection). This work will allow company to develop a unique system for remote video monitoring.

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Faculty Supervisor:

Dr. Kyle O'Keefe

Student:

Elmira Amirloo Abolfathi

Partner:

Osprey Informatics Ltd.

Discipline:

Engineering - other

Sector:

Oil and gas

University:

University of Calgary

Program:

Accelerate

Design and Development of a Mobile-based Medical Image Archiving System for Skin Cancer Screening

This project will help to design and develop the user interface and an image picture archiving and communication system (PACS) for mobile teledermatology for use in an application of skin imaging. This will enable both patients and specialists to acquire, archive and manage dermatological images for further diagnosis, triage and follow-up purposes. The project goals are to design, implement and evaluate the app interface of the new “MoleScope” dermoscope which attaches to a smartphone camera, in order to acquire and store images. One aspect of this interface is to provide a 2D body-map for users to locate the imaged lesions on the body for future follow-up. Also, this project will design and implement the desktop web-based interface for the specialist to evaluate acquired mole images (the clinical software). This requires implementing the communication module which will interact with a patient electronic management system.

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Faculty Supervisor:

Dr. M. Stella Atkins

Student:

Bardia Mohabbati

Partner:

MetaOptima Technology Inc.

Discipline:

Computer science

Sector:

Life sciences

University:

Simon Fraser University

Program:

Accelerate

Datalink Processing System (DLPS) – Research and Development – Naval to Air Force Replatforming

The IBM DLPS software is used to provide an intelligent interface system that enables a ship’s Command System to interface to Tactical Data Links for the exchange of information with other friendly units. The DLPS software integrates the ship's Command System data with the tactical networks of data links. IBM would like to expand and modernize the DLPS solution through the use of new technologies and improved software programming techniques. Our proposed research will develop a framework consisting of reverse engineering tools and methods to assist in the evolution of the DLPS software. IBM Canada sees potential benefits of this research work as improving maintainability, adaptability and contributing to a more robust architectural framework for DLPS and positioning the DLPS for renewed application within a new Force environment. An improved Canadian DLPS product increases commercialization opportunities for DLPS globally.

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Faculty Supervisor:

Dr. Stéphane Somé

Student:

Dany Wilson

Partner:

IBM Canada

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Ottawa

Program:

Accelerate

Personalization of Web Tasking

A web task is defined as the set of services, sessions, and sequence of interactions that are required to perform a certain user objective. The current Web tasking model does not consider user preferences and context when executing a Web task. The proposed research project aims to improve the experience of Web users through personalization of Web tasks. Personalization integrates the user's personal context with the task execution plan to serve the user's interest at best. We will develop a flexible task representation model that can accommodate the user's context, mechanisms for context solicitation, interpretation and transfer, and efficient context aggregation and handling.

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Faculty Supervisor:

Dr. Patrick Martin

Student:

Khalid Elgazzar

Partner:

IBM Canada

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Queen's University

Program:

Accelerate

Improving user engagement with a social network gaming platform: Identifying and adapting to significant user traits and behaviors

This project will involve leveraging existing work completed from a previous MITACS grant, by using statistical modeling and machine learning techniques in order to identify significant player behaviour in terms of the effectiveness of multiple communication/messaging channels. This project aims to build, evaluate, and expand on an existing prototype system already running which has established both a significant revenue stream, as well as a test-bed for countless research opportunities in the field of games user research, social network systems research, and information visualization research. The ultimate goal of this project is to widen the scope of this messaging tool in order to improving player engagement and monetization, as well as generate a significant academic research publication stream.

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Faculty Supervisor:

Dr. Cristina Conati

Student:

Dereck Toker

Partner:

East Side Games

Discipline:

Computer science

Sector:

Digital media

University:

University of British Columbia

Program:

Accelerate

Realistic and High-Performance Rendering Renewal

The goal is to investigate the realistic appearance models for complex reflectance properties, modeling reflectance, masking and inter-reflection at many scales. In the end, comparison and basis-space representation will be leveraged to develop an interactive rendering application for pre-visualization and in-game portrayal of complex materials.

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Faculty Supervisor:

Dr. Derek Nowrouzezahrai

Student:

Mahdi Mohammad Bagher

Partner:

Microsoft Canada

Discipline:

Computer science

Sector:

Digital media

University:

Université de Montréal

Program:

Accelerate

Export Marketing & Needs Analysis for Solanum Genomics Int’l Inc. (SGII)

This project will help Solanum Genomics International determine the export potential of one its technologies for improving potatoes. The commercial opportunity for this technology lies in improving the potato by increasing its genetic variability through a process called somaclonal variation. By understanding the market and its needs – knowing what traits the market is interested in, this technology can be used to select and clone for those traits and ensure a product with a market identified. The end result being an identified market for one of Solanum’s technologies.

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Faculty Supervisor:

Dr. Karen Mudock

Student:

Brando Lee-Young

Partner:

BioAtlantech

Discipline:

Business

Sector:

Manufacturing

University:

University of New Brunswick

Program:

Accelerate

Extending and refining the original automated text mining algorithm for an initial market trial

Text documents often include information pertaining to geographic locations. Mapping these place names to specific geographic locations currently requires a considerable amount of human effort to match the text with a GIS or other mapping system. This becomes especially challenging when the same place name is represented by multiple places, such as in the naming of waterbodies (e.g. lakes and rivers). To overcome this challenge, we propose a new algorithm that could improve the accuracy of geo-parsing applications, with the intention of testing this in a real world situation and evaluate these results.

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Faculty Supervisor:

Dr. Liang Chen

Student:

Negar Hassanpour

Partner:

Goldstream Publishing Inc.

Discipline:

Computer science

Sector:

Information and communications technologies

University:

University of Northern British Columbia

Program:

Accelerate

Decision Making Using Multi-Criterion DecisionAnalysis

This project is to enable groups of people to better brainstorm decisions in which people can have divergent opinions. Building on ValueCharts that lets people input their utility, we will build a tool that lets decision makers explore the space of the expressed opinion to see where there are differences and whether they matter to the decision being made.

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Faculty Supervisor:

Dr. David Poole

Student:

Sanjana Bajracharya

Partner:

AeroInfo Systems - A Boeing Company

Discipline:

Computer science

Sector:

Aerospace and defense

University:

University of British Columbia

Program:

Accelerate

Sterilization of Foie Gras – Demonstration of Safety and Stability under Minimal Processing Conditions

The goal of this project is to demonstrate the adequacy of mild thermal processes (Fo ~1 min) for meeting the requirements for commercial sterility of foie gras in cans or jars. It was previously demonstrated that the sensitivity of thermal destruction of microbial spores increases with an increase in FFA concentration. The proposed project will be focused on the safety and stability of the product under industrial processing conditions. The study would encompass the following: incorporate a characterized surrogate (C. supergenes) at a high concentration level into foie gras in the can or the jar, establish an equivalent thermal process and demonstrate deliverance of the desired degree of sterility. In this study selected spore formers will be incorporated into fois gras, contained in small pouches/pans/simulated particles and placed in the central regions of test cans, and are given processes equivalent to different Fo values. The survivors will determine the level of severity of the process and incubation tests will determine the stability of the product, storage studies will indicate stability.

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Faculty Supervisor:

Hosahalli Ramaswamy

Student:

Nikhil Hiremath

Partner:

Aurpal Inc.

Discipline:

Food science

Sector:

Consumer goods

University:

McGill University

Program:

Accelerate

A Window into the Mind at a Price You Can Afford: Developing an Online and Offline Pupil-Size Analysis Plug-in

We will harness the power of Mirametrix eye-tracking technology to offer a viable means of probing internal mental processes that were previously intractable without more expensive or invasive techniques. Through the innovative application of popular statistical methods and state-of-the-art machine learning techniques, we will produce a software plug-in capable of online and offline pupil size analysis. The present study aims to make pupillometry more affordable and practicable for applications in research, education, clinical practice, and human-device interfaces such as video games. This partnership will help Mirametrix attract a wider demographic, gain competitive advantage, and increase sales revenue.

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Faculty Supervisor:

Amir Raz

Student:

Derek Albert

Partner:

Mirametrix

Discipline:

Psychology

Sector:

Information and communications technologies

University:

McGill University

Program:

Accelerate

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