Innovations 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

Automating Configuration and Performance Management of Data Centers – Year two

Data centers (DCs) in network softwarization and 5G eras are significantly different from those operated nowadays by public cloud providers. They are massively distributed, closer to end-users, heterogeneous (e.g., multi-access edge, central office as a data center, etc.) and rely on much more complex technologies (e.g., Network Functions Virtualization [NFV] and Software-Defined Networking [SDN]). This makes their Operation and Management (O&M) much more challenging. Much more intelligence is required for automating the various tasks. Several technologies that have recently emerged could help in this automation. Some examples are the new technologies on which data centers rely. An SDN based – management system, for instance, could assist in automating configuration and reconfiguration of intra-DC and inter-DC paths. Other examples are machine learning and big data analysis. Machine learning, for example, could aid in performance management by predicting the performance metrics for autonomic tuning of the behavior. This project aims at designing and validating architectures and models for automated performance and configuration management of large-scale, geo-distributed, highly heterogeneous, and NFV-SDN enabled-DC. An incremental approach will be followed. The first year will be devoted to configuration management and we will deal with performance management (including resource provisioning) during the second year.

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Faculty Supervisor:

Roch Glitho

Student:

Mohammad Abu-Lebdeh

Partner:

Ericsson Canada

Discipline:

Engineering

Sector:

University:

Concordia University

Program:

Elevate

Data Science in Pilot Performance Assessment

Automatically assessing a pilot performance during a flight training session is a capability that can enhance the flight instructor during his duty. From data gathered during a flight maneuver, we are looking for a way to automatically assess pilot performance to augment instructor performance and provide objectivity during flight training assessment.

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Faculty Supervisor:

Sabine McConnell

Student:

Yang Meng

Partner:

CAE Inc.

Discipline:

Computer science

Sector:

University:

Trent University

Program:

Accelerate

Developing Gaze and Movement Key Performance Indicators for User Experience Assessment

There’s nothing quite as delightful as using a well-designed product, especially a piece of software. A field of research known as User eXperience (UX) tries to define measures that describe what a good design feels like. While conventional measures of UX for software work well (how long things take, whether or not you complete your task successfully), we suggest that tracking your eye and hand will reveal other useful information. These easy-to-get measures, which we call Gaze and Movement Assessment Key Performance Indicators (GaMA KPI), are calculated from where the eyes look, how the hand moves and their coordination, to tell us how the user’s experience is going. The videogame Anthem will be used as a tool to assess the feasibility and usefulness of these GaMA KPI. We hope to demonstrate that GaMA KPI are useful measures to collect during the design process in the development of a software product.

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Faculty Supervisor:

Craig Chapman

Student:

Scott Stone

Partner:

BioWare

Discipline:

Psychology

Sector:

University:

University of Alberta

Program:

Accelerate

Water Penetration of Brick Veneer Walls Made of Clay Bricks with Large Voids

Rain water penetration can cause severe damage to building materials and facilitates the growth of mould, endangering the health of the occupants of the building. This Mitacs project will determine the water penetration resistance of various clay brick veneers used in various buildings. This research will also provide very important test data that may allow engineers and builders to use much lighter clay bricks (clay bricks with large voids) as the brick veneer. Use of lighter bricks translates to less carbon footprint and hence, is a sustainable choice. The research work will be completed using wall tests in special environmental chambers under the joint supervision of Dr. Sreekanta Das at the University of Windsor and Mr. Patrick Kelly at the Clay Brick Association of Canada.

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Faculty Supervisor:

Sreekanta Das

Student:

Babak Hajimohammadi

Partner:

Clay Brick Association of Canada

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

University of Windsor

Program:

Accelerate

Internet-based mental state monitoring using patient’s textual data

Among all chronic diseases, mental health issues have the highest burden on health care systems. However, unlike other chronic diseases, like Diabetes or hypertension, no monitoring procedures exist to monitor patients’ mental health status to prevent relapse and crisis situations. It is therefore necessary to develop cheap, convenient and accessible monitoring systems that could be used outside clinical setting. Most mental health diseases demonstrate a range of physical and behavioral symptoms (e.g. change in tone, posture and use of words, aka psychomotor symptoms) that could be measured using smart devices prevalently used by patients. Recent Internet-based methods of care delivery (eg online psychotherapy) provide the opportunity to utilize such digital evaluations of behavior (behavioral phenotyping) for long-term and remote monitoring of mental health status. Our proposal is to process digital behavioral data generated by the patients in an online platform (i.e. text, voice and video feedback) using machine learning approaches to develop an algorithm to predict their mental status. Furthermore, using recent advancements of deep learning in natural language processing, we are going to generate more personalized therapy content for patient interactions to improve the quality of the care.

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Faculty Supervisor:

Nazanin Alavai;Roumen Milev

Student:

Amirhossein Shirazi

Partner:

OPTT

Discipline:

Psychology

Sector:

Health care and social assistance

University:

Queen's University

Program:

Elevate

Achieving consistently flavoured sour beers through better chemical understanding

The popularity of sour beers is continuously increasing. Producing sour beers is time consuming and obtaining a consistent flavor profile over multiple batches can be challenging. This in addition to scaling up production to meet customer demands can negatively influence the quality and flavor of the beer. This project aims to develop advanced analytical techniques to help understand the relationship between chemical composition and flavor. Knowing this can help brewers pick the right conditions for productions to that they can optimize the flavor profile of their beer and consistently produce high quality beer to satisfy their customers.

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Faculty Supervisor:

J Scott McIndoe

Student:

Harmen Zijlstra

Partner:

Komplex Analytics

Discipline:

Chemistry

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Developing a Technique for Characterization of Upper Airway and Screening of Obstructive Sleep Apnea Using Tracheal Breathing sounds

Obstructive sleep apnea (OSA) is a prevalent yet underdiagnosed health problem. Assessment of OSA is currently based on sleep studies that are time-consuming and expensive. This proposal presents three research projects/points to apply machine learning techniques and statistical tests on tracheal breathing sounds (TBS) signals for OSA screening. We will investigate the pathology of the OSA using TBS analysis during wakefulness, sleep, and in the transition from wakefulness to sleep, compare various techniques for feature selection and classification, and finally enhance the current OSA screening algorithms. The main expected outcomes of this work will be finding the TBS characteristics that reveal the structural and physiological changes of UA in relation to OSA in a detailed but straightforward manner. Also, providing a non-time-consuming and less expensive method to stratify the severity of OSA patients in a fast but more precise way.

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Faculty Supervisor:

Zahra Kazem-Moussavi

Student:

Farahnaz Hajipour

Partner:

F&M Biomed Tech

Discipline:

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Developing ‘all-natural’ approaches to food-grade Malic acid production

Malic acid is a naturally-occurring chemical found in fruits such as blueberries, apples, cherries and grapes. Malic acid gives food a sour or tart taste. Because of this, it is an important food additive used to balance sweetness or salt. Examples of industrial malic acid use in snack foods are sour gummy candies and flavoured potato chips. Bartek Ingredients Inc. is a Canadian company and the largest manufacturer of malic acid in the world. Malic acid is made commercially from petroleum products, a non-renewable resource. Bartek Ingredients Inc. would like to develop methods to use natural, renewable resources and generate malic acid for the food industry. Our project’s goal is to test and develop strategies that might be scaled up for Bartek’s commercial use. First, we examine methods to extract malic acid from food (a renewable resource); particularly, by-products of farming that would otherwise not be used. Second, we develop methods to make malic acid in yeast cultures that are similar to wine making, but where the end product is malic acid. Third, we test methods to purify food-grade malic acid that use less water and energy and contribute to greater industrial sustainability and lower costs.

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Faculty Supervisor:

Bryan Koivisto;Russell Viirre;Sarah Sabatinos

Student:

Sahana Sritharan;Phillip Junor;Mackenzie Hurst

Partner:

Bartek

Discipline:

Biology

Sector:

Manufacturing

University:

Ryerson University

Program:

Accelerate

Detecting Attacks on Connected Vehicles

Attacks on connected vehicles require special attention and there is a need for new sophisticated security solutions that will cover the integration of different domains in connected vehicles and help proactively address potential threats to connected vehicles. The overall goal of this project is to provide various security solutions for integrity, access control, availability, and privacy of connected vehicles against security attacks. This project will help industry partner in developing and improving the security of connected vehicles. The internships will provide the industry partner with significant research talent, expertise and resources to realize their automobile security development plans.

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Faculty Supervisor:

Mohammad Zulkernine

Student:

Lama Moukahal;Anika Anwar;Mohammed Abdelmaguid

Partner:

Irdeto Canada

Discipline:

Sector:

University:

Queen's University

Program:

Accelerate

Research on Fast and Accuracy Photonic Integrated Devices and Circuit Simulation Method

In comparison to the well-developed electronic design automation (EDA) tools of microelectronics, the simulation tools of burgeoning photonics are too coarse. Time-assuming and computer memory hungry characters restrict tradition method application on photonic devices and circuits simulation. So, the aim of the proposed research project is to find a high accuracy and efficiency simulation method and models for simulating of photonic integrated devices and circuits. With the previse work of applicant and the support of Accelerate program, the basic theory and simulation frame work will be finished within program duration. After that, the new tool will shorten the design interval and improve the quality of the products, which will reduce the costs. Further, the new tool can be applied to comprehensive simulation platform with additional benefits.

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Faculty Supervisor:

Xun Li

Student:

Chonglei Sun

Partner:

Hisense

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Development of cold anesthetization and packaging technologies for waterless transportation of live shrimp

Warmwater shrimp are dominant in Canada’s shrimp market, and they are mainly imported from Asian countries. Final market value of the imported shrimp can be increased if they are alive; however, shipping live shrimp in water is cost-prohibitive. To reduce the weight-associated cost, shrimp growers are interested in transporting live shrimp in waterless conditions. Unfortunately, the waterless environment can cause a poor survival rate of shrimp. Thus, we aim to reduce the mortality of shrimp during waterless transportation by developing cold anesthetization and packaging technologies. Both cold anesthetization and packaging processes will be optimized based on their effects on shrimp’s weight loss, survival rate, antioxidant enzyme activities, and lipid peroxidation. This project will provide a cost-effective and practical approach to achieve a high survival rate of shrimp during 18-h waterless transportation.

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Faculty Supervisor:

Xiaonan Lu;Keng Chou

Student:

Zhilong Yu

Partner:

1218875 BC Ltd

Discipline:

Food science

Sector:

Other

University:

University of British Columbia

Program:

Accelerate

Optimization and modeling of BioCord fixed-film technology for nutrient and organic carbon removal from domestic wastewater

Many biological wastewater treatment options are available, ranging from advanced technologies to conventional treatment options. Fixed-film biological wastewater treatment systems are in an increasing demand for conventional plant upgrades. In this study a fixed-film media called BioCord, developed by Bishop Water Technologies, will be used. The research will propose a new opportunity to enhance the removal of contaminants (such as organic carbon and nitrogen) at higher intensity and lower energy input. The study will focus on modelling and optimizing different process parameters that include carbon and nitrogen loading rate, carbon-to-nitrogen ratio, aeration intensity and hydraulic retention time. The outcomes of this study will enable further energy savings that will increase potential marketability of the BioCord wastewater treatment technology for small communities and decentralized wastewater systems. Furthermore, it would benefit Bishop Water Technology in achieving its objective of remaining competitive in the wastewater treatment industry.

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Faculty Supervisor:

Martha Dagnew

Student:

Wudneh Shewa

Partner:

Bishop Water Technologies Inc

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

Western University

Program:

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