Innovative Projects Realized

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

30156 Completed Projects

2861
AB
5059
BC
812
MB
673
NL
842
SK
8957
ON
9368
QC
96
PE
579
NB
1120
NS

Projects by Category

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:

Partner:

Ericsson Canada Inc (Quebec)

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Concordia University

Program:

Elevate

Automating Configuration and Performance Management of Data Centers

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:

Partner:

Ericsson Canada Inc (Quebec)

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Concordia University

Program:

Elevate

Development of Coxsackievirus B3 as an Oncolytic Virus for KRAS-Mutant Lung Cancer Treatment

In Canada, lung cancer is the leading cause of cancer-related deaths for both sexes. Non-small-cell lung cancer (NSCLC) constitutes ~85% of lung cancer cases. Mutations in the KRAS and EGFR genes are two most common oncogenic drivers for NSCLC and responsible for ~30% and ~15% of NSCLCs, respectively. Unlike the EGFR-mutant type, KRAS-mutant NSCLC is currently undruggable and associated with poor prognosis. Our lab has recently demonstrated that Coxsackievirus B3 (CVB3) is a potent oncolytic virus against KRAS-mutant NSCLC. Nevertheless, it was observed that efficient tumor suppression is accompanied with damage to multiple organs, particularly the heart. Here we propose to develop an innovative CVB3-based oncolytic virus with enhanced tumor-specificity. If a therapeutic effect is achieved, the clinical significance may grant Virogin Biotech Ltd. one possibility to provide the first-ever effective and safe treatment for this deadly disease for Canadians.

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Faculty Supervisor:

Honglin Luo

Student:

Partner:

Virogin Biotech Ltd

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Electrospinning as a Novel Method of Preparing Nanofilled Epoxy Composites

Electrospinning technique will be used as a new mixing method to disperse nanofillers into the epoxy base polymer in this project . The single-needle electrospinning scheme has been successfully used in the preparation of nanofilled silicone rubber composites. However,its low volume product has limited the industrial applications,so another electrospinning scheme will be investigated to scale up the electrospinning process. The electrospun epoxy compounds will be prepared by two schemes of electrospinning. Nanofiller dispersion in the epoxy base polymer will be studied through SEM. The dielectric properties of electrospun nanofilled epoxy composites and conventional mixer prepared epoxy composites will be investigated to see the effect of nanofiller dispersion on them . GABAE is currently engaged in nanofiber product development using electrospinning which is involving in projects of high economic potential and research that needs a complex combination of scientific and management skills, this proposed project to GABAE is very significant.

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Faculty Supervisor:

Sheshakemal Jayaram

Student:

Partner:

Concordia University;GABAE Development

Discipline:

Engineering

Sector:

University:

University of Waterloo

Program:

Accelerate

Antimicrobial Properties of Kisameet Clay IV

Natural clay minerals have a long history of medicinal applications. Recent studies have described their antibacterial properties and have suggested that specific physical and geochemical characteristics of clay are involved in this effect. Kisameet clay (KC), a natural deposit found in British Columbia has been used for healing purposes for generations, still little more than anecdotal information about its use has reported. We have confirmed broad-spectrum antimicrobial activity of KC against a variety of human pathogens. Then, our goal has been elucidating the mechanism(s) which make it antibacterial. We have proposed to carry out microbiological and geochemical analyses to reveal the mode of action. In parallel, potential microbial sources of active compounds have been identified by using metagenomic analyses of DNA extracted from clay. TO BE CONT’D

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Faculty Supervisor:

Julian Davies

Student:

Partner:

Kisameet Glacial Clay Inc

Discipline:

Life Sciences

Sector:

Mining

University:

The University of British Columbia

Program:

Accelerate

A weighted graph approach to IP geolocation

When you load a page on the internet, or watch a video, or send an email, packets of information travel along a path from your computer to the destination. Where does this path go? If both you and your destination are located in the same country, does the path respect international boundaries? We propose a method for answering these questions that builds upon previous techniques. Our partner organization, CloudPBX Inc, develops and operates network infrastructure for telephonic communications. They are interested in offering their customers the assurance that their calls are not unintentionally crossing international borders.

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Faculty Supervisor:

Matthew DeVos

Student:

Partner:

Corvum

Discipline:

Mathematics

Sector:

Information and Communications Technology; Energy and Utilities; Technology

University:

Simon Fraser University

Program:

Accelerate

Interactive Annotations of Large-Scale Image Data for Training of Recognition Models

The main objective of this project is to investigate, develop and evaluate state-of-the-art color image/video analysis and machine-learning algorithms, which are suitable for accurate modeling and recognition from large-scale image datasets that are weakly labeled. In particular, we will focus on investigating and developing interactive (partially-supervised) algorithms for annotating massive sets of color images, while minimizing the user efforts. The ultimate goal is to build stat-of-the-art color image classification models, a computer vision application area of high interest to QuindiTech. The specific objectives are: (1) Interactive object delineations in massive image/video data sets; and (2) Active categorization of images at a web-scale level. Learning weakly supervised image recognition models typically leads to complex and ill-posed optimization problems. This project will leverage some limited and targeted interactions with humans, as needed, to set optimization constraints and to drive advanced learning methods. TO BE CONT’D

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Faculty Supervisor:

Ismail Ben Ayed;Éric Granger

Student:

Partner:

QuindiTech

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

The influence of local and global stressors on coral reef ecosystems

Vibrant coral reefs are amongst the world’s most diverse and economically important marine ecosystems, but are also imminently threatened by climate change and local threats, including fishing and pollution. Understanding how these threats impact coral reefs, and the capacity for reefs to recover after bleaching events is critically important. This project will focus on Kiritimati (Christmas Island), a ‘natural laboratory’ in the equatorial Pacific Ocean, which experienced extensive coral bleaching during a recent intense heat wave. We will use underwater surveys and videos, along with novel acoustic and imagery methods, to quantify how coral and fish communities, as well as the structure of the reef habitat itself, have changed in the four years following the event. We will also examine if underwater acoustics can be used to assess reef health. This information will inform World Wildlife Fund’s Coral Reef High Impact Initiative’s efforts to develop solutions for coral reef conservation.

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Faculty Supervisor:

Julia Baum

Student:

Partner:

World Wildlife Fund (St. John's, NL)

Discipline:

Life Sciences

Sector:

Other services (except public administration)

University:

University of Victoria

Program:

Accelerate

Bipolar Membranes for Electrochemical Technologies

Bipolar membranes (BPMs) are already a commercially relevant technology as they are used in the electrodialysis process, that is, they are used to convert salt water into industrially useful acid and base products. Recent research, on the laboratory scale, has demonstrated that bipolar membranes also have useful applications in water splitting technologies that produce hydrogen gas, which can then be captured, stored and used as an alternative to fossil fuels. This project aims to develop next-generation bipolar membranes by combining the cutting-edge membrane technologies developed at Simon Fraser University with the industrial throughput capabilities of Ionomr Innovations Inc.

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Faculty Supervisor:

Steven Holdcroft

Student:

Partner:

Ionomr Innovations Inc

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

Building a framework to use banking data for learning, warning, and prevention

This project, in partnership with ATB Financial, will focus on the application and development of machine learning techniques in banking. We will delve into early prediction of customer events, such as encountering financial difficulties, that could indicate other issues and present opportune moments for ATB Financial to help customers get back on track. We will develop a framework to make statistical inferences from such early predictions of customer events to measure more accurately risks across the financial institution. Analyzing the situation around the 2016 Fort McMurray wildfire, a particular focus will be on the study of how people react to a disaster and change their banking transactions in such an event.

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Faculty Supervisor:

Christoph Frei

Student:

Partner:

ATB Financial

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

University of Alberta

Program:

Accelerate

Global Dynamic Financial CGE Model

This project aims to develop a dynamic financial computable general equilibrium model (CGE) with interaction between real and financial side of the world economy. It seeks to understand how monetary policy changes such as interest rate changes, QE measures, and exchange rate changes affect the real economy by applying the financial dynamic CGE model. This project collaborates with the partner organization–the Infinite-Sum Modeling Inc.—to build a CGE-FDI database and to develop the financial CGE model. It will provide the partner organization and the academic institutions with a model of policy simulation to unde

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Faculty Supervisor:

Jing Li

Student:

Partner:

Infinite-Sum Modeling Inc;Beijing Technology and Business University

Discipline:

Sociology

Sector:

Finance and Insurance

University:

Simon Fraser University

Program:

Accelerate

Étude des contraintes mécaniques des films de MgO : mise en évidence de gradients diminuant la symétrie locale par la spectroscopie TERS

De nos jours, les ordinateurs, les téléphones cellulaires et beaucoup de gadgets électroniques voient leur taille diminuer de plus en plus au fur et à mesure que les années passent. Actuellement, la technologie de ces dispositifs électroniques est basée sur le silicium. Or, le silicium atteint les limites de sa performance plus la taille des dispositifs électroniques diminue. Les chercheurs doivent donc trouver d’autres moyens pour fabriquer les mêmes appareils mais sans utiliser le silicium. Le film de MgO est le candidat idéal qui entre dans la fabrication des jonctions de tunnel magnétiques (JTM) qui constituent la composante essentielle des mémoires magnétorésistives volatiles à transfert de spin. Mais lorsqu’on dépose le MgO sur un autre matériau pour fabriquer les JTM, il y a apparition de contraintes mécaniques qui altèrent significativement les propriétés électriques et optiques du MgO. Mon projet de recherche consiste à calculer les contraintes mécaniques occasionnées dans les films de MgO à l’aide de simulations numériques afin de valider nos résultats expérimentaux obtenus par TERS […]

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Faculty Supervisor:

Andreas Ruediger

Student:

Partner:

Université de Toulon

Discipline:

Physics

Sector:

Nanotechnology; Advanced Manufacturing; Technology

University:

Université du Québec : Institut national de la recherche scientifique

Program:

Globalink Research Award

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