Innovative Projects Realized

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

30156 Completed Projects

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

Projects by Category

Extension of feature selection with a ML algorithm for wireless network traffic prediction

The release of 5G network in near future will provide reliable connectivity, higher throughput, better service quality, and more efficient signaling. The network traffic load will continuously rise with more and more mobile users using the internet services. There is a need to forecast wireless network traffic load to manage network resources efficiently and provide better quality of service. This network traffic dataset is complex and nonlinear in nature that contains large number of variables. The proposed research will combine the feature selection techniques with an advanced machine learning (ML) method to handle this network traffic dataset, which employing 4 feature selection techniques to extremely reduce the data size with keeping significant features in the dataset, and further result in the increasing of the prediction accuracy for the ML model. The feature selection aids in better prediction accuracy of machine learning algorithm on wireless network traffic with overall interpretability of the prediction model.

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Faculty Supervisor:

Wei Peng

Student:

Partner:

Ericsson Canada Inc (Quebec)

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Regina

Program:

Accelerate

A Realistic Machine Learning-based Model for Failure Prediction and Propagation in Smart Grid Networks

Cyber-Physical Systems (CPS) combine communication and information technology functions to the physical components of a system for purposes of monitoring, controlling, and automation. The power grid is becoming one of the largest CPS, where grid components are controlled based on the synergies in the cyberspace. CPS hold a great promise to improve the efficiency and productivity of numerous sectors in Canada and around the world. However, cyber-security is a major concern in CPS including the smart grid where an intrusion in one part of the system can cause a failure in the entire network if not detected and dealt with in a timely fashion. The main objective of this research project is to develop a realistic model to enable the implementation of machine learning-based algorithms to detect cyber-attacks in a smart grid environment.

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Faculty Supervisor:

Irfan Al-Anbagi;Kin-Choong Yow

Student:

Partner:

Ericsson Canada Inc (Quebec)

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Regina

Program:

Accelerate

Secure blockchain technologies

In the recent years, blockchain technologies have shown promise as infrastructure for decentralized trustless anonymous digital asset exchange. The technology promises to transform how the data is shared in many areas including financial sector, insurance and gaming industries. Yet several obstacles prevent mainstream adoption of this technology – one of these challenges is security. To facilitate trustworthy data collection, and management in blockchain, ensuring secure communication is essential.
The blockchain’s underlying cryptographic theory makes it difficult for an adversary to modify the data provenance. Yet, the technology is not immune to unauthorized access, modifications, and repudiation of origin. This research aims to address these security problems and develop methodologies to predict, track and analyze suspicious users, their behaviour, and corresponding threats in blockchain.

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Faculty Supervisor:

Natalia Stakhanova

Student:

Partner:

Ericsson Canada Inc (Quebec)

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Saskatchewan

Program:

Accelerate

Incorporation de produits alimentaires intermédiaires d’algues dans le yogourt : Impact sur les propriétés fonctionnelles, sensorielles, sur la qualité nutritionnelle et sur la conservation

Les algues sont considérées comme un aliment à haute valeur nutritive. Cependant, la consommation de ces dernières en tant qu’aliments est peu répandue dans les pays occidentaux. Une manière d’augmenter l’apport en algues serait de les incorporer dans des produits traditionnels. Pour ce faire, il est possible de préparer des produits alimentaires intermédiaires (PAI) d’algues sous forme de farines ou de flocons, qui seront livrés à d’autres entreprises alimentaires pour la préparation des produits finis enrichis en algues. Cependant, peu d’études ont été consacrées à mesurer l’effet de l’ajout d’algues sur les propriétés des yogourts. La stagiaire évaluera l’impact de l’incorporation d’algues du Québec dans le yogourt sur ses propriétés fonctionnelles, sensorielles, sur sa qualité nutritionnelle et sa conservation. Ces travaux permettront à l’organisme partenaire de guider des producteurs et transformateurs d’algues dans la diversification de leurs activités.

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Faculty Supervisor:

Lucie Beaulieu;Steve Labrie

Student:

Partner:

Merinov (Grande-Rivière, QC)

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

Design of porous hydrogels for biomedical applications

Biocompatible hydrogels have been used for a long time in biomedical applications (e.g. microcarriers for adherent cell growth; drug delivery vehicles). For these applications, controlled pore size and pore interconnectivity are important parameters. The project aims at better characterizing several physicochemical strategies for pore generation. Then, as second objective, the influence of pore size upon cell growth/survival or drug delivery will be studied.

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Faculty Supervisor:

Gregory de Crescenzo

Student:

Partner:

Nagoya University

Discipline:

Engineering

Sector:

Advanced Manufacturing; Life Sciences (not health)

University:

Polytechnique Montréal

Program:

Globalink Research Award

Affordability Dashboard – Vancouver

The VEC, under its Economic Transformation Lab and in partnership with SFU and MITACS, seeks to research, design, and publish an affordability dashboard that consolidates all important metrics/statistics on affordability, relevant to Vancouver businesses and talent. The Dashboard will not only focus on affordability of office, retail, and industrial space, as well as other pertinent business operation affordability metrics, but will also contain affordability metrics that inform businesses of the cost of living for their talent. The dashboard will also include benchmarking against other ‘peer’ cities; the comparison cities will be identified through similarities in city population, brand, GDP, etc. The intent behind this dashboard is to make all of the metrics available in one place to help inform businesses and talent of current affordability conditions.

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Faculty Supervisor:

Andrey Pavlov

Student:

Partner:

Vancouver Economic Commission

Discipline:

Business

Sector:

Public administration

University:

Simon Fraser University

Program:

Accelerate

Materialized View Performance at Massive Scale for Data Analytics Workloads

View materialization in relational database systems helps in improving the performance of
querying the stored data. With the emergence of large scale data analytics, there are several
challenges that need to be considered for robust view management. In this project, we study
the performance of materialized views at large scale, when there are thousands of users
creating tens of thousands of views. Further, the challenges that emerge from new
computing paradigms like cloud computing wi ll also be investigated

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Faculty Supervisor:

Ashraf Aboulnaga

Student:

Partner:

LogicBlox

Discipline:

Computer science

Sector:

University:

University of Waterloo

Program:

Accelerate

Controlling Flow-Induced Vibrations with Novel 3D-Printed Devices

Continuous flexible systems such as aircraft wings, pipelines, risers, bridges, power towers, and transmission lines are always subjected to unwanted vibrations induced by unsteady wind loading. The typical engineering solution is to add a tuned-mass
damper to these structures. This typically works in removing the unwanted resonance, but it creates new problems as it adds two new natural frequencies. Here, we seek to develop a new class of dampers without a natural frequency, making them useful at damping vibrations over a broad spectrum of frequencies.

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Faculty Supervisor:

Frederick Gosselin

Student:

Partner:

Universität Stuttgart

Discipline:

Engineering

Sector:

Education

University:

Polytechnique Montréal

Program:

Globalink Research Award

Development and application of a field method that evaluates propulsive force generation and transfer in Canoe Kayak Sprint

Canoe Kayak Sprint is a highly technical sport, where small changes in athlete stroke technique and/or boat movement can have large implications on race performance. Due to the complexity of these movements it has been difficult in the past to obtain equipment that is precise enough to measure kayak sprint technique accurately. With continual advancements in kinematics and kinetics measurement equipment/technology this problem can now be solved. The objective of this project is to create an instrumented kayak system (i.e. boat, paddle) that can be used to accurately measure kayak sprint technique in the athletes’ daily training environment. The researchers will develop and validate a kayak foot board, seat, and paddle which will measure the forces and moments (i.e. kinetics) being transferred from the water to the boat by the athlete. In addition, full-body and boat movements (i.e. kinematics) will be collected to better understand the temporal and spatial relationships of kinetics and kinematics during the kayak stroke.

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Faculty Supervisor:

Michel Ladouceur

Student:

Partner:

Canoe Kayak Canada (ON)

Discipline:

Physics

Sector:

Arts, entertainment and recreation

University:

Dalhousie University

Program:

Accelerate

Simulation of Aeration inside a Hydroelectric Turbine

This research project is aimed at improving the oxygenation of water downstream of hydroelectric dams; one of the issues being to preserve the aquatic fauna. The goal is to develop the fundamental understanding and applied technology needed by industry in the field of two-phase flows. Experimental and numerical tools are developed to design similar laws, to obtain validation data for numerical simulation of aerodynamic wind turbines. The student will perform numerical simulations of the two-phase flow characteristic of those encountered in aerating hydroelectric turbines. The student will perform numerical analysis (verification, validation) of the computations, analyze results such as the total air-water interface area critical for oxygenation efficicency.

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Faculty Supervisor:

Stéphane Étienne

Student:

Partner:

National Cheng Kung University

Discipline:

Engineering

Sector:

Aerospace

University:

Polytechnique Montréal

Program:

Globalink Research Award

API Usability of Machine Learning Libraries

API usability specifies how easy, efficient, error-preventing, and pleasant an API of a software library is from its users’ perspective. With machine learning (ML) techniques becoming increasingly powerful and pervasive, many non-programmers
and casual users (e.g. domain experts in medicine or geography) started to explore ML libraries. However, many find them challenging to use because of bad API design. This project aims to investigate the API of ML libraries through the lens of
user-centered design. The knowledge gathered will help developers of ML libraries improve their APIs and establish preliminary methodologies to evaluate API usability of ML libraries.

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Faculty Supervisor:

Jinghui Cheng

Student:

Partner:

National Taiwan University

Discipline:

Engineering

Sector:

Technology; Information and Communications Technology

University:

Polytechnique Montréal

Program:

Globalink Research Award

Integration of printable polymers with composite nanomaterials for wearable microfluidics

Research into wearable systems, functional nanomaterials, 3D printing, flexible microfluidics, and commercial thermoplastic polymer (TP) microfluidics, is reported daily. However, much of this research is hindered by difficulties in integrating structures, devices, and systems realized using different materials platforms. While polymers such as SU-8 and polydimethylsiloxane (PDMS) are popular with academics, TPs such as optically transparent cyclic olefin copolymer (COC) dominate in commercial microfluidics. TPs are expensive to prototype with, and are difficult to combine with flexible elastomer materials (PDMS, polyurethane) for high-stroke actuators. The proposed student project will combine thermoplastic materials such as COC and plastisol with functional nanomaterials developed in the Simon Fraser University (SFU) Microinstrumentation Lab. These functional nanomaterials include magnetic, piezoresistive, and piezoelectric composite polymers, with highly flexible polymer base materials. The student will work on materials integration techniques for portable thermoplastic based systems, and/or wearable textile based systems.

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Faculty Supervisor:

Bonnie Gray

Student:

Partner:

Jamia Millia Islamia

Discipline:

Engineering

Sector:

Nanotechnology; Health and Related Sciences & Technology; Biotechnology

University:

Simon Fraser University

Program:

Globalink Research Award