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

A comparative phase behavior study of different alkali/heavy oil/water systems on heavy oil water flooding

For many mobile heavy oil reserves in Western Canada, thermal-based enhanced oil recovery methods are not economically applicable due to the thin payzone thickness. Alkaline flooding, one of chemical recovery methods, has great potential for enhancing oil recovery. In this process, alkali-containing fluid is injected into the heavy oil reservoir and reacted with the saponifiable components to generate natural surfactant in-situ. The formation of surfactant and associated phase behavior phenomena, will contribute to additional oil recovery due to reducing oil/water interfacial tension and altering wettability. The proposed study is concentrating on the complex phase behavior of alkali-heavy oil-brine systems using three different alkalis (sodium carbonate, ammonium hydroxide, and sodium hydroxide) at ambient or high pressure. This study will identify the type of micro-emulsion phases formed, analyze the detailed composition and fluid properties of generated equilibrium phases, and measure interfacial tensions between equilibrium phases to prove the reaction mechanisms for alkali flooding process.

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Faculty Supervisor:

Na Jenna Jia

Student:

Partner:

Petroleum Technology Research Centre

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

University of Regina

Program:

Accelerate

NLP Techniques for Automated Entity Recognition

The primary goal of this project is to explore a variety of new and existing Natural Language Processing (NLP) techniques to improve the performance, and further the automation of, Knote’s text analysis software – specifically with entity recognition. Entity recognition is the process of identifying all groupings of words in a collection of documents that fall within that entity’s purview, such as proper names or chemical compounds. We will study the applicability of classic statistically driven approaches to classification, and evaluate the viability of newer techniques that make use of semantic encoding (such as word2vec).

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Faculty Supervisor:

Frank Rudzicz

Student:

Partner:

9636668 Canada Corp

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Cartographie de l’offre et de la demande des services juridiques au Québec

Peu d’outils sont présentement disponibles pour éclairer les professionnels du droit au sujet de l’état du marché des services juridiques, les concurrents en place, les tendances, les stratégies de mise en marché et de fixation des prix, les besoins de la population en matière de services juridiques, etc. Ce projet consiste à effectuer une veille sectorielle rassemblant un ensemble de données clés liées au marché des services juridiques, tant pour documenter l’offre pour des services juridiques que pour la demande. Ce projet vise à établir sur une base permanente, un outil de veille qui pourra servir à favoriser une meilleure distribution des services d’avocats en régions, à cibler les endroits propices de développement d’affaires pour les jeunes avocats ainsi qu’identifier les besoins de la population qui sont non desservis.

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Faculty Supervisor:

Kim Lehrer

Student:

Partner:

Barreau du Québec

Discipline:

Business

Sector:

Other services (except public administration); Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Construction of a Genetic Variant Store

This project proposes to explore and implement a method of storing and retrieving data relating to genetic variation across a population of individuals. Due to the large amount of genetic information each person possesses, such a database requires special attention to minimize the amount of data stored and to create efficient methods of accessing the data. This work will research and test different strategies to build a compact data store that will return results quickly. This data store will be incorporated into the PhenoTips software provided by Gene42 Inc. for use by hospitals specializing in genetic diseases.

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Faculty Supervisor:

Eyal de Lara

Student:

Partner:

Gene42 Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Automatic Code Partitioning for XPU Acceleration

Based on 7 years of R&D, Secodix has developed a processor, the XPU, that is faster by two orders of magnitudes compared to existing processors. To leverage the technology, we need to provide software programmers the ability to use existing programming languages (in particular, C++) while benefiting from XPU performance. To enable that, we need to develop tools and methods that can take performance-critical portions of software and accelerate them on the XPU. The aim of this project is to investigate those techniques. While the research organization will benefit by expanding its knowledge on utilizing high-performance architectures, the partner organization will benefit by incorporating research results into its products. The ability to use existing programming languages is one of the key product requirements that are being driven by Secodix’s customers.

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Faculty Supervisor:

Karthik Pattabiraman

Student:

Partner:

Secodix

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Network Traffic Classification for Cyber Threat and Malware Detection

Bell’s Cyber Threat Intelligence (CTI) team is collaborating with academic institutions in order to further research and develop cyber security analytics for the protection of critical infrastructure and data. The focus of this research is to create and leverage a traffic classification project specifically for network security purposes. This research to design distributed algorithms fast enough for analyzing massive high-dimensional
data generated by network traffic to detect cyber threats/ attacks and anomaly in the network.

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Faculty Supervisor:

Bijan Raahemi

Student:

Partner:

BCE Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Ottawa

Program:

Accelerate

First Nation Environmental Review and Analysis

The Government of Canada is in the process of reviewing legislation and procedures related to environmental processes, e.g. the Canadian Environmental Assessment process (CEAA) and the National Energy Board process (NEB). Indigenous groups across Canada have participated in engagement sessions, and made formal written submissions which have been made publically available. This research project will review and analyze of all the Indigenous submissions on the NEB and CEAA processes to identify the key themes, gaps and contradicting view noted with the various Indigenous approaches to these environmental processes as compared to current legislation. The outputs will provide the Atlantic Policy Congress (APC) with knowledge and material to ensure legislative changes align with Indigenous world views and priorities in accordance with the empirical evidence provided by the actual written submissions.

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Faculty Supervisor:

Michelle Adams

Student:

Partner:

Atlantic Policy Congress of First Nations Chiefs Secretariat

Discipline:

Sociology

Sector:

Agriculture; Professional, scientific and technical services; Public administration

University:

Dalhousie University

Program:

Accelerate

Ground Spatial Filtering in Near-Field Scanners

Near-field measurement is a key and inseparable part of Antenna characterization and electromagnetic diagnosis applications. Providing a fast method to perform this type of measurement will be of significant added value to the RF industry. Traditionally, near-field measurements are performed inside an echoic chambers and using a mechanically sweeping probe. This type of measurement is accurate but is also relatively costly and time-consuming. Moreover, due to the time it takes for mechanical probes to sweep, it might not be very efficient for certain types of diagnosis applications where it near-field data has to be acquired in a short time window. EMSCAN Corporation has introduced a new scanner which enables near-field measurement tests to be performed in real-time inside lab-environment. Besides all of the features this type of scanner has to offer, they can be improved in a few aspects. TO BE CONT’D

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Faculty Supervisor:

Pedram Mousavi

Student:

Partner:

EMSCAN Corporation

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Alberta

Program:

Accelerate

Development of new techniques for power system model validation and calibration

Dynamic modeling is one of the most important tools for the power system operation and planning purposes. In order to study the behavior of the system, which is subjected to disturbances, a valid knowledge of parameters of system components is essentially required. The objective of this project is to propose an applicable algorithm to identify the parameters of the power system components’ models. For the identification purpose, the actual power systems’ subsections data collected by phasor measurement units (PMUs) are employed. Afterward, the acquired model needs to be validated to assess the capability of the model in performing accurately in different operation conditions. This study is in line with the intern’s research topic, which is modeling, identification, and control of power generation systems. Moreover, this project will help the Powertech to add a tool to their software to predict the behavior of the power systems’ components.

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Faculty Supervisor:

Jeffery Kurt Pieper

Student:

Partner:

Powertech Labs Inc.

Discipline:

Engineering

Sector:

Technology; Energy and Utilities; Other

University:

University of Calgary

Program:

Accelerate

Increasing Patient Engagement and Informing Marketing Decisions through the use of Patient Personas and Patient Journey Mapping

Mobile health (mHealth) apps allow patients to practice self-care and manage their chronic diseases. Common functions in mHealth tools allow users to monitor their symptoms and mood, keep a thought diary, track medication use and trend information; this provides data that can be used to better understand patient behaviour to ensure that patient needs are being met. By using a user-centered design approach for app design, the patient experience is captured through understanding their goals and challenges as well as their journey in living with or recovering from chronic disease(s). The Health Storylines platform, offered by the patient analytics company Self Care Catalysts, offers self-care tools which can provide these valuable insights in order to improve the app design and inform marketing strategies for specific patient groups, which will in turn drive higher engagement levels and improve patient empowerment.

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Faculty Supervisor:

Aviv Shachak

Student:

Partner:

Self Care Catalysts Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Waste heat recovery in aluminium smelters: technical and economic analysis

Aluminium smelter are energy intensive and not particularly energy efficient, as most of the energy required to produce aluminium is lost along the production line. This is the reason why it is mandatory to perform a detailed analysis of the thermal wastes produced in these factories. The main objective of this project is to investigate the solutions to recover the thermal wastes and to convert them into useful power. The feasibility of these solutions are analysed by considering technological and economic aspects: in this way, a reliable solution to improve the energy efficiency in aluminium smelter is provided.

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Faculty Supervisor:

Mikhail Sorin

Student:

Partner:

Rio Tinto Alcan (Jonquière, QC)

Discipline:

Engineering

Sector:

Manufacturing; Mining; Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Webpage customer persona discovery and push notification guidelines

Cellphones get notifications from different companies every day, but we do not know whether these notifications have a significant impact on customers’ behaviour. Knowing the impact of these notifications would provide useful insights to marketing strategists. Since user behaviour will determine the efficacy of push notifications, this project initially aims to build a behavioural model, which will group customers based on their web site navigation behaviour. Phase 2 of this project will use that behavioural model to propose strategies for using push notifications to target different customer types. Phase 3 of this project will examine the effect of the notifications and generalize to a wider range of webpage datasets.

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Faculty Supervisor:

David A Campbell

Student:

Partner:

Mobify Research and Development Inc

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

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