Innovative Projects Realized

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

31133 Completed Projects

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BC
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Projects by Category

Dynamique environnementale d’un sous-bassin de l’hydrosystème de Drâa, sud du Maroc

Le projet de la stagiaire Imane Nafouri, vise l’élaboration d’une carte de risque d’érosion hydrique de Dadès, un des principaux sous-bassins de l’hydrosystème de Drâa, situé au sud du Maroc. L’ensemble de cet hydrosystème est affecté par des évènements météorologiques extrêmes, à savoir des périodes de sécheresses sévères et quelques épisodes de précipitations soudaines et intenses. Toutefois, très peu d’études ont porté sur cet enjeu.
Les zones à risque d’érosion seront cartographiées en se basant sur les données de la télédétection (modèle numérique de terrain, images satellitaires, photographies aériennes, et images LiDAR (Light Detection and Ranging) et sur les données de terrain et de laboratoire (sédimentologie, minéralogie) qui sont en cours d’acquisition depuis l’automne 2022.
Ce projet s’inscrit d’un projet global soumis par les co-superviseurs du stage au Ministère des Affaires internationale et Francophonie suite à l’Appel à projet Québec-Royaume du Maroc 2022-2023, intitulé : Dynamiques hydro-géomorphologiques d’un socio-hydrosystème désertique

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Faculty Supervisor:

Najat Bhiry

Student:

Partner:

Cadi Ayyad University

Discipline:

Earth science

Sector:

Education

University:

Université Laval

Program:

Globalink Research Award

Application of multi-agent systems and block chains in additive manufacturing network scheduling

Additive manufacturing technologies enable facilities at any location in the global supply chain to bid for customer jobs. In this setting, job scheduling is based on due-dates, proximity to customer location, opportunities for cheaper consolidated shipments with other customers, etc. Both multi-agent systems and block chains can support scheduling for decentralized manufacturing. In this project, the student is expected to investigate how these technologies can work together and support intelligent scheduling of additive manufacturing tasks. The project will involve a broad literature review and the development of a case study with numerical modelling, implementation, and analysis.

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Faculty Supervisor:

Uday Venkatadri

Student:

Partner:

ISEN

Discipline:

Engineering

Sector:

Advanced Manufacturing; Information and Communications Technology; Other

University:

Dalhousie University

Program:

Globalink Research Award

Robust scheduling of liner shipping under disruption scenarios

This research proposes a new recovery model for addressing issues with container ship disruptions. To minimize the negative impact of these disruptions, the model formulates a mixed-integer programming approach that simultaneously considers three recovery strategies, namely vessel speeding-up, port skipping, and alternative routes.
The study clusters call-ports and utilizes port hubs to minimize transshipment costs while considering factors such as port capacity, queuing time for loading/unloading, and the economic value of cargo to identify the optimal port hubs.
The nonlinear problem is initially linearized using precise methods and then solved using CPLEX software. The results are anticipated to demonstrate a reduction in disruption losses. To account for the uncertainty in delay duration and disruption location, the study uses a robust optimization approach as a two-stage stochastic programming methodology.

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Faculty Supervisor:

Hamid Afshari

Student:

Partner:

ISEN

Discipline:

Engineering

Sector:

Transportation (excluding aerospace); Sustainability & the Environment; Ocean Tech

University:

Dalhousie University

Program:

Globalink Research Award

Hole spin in direct bandgap group IV quantum dots

This internship is to investigate the properties of charge carriers confined into nano-scale structures commonly known as quantum dots. The internship will focus on exploring a novel family of group IV semiconductors exhibiting a direct bandgap. The core paradigm here is to harness the favorable properties of hole spin in group IV quantum dots along with the efficient interaction with photons resulting from the bandgap directness to engineer new device architectures for quantum computing and quantum communication. The spin of a charge carrier is central in these technologies as it provides the mean to encode information. Thus, this research aims at modeling the properties of spins in group IV quantum dots and how resilient the spins are to electrical noise and coupling with the environment. This research will address a significant gap in the current knowledge pertaining to spin dynamics in emerging silicon-compatible materials with numerous attractive properties regrading performance and information transfer efficiency. This collaboration will thus extend the knowledge in the field of quantum technologies towards a new family of devices with properties leading to high quality spin systems and their effective interface with photons.

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Faculty Supervisor:

Oussama Moutanabbir

Student:

Partner:

University of Basel

Discipline:

Physics

Sector:

Quantum Science; Nanotechnology

University:

Polytechnique Montréal

Program:

Globalink Research Award

Assessing Snow Properties’ Impact on Various Sensors with the Snow Microwave Radiative Transfer Model

Arctic Sea-ice extent is declining due to climate change. Wildlife, maritime operations and northern communities that depend on sea-ice for traveling and hunting are negatively affected by its decline. Monitoring sea-ice thickness is an important tool to help in decision making in Arctic regions but, due to the snow covering the sea-ice, remote sensing’s sea-ice thickness retrieval methods are not yet accurate enough to assess every situation.
The Snow Microwave Radiative Transfer (SMRT) model is used to understand how snow properties impact radar scattering. This internship offers the first opportunity to assess the capacity of SMRT to simulate a frequency-modulated continuous wavelength radar responses to snow properties on sea-ice. It will also allow to evaluate the influence of snow variability and its aggregation across different footprint sizes of space born sensors, such as Sentinel-1 and CryoSat-2. This work will contribute directly to increase the accuracy of sea-ice thickness retrievals.

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Faculty Supervisor:

Alexandre Langlois

Student:

Partner:

Northumbria University

Discipline:

Earth science

Sector:

Environmental Science and Technology; Water; Aerospace

University:

Université de Sherbrooke

Program:

Globalink Research Award

A Nanomaterial-Integrated Paper Microfluidic Device for Detecting and Predicting Myocardial Infarctions

Cardiovascular disease kills 17.9 million people globally each year. 85% of these deaths were caused by either a myocardial infarction (heart attack) or stroke. Current tests for predicting heart attacks provide rapid results when presented with a blood sample, but these samples must be preprocessed using time-consuming methods. This project will develop a paper-based platform to detect heart attack markers in blood without external preprocessing. This will be accomplished by integrating a blood processing device into the testing platform. Ideally, this platform will predict heart attacks within five minutes of drawing blood from patients, facilitating life-saving medical treatment. The partner organization, Mitra Biotechnologies, previously developed a paper-based blood processing device. They are now partnering with researchers at the University of Waterloo with expertise in paper-based medical tests to turn this device into an all-in-one blood processing and testing platform that can be brought to market to save lives.

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Faculty Supervisor:

Sushanta Mitra

Student:

Partner:

Mitra Biotechnologies Inc.

Discipline:

Life Sciences

Sector:

Manufacturing

University:

University of Waterloo

Program:

Accelerate

High-threshold photonic quantum computing

Today, quantum computers of any architecture still operate in the noisy intermediate-scale quantum (NISQ) regime, with systems composed of tens to hundreds of noisy qubits that are not protected from errors. To meaningfully solve challenging problems from industries using quantum computers, we need to make a system that is large enough in scale and robust to errors. The intern will be involved in Xanadu Architecture team’s efforts in investigating promising approaches for tolerating and lowering noise and errors affecting photonic platforms. The aim is to lower the demands on hardware, shortening the time to build a universal, fault-tolerant quantum computer.

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Faculty Supervisor:

Robert Raussendorf

Student:

Partner:

Xanadu

Discipline:

Physics

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Détection des engins perdus pour protéger les espèces aquatiques en péril dans le golfe du Saint-Laurent en utilisant l’intelligence artificielle

La perte d’engins de pêche en mer représente un danger pour la vie marine, en particulier pour les baleines noires qui risquent de s’emmêler dans les cordages. C’est pourquoi la détection des engins de pêche abandonnés est une préoccupation majeure pour les scientifiques et les autorités maritimes. Les avancées dans l’intelligence artificielle offrent une solution prometteuse à ce problème. En utilisant des algorithmes de détection, il est possible d’identifier et de localiser les zones où les engins de pêche fantômes sont susceptibles de se trouver, ce qui facilitera les efforts de récupération. Cela permettra également de réduire le temps et les coûts nécessaires pour ces campagnes de récupération. En fin de compte, l’utilisation de l’intelligence artificielle peut aider à protéger les écosystèmes marins et les espèces qui en dépendent.

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Faculty Supervisor:

Noureddine Barka;Tawfik Masrour

Student:

Partner:

Merinov (Gaspé, QC)

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

Université du Québec à Rimouski

Program:

Accelerate

AI-based decision support tool for storm damage prediction in Nova Scotia

Nova Scotia Power Inc. (NSPI) is the main provider of electricity in Nova Scotia. The largest disruptor to its system is the weather, which can lead to widespread equipment failure and outages across the grid. NSPI attempts to predict these damages before they occur to decide on the appropriate level of response and allocation of resources to restore service to their customers as soon as possible, during and after a weather event. Currently, NSPI uses a simple MS Excel-based tool to make predictions. However, its accuracy is relatively low. This project investigates whether modern AI/ML tools like Artificial Neural Networks, Random Forests, and Reinforcement Learning can be harnessed to improve the prediction accuracy of storm damage in Nova Scotia. The objective is to develop and test a prototype prediction tool that uses weather data like wind speed and direction, precipitation levels, ground thaw and foliage, as well as system information, e.g., the number of transformers and electricity poles and the distribution of customers across the province, to make systematic predictions about the damage to be experienced in different geographical regions as a result of forecasted extreme weather events.

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Faculty Supervisor:

Ahmed Saif

Student:

Partner:

ISEN

Discipline:

Engineering

Sector:

Artificial Intelligence; Energy and Utilities; Environmental Science and Technology

University:

Dalhousie University

Program:

Globalink Research Award

Investigation of Striped Bass Morone saxatilis, Atlantic Sturgeon Oxyrinchus oxyrinchus, and American Eel Anguilla rostrata movements and migrations in Annapolis River, Nova Scotia

Following the completion of the Annapolis River Tidal Power Generating Station in 1984, the abundance of many native diadromous fish species declined in the river. In 2019, new regulatory directives resulted in the abrupt termination of power generating activities, and tide gates that had barred access to the river were left open for the first time in 35 years. In a collaboration, Nova Scotia Power, Clean Annapolis River Project, and Acadia University are currently assessing the recolonization and habitat use by COSEWIC designated species of concern including Striped Bass and Atlantic Sturgeon and will soon monitor the movements of American Eel within the system. The goal of this project is to monitor river recolonization including spawning habitats and to collect data on critical habitat.

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Faculty Supervisor:

Michael Stokesbury;Trevor Avery

Student:

Partner:

Nova Scotia Power;Clean Annapolis River Project

Discipline:

Life Sciences

Sector:

Utilities

University:

Acadia University

Program:

Accelerate

Lobed Mixer and Inter-Turbine Duct Aerodynamics

The intern will assess computer-based simulation tools used by a leading Canadian aerospace organization to determine the accuracy of these tools. Specifically, the objective is to establish the extent to which these engineering tools can be used to capture the performance benefits of novel aerodynamic design strategies recently developed at Carleton University for aerodynamic shaping of inter-turbine ducts and compact exhaust diffusers, which are two components used on gas-turbine engines. Upon confirming sufficient accuracy of the simulation tools for this purpose, the partner organization will be able to integrate the research findings developed at Carleton University into the design of their gas turbine engines.

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Faculty Supervisor:

Metin Yaras

Student:

Partner:

Pratt & Whitney Canada

Discipline:

Engineering

Sector:

Aerospace

University:

Carleton University

Program:

Accelerate

Reduced order modeling and machine-learning techniques for environmental flows problem

The project involves enhancing and extending the in-house fluid flow solver using advanced mathematical and computing framework to be undertaken at the host university. The current in-house solver code can be efficiently applied to aerospace, marine and environmental flow problems. The collaboration with host university will result in a more advanced version of the code due to the implementation of mathematics based reduced order models which will speed-up the computations without any loss of physics. The reduced order modeling method has proven to reduce the complexity of the problem from millions of elements to just tens or hundreds of elements with almost similar accuracy. Another part of the research collaboration consists of application of machine learning based models to the in-house flow solver. An artificial neural network will be fed in physics of the fluid flow problem and using training data it will be trained to “learn” how to solve the physics for the particular problem. These are the main objectives of the proposed research project which will be completed in the time frame of 24 weeks under the host supervisor.

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Faculty Supervisor:

Artem Korobenko

Student:

Partner:

Scuola Internazionale Superiore di Studi Avanzati

Discipline:

Computer science

Sector:

Environmental Science and Technology; Artificial Intelligence

University:

University of Calgary

Program:

Globalink Research Award

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.