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

Determing the value of delivering light >500nm to dental resins

A new curing light, PinkWave (Apex, Racine, WI) was introduced last year (https://vistaapex.com/pinkwave). This light is unique because it has four distinct wavelength bands that deliver red (625 – 750 nm), infrared (800 – 900 nm), blue, and violet light. The manufacturer also claims that this ‘quad-wave’ light can reduce polymerization shrinkage stress.[13] Initial reports indicate that the value of using this ‘quad-wave’ light to photo-cure current RBCs remains uncertain because the absorbance spectra of four most common photoinitiators used in dental resins; camphorquinone (CQ), 2,4,6-trimethylbenzoyl)-phosphine oxide (BAPO), Ivocerin, and Lucirin TPO will not benefit from receiving light above 500 nm. In view of the fact that dentists are using this light to photo-cure dental fillings in Canada, more research is required to determine the effectiveness of this particular curing light that dentists both in Canada and the rest of the world are using on patients.
This research will:
(1) Measure the spectral radiant power from the PinkWave using a fiber optic spectrometer;
(2) Evaluate the benefit of including light above 500 nm from a curing light using the hardness (VH) and degree of conversion (DC) of flowable and regular-viscosity four different dental resins 24 h after exposure PinkWave

View Full Project Description
Faculty Supervisor:

Richard Price

Student:

Partner:

Ivan Horbachevsky Ternopil National Medical University

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Technology

University:

Dalhousie University

Program:

Globalink Research Award

Carboxyalkylated and sulfoalkylated nano lignin as an emulsifier for coating application

The overall objective of this study is to generate lignin-derived sustainable emulsion systems for coating applications. The main focus of this study is on the generation of functional lignin derivatives and then the conversion of these lignin derivatives to lignin nanoparticles. Afterward, the use of lignin nanoparticles in oil-water emulsions will be studied for coating applications.
Specifically, she will study the generation of lignin nanoparticles from carboxyalkylated and sulfoalkylated lignin and comprehensively characterize them. Then, she will study how these nanoparticles can be used as oil-water emulsifiers with different characteristics.
This project will examine the use of carboxyalkated and sulfoalkylated lignin in an application that has not been studied in Canada, and therefore will widen the activities of lignin valorization at Lakehead University (and Canada). Although Lakehead University has an advanced laboratory for lignin characterization, it is not equipped for assessing coating applications. Therefore, this internship will not only provide an opportunity for the intern to learn new methods and visit KTH but also a chance for Lakehead university to explore the use of lignin in a new application (i.e., coating formulations).

View Full Project Description
Faculty Supervisor:

Pedram Fatehi

Student:

Partner:

Kungliga Tekniska Högskolan

Discipline:

Engineering

Sector:

Sustainability & the Environment; Advanced Manufacturing; Nanotechnology

University:

Lakehead University

Program:

Globalink Research Award

Free radical polymerization of lignin and PCL for 3D printing materials

The main goal of her study is to make sustainable polymers from lignin that can be used in three dimensional (3D) printing material production. The student will work on making 3D printing materials from polymerized lignin and polycaprolactone (PCL). At Abo Akademi, the student will use different monomers to generate composites of lignin and PCL. Then, she will characterize the properties and performance of the produced lignin-PCL as a 3 D printing material using the advanced tools available at Abo Akademi. She will optimize the properties of the polymers to achieve the best performance. It is expected that she will need 6 months (starting June 2023) to complete this project in Finland. It is also expected that, in addition to scientific outcomes that benefits both institutes, this student mobility will strengthen the collaboration between Lakehead and Abo Akademi universities. It is also expected that this collaboration will create an opportunity for Canada to strengthen itself in knowledge and material development for sustainable product fabrications.

View Full Project Description
Faculty Supervisor:

Pedram Fatehi

Student:

Partner:

Åbo Akademi University

Discipline:

Engineering

Sector:

Education

University:

Lakehead University

Program:

Globalink Research Award

3D computer vision

Monocular depth estimation aims to infer the distance information of objects in a 2D image. It is an integral part of many computer vision tasks and has applications to autonomous driving, robotics, and virtual reality, among others. This project focuses on developing a new deep-learning-based monocular depth estimation method with high efficiency, competitive performance, and low generalization error. To this end, various approaches will be explored, including the exploitation of 3D prior and geometric information as well as the design of new loss functions. The project will lead to publications in top computer vision conferences /journals, new datasets, and patents.

View Full Project Description
Faculty Supervisor:

Jun Chen

Student:

Partner:

New York University

Discipline:

Engineering

Sector:

Education

University:

McMaster University

Program:

Globalink Research Award

Photovoltaic window coatings

This project aims to conduct research towards the development and implementation of photovoltaic energy generating windows. Through the use of window coatings, the windows of an everyday home will be converted to a source of generating energy to power the home. This research will take us a step closer to our goals of net-zero by developing windows that can generate energy to power the home as well as tests on their use in charging applications. The benefits to the partner organization will be the data then allowing the company to develop and implement solar windows.

View Full Project Description
Faculty Supervisor:

Wayne Groszko

Student:

Partner:

Kohltech Windows And Entrance Systems

Discipline:

Engineering

Sector:

Manufacturing

University:

Nova Scotia Community College

Program:

Accelerate

Canadian Faces of Learning Disabilities (CFOLD) – Obtaining and Disseminating Knowledge

The objective of this project is to provide a research report synthesizing Canadian research that directly relates to Learning Disabilities (LD). This project will benefit Canadians as it will provide stakeholders who support individuals with LD with easy access to information. Easy access to recent research will help to educate Canadians on a variety of aspects pertaining to LD such as causes, diagnostic criteria, assessment procedures, underlying cognitive processing difficulties, learning strategies, assistive technology, and help individuals to develop an understanding of their diagnosis. The objectives of this project are to: i) collect research; ii) provide an analysis of recently published Canadian research; and iii) support knowledge mobilization pertaining to the last decade of Canadian research on LD, and identify topics in need of further exploration.

View Full Project Description
Faculty Supervisor:

Lauren Goegan;Gabrielle Young

Student:

Partner:

Learning Disabilities Association of Canada (ON)

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Business Strategy Internship

Investigating Smart Wearable Systems for Workplace Wellness Management

Japan is a leading example of a nation with a rapidly ageing society and currently consists of the highest proportion of elderly adults worldwide. Among others, this has led to a series of downstream concerns, including labour shortage issues and reduced ability of working individuals to finance those who are retired. As one of the strategies to address these concerns, combined government and society-wide efforts over recent years have encouraged greater employment opportunities for elderly. However, given that elders are often more prone to age-related difficulties, such as decreased physical and cognitive function, this higher proportion of working elders gives rise to a pressing need for an effective workplace wellness management system. Hence, this project aims to investigate the physiological differences between a “healthy” and “diseased” worker as well as to refine the tolerance that is used when differentiating between the two states. By exploring various ways of defining the health-disease boundary, the project will reduce the likelihood of false positives when identifying “disease”, thus improving confidence when separating the two states for use in real-world conditions.

View Full Project Description
Faculty Supervisor:

Arthur Chan

Student:

Partner:

Osaka University

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

NEGF based Cryogenic MOSFET simulation including inelastic scattering

The project aims to develop a state-of-the-art numerical simulator to compute transistor’s physical behaviors at deep cryogenic temperatures. First of its kind, the simulator will incorporate physical effects critical for transistor’s operations at cryogenic temperature such as inelastic scattering, while maintaining computational efficiency and robustness. The successful outcome will provide the research community a widely desired tool for understanding and predicting how realistic MOSFETs behave under deep cryogenic temperatures. It is expected that the simulator will provide critical enhancement to the current product line of the partner organization, Nanoacademic Technologies, a leading company in cryogenic temperature numerical simulation for semiconductor devices.

View Full Project Description
Faculty Supervisor:

Lan Wei

Student:

Partner:

Nanoacademic Technologies Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Preparation of Quantum Machine Learning Datasets with Quantum Advantage and Challenges using State-of-the-art Classical Machine Learning

Machine Learning (ML) approaches generally consist of training an algorithm on a given dataset containing data which has to be analyzed or otherwise understood. For an ML application to be successful, careful thought must be given to ensuring that the architecture of the algorithm chosen is fit for the task at hand: some architectures are tailored for sequential data (stock market data, audio data, etc.) while others are tailored for image data. One subset of ML algorithms is Quantum Machine Learning, which seeks to utilize quantum computing techniques. This research project aims to select a set of quantum datasets and evaluate the performance of both quantum and traditional ML algorithms on them, in order to demonstrate that quantum machine learning can outperform classical machine learning methods on certain tasks of interest, such as classifying quantum circuits. The expected outcomes of this research are to advance the field of quantum machine learning and to lay the groundwork for future work in this area.

View Full Project Description
Faculty Supervisor:

Arthur Chan

Student:

Partner:

Osaka University

Discipline:

Computer science

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

Natural Health Products to Manage Cancers of Dogs: A Pre-clinical Investigation

More than half of Canadian households have companion animals such as dogs or cats. However, cancer has become the leading cause of death in dogs. Currently, available treatments have limitations and compromise the quality of life of dogs. Dragonfly Research Inc (Adored Beast Apothecary) wishes to develop unique natural health products (NHP) to prevent and treat the cancers of dogs. The overall objective of the proposed research project is to assess the anti-oxidative, anti-inflammatory, and tumor suppression ability of the patent-pending natural product formula derived from Chaga mushroom and microalgae using a pre-clinical experimental model of mice. The intern (a postdoctoral fellow) will conduct the animal study to examine cancer preventive and treatment properties of the new natural health product in comparison to two major components. The expected result will become useful for the industry partner to design and perform a clinical study using dogs, and progress with business development and commercialization.

View Full Project Description
Faculty Supervisor:

Vasantha Rupasinghe

Student:

Partner:

Dragonfly Research Inc.

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Advanced Manufacturing; Agriculture and Food

University:

Dalhousie University

Program:

Accelerate

Generative 3D Modelling for Game Asset Creation using Deep Learning Techniques

The 3D entertainment industry has expanded quickly in recent years, largely driven by animated content, streaming services, video game development, AR/VR/XR. The new trend enabled by the ubiquitous graphics processing power is that users are becoming creators. Surprisingly, the fundamentals of 3D creation have not changed in 45 years. This puts the creation of 3D out of reach for 99.8% of consumers and, for professionals, state-of-the-art methods are still too costly and labor intensive to practically meet growing 3D demand. Generative Adversarial Networks (GANs) and other AI technologies offer new possibilities in the AI generation of 3D and 2D art assets. This project investigates the potential of using deep learning techniques for generative 3D modelling for game development and has significant implications for the industry revenue stream.

View Full Project Description
Faculty Supervisor:

Ali Mahdavi-Amiri

Student:

Partner:

Tori Technologies

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

Two-step personalized federated learning algorithm in reality

Machine learning attempts to model high-level abstractions in data using multiple processing layers with complex structures or non-linear transformations. Federated learning is a distributed machine learning approach that allows multiple parties to collaborate on training while preserving user data privacy. However, the data from each party is typically non-independent and identically distributed (Non-IID), which can negatively impact the training effectiveness of the model. This study proposes a contrastive learning method to mitigate the impact of Non-IID data distribution on model training. Additionally, this study researches the feasibility of deploying this method on edge devices, for example, the Internet of Things (IoT). The primary objective of this research project is to demonstrate combining contrastive learning with clustering methods. It can solve the impact caused by Non-IID distribution in federated learning and produce models that balance both generality and personalization. The study aims to validate the research methods through more diverse datasets and data distributions closer to reality.

View Full Project Description
Faculty Supervisor:

Patrick Hung

Student:

Partner:

National Cheng Kung University

Discipline:

Computer science

Sector:

Artificial Intelligence; Technology

University:

University of Ontario Institute of Technology

Program:

Globalink Research Award

Previous
1…974975976977978979980…2,513
Next

Join a thriving innovation ecosystem.

Subscribe to our newsletter now!

Subscribe