Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

30 508 projets complétés

2882
AB
5105
C.-B.
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projets par catégorie

Scheduling and Routing of Personal Support Workers at Nucleus Independent Living Co

This project aims to propose a decision support tool for Nucleus Independent Living that optimizes the scheduling of clients visits, the assignment of PSWs to clients, and the routing of the daily visits of each PSW while trying to minimize the traveling distances for the PSWs, the number of different PSWs visiting a client, and the inequality between the PSWs’ workload (in terms of the number of client visits assigned and the distance traveled). The decision support tool allows the organization to do the scheduling and routing piece faster and with less human intervention, which results in less risk of human error, better-quality decisions, and higher satisfaction among PSWs and clients. This research provides evidence to the organization’s decision-makers concerning the efficiency of practice for PSWs and workload equity, and patient satisfaction by considering clients’ preferences in choosing their visit hours and the gender of the PSW(s) who serve them.

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Superviseur du corps professoral :

Jonathan Patrick;Onur Ozturk

Étudiant :

Partenaire :

Nucleus Independent Living

Discipline :

Business

Secteur :

Health and Related Sciences & Technology

Université :

University of Ottawa

Programme :

Accelerate

Discourse Representation Framework for Consumer NLP

With the ultimate goal of enhancing Nexxt Intelligence’s market research SaaS platform, inca, this project will create a flexible framework for facilitating conversations with consumers using an agent powered by natural language processing and deep learning models. This ‘discourse representation framework’ will be capable of engaging with consumers in fluent English, and is designed to ask sensible and specific questions which are pertinent to ad-hoc research objectives. The agent will do so by adhering to a ‘discourse policy’, which will be a non-technical conversational design document which can be easily created by market researchers for their research goals. The framework will simultaneously extract structured information from user utterances, using a combination of deep learning and rule-based heuristics, and will navigate through the conversation based on the information it is able to extract.

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Superviseur du corps professoral :

Shurui Zhou

Étudiant :

Partenaire :

Nexxt Intelligence

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

The PEACE + FREEDOM Project – Remote Areas Using Hydrogen for Energy Self-Reliance

Remote areas have the world’s highest death rates and cost of operations. As the global community struggles with shared problems including pandemics and climate change, connecting remote areas with the global community is becoming increasingly important.
The current economic model of remote areas is dominated by reliance on oil, yet oil supplies are not reliable in remote areas, with frequent fuel supply shortages, and prices are not predictable and not sustainably affordable. The result is remote areas in most of the world do not have reliable, affordable energy. This is a primary obstacle to connecting remote areas with the global community.
With this need, hydrogen applications appear in transportation, communications, and electricity as an option to allow remote regions to be connected to the benefits of the global community. In this study, specific technical and economic applications of hydrogen will be studied, quantified and analyzed, like simulation model to hydrogen economy for transport and communications systems for remote areas, energy for propulsion systems used in transport, particularly aviation, buoyant Lift for use in airships and aerostats, global trends and prediction models for the economics of oil versus hydrogen and cost comparison (Helium vs hydrogen – Photovoltaic vs Hydrogen).

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Superviseur du corps professoral :

Loïc Boulon

Étudiant :

Partenaire :

Solar Ship Inc

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

Université du Québec à Trois-Rivières

Programme :

Business Strategy Internship

Enhancing adherence to online PBC wellness programming

Online wellness programming offers a promising avenue to positively influence the mental well-being of older adults with chronic conditions in a manner that is accessible and acceptable. This project aims to build on our collaborative relationship with the Canadian PBC Society to iteratively refine an online wellness program to the unique needs of individuals with primary biliary cholangitis, including strategies such as enhanced social interaction. Additional evaluation will also focus on the program impact on perceived fatigue.

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Superviseur du corps professoral :

Puneeta Tandon

Étudiant :

Partenaire :

Canadian PBC Society

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology

Université :

University of Alberta

Programme :

Accelerate

Deep Learning Classification and model compression

Deep neural networks (DNNs) have achieved great success in many visual recognition tasks. However, existing state of the art deep neural network models are computationally expensive and memory intensive, hindering their deployment in devices with low memory resources or in applications with strict latency requirements. Therefore, a natural thought is to perform model compression and acceleration in deep networks without significantly decreasing the model performance. Developing models for inference on clients has multiple economical benefits, but it becomes difficult to match the performance of bigger architectures by simply training smaller architectures. Therefore, we have to look for solutions like Knowledge Distillation, Network Pruning, Quantization to obtain highly efficient models that can match the performance of bigger architectures.

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Superviseur du corps professoral :

Ioannis Mitliagkas

Étudiant :

Partenaire :

Jumio

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Université de Montréal

Programme :

Accelerate

Social and Community Economic Development Planning in Toronto

“Social and Community Economic Development Planning” is a BSI project is comprised of four internships associated with four non-profit partner organizations engaged in organizing, advocacy and planning for affordable housing and community supports in low-income, racialized and marginalized neighborhoods. The shared context for this work is the ongoing gentrification in downtown Toronto , coupled with displacement pressures associated with transit-led redevelopment in suburban regions of the GTA. Two projects entail research that will support the partner in developing community benefits strategies associated with major infrastructure redevelopments. Two focus more explicitly on researching possibilities for supporting the development of community land trusts that could take land off the market in perpetuity and preserve affordability for low-income residents and businesses as well as social enterprises. The partner organizations, who are among Canada’s leading practitioners of community economic development, will benefit from background research to support strategic planning, popular education and engagement of low-income and marginalized constituencies.

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Superviseur du corps professoral :

Katharine Rankin;Lindsay Stephens;Jason Spicer

Étudiant :

Partenaire :

Black Urbanism Toronto;North York Community House;Jane/Finch Centre;The Neighbourhood Land Trust

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology

Université :

University of Toronto

Programme :

Business Strategy Internship

Advancement of biosensor technologies for use in healthcare/cancer research and detection

The detection of specific carbohydrates is critical for several processes including biofuel production, textile finishing, food production and human health. These carbohydrates play roles in human health including stem cell differentiation, genetic diseases, and viral infection (i.e., COVID-19). Presently, the largest barrier to understanding the role carbohydrates play in human health is the lack of suitable tools to study them. Biosensors are devices that are used to detect and quantify the concentration of biomolecules or microorganisms. Protein-based biosensors, like those described in this proposal, are composed of one or more fluorescently labelled proteins that interact with a target molecule in solution. The interaction of the target molecule with the biosensor induces a change in the protein, which in turn, alters the position/ environment of the fluorescent dye. This change results in an altered fluorescence output, which can be measured. The challenge for developing new protein-based biosensors is that often multiple rounds of the design, build, and test cycles are required to find labeling positions that provide a change in fluorescence upon binding the target molecule yet do not disrupt the binding properties of the protein.

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Superviseur du corps professoral :

Trushar Patel

Étudiant :

Partenaire :

Allos Bioscience Ltd.

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

University of Lethbridge

Programme :

Accelerate

Mimicking medial-knee brace gait using PCA and biofeedback

Knee osteoarthritis is a disabling disease affecting millions of people worldwide. Knee braces have been adopted as a treatment strategy to help manage osteoarthritis pain. These braces apply a force to the knee, which, in theory, reduces the joint loads in the knee. They also however change the way people walk, which can also reduce pain. The purpose of this research is to determine whether the positive effects of the knee braces are due to the altered walking patterns, or the force they apply to the knee. If the altered walking patterns are what reduce knee pain, patients with osteoarthritis can potentially reduce treatment cost and avoid wearing a brace. This research is being performed in collaboration with HAS-Motion, who has recently released a product required to perform this research. This project will test the capabilities of this new product, before it is distributed, in a real laboratory environment.

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Superviseur du corps professoral :

Kevin Deluzio

Étudiant :

Partenaire :

HAS Motion

Discipline :

Engineering

Secteur :

Biotechnology; Health and Related Sciences & Technology; Biotechnology; Health and Related Sciences & Technology

Université :

Queen's University

Programme :

Accelerate

Heart and Stroke Atlantic Canada Cardiac Arrest Policy Strategic Plan

The Heart and Stroke Foundation of Canada has set out four high-level pillars for a nationwide campaign to improve response and outcomes for out-of-hospital cardiac arrest. Heart and Stroke in Atlantic Canada, which covers the provinces of Nova Scotia, Prince Edward Island, and Newfoundland and Labrador, requires a process that will translate the high-level pillars into a strategic and tactical advocacy plan that is tailored to each province’s current state in terms of legislation, political and public receptiveness, and infrastructure, as well as their anticipated needs over the next five years. The interns will conduct a thorough analysis of the current state within each province with regards to cardiac arrest response and policy, leverage political relationships that can enable systematic change, and create strategic campaigns in line with the specific needs and advocacy goals of each province, creating an evidence-driven and actionable roadmap for Heart & Stroke in Atlantic Canada to successfully carry out the campaigns.

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Superviseur du corps professoral :

Katie Dainty;Timothy Chan

Étudiant :

Partenaire :

Heart and Stroke Foundation (NS)

Discipline :

Business

Secteur :

Other services (except public administration)

Université :

University of Toronto

Programme :

Business Strategy Internship

Stream Data Analytics Pipeline Based on IoT Big Data Environment for Safer Fleets and Smart Cities

Road safety affects everyone, not just Geotab customers. With several years of driving and environmental data
from over 2 million connected vehicles we have an opportunity to make our customers safer, as well as our
communities and cities. To reduce accidents, we need to understand both the driving behavioural patterns that
are predictive of accidents, and the environmental factors involved. To achieve this, the data infrastructure
should be capable of processing a series of real-time telematics data, as well as time-series historical records
generated from existing machine learning models to respond to real world incidents within a short period of
latency.

Voir la description complète du projet
Superviseur du corps professoral :

Ben Liang

Étudiant :

Partenaire :

Geotab Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services; Transportation and warehousing

Université :

University of Toronto

Programme :

Accelerate

Face Matching 1 to N

Fraudsters and money launderers have no place in today’s digital economy. To protect against fraud and financial crime, businesses online need to know and trust that their customers are who they claim to be – and that these customers continue to be trustworthy. Jumio uses the power of AI, biometrics, machine learning and certified liveness detection to help you rapidly convert more customers, stop fraudsters from infiltrating your online ecosystem and get in compliance with KYCIAML. The main goal of this project is to identify an individual from a face image by searching in a gallery of stored face images. The idea is to employ machine learning techniques to solve this problem. For this purpose, we want to review and evaluate existing solutions in order to develop an in-house approach. The fundamental challenges to tackle are: the particular conditions of our data, the huge amount of data to be handled and the quick response time demanded by our use case.

Voir la description complète du projet
Superviseur du corps professoral :

Ioannis Mitliagkas

Étudiant :

Partenaire :

Jumio

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Université de Montréal

Programme :

Accelerate

Efficient Multi-frame Obstruction Removal

Modern mobile phones have become the dominant photography device in recent years. However, their users are often not professional photographers. Thus, they lack the skills of choosing proper lighting, proper shot framing, and proper settings on the camera. In particular, photographs are often taken in unfavourable conditions where the scene of interest is obstructed by a fence or a window. We would like to remove such obstruction automatically. Capturing scenes from multiple viewpoints, not only helps to identify the obstruction better, but also helps in removing it. There are existing multi-frame obstruction removal methods, but they are too computationally intensive. This project will focus on a multi-frame obstruction removal approach that is accurate while keeping in mind the computational constraints that would enable mobile deployment. This is of major interest to Samsung as one of the leaders in the mobile phone industry.

Voir la description complète du projet
Superviseur du corps professoral :

Kiriakos Neoklis Kutulakos

Étudiant :

Partenaire :

Samsung Electronics Canada

Discipline :

Computer science

Secteur :

Manufacturing

Université :

University of Toronto

Programme :

Accelerate

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