Projets novateurs réalisés

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

31 132 projets complétés

2940
AB
5159
C.-B.
837
MB
685
NL
882
SK
9291
ON
9695
QC
97
PE
601
NB
1161
NS

Projets par catégorie

Fast and robust real-time precise point positioning

Current real-time precise point positioning (PPP) systems still suffer significant challenges. One is its long position convergence time necessary before precise position solutions become obtainable. Another is its sensitivity to the loss/latency of high-frequency precise orbit and clock corrections, resulting in degraded performance. Those challenges have limited PPP’s adoption in many applications. This project aims to develop a fast and robust real-time PPP system. A positioning model based on uncombined observables will developed to facilitate ambiguity resolution (AR) and ionosphere-aiding which will help significantly reduce the position convergence time. A new real-time orbit and clock generation method will be developed to improve the robustness of PPP by reducing the system’s sensitivity to the loss/latency of precise orbit and clock corrections. A prototype system will be developed to assess the performance of the system for product development.

Voir la description complète du projet
Superviseur du corps professoral :

Xin Wang

Étudiant :

Partenaire :

Profound Positioning Inc

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Calgary

Programme :

Elevate

Smart fusion of multi-sensors for UAVs Navigation – Year 2

The main outcome of this Mitacs-sponsored project will be a robust navigation software capable of providing accurate navigation solutions for commercial Unmanned Aerial Vehicles (UAVs). Such a software will further elevate the industrial competitiveness for the partner corporation, the Profound Positioning Inc. (PPI). After finishing this project, PPI will be able to offer more comprehensive embedded integrated UAV navigation products. Furthermore, Canada will benefit from the established knowledge and expertise in technologies of growing demand worldwide, thus making the Canadian academia and industry sectors leaders in commercial UAVs operation and navigation.

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Superviseur du corps professoral :

Steve Liang

Étudiant :

Partenaire :

Profound Positioning Inc

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Calgary

Programme :

Elevate

Smart fusion of multi-sensors for UAVs Navigation

Nowadays, there is a rapid increase in the use of Unmanned Aerial Vehicles (UAVs) for commercial and civil applications. Fully autonomous or remotely controlled UAVs requires a reliable and continuous navigation system providing meter level accuracy. The cost, size, and power demand of navigation systems providing this level of accuracy preclude their use on commercial UAVs. To provide a viable and alternative option, this research will focus on developing a navigation system for UAVs that minimizes costs, while maintaining reasonable performance standards. More specifically, the applicant intend to create new navigation algorithms and methods for both data acquisition and processing while considering using low cost sensors. The main outcome of the proposed research will be a robust navigation software capable of providing accurate navigation solutions for commercial UAVs. Such a software will further elevate the industrial competitiveness for the partner corporation.

Voir la description complète du projet
Superviseur du corps professoral :

Steve Liang

Étudiant :

Partenaire :

Profound Positioning Inc

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Calgary

Programme :

Elevate

Development and Validation of Software for the Three-dimensional Quantification and Visualization of Blood Flow Hemodynamics in Patients with Aortic Insufficiency using 4D flow MRI. Year 2

The aim of this proposal is to assist in the development and validation of a dedicated 4D flow MRI analysis software for the evaluation of aortic valve insufficiency. Before being commercialized this software requires validation considering the large amount of data required to be pre-processed (over 2,000 files per case), elemental data corrections, data analysis preparation, data analysis algorithms, and 3D visualization. We will develop an efficient and standardized workflow for 4D flow MRI pre-processing and blood flow analysis with the aim of validating the latter against current clinical reference standard of Doppler Echocardiography to assess the severity of aortic insufficiency across various disease models.

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Superviseur du corps professoral :

James A White

Étudiant :

Partenaire :

Circle Cardiovascular Imaging

Discipline :

Engineering

Secteur :

Health and Related Sciences & Technology; Technology

Université :

University of Calgary

Programme :

Elevate

Economic Fire Design of Buildings

With my research project I wish to contribute to a body knowledge that will assist with Halsall’s current needs and future directions. A review of relevant literature on methods and procedures for designing more economical, fire-resistant buildings would serve Halsall by providing them with a reference works with which their design engineers can use to make informed decisions in the choice how their projects come to fruition. With Halsall already being an industry leader in restoration engineering, a focus on more economical fire-resistant design may help reduce costs on major restoration projects. Halsall’s sustainable design contracts and environmental initiatives may benefit by reducing the amount of building materials used and thus potentially reducing the project’s environmental impact. A furthered understanding of fire resistance may also allow for better response complicated designs in new buildings. All of this could be used by Halsall to establish market advantage over competing firms.

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Superviseur du corps professoral :

Mark Green

Étudiant :

Partenaire :

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Queen's University

Programme :

Accelerate

Development and Validation of Software for the Three-dimensional Quantification and Visualization of Blood Flow Hemodynamics in Patients with Aortic Insufficiency using 4D flow MRI.

The most common cause of chronic aortic insufficiency (AI), a backwards leaking of blood through the aortic valve, are congenital valve disease, degenerative valve disease, and primary diseases of the surrounding aorta. Current management of severe AI is to surgically replace the valve based upon generic 2D imaging measures of severity and progression. However, 4D MRI flow has been recently introduced and may offer a paradigm shift in the ability to characterize AI, particularly due to different disease states. As such, improved decision-making regarding the need and the timing of surgical intervention may be feasible. In partnership with Circle Cardiovascular Inc., we aim to: a) establish a novel software environment for the pre-processing and analysis of 4D flow MRI data; b) validate flow quantification using an in-vitro model of AI; and c) validate in-vivo accuracy and reproducibility of 4D MRI flow in patients with severe AI across various disease states.

Voir la description complète du projet
Superviseur du corps professoral :

James White

Étudiant :

Partenaire :

Circle Cardiovascular Imaging

Discipline :

Engineering

Secteur :

Health and Related Sciences & Technology; Technology

Université :

University of Calgary

Programme :

Elevate

Applications of Neural Network Curve Fitting Methods for Least-squares Monte Carlo Simulations in Financial Risk Management

Monte Carlo simulation methods are commonly used as a risk management tool to estimate the risk exposure of financial asset portfolios. However, the traditional brute-force Monte Carlo (BFMC) method is often very timeconsuming, which makes it difficult to serve the risk management needs of modern insurance industry. An alternative approach, the least-squares Monte Carlo (LSMC) method, could substantially reduce the computation cost by fitting a proxy function of liabilities using simple nonlinear regression methods. However, the LSMC does not work well in capturing the true risk properties of hedged assets and some other variable annuities. To improve the LSMC method, we propose to use neural network method during the curve fitting process. Since the neural network method allows more curve-fitting flexibility, the proxy functions of liabilities and Greeks are expected to be improved. By using the improved proxy functions to predict the liabilities and Greeks, the risk exposure of financial portfolios can be more properly quantified.

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Superviseur du corps professoral :

Longhai Li

Étudiant :

Partenaire :

Aon Securities Inc.

Discipline :

Mathematics

Secteur :

Finance and Insurance

Université :

University of Saskatchewan

Programme :

Accelerate

Monitoring the genetic health and structure of Grizzly bear populations in British Columbia to inform ecotourism and resource management

Grizzly bears represent a valuable economic, ecological, cultural and symbolic resource for British Columbia. In order to preserve this resource the current population of brown bears needs to be monitored to ensure the health of the population. One marker of health is the genetic health of the population. Genetic monitoring can also tell us important information about how related different bear populations are and how well these populations are adapted to their ecosystem. This study will use genetic markers to look at this population structure and adaptation of bears across the unique and varied landscape of British Columbia. We will additionally use genetic markers to investigate a recent island colonization by brown bears outside of all current bear population units. This information is crucial to the conservation initiatives of our partner Raincoast International and its Ecotourism partners.

Voir la description complète du projet
Superviseur du corps professoral :

Chris Darimont

Étudiant :

Partenaire :

Raincoast Conservation Foundation

Discipline :

Earth science

Secteur :

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

Université :

University of Victoria

Programme :

Accelerate

Broadband Internet Policy and Farmers’ Collective Agency in Vietnam

Vietnam approved the national rural information and communication plan in 2011 that includes the building of a 420 million CAD broadband network infrastructure intended to link all smallest administrative units by 2015. However, the country has not achieved this goal yet. Vietnam has experienced countless failures in rolling out Information Communication Technology systems mainly because of a top-down diffusion approach which sees users as passive recipients. To
avoid those common pitfalls, the project – a part of my dissertation – views that farmers are active agents whose collective agency has a say in shaping the Internet policy that works and responds to their needs; erases undemocratic practices; and expands their political, economic, social, and personal freedoms. In this project, I plan to gather broadband Internet development information and travel across the country to select representative villages for public consultations about the technology policy when broadband Internet is still in the making and has not got entrenched.

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Superviseur du corps professoral :

Maria Bakardjieva

Étudiant :

Partenaire :

Vietnam National University

Discipline :

Sociology

Secteur :

Education

Université :

University of Calgary

Programme :

Globalink Research Award

Measurement and Analysis of Ultrasonic Sensors

Ultrasound technology is widely used in medical diagnosis area. Its non-invasive, high resolution, no side effects and other features make it popular. The ultrasound sensor is the critical component and its performance decides the signal quality. A good sensor can stand the environment noise and supply high signal noise ratio (SNR) signal to the processors in order to get high quality images. In this project, sensors from different manufactures with different characteristics should be measured by a custom designed test environment to collect the data and analyze the specification to determine the qualified candidates. Only sensors which satisfy the requirements can be used in the UPNS to reach the designed performance.

Voir la description complète du projet
Superviseur du corps professoral :

Adrian Chan

Étudiant :

Partenaire :

iNano Medical Inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Carleton University

Programme :

Accelerate

Conception d’un algorithme pour déterminer en temps réel l’affectation d’une flotte de taxis

L’objectif du projet est de concevoir un algorithme pour repositionner dynamiquement la flotte de taxis électriques de Taxelco. L’algorithme prend la forme d’un problème d’optimisation qui vise à minimiser le temps d’attente des clients. Pour ce faire, le modèle considère la demande prévue, l’autonomie limitée des véhicules, la circulation, la position des centres de maintenance et des bornes de recharges. Au final, il donne des indications quant à l’affectation d’un taxi à un client et à l’ordre de rabattre un taxi. Pour vérifier si l’algorithme permet d’atteindre les objectifs, un simulateur de données devra également être conçu. Une fois le prototype approuvé, ce dernier sera implémenté dans l’infrastructure informatique de l’entreprise. Selon nos recherches, un algorithme pour l’affectation de taxis avec ce niveau de complexité n’existe pas dans la littérature.

Voir la description complète du projet
Superviseur du corps professoral :

Jean-Francois Cordeau

Étudiant :

Partenaire :

Taxelco

Discipline :

Mathematics

Secteur :

Transportation and warehousing

Université :

HEC Montréal

Programme :

Accelerate

Capacity Building to Bolster Well-Being Among Early Childhood Educators and the Children they Support in Alberta

Well-being problems (e.g., burnout, depression, and efficacy) have been a long standing issue among educators in Early Learning and Care (ELC) settings. This issue not only impacts the health status and work performance among educators, and by association influences the social and emotional development of children. To address this problem, a coaching model has been adopted by Getting Ready for Inclusion Today (GRIT) to support educators in social and emotional teaching to children. The present research aims to examine whether coaching supports can 1) prevent burnout, depression and maintain a healthy work environment among early childhood educators; 2) improve the outcomes among the targeted children.

Voir la description complète du projet
Superviseur du corps professoral :

Veronica Smith

Étudiant :

Partenaire :

Getting Ready for Inclusion Today

Discipline :

Sociology

Secteur :

Education

Université :

University of Alberta

Programme :

Accelerate

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Mitacs — Retour sur innovation

Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.