Projets novateurs réalisés

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

30156 projets achevés

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Projets par catégorie

A systems biology approach to investigate chemoresistance in urothelial carcinoma of the bladder.

To perform a complete molecular analysis of muscle invasive bladder cancer (MIBC) before and after pre-operative chemotherapy to find changes responsible for resistance to treatment. Analysis will include a combination of DNA sequencing, RNA expression analysis and quantification of protein. Together this information will reveal the molecular landscape for these tumors. We will use these complex datasets to address two specific comparisons: 1) chemotherapy responders versus chemotherapy non-responders (defined by extent of tumor remaining in bladder after chemotherapy); and, 2) tissue before and after pre-operative chemotherapy in non-responders, in order to assess for enriched molecular pathways that are indicative of resistance. Specific computer tools will be used to test the biologic functional of the changes described. The proposed methods include protein-protein interactions, gene-regulatory network and pathway-enrichment analysis. Novel analytic algorithms will also be developed to benefit the partner organization for day-to-day processing of clinical data.

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Superviseur du corps professoral :

Peter Black

Étudiant :

Partenaire :

GenomeDx Biosciences Inc

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

The University of British Columbia

Programme :

Elevate

MiX – Motion Capture in XNA

XNA (Xbox New Architecture) allows independent game/digital-media content developers to build, deploy, and publish games on the Xbox360 and PC platforms. The technical objective of this project is to bridge Vicon MOCAP technology with XNA to allow for Real Time Visualization of Motion Capture data on the PC and Xbox360 platforms using XNA.The Vicon Real-time Engine processes motion capture data in real-time allowing you to stream to your preferred viewing software. Directors can then, with the help of MiX (Motion Capture in XNA) map the motion capture data to the character(s) or objects producing a real-time visualization of the motion capture session. Real-time motion capture visualizations, increase Director efficiency, provide immediate Actor feedback, and reduce expensive pick-ups or recapture sessions.

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Superviseur du corps professoral :

Maria Lantin

Étudiant :

Partenaire :

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Emily Carr University of Art + Design - Main Campus

Programme :

Accelerate

Ciena Environment for Network Innovation (CENI)

The NSERC Strategic Network for Smart Applications on Virtual Infrastructures is a five-year partnership between Canadian industry, universities, researchers, research and education (R&E) networks, and high performance computing centres to investigate the design of future application platforms that will deliver software applications of greater capability and intelligence. These application platforms will be supported by an extended computing cloud, encompassing a virtual converged infrastructure and control software that also serves as a live testbed for exploring novel concepts in application-oriented networking, cloud computing, integrated wired/wireless access, and smart applications. Novel software applications will build on advanced services provided by the platform, including context, mobility, location, identity, social network, media recognition, and intelligence. The SAVI network will involve the academic community in the creation of new content and novel applications.
This MITACS proposal is to support a SAVI internship program that will strengthen the Canadian industrial base in information and communications technology through the preparation of highly qualified manpower with expertise in the design and operation of globally competitive ICT infrastructure and the creation of innovative and disruptive products, services, and applications. TO BE CONT’D

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Superviseur du corps professoral :

Alberto Leon-Garcia

Étudiant :

Partenaire :

Ciena Corporation (Ottawa, ON)

Discipline :

Engineering

Secteur :

Information and Communications Technology; Technology

Université :

University of Toronto

Programme :

Accelerate

Genetic evaluation of sow efficiency traits using single step genomic evaluation methods – Year 2

Most economically important traits associated with lactation and reproduction in pigs are either less heritable, sex-limited, expressed later in life, or difficult to measure on a routine basis. Genomic predictions using single step best linear unbiased prediction (SSBLUP) methodologies, which utilizes information on phenotypes, pedigree and markers from genotyped and non-genotyped animals simultaneously, is an alternative to phenotype and pedigree based (BLUP) methods. The goal of this project is to develop genome enhanced estimated breeding values (EBVs) for sow reproductive traits using single step methodologies. The objectives are to 1) develop single step EBVs for sow traits associated with lactation and reproduction 2) to estimate the accuracies of prediction using SSBLUP and compare it with the pedigree based estimates and 3) to incorporate single step methodologies into routine genetic evaluations. The overall outcome is to demonstrate and integrate SSBLUP genomic selection methodologies to improve key economic reproductive traits.

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Superviseur du corps professoral :

Graham Plastow

Étudiant :

Partenaire :

Genesus Genetic Technology Inc.

Discipline :

Life Sciences

Secteur :

Agriculture and Food; Biotechnology; Life Sciences (not health)

Université :

University of Alberta

Programme :

Elevate

Genetic evaluation of sow efficiency traits using single step genomic evaluation methods

Most economically important traits associated with lactation and reproduction in pigs are either less heritable, sex-limited, expressed later in life, or difficult to measure on a routine basis. Genomic predictions using single step best linear unbiased prediction (SSBLUP) methodologies, which utilizes information on phenotypes, pedigree and markers from genotyped and non-genotyped animals simultaneously, is an alternative to phenotype and pedigree based (BLUP) methods. The goal of this project is to develop genome enhanced estimated breeding values (EBVs) for sow reproductive traits using single step methodologies. The objectives are to 1) develop single step EBVs for sow traits associated with lactation and reproduction 2) to estimate the accuracies of prediction using SSBLUP and compare it with the pedigree based estimates and 3) to incorporate single step methodologies into routine genetic evaluations. The overall outcome is to demonstrate and integrate SSBLUP genomic selection methodologies to improve key economic reproductive traits.

Voir la description complète du projet
Superviseur du corps professoral :

Graham Plastow

Étudiant :

Partenaire :

Genesus Genetic Technology Inc.

Discipline :

Life Sciences

Secteur :

Agriculture and Food; Biotechnology; Life Sciences (not health)

Université :

University of Alberta

Programme :

Elevate

Fast and robust real-time precise point positioning – 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 :

Xin Wang

Étudiant :

Partenaire :

Profound Positioning Inc

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Calgary

Programme :

Elevate

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.

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

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.

Voir la description complète du projet
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

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