Projets novateurs réalisés

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

29 670 projets achevés

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4990
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801
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663
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825
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95
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568
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Projets par catégorie

Hyperspectral image analysis of skin erythema after radiation therapy

Acute skin erythema is a common side effect with patients undergoing radiotherapy treatment. It displays itself as an increase in skin redness and irritation. Erythema has been reported to correlate to individual patient response to radiation and therefore may be useful to guide and modify courses of treatment in a timely manner. Currently, upon visual examination, a qualitative score can be assigned to characterize the severity of erythema, which then may be used for assessing radiation response. As this clinical assessment is not a quantitative measure and in fact is a highly subjective one, we aim to develop an alternative objective measure to accurately quantify skin erythema. This project is aimed to use data from a new hyperspectral imaging technology developed at McMaster University in Canada and to propose relevant image analysis algorithms that can precisely quantify skin erythema and objectively correlate this phenomenon to
radiation response.

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Superviseur du corps professoral :

Mark Drew

Étudiant :

Partenaire :

Inria Sophia Antipolis - Méditerranée Research Centre

Discipline :

Engineering

Secteur :

Education

Université :

Simon Fraser University

Programme :

Globalink Research Award

Task-optimized parallel manipulators

This research focuses on the optimization of parallel mechanisms, a specific class of robotic mechanisms, such that an optimal design guarantees that a desired task, having certain requirements, is able to be completed by the mechanism. The Inria Sophia Antipolis Coprin
project (now the Hephaistos project) have worked on the development of interval analysis algebraic geometry tools. These tools greatly extend the possibilities of improving both the analysis and optimization algorithms used in this research, providing guaranteed results. The
application of such tools is very exciting since it may be possible to verify that a resulting design is indeed optimal. The outcome from this research project will be the development of a set of interval-based algorithms for the optimal determination of a parallel mechanism for a
desired task.

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Superviseur du corps professoral :

Juan Carretero

Étudiant :

Partenaire :

Inria Sophia Antipolis - Méditerranée Research Centre

Discipline :

Engineering

Secteur :

Education

Université :

University of New Brunswick

Programme :

Globalink Research Award

Designing Interaction for Token Based Physical Visualizations

This project explores the design of different manual and semi-automatic instruments to support interaction with token-based physical data visualizations (or physicalizations). The recent advance in digital fabrication has made data physicalization – encoding data in the geometry or material properties of a physical artifact – a growing research interest in the information visualization community. However, interaction with data physicalizations still remains a challenge and most existing examples to date remain static. The objective of this project is the
development of several instruments that facilitate the interaction with token-based physicalizations and evaluate their effectiveness. We will further explore which material and physical properties (e.g. weight, friction, form, size) can be used to represent data and support
interaction with the instruments we develop. Our hypothesis is that the use of manual and semiautomatic tools can improve the efficiency of interacting with token-based physicalizations and support standard data operations (e.g. selection, filtering, and aggregation).

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Superviseur du corps professoral :

Sheelagh Carpendale

Étudiant :

Partenaire :

Inria Saclay - Île-de-France Research Centre

Discipline :

Computer science

Secteur :

Université :

University of Calgary

Programme :

Globalink Research Award

Human Performance of Finger Identification for Multitouch Input

The project first aims at developing a robust and low latency hardware system for identifying which fingers are in contact with a surface. The second objective is to implement and refine finger identification interaction techniques that would improve the interaction with touch surfaces
(smart phone, tablets, tabletops). These techniques will be evaluated to state of the art interaction techniques in controlled experiments. The expected outcomes are the development of the most robust and low latency finger identification prototype to date. This prototype will
allow running the first studies for measuring the quantitative and qualitative benefits of this rich information input space.

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Superviseur du corps professoral :

Daniel Vogel

Étudiant :

Partenaire :

Inria Lille - Nord Europe Research Centre

Discipline :

Computer science

Secteur :

Université :

University of Waterloo

Programme :

Globalink Research Award

Multivariate polynomial interpolation: efficient algorithms and applications

This research project aims at providing efficient methods to solve a mathematical problem which has practical applications in digital communication and online storage. In the domain of communications, these methods perform the decoding stage of some error-correcting codes, which are used to ensure reliable data transmission over an unreliable or noisy communication channel such as in Digital Video Broadcasting (digital television), or when reading Blu-Ray discs or bar codes. Concerning storage, the methods are used in private information retrieval, which refers to techniques that allow the user to retrieve information from an online database without letting the server know the keywords that were used to search for this information; this has applications such as anonymous email, or domain name registration. With the steady growth of the size of the manipulated data, conceiving efficient methods for such practical problems becomes crucial; it requires both a thorough theoretical study, which is already partially done in our case, and a careful implementation relying on state-of-the-art building blocks for its most basic components.

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Superviseur du corps professoral :

Éric Schost

Étudiant :

Partenaire :

Inria Grenoble - Rhône-Alpes Research Centre

Discipline :

Computer science

Secteur :

Université :

University of Waterloo

Programme :

Globalink Research Award

Spatial Optimization Modelling for China’s County-level Land Use Planning

Considering the research gap that there lack quantitative models and advanced techniques to solve the land spatial allocation problem in China’s county-level, my PhD project aims at developing spatial optimization models to assist land spatial allocation that reconciles the market value, social value and ecological value of land, land utilization zoning and boundary setting in constructive expansion regulation zoning for China’s county-level land use planning. The field work in Wuhan, China will finish the data collection, database establishment, personal interview and land suitability evaluation work for the project. The expected outcomes for the work in China include: (1) Build GIS Geodatabase of land use and environmental data for the study area; (2) generate land suitability map for land utilization zoning and land suitability map for agricultural utilization in the GIS raster format for the study area.

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Superviseur du corps professoral :

DongMei Chen

Étudiant :

Partenaire :

University of Chinese Academy ofSciences (Institute of Geodesy and Geophysics)

Discipline :

Sociology

Secteur :

Université :

Queen's University

Programme :

Globalink Research Award

Liver cancer detection using recent advances in deep learning

Approximately half of today’s population will be affected by cancer during its lifetime. Knowing that the earlier cancer is detected, the better the life expectancy, accurate radiological detection can make the difference between life and death. Primary liver tumor, known as hepatocellular carcinoma (HCC), and secondary liver tumor (metastasis) represent, in aggregate, the second most common cause of cancer-related mortality in North America. Existing Computed Assisted Diagnosis (CADx) software use traditional image analysis techniques and as such their applications are mainly oriented towards type of cancer that show specific imaging characteristics (e.g. lung nodules, colon polyps and breast micro calcifications). The goal of this project is to innovate in the field of automatic medical image analysis by using the latest developments in artificial intelligence, computer vision and machine learning. Using readily-available data of sufficient quantity from the liver through extensive datasets hand-segmented, we plan to develop a framework that will detect and segment tumors in a liver segmented from CT and MRI images. This approach opens new prospects for medical imaging applications, by proposing of models that exhibit high accuracy with minimal human intervention, broadening their use and ultimately leading to improved patient care.

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Superviseur du corps professoral :

Samuel Kadoury;An Tang;Christopher Pal

Étudiant :

Partenaire :

Imagia;ApSTAT Technologies Inc;Global Imaging On Line

Discipline :

Engineering

Secteur :

Health and Related Sciences & Technology; Other; Information and Communications Technology

Université :

École Polytechnique de Montréal; Polytechnique Montréal; Université de Montréal

Programme :

Accelerate

Development of court booking module and algorithm

OrbitHub is a web/mobile platform that helps its clients coordinate activities more efficiently and maximize the utilization of their resources and time. In addition to being a global social network, OrbitHub also offers tournament, league and ladder management functionality, as well as registrations, payments, rankings, court booking and more. This project aims to focus on leveraging the global social network data and geo data to efficiently link up similar-skilled sport players with under-utilized facilities so that players have a chance to play more while clubs/facilities can maximize their facilities’ usage.

Voir la description complète du projet
Superviseur du corps professoral :

Daniel Amyot

Étudiant :

Partenaire :

OrbitHub Inc

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Ottawa

Programme :

Accelerate

An analysis of aural and visual cross-modal recognition of paths of moving sources for authoring and editing trajectories in 3D audio composition and production.

Current advanced audio playback systems can provide a feeling of 3D immersion to listeners. Though the technology to listen to 3D audio can provide a good listening experience, the technology used to create 3D audio content has not adapted to those advances. One major reason is due to human aural localization ability that is not as accurate as the visual localization ability, making it difficult for users to create a 3D experience because common authoring tools use visualizations to interact with. The proposed research project is to study how the 3D audio systems affect listeners’ ability to track moving sounds by examining the association of visual representations to different paths of moving sounds. We expect to have measurable discrepancies between the visual representation and the path of the moving sound in our findings that will be used to design and evaluate new input methods for creating 3D audio content.

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Superviseur du corps professoral :

Catherine Guastavino

Étudiant :

Partenaire :

Inria Lille - Nord Europe Research Centre

Discipline :

Computer science

Secteur :

Université :

McGill University

Programme :

Globalink Research Award

optimization of Software Systems driven by the Wisdom of Crowds

The popularity of smartphones is leading to an ever growing number of mobile apps that are published in official app stores. However, users might experience failures and crashes for some apps installed on their devices. For developers, diagnosing failures that users experience is a major challenge, since the diversity of contextual conditions makes it difficult to reproduce unexpected behaviors that emerge in the field. This project aims to drastically improve the quality of mobile apps by assisting developers to reproduce failures, based on the experience faced by a multitude of individuals.

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Superviseur du corps professoral :

Bram Adams

Étudiant :

Partenaire :

Inria Lille - Nord Europe Research Centre

Discipline :

Computer science

Secteur :

Université :

École Polytechnique de Montréal

Programme :

Globalink Research Award

Combining Structural and Behavioural Modelling of Software Product Lines

Embedded Software is designed to work with and control physical systems such as car brakes. These systems come in many configurations and the software embedded on them also has to be configured for each one. Software product lining is a methodology to develop a family of related systems that can be configured for each product, reducing development costs and reusing common parts. Our research will explore ways to model quality attributes, such as response time or cost, of different products and will provide tools to consider those attributes when designing or using a software product line.

Voir la description complète du projet
Superviseur du corps professoral :

Joanne Atlee

Étudiant :

Partenaire :

Inria Rennes - Bretagne Atlantique Research Centre

Discipline :

Computer science

Secteur :

Université :

University of Waterloo

Programme :

Globalink Research Award

Implementing a Sustainability Toolkit

The Sustainability Toolkit has been developed to address the lack of available practical guidance on how to implement sustainability in an organization. In essence, the Toolkit integrates globallyrecognized approaches to sustainability and systems-based management (ISO 14001, OHSAS 18001, and ISO 26000). The basis for the system-based approach is the Plans-Do-Check-Act (PDCA) process which breaks down initiatives into smaller manageable steps and leads to continual improvement. By integrating a management system framework into the social responsibility guidance defined by ISO 26000, the Toolkit is a practical and flexible approach to sustainability implementation that is applicable to all sizes of organizations across various industry sectors. This project will validate the tool by testing the 13-step approach to sustainability integration within SMEs across various sectors.

Voir la description complète du projet
Superviseur du corps professoral :

Ian Colquhoun

Étudiant :

Partenaire :

Tavares Group Consulting Inc

Discipline :

Earth science

Secteur :

Professional, scientific and technical services

Université :

Western University

Programme :

Accelerate

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