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

Technology Acceleration of Selected Water Treatment Processes

Teck Resources Limited is exploring ways to improve water treatment efficiency as part of its commitment to responsible environmental practices. While various technologies are currently in the piloting stage there is no need to continue exploring potential treatment options for future implementation. The objective of this project is to generate technical and engineering information that will help determine whether the water treatment technologies developed by the University of Alberta have the potential to move into the engineering/scoping phase by the end of 2013 for possible field implementation. Students will have the opportunity to participate in an applied research environment on projects that could eventually be tested on pilot commercial scale.

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Superviseur du corps professoral :

Qingxia (Chad) Liu

Étudiant :

Partenaire :

Teck Metals Ltd (Trail, BC);Teck Ltd (Trail, BC)

Discipline :

Engineering

Secteur :

Mining

Université :

University of Alberta

Programme :

Accelerate

Application of Data Mining Methods for Detecting Irregularities in Securities Market

Current procedure for monitoring securities market in Canada relies heavily on tips from outside and hard coded rules and thresholds. This approach leaves many suspicious cases out of investigation (i.e. false negatives). We introduce a data mining approach to identify irregularities in securities market. These irregularities are known as suspicious cases that might be associated with fraudulent activities and need to be investigated by auditors. Developing such methods requires a deep understanding of strategies that investment componies employ. During this internship, Koosha will work on building strategies for investments in securities market at FreeThink Capital, a hedge fund based in Edmonton. FreeThink Capital uses statistical analysis to understand the market and build investment strategies. Koosha will focus on time series analysis methods to detect patterns in securities market. This internship provides him an understanding of investoors’ approach and various investment strategies in securities market.

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Superviseur du corps professoral :

Osmar Zaiane

Étudiant :

Partenaire :

First Canadian Financial Group

Discipline :

Computer science

Secteur :

Information and Communications Technology

Université :

University of Alberta

Programme :

Accelerate

New sensing appoach for illicit drugs by supramolecular chemosensors

The opioid crisis in North America lead to the emergence of illicit drugs sold on the streets that are mixed with „buffs“, thereby possessing additional harm. Fast, low-cost and reliable drug tests applicable by the layman could therefore reduce the danger associated with polluted opioids, but are not available so far. The Hof and the Biedermann groups have both developed different chemosensors, which are able to detect drug molecules with a fast read-out. The proposed project combines both chemosensor types to an array of supramolecular chemosensors that should establish the detection and identification of drugs and their ‘buffs’ from a complex mixture. The student will therefore synthesize a new chemosensor based on former work of the hosting group and combine these with existing chemosensors from the student’s home working group. This will explore fundamentally new science in the area of complex systems chemistry, and in the long term will help establish a cheap and accessible identification of complex mixtures of drugs.

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Superviseur du corps professoral :

Fraser Hof

Étudiant :

Partenaire :

Karlsruher Institut für Technologie

Discipline :

Physics

Secteur :

Education

Université :

University of Victoria

Programme :

Globalink Research Award

L’entrepreneuriat international féminin à l’ère du numérique

En se positionnant dans un contexte d’économie numérique, nous nous attachons au travers de ce projet de recherche à étudier le processus d’internationalisation des entreprises créées et dirigées par des femmes. En effet, nous nous apprêtons à identifier les spécificités de l’entrepreneuriat international féminin dans le domaine du numérique et de la digitalisation, à s’interroger sur les stimuli décisionnels de leur internationalisation et à comprendre le rôle de la dimension réticulaire et des liens sociaux dans le déploiement international des entreprises féminines naissantes. De surcroit, dans la logique de comparaison internationale, l’objectif de ce projet est également d’examiner les caractéristiques contextuelles et entrepreneuriales qui différencient l’entrepreneuriat international féminin et masculin dans les deux contextes étudiés, à savoir le Canada et le Maroc.

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Superviseur du corps professoral :

Maarouf Ramadan

Étudiant :

Partenaire :

Université Ibn Tofaïl

Discipline :

Sociology

Secteur :

Information and Communications Technology; Artificial Intelligence; Other

Université :

Université de Sherbrooke

Programme :

Globalink Research Award

Advanced Analytics and Fault Detection of Industrial Steam Traps via Machine Learning

Steam is flexible and very cost-effective in terms of gases that can be used to transfer heat. All steam systems require that the steam arrives at the right quantity, temperature, and pressure for it to work efficiently. The presence of foreign materials such as air, condensate, and other gases can lead to a reduction in this efficiency. To that end, steam traps are used to remove condensate, debris, and other gases from the steam system to maintain operating efficiency and prevent system damage. Due to constant operation, steam traps have a high failure rate of about 20%, according to the US State Department of Energy. Pulse Industrial’s steam trap sensor provides monitoring capabilities and early detection of these steam trap failures. This leads to vast improvements in the operating performance of partner facilities and reduced operating costs. This research project will optimize the analytics and diagnostics performance of currently deployed steam trap monitors. This optimization will be done by developing the AI model using collected data from partner plants. This will allow for a holistic improvement of the overall system, which is expected to increase the accuracy performance of the steam trap sensors

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Superviseur du corps professoral :

Xianke Lin

Étudiant :

Partenaire :

Pulse Industrial

Discipline :

Engineering

Secteur :

Manufacturing

Université :

University of Ontario Institute of Technology

Programme :

Accelerate

Improving the Efficiency in Customer Interactions and Investment Selection

The purpose of this research is to develop a solution that uses Artificial Intelligence and Predictive Analytics to Improving the Efficiency in Customer Interactions and Investment Selection.

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Superviseur du corps professoral :

Christian Jacob

Étudiant :

Partenaire :

Boast Capital

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Calgary

Programme :

Accelerate

Émulation d’une plateforme transactionnelle dans un marché local de l’énergie

Dans ce projet, nous proposons l’émulation d’une plateforme transactionnelle dans un marché local de l’énergie pour apprendre et tester les différents algorithmes et approches d’optimisation et de contrôle décentralisés sur les échanges entre les agents, comprendre les contraintes techniques et les bloqueurs, et définir les enjeux d’intégration des RED dans le réseau électrique. Dans un premier temps, l’approche multi-agents au niveau du client sera analysée et des stratégies et algorithmes pour la gestion transactionnelle seront proposés. Ensuite, ces algorithmes et stratégies seront étendus aux différents niveaux hiérarchiques du réseau depuis le client au poste de distribution. Dans cette hiérarchie, les contrôleurs des charges domestiques et des systèmes de chauffage constituent des agents de base et les gestionnaires

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Superviseur du corps professoral :

Kodjo Agbossou

Étudiant :

Partenaire :

Hydro-Quebec;Mitacs - Vancouver

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Utilities

Université :

Université du Québec à Trois-Rivières

Programme :

Accelerate

Innovative tools to improve knee health and predict an athlete’s risk of anterior cruciate ligament (ACL) injury

Anterior cruciate ligament (ACL) injuries are one of the most frequent injuries among athletes. Currently, the only way to predict an individual’s risk of incurring an ACL injury is through prohibitively expensive motion analysis laboratories. There is a critical need to develop novel tools that improve knee-health and are well-received by the athletic community.
This proposal will develop (1) a Kinect-ACL Injury Prediction System (K-AIPS-pro) for sports-medicine and orthopaedic clinics to: (i) score the risk of ACL and secondary injury; (ii) an athlete’s ability to return to play; and (iii) identify biomechanical features to promote knee-health using a personalized exercise plan, and (2) a Smartphone-Knee Improvement Performance System (SKIPS) for athletes. Through the integration of exercise videos and knee health tutorials, SKIPS represents a tool enabling athletes to take preventative measures to reduce their risk of ACL injury.

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Superviseur du corps professoral :

Paul Martineau

Étudiant :

Partenaire :

Emovi Inc

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Research Institute of the McGill University Health Centre

Programme :

Accelerate

Hydrologic regulating services of non-woody grassed and meadow urban landscapes

Due to urbanization in the GTA, many green areas are replaced by impervious infrastructure, preventing runoff infiltration and increasing flood risks. The Meadoway project proposed by the Toronto and Region Conservation Authority (TRCA) aims to restore meadow habitats with native plants along a hydro-corridor over 16 km across Scarborough, which can potentially improve the runoff retention and reduction capacity of the land due to the larger and longer roots, greater root density, and different evapotranspiration patterns of native plants compared with pre-restored turf and non-native cultural meadows. The proposed research will investigate the hydrologic response of meadows to storm events compared with turf lands, hardscaping, and potentially non- native cultural meadows. Laboratory rainfall simulation will be conducted upon intact soil columns collected from the field to mimic hydrologic process including rainfall, runoff, infiltration, and subsurface discharge. The results of the study can help TRCA develop plans for long-term assessment and aid the planning and management of future restoration project.

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Superviseur du corps professoral :

Jennifer Drake

Étudiant :

Partenaire :

Toronto and Region Conservation Authority (Vaughan, ON)

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Public administration

Université :

University of Toronto

Programme :

Accelerate

Development and Control of Smart End effector for Robot assisted Epidural Needle insertion

Epidural injection is a medical intervention to inject therapeutics directly at the vicinity of the spinal cord and the nerves branching from it. This procedure may be performed for regional anesthesia, e.g., for painless labour, or pain management, e.g., for persistent low back pain. For epidural injection, a long thin needle is inserted into the patient’s spinal cavities through the skin and underlying soft tissues. Accurate insertion of the needle is a precise task that unless performed correctly may result in irreversible damage to the nerves or spinal cord. In this project, a remote-controlled robotic system is proposed, developed, and tested for precise and safe robot-assisted epidural injection. With this technology, the physician uses a haptic interface to control the robot remotely. The robot follows the physician’s lead on needle insertion while monitoring the needle pressure and insertion depth for safety purposes. The robotic system also uses artificial intelligence to detect if the needle’s tip is inside the target area.

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Superviseur du corps professoral :

Jake E Barralet

Étudiant :

Partenaire :

Kinova Robotics

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Research Institute of the McGill University Health Centre

Programme :

Accelerate

Managing Shared State for Video Games in a Networked Multi-core Environment

Video Games require a vast array of different computations to present the desired experience. These computations must be completed consistently to make the software responsive to the user. The industry trend towards many separate processors (multi-core) in the same physical device and the emergence of network based ‘cloud’ computing have created many opportunities, but also many challenges for the game industry. The goal of this project is to create efficient techniques to organize and schedule the computations to take advantage of all the processors available. These techniques must ensure that the results produced correctly and are obtained quickly enough to satisfy responsiveness. Each of these techniques will have a corresponding aspect that allows them to be used by programmers who are not experts in utilizing multiple processors. While this project focuses on games, the benefits will be applicable to many domains, especially in the emerging field of mobile consumer-oriented applications.

Voir la description complète du projet
Superviseur du corps professoral :

Alexandra Fedorova

Étudiant :

Partenaire :

Gaslamp Games

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Simon Fraser University

Programme :

Accelerate

Coveo : Algorithmes de recommandation

Ce projet s’inscrit dans la grande famille des projets de systèmes de recommandation, où un algorithme doit recommander aux utilisateurs des produits ou des documents qui seraient intéressants pour eux, basé sur ce que nous connaissons de l’utilisateur et sur sa session de recherche actuelle. Coveo a déjà des modèles de recommandation en place, dans le domaine du service et le domaine du commerce en ligne. Le stage a pour objectif de collaborer avec l’équipe de d’apprentissage automatique pour améliorer la qualité des modèles en place et explorer de nouvelles idées qui permettraient de résoudre de nouvelles problématiques provenant de nos clients. Durant ce projet, le commerce électronique sera le principal sujet, sans y être strictement limité.

Voir la description complète du projet
Superviseur du corps professoral :

Christian Gagné;Audrey Durand

Étudiant :

Partenaire :

Coveo Solutions Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

Université Laval

Programme :

Accelerate

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