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

Interactive preference elicitation application for book recommendations

Kobo is an online e-book retailer that provides recommendations for future purchases to its user base. One difficulty that recommendation systems face is what is known as the “cold-user” problem. In this scenario, when we know so little of a user’s preferences (for example, if they are new to the platform), we do not have any basis for recommendations. The goal of this project is to develop an interactive application that can elicit such preferences from users about whom we have little information, and that can help improve recommendations for power users. For new users, the preference elicitation process during onboarding can help them find books of interest much faster; for established users, it gives them the ability to refine their recommendations. Such improvements facilitate a more streamlined discovery experience.

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Superviseur du corps professoral :

Scott Sanner

Étudiant :

Partenaire :

Rakuten Kobo Inc.

Discipline :

Computer science

Secteur :

Information and Communications Technology; Entertainment and Media

Université :

University of Toronto

Programme :

Accelerate

Évaluation préliminaire des scénarios de restauration du parc principal à résidus minier de la mine LaRonde

Une grande partie des rejets produits par l’industrie minière est souvent entreposée en surface. En contact avec l’oxygène atmosphérique et l’eau, les minéraux sulfureux contenus dans ces rejets s’oxydent et génèrent un drainage minier acide (DMA) comportant des contaminants préjudiciables pour l’environnement. Une des techniques utilisées pour contrôler ce phénomène est les recouvrements à plusieurs couches. Ces couvertures sont habituellement constituées des matériaux meubles d’origine naturelle. Ces derniers ne sont pas dans tous les cas, en quantité et qualité utiles localisés à proximité des sites à restaurer. Notre projet de stage à la mine LaRonde (Québec, Canada) a pour objectif d’évalue de façon préliminaire, à partir de parcelles expérimentales, la possibilité d’utiliser que des matériaux miniers dans de tels couvertures. TO BE CONT’D

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Superviseur du corps professoral :

Bruno Bussière;Isabelle Demers

Étudiant :

Partenaire :

Agnico Eagle Mines Limited

Discipline :

Earth science

Secteur :

Mining; Natural Resources; Sustainability & the Environment

Université :

Université du Québec en Abitibi-Témiscamingue

Programme :

Accelerate

Analysis of TGF-? traps as effective immunostimulating cancer treatments

AVID200 is a TGF-? trap that specifically sequesters TGF-?I and TGF-?III to enhance antitumour immunity to inhibit tumor growth. AVID200 also avoids adverse side effect of depleted of TGF-?II. AVID200 is relatively short-lived in circulation, decreasing its capacity to exert desirable enhancement of anti-tumour immunity. To increase the effectiveness of TGF-? traps, a panel of candidate molecules that retain TGF-? isoform specificity and inactivating capacity, but with projected increased stability, have been generated by Formation Biologics. To support an investigational new drug (IND) application, mouse models of breast, melanoma and ovarian cancers will be treated with these TGF-? traps. Their effect on the immune system and tumor inhibition will be determined both as single agents and in combination with immune stimulating drugs. These experiments will provide preclinical evidence of the effectiveness of candidate TGF-? inhibitors on mouse models of cancer in preparation for an IND application and clinical trials.

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Superviseur du corps professoral :

James Koropatnick

Étudiant :

Partenaire :

Formation Biologics Inc

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Western University

Programme :

Accelerate

Development and Demonstration Engine Technology for Class 8 Heavy Duty Trucks Fueled by Waste Hydrogen

Hydra Energy Corporation Commercial Demonstration Project will be based in Prince George, British Columbia 12.4 MT/day of waste hydrogen will be captured, purified and transported to an onsite hydrogen refueling station from which (at least) 53 Class 8 tractor-trailer trucks will refuel daily. Hydra’s demonstration project can provide a significant reduction in fleet greenhouse gas(GHG) emissions, Particulate Matter and other air emissions. Hydra is currently testing the first prototype dual-fuel hydrogen/diesel heavy-duty class 8 truck in North America. And, in collaboration with the University of British Columbia (UBC) is conducting thorough experimental investigation of the potential fuel efficiency improvements and emissions reductions that may be realized by fueling an internal combustion engine with hydrogen and diesel fuel at various. The R&D project results will advance the scientific knowledge of hydrogen in internal combustion engines, and will help to expand the availability of clean energy transportation technologies in and beyond B.C.

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Superviseur du corps professoral :

Steven Rogak;Patrick Kirchen

Étudiant :

Partenaire :

Hydra Energy Corporation

Discipline :

Engineering

Secteur :

Manufacturing; Transportation and warehousing; Utilities

Université :

The University of British Columbia

Programme :

Accelerate

Prediction Improvement on User’s Consumption

The goal of the research is to implement different data mining algorithms in order to improve the prediction on a user’s electricity consumption. The research will be dedicated to improve the existing algorithms or implementing new algorithms for the improvement of the prediction accuracy. Besides application of the prediction algorithms, different data pre-processing methods will be used. Research will include supervised and unsupervised modelling of the dataset by using the R programming language. As well, the segmentation of the customers based on the similarity measures in order to increase the prediction accuracy will be investigated. This research will lead to the improvement of the prediction accuracy which will bring more customers to the company as well as help the existing customers to save more energy, therefore more money.

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Superviseur du corps professoral :

Sabine McConnell

Étudiant :

Partenaire :

Lowfoot Inc

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Trent University

Programme :

Accelerate

Applied Machine Learning for Malware and Network Intrusion Detection

Wedge Networks is a leading cybersecurity solution provider in Canada. In this project, we aim to investigate the application of statistical machine learning and deep learning to cyber threat detection, aiming to detect both network intrusions and malware binaries transmitted in the network. Based on the big data collected from Wedge’s system logs and anonymized domain-specific data gathered from the clients of Wedge Networks distributed worldwide, we will investigate: 1) Distributed Denial-of-Service prevention and network intrusion detection based on both supervised and unsupervised machine learning techniques, and 2) shallow and deep neural network models for malware detection and prevention. To scale up to the big data at Wedge Networks, we will implement the developed machine learning and deep learning algorithms on distributed processing platforms such as Spark and TensorFlow. We will also integrate the learning-based threat detection module in the WedgeARP product line.

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Superviseur du corps professoral :

Di Niu

Étudiant :

Partenaire :

Wedge Networks Inc

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

University of Alberta

Programme :

Accelerate

Resource potential of the Post Creek Property, Sudbury, Ontario

Sudbury represents the site of a meteorite impact structure originally greater than 200 km in diameter and that formed 1.85 billion years ago. Despite the proven and potential economic benefits of resource development at Sudbury, there are still major outstanding questions concerning our understanding of the structure and its ore deposits. A series of objectives have been composed concerning the origin of Sudbury Breccia, host to footwall vein deposits, and Offset Dykes at the Post Creek locality and their mineralization. Fieldwork forms the basis for this proposed research, coupled with sample investigation using a range of micro-analytical techniques. The results of the proposed research will address significant gaps in our current knowledge of the origin and emplacement of Offset Dykes and Sudbury Breccia and will enable the resource potential of the Post Creek Property to be determined.

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Superviseur du corps professoral :

Gordon Osinski

Étudiant :

Partenaire :

North American Nickel Inc

Discipline :

Earth science

Secteur :

Mining

Université :

Western University

Programme :

Accelerate

A decision support framework for optimizing tube utilization in laboratory tests

In this project, the intern will design a decision support framework for optimizing tube utilization in laboratory tests. Given a prescription, the framework automates the tube selection process and outputs low cost tube configurations. The framework is designed to be easily adapted to different lab configurations. It consists of three processes, namely data profile configuration, tube optimization and solution prioritization. Data profile configuration process will formulate code and machine configuration files as the inputs to the tube optimization process. Solutions generated by tube optimization will then be evaluated by the solution prioritization process based on business and operational rules and preferences. Once integrated with mobile devices, users can obtain the optimized tube configuration in a real time manner by a simple scanning on the prescription. The proposed framework optimizes the tube utilization, reduces the cost throughout the whole laboratory testing process and saves time for agency, nurses and patients.

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Superviseur du corps professoral :

Chun Wang

Étudiant :

Partenaire :

Medialpha Laboratories Inc

Discipline :

Engineering

Secteur :

Health and Related Sciences & Technology; Commercial Services; Information and Communications Technology

Université :

Concordia University

Programme :

Accelerate

Habitudes d’utilisation de thermostats à tension de secteur

Les thermostats à tension de secteur pilotent le plus grand poste de consommation énergétique des résidences chauffées par plinthes électriques. Jusqu’à maintenant, les habitudes d’utilisation de ces thermostats par les occupants des résidences étaient obtenues par sondage, ce qui limite la quantité et la qualité de l’information récoltée. Le stage vise à traiter les données de thermostats communicants obtenues dans le cadre d’un projet pilote couvrant la plupart des pièces de trente résidences. Le stage permettra d’établir comment les occupants utilisent les thermostats, comment cette utilisation varie d’une pièce à l’autre et d’une résidence à l’autre; le tout avec un niveau de détail inégalé. Ces nouvelles connaissances permettront d’améliorer le réalisme des simulations énergétiques et possiblement d’identifier de nouvelles opportunités de gestion de la consommation associées au chauffage par plinthes électriques.

Voir la description complète du projet
Superviseur du corps professoral :

Sousso Kelouwani

Étudiant :

Partenaire :

Institut de Recherche Hydro-Québec

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Utilities

Université :

Université du Québec à Trois-Rivières

Programme :

Accelerate

Les indicateurs de performance de l’Industrie 4.0 : une étude empirique auprès d’entreprises manufacturières québécoises

Lorsqu’une entreprise investit de larges sommes d’argent dans une technologie, elle espère en tirer des bénéfices : diminution de ses coûts d’opérations, amélioration de la relation client, amélioration de la qualité des produits, etc. Ces faits sont mesurés à l’aide d’indicateurs de performance. Chaque entreprise est libre de choisir les indicateurs qu’elle souhaite suivre, mais certains sont traités comme étant universels et peuvent être utilisés dans la comparaison entre les entreprises dans un secteur donné. Cette étude cherche à déterminer le caractère universel des indicateurs de performance couramment cités dans les études scientifiques en intelligence d’affaires manufacturières, et particulièrement dans le cadre des projets liés à l’Industrie 4.0. Sont-ils vraiment répandus dans les entreprises québécoises ? Leur utilisation contribue-t-elle à l’amélioration des performances de l’entreprise ? Nous tenterons d’apporter des réponses à ces questions.

Voir la description complète du projet
Superviseur du corps professoral :

Elaine Mosconi;Luis Antonio De Santa Eulalia

Étudiant :

Partenaire :

Productique Québec Inc.

Discipline :

Business

Secteur :

Information and Communications Technology; Manufacturing and Construction

Université :

Université de Sherbrooke

Programme :

Accelerate

Ignition control on DME/OME engines

Considering the soot-free burning characteristics of DME/OME fuel, highly diluted intake charge can be introduced in order to realize ultra-low nitrogen oxides emissions. However, the ignition process of the highly diluted fuel/air mixture is difficult, and an unstable ignition process is detrimental to fuel efficiency and engine performance. In this project, innovative ignition systems including a multi-site ignition system. and volumetric ignition system, together with novel ignition strategies will be developed. A high pressure optical combustion vessel will be used to investigate the ignition mechanism of DMEIOME fuel, while engine experiments will also be carried out to study the effect of ignition strategies on engine performance. The ignition control study is critical to improve engine efficiency and robustness while maintaining ultra-low nitrogen oxides and soot. The proposed outcome will have the potential to be used in or integrated into Ford vehicles to promote more efficient combustion.

Voir la description complète du projet
Superviseur du corps professoral :

Ming Zheng

Étudiant :

Partenaire :

Ford Motor Company

Discipline :

Engineering

Secteur :

Manufacturing; Professional, scientific and technical services

Université :

University of Windsor

Programme :

Accelerate

Investment portfolio design and optimal execution of automated trading strategies: An exploratory research program

Non-parametric models such as supervised and unsupervised machine learning algorithms seem to be an interesting choice when trying to extract decision-making signals out of this ever-increasing volume of information. These models have been used extensively in the last decades and are now more relevant than ever thanks to the development of new techniques in artificial intelligence and increasing power and scalability of numerical computations. In this project, we set to explore the direct application of such methods and mathematical technology in the design and testing of algorithmic trading strategies and portfolio selection and optimization. This exploratory research program seeks to gain first-hand insight as to the challenges in data collection and curation that is required as well as delivering the enhanced strategies and portfolios resulting from such implementations.

Voir la description complète du projet
Superviseur du corps professoral :

Manuel Morales;Alejandro Murua;Mohamed Tarik Moutacalli;Jia Yuan Yu;Erick Delage;Christian Dorion;Frédéric Godin

Étudiant :

Partenaire :

Golden Square Mile Asset Management;Quantolio Financial Technologies Inc

Discipline :

Mathematics

Secteur :

Professional, scientific and technical services

Université :

Concordia University; HEC Montréal; Université de Montréal; Université du Québec à Rimouski

Programme :

Accelerate

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