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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801
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568
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Projets par catégorie

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.

Voir la description complète du projet
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.

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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.

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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

Mapping issues and stakeholders related to the development of Canada’s restoration plan for the Great Lakes and St. Lawrence Basin

The Great Lakes St Lawrence (GLSL) Basin is central to Canada’s economy and culture, and a primary water source. Several stressors are deteriorating these critical ecosystems.
This proposed project aims to lay the foundations for efforts to improve coordination related to the restoration of the GLSL region. The proposed project consists of mapping stakeholders, issues, and existing initiatives and infrastructure regarding the Canadian side of the GLSL restoration plan. This includes the systematic identification of stakeholders (e.g., First Nations, public policy-makers, private and business organizations, civil society organizations) and analysis of their current initiatives, issues and concerns, as well as the mapping of their interdependencies. Building on these initiatives, infrastructures, and interdependencies, this project will contribute to the establishment of a collaborative framework to develop a restauration plan for the GLSL.

Voir la description complète du projet
Superviseur du corps professoral :

Emmanuel Raufflet

Étudiant :

Partenaire :

De Gaspé Beaubien Foundation

Discipline :

Business

Secteur :

Other services (except public administration)

Université :

HEC Montréal

Programme :

Accelerate

Sentiment Analysis with Parsed Representation of News Articles

Information published by financial news agencies is used as one of the inputs to make investment decisions. News articles from multiple sources can be used to gauge market sentiment towards an industry or a specific company. Deep learning techniques have been successful in producing state of the art results on various benchmark datasets (Dai & Le, 2015; Miyato et al., 2016). Most of the popular algorithms extract features from words, sentences or paragraphs and represent them as fixed-length vectors (Mikolov et al., 2013; Le & Mikolov, 2014). We propose the use of parsed representations of text along with fixed-length feature vectors as input for recurrent neural networks. The performance of these models will be evaluated on sentiment analysis tasks.

Voir la description complète du projet
Superviseur du corps professoral :

Graham Taylor

Étudiant :

Partenaire :

RBC Royal Bank (Toronto, ON)

Discipline :

Engineering

Secteur :

Finance and Insurance; Management of companies and enterprises

Université :

University of Guelph

Programme :

Accelerate

Interaction of Cyclin-dependent kinase 2 with CR6-interacting factor 1, and the inhibitor search for such interaction against leukemia treatment resistance

Cyclin-dependent kinase-2 (CDK2) regulates cell cycle, whose structure and biological characteristics are well known. CRIF1 plays a regulatory role in the bone marrow microenvironment-induced leukemia cell cycle arrest through inhibiting CDK2. In this multi-disciplinary research, we will use a combined structure function study to reveal the interaction between CDK2 and CRIF1. This will facilitate the design of inhibitors for the interaction of the two important proteins, for eventual treatment of leukemia.

Voir la description complète du projet
Superviseur du corps professoral :

Sheng-Xiang Lin

Étudiant :

Partenaire :

JingYinJi Medical Inspection Inc;Pyrovac Inc

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

Université Laval

Programme :

Accelerate

Validation of an innovative industrial process for the pre-treatment of hay in controlling inflammation and respiratory obstruction associated with Severe Equine Asthma (SEA)

Severe Equine Asthma (or “heaves”) is the most common respiratory disorder affecting horses in stables, and impacts an estimated ~15% of the equine population in the northern hemisphere. Heaves is a chronic condition for which there is currently no cure, and its symptoms are quite dramatic causing severe breathing difficulty for affected horses, making it impossible for owners to ride or work with them. As a result, heaves has an important economic impact as it very often leads to euthanasia of affected horses. In the short-term, the symptoms of heaves can be effectively managed with drug treatments, however these drugs are not viable as a long-term treatment option due to their risk of adverse effects, as well as their high costs. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Jean-Pierre Lavoie

Étudiant :

Partenaire :

Nutri-Foin Système

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Accelerate

Cocktails of Different Populations of Genetically Modified Human Umbilical Cord Perivascular Cells for Bone Regeneration

The loss of bone is a massive burden on the health care system and severely impacts the quality of life of several hundred million people. The need for alternative strategies to replace or regenerate bone tissue is overwhelming. We are proposing a completely new approach to the engineering of bone using a ?cocktail? of genetically modified human umbilical cord perivascular cells (HUCPVCs) that can be produced in vast numbers, stored in liquid nitrogen so that they could be ready for therapeutic purposes. The HUCPVC technology is represents the core IP of our industrial partner, Tissue Regeneration Therapeutics Inc. The intern will conduct experiments to test the effects of varying the percentages of different cells within the cocktails; generate quantitative data concerning the absolute amount of secreted protein; and assess the bioactivity of the released protein. Tissue engineering and ex-vivo gene therapy can be used synergically as a tool to …

Voir la description complète du projet
Superviseur du corps professoral :

Bernhard Ganss

Étudiant :

Partenaire :

Tissue Regeneration Therapeutics Inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

The viscous disk model for 66 Ophiuchi constrained by spec

My project focuses on a particular kind of massive star that are surrounded by disks called B-emission (Be) stars. These objects
are ideal laboratories for studying disks. Massive stars can spew out a thousand times more energy per second than our Sun and
because the disk is formed from gas launched from the star, they are not shrouded in dust like star forming regions where we find
disks. They are also numerous – hundreds of Be stars exist right in our own galaxy!
Despite decades of study we still don’t know why the disk forms and this is the major puzzle in this field of research. The rapid
rotation of the star certainly helps to propel material off the surface into the disk but we don’t think that this quick rotation provides
enough of a kick. Something else must help to eject the material – perhaps gravity from an orbiting star, a wave or pulsation on
the stellar surface or a push from the stellar radiation. TO BE CONT.

Voir la description complète du projet
Superviseur du corps professoral :

Carol Jones

Étudiant :

Partenaire :

Universidade de São Paulo

Discipline :

Physics

Secteur :

Université :

Western University

Programme :

Globalink Research Award

Hydrolytic de-polymerization of hydrolysis lignin using alkaline catalysts: effects of process parameters and optimization

Hydrolysis lignins (HL) are a byproduct from acid or enzymatic biomass pretreatment processes such as the ones employed in cellulosic sugar and/or ethanol plants. They are mainly composed of lignin , unreacted cellulose and mono and oligosaccharides. These lignins are, to a great extent, covalently bonded to cellulose and/or hemicellulose to form lignin carbohydrate complexes (LCCs) thereby making them insoluble in alkali and most common organic solvents – this, obviously, limits the range of applications in which they can be used, in particular, as a bio-substitute for aromatic chemicals for the synthesis lignin-based materials such as lignin-based phenol formaldehyde, polyurethane and epoxy resins. To address the above challenges in the valorization of HL as a chemical feedstock, this research targets hydrolytic depolymerization of HL in water in the presence of an alkaline catalyst to obtain de-polymerized hydrolysis lignin (DHL) with a much lower molecular weight, a higher solubility in various common solvents and, as a result, a higher chemical reactivity. In this proposal, different types of alkaline catalysts will be tested as catalysts for the process. TO BE CONT.

Voir la description complète du projet
Superviseur du corps professoral :

Charles Chunbao Xu

Étudiant :

Partenaire :

FPInnovations

Discipline :

Engineering

Secteur :

Agriculture; Professional, scientific and technical services

Université :

Western University

Programme :

Accelerate

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