Projets novateurs réalisés

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

31 133 projets complétés

2940
AB
5159
C.-B.
837
MB
685
NL
882
SK
9292
ON
9695
QC
97
PE
601
NB
1161
NS

Projets par catégorie

Feasibility Study of Incineration of Municipal Solid Waste in Churchill

Churchill is experiencing different types of challenges. Because of the remoteness of this place, the communication and transportation systems are very costly and challenging. Managing municipal solid waste manage is another emerging problem for Churchill community. The current waste management system in the town of Churchill is very costly, and environmentally unfriendly. Town of Churchill is evaluating the viability of a more environmentally friendly and cost-effective solution for the future solid waste management for the community. The project will use highly efficient incinerator which will burn appropriate type of waste and will reduced amount of greenhouse gas compared to the existing system. Moreover, the project will help to decrease the utilization of large areas for landfill and transportation cost during waste handling, and recover the energy from the waste that can be used for heating of the town’s water system and buildings. The study will assist to set up an environmentally and economically viable solid waste management system (incineration unit) in the town of Churchill municipality.

Voir la description complète du projet
Superviseur du corps professoral :

Qiuyan Yuan

Étudiant :

Partenaire :

Town of Churchill

Discipline :

Engineering

Secteur :

Public administration

Université :

University of Manitoba

Programme :

Accelerate

Data management on future hardware and cloud environments

Data management systems are the backbone of the modern society powering many impactful applications. As data volume and the need for fast data processing continue to grow, it is paramount for data management software to evolve and provide high performance. This in turn must be done by co-designing data management software with the underlying hardware and deployment environments. Recently, ultra-fast networking technology gave rise to disaggregated data center (DDC) environment which provide many unique challenges in building and deploying data management systems. In this project, we are bridging the gap between the database world and the DDC environment. We aim to propose platform/API to set the appropriate standard for the field in building data intensive application on DDC.

Voir la description complète du projet
Superviseur du corps professoral :

Tianzheng Wang

Étudiant :

Partenaire :

The Chinese University of Hong Kong

Discipline :

Computer science

Secteur :

Education

Université :

Simon Fraser University

Programme :

Globalink Research Award

Smart ELISA Protocol Development and Implementation using Somru Intelli.R Automation Systems

Enzyme-linked immunosorbent assay (ELISA) it is an immunochemical test that utilizes an enzyme (a protein that facilitates a biochemical reaction) and an antibody or antigen (immunologic molecules) to detect and quantify specific substances in a biological solution. The development of an ELISA protocol presents several challenges, however. For example, ELISA technology currently is developed largely on a “trial and error” basis, rather than being executed systematically, and is not capable of performing large numbers of assays in a timely and cost-effective manner. To improve ELISA development by increasing automation and implementing informed decision-making, we propose to: 1) develop an intelligent knowledge-based decision support system (DSS) to drive efficient new protocol development for novel ELISA-based molecular identification, and; 2) integrate the DSS with an intelligent robot-based experimental apparatus (the Somru Intelli.R automation system) to create an efficient and reliable automated platform for assay-specific investigations of new drugs and vaccines.

Voir la description complète du projet
Superviseur du corps professoral :

Robert Gilmour

Étudiant :

Partenaire :

Somru BioScience Inc

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

University of Prince Edward Island

Programme :

Accelerate

Développement des connaissances en droit de la cybersécurité et protection des renseignements personnels

Le droit peine à se développer pour répondre aux enjeux multiples et diversifiés que pose le développement rapide des enjeux et des moyens mobilisés par la cybercriminalité et la protection des renseignements personnels.
Dans ce contexte, les stages envisagés visent à tirer avantage de l’expertise de pointe développée par l’organisme partenaire pour développer un programme de recherche de pointe pour les stagiaires sur les problématiques émergentes dans les domaines du droit de la cybersécurité et de la protection des renseignements personnels.
Les connaissances développées permettront à l’organisme partenaire de mieux répondre aux besoins évolutifs de ses clients et de contribuer à former des experts du domaine. Cet ambitieux programme permettra également de faire avancer les connaissances dans ces domaines par la diffusion des résultats de recherche.

Voir la description complète du projet
Superviseur du corps professoral :

Sébastien Lebel-Grenier;Patrick Mignault;Arthur Oulaï

Étudiant :

Partenaire :

Norton Rose Fulbright

Discipline :

Sociology

Secteur :

Professional, scientific and technical services

Université :

Université de Sherbrooke

Programme :

Accelerate

Synthesis of 2,2?-bipyridinediol ligands

Our project list is the field of organic chemistry, where the synthesis of small molecules, having potential biological activities, is a paramount objective. Also, the essence of the project lies in new effective green iron catalysts for enantioselective reactions, which is one of the most important tasks of modern organic chemistry to save the environment. This project will allow to reduce the cost of organic synthesis and make it less harmful to the environment. As a result, catalysts based on C2-symmetric 2,2?-bipyridinediol ligands and iron salts will be designed. These iron-derived catalysts will allow replacing metal catalysts based on toxic and expensive noble metals as Pd, Rh, Ru, Ir. The newly designed chiral iron complexes will be tested in a selection of benchmark reactions.

Voir la description complète du projet
Superviseur du corps professoral :

Thierry Ollevier

Étudiant :

Partenaire :

Taras Shevchenko National University of Kyiv

Discipline :

Physics

Secteur :

Pharmaceuticals; Other

Université :

Université Laval

Programme :

Globalink Research Award

External visual observers for understanding manufacturing operations & predicting faults

ATS Automation Tooling Systems Inc. provide solutions for factory design and automation. Their life sciences division provides manufacturing solutions for world leading companies engaged in medical devices, pharmaceuticals & diagnostics. ATS also develops automation systems for the transportation, energy as wells the consumer & electronics sectors. The Vision Image Processing (VIP) lab at the University of Waterloo is dedicated to understanding visual processes and finding solutions for the outstanding problems in image and video processing and intelligent systems. ATS currently utilizes camera sensors in machine vision monitoring of existing processes in addition to a collection of other sensors. After a manufacturing machine is produced, it is difficult to retrofit an existing machine with new sensors. This project will explore external observing cameras that can be placed around the machine and learn what is the normal operation and be able to detect and predict anomalous operations. There are three machine scenarios of interest: (1) a conveyor system; (2) an assembly machine; and (3) a bowl feeder machine. however VIP hopes to improve robustness and accuracy by providing AI based algorithms that understand the process including the visual scene landscape of the manufacturing process components and parts.

Voir la description complète du projet
Superviseur du corps professoral :

John Zelek

Étudiant :

Partenaire :

ATS Automation

Discipline :

Engineering

Secteur :

Manufacturing

Université :

University of Waterloo

Programme :

Accelerate

An NLP-based approach for Pipeline Monitoring and Leak Detection

Pipelines are an imperative part of the energy sector and have a substantial impact on the Canadian environment, and economy. The slightest mishap in pipelines can lead to devasting environmental impacts as well as huge financial consequences. Therefore, developing sound automated pipeline monitoring by leveraging artificial intelligence (AI) and machine learning (ML) for safe and reliable leak detection is highly desirable. The use of ML/AI techniques in pipeline monitoring is challenging mainly due to the vast amount and frequency of data. This study seeks to devise an innovative and novel Natural Language Processing (NLP)-based approach for pipeline leak detection by leveraging Hifi’s innovative fiber technology which provides a recognizable sequence, known as signature, to events based on the sounds they make.

Voir la description complète du projet
Superviseur du corps professoral :

Mohammad Moshirpour

Étudiant :

Partenaire :

Hifi Engineering Inc

Discipline :

Engineering

Secteur :

Mining

Université :

University of Calgary

Programme :

Accelerate

Storage, fluidization, and distribution of the high solid fraction ice slurry

Deepchill and slurry ice is a dynamic medium whose fluid properties change with many different factors such as solute concentration, ice fraction or thickness, temperature, time (settling) and agitation. Once it is generated, it must be stored in different forms depending on the required final applied. Storage, fluidization and distribution of this medium is a critical part of the Deepchill System. The primary objective of this project is to simplify the design and operation of the system with reference to storage and discharge. The second goal of the system is to increase the density of storage by 50-70% and thus reducing the size and cost of the storage vessel.

Voir la description complète du projet
Superviseur du corps professoral :

Martin Mkandawire

Étudiant :

Partenaire :

Deepchill Technologies

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Cape Breton University

Programme :

Accelerate

Application of deep learning generative network algorithms linked with super-resolution methods and fusion techniques to improve the quality of noisy and unlabeled ultrasound images

We aim at developing new approaches which have not been performed so far, such as i) enhancing the resolution and quality of noisy and unlabeled conventional ultrasound images through deep learning SRMs, ii) synthesizing high-quality MRI from the enhanced ultrasound images through generative networks, iii) fusing ultrasound and synthetic MRI images for different aspects such as classification, early diagnosis, clustering, segmentation, iv) employing few-shot learning approach in the adversarial training process to reduce processing time, computational costs and training data and others, and v) assessing the developed algorithms via quantitative and qualitative validation, different public ultrasound datasets and available ultrasound data. The partner benefits from this project through developing and sharing an open-source code for future medical imaging research, attracting top talent in a competitive AI job market, several scientific publications, processing and analysis of ultrasound images, and gaining domain knowledge through interaction with the intern and intern’s academic/clinical supervisor and others.

Voir la description complète du projet
Superviseur du corps professoral :

Ilker Hacihaliloglu

Étudiant :

Partenaire :

Microsoft Canada Development Centre

Discipline :

Life Sciences

Secteur :

Artificial Intelligence; Health and Related Sciences & Technology; Technology

Université :

The University of British Columbia

Programme :

Accelerate

Regulation of T-type calcium channel activity by targeting channel trafficking – a novel approach for pain management Year two

Current therapies to manage pain either result in side effects or are insufficient and the associated medical costs and loss of work days come pose a tremendous socioeconomic burden. We recently showed that T-type channel activity is aberrantly regulated in inflammatory and neuropathic pain by the deubiquitinase USP5, and we have begun to explore this mechanism as a new therapeutic avenue based on interfering TAT peptides. We now plan to test our TATpeptides in diabetic neuropathy and inflammatory bowel pain. We also plan to generate additional TAT peptides to enhance efficacy in vivo and validate them at the cellular and whole animal level. Compared with ion channel blockers which often lack specificity, our approach specifically targets a process that is involved in aberrant upregulation of channel activity, while sparing normal channel function, thus reducing the risk of adverse side effects.

Voir la description complète du projet
Superviseur du corps professoral :

Gerald Werner Zamponi

Étudiant :

Partenaire :

Innovate Calgary;University of Calgary

Discipline :

Life Sciences

Secteur :

Education

Université :

University of Calgary

Programme :

Elevate

Selecting appropriate steel-grades for polar-class icebreakers construction

In shipbuilding industry, selecting an appropriate grade of steel and the associated characterization techniques, tailored well for low temperature application, have always been a challenge. This subject can be even more critical when we are talking about the materials selection and the characterization techniques for polar class icebreakers. Therefore, Chantier Davie Canada Inc. (CDCI) in a close collaboration with Université du Québec à Chicoutimi (UQAC) has defined the current research project to address the challenges on the material (i.e., steel grade) selection in manufacturing the vessel used in polar class icebreakers.

Voir la description complète du projet
Superviseur du corps professoral :

Mousa Javidani

Étudiant :

Partenaire :

Davie

Discipline :

Engineering

Secteur :

Manufacturing

Université :

Université du Québec à Chicoutimi

Programme :

Accelerate

The cellular-molecular landscape of the living human hippocampus

The human brain consists of more than 100 billion cells, many with specific structures and functions, performing complicated computations every day. Understanding these properties is a key component for the development of therapies for neurological disorders such as epilepsy, depression and brain tumours. So far, most of our knowledge of the human brain has been informed by model organisms engineered to replicate parts of the human brain. However, these studies do not fully capture the unique and complex properties of the human brain.
For our proposed project, we will use surgically removed brain samples from patients suffering from epilepsy. As part of one of very few laboratories worldwide with access to these precious samples, we will use cutting-edge methods and technology to identify gene-expression differences in individual cells. Leveraging this cellular-resolved access and knowledge, will help us identify new mechanisms involved in epilepsy, and develop novel therapeutic strategies.

Voir la description complète du projet
Superviseur du corps professoral :

Mark Cembrowski

Étudiant :

Partenaire :

Universität Bremen

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology

Université :

The University of British Columbia

Programme :

Globalink Research Award

Précédent
1...1,1891,1901,1911,1921,1931,1941,195...2,595
Suivant

Joignez-vous à un écosystème d’innovation florissant.

Abonnez-vous à notre infolettre dès maintenant!

S’inscrire

Mitacs — Retour sur innovation

Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.