Projets novateurs réalisés

Machine learning in the operating room: focus, performance, and the medical record

This proposed study will significantly enhance our current understanding of how specific intra-operative factors can impact patient outcomes. Our proposed work will provide a proof of concept that machine learning can objectively predict a specific, high-impact post-operative complication, allowing us to move forward with scaling this work to a wide variety of surgical settings. Moreover, the use of machine learning to automatically assess high-risk points of a surgery has many implications, including the ability to direct risk mitigation efforts, work towards real-time assessment of operations, as well as standard-setting and credentialing for surgical procedures. The ability to automate the evaluation of a high-risk step of an operation in real time, and potentially change a patient’s outcome, undoubtably has the potential to significantly improve patient safety on a large scale.

The digital e-commerce logistics and supply chains management using block chain technologies

E-commerce has become one major marketing channel for many firms in Canada and world-wide and has increased dramatically in recent years. As firms migrate from traditional physical retail channels to combined physical and virtual channels, the shift brings new significant challenges to supply chain and logistics management. Blockchain is able to maintain authoritative records in a fully decentralized, secure, and trustless manner and far-reaching implications in supply chain management. Blockchain technology will revolutionize several aspects of supply chains; financial and non-financial. However, it will also face security, legal, regulatory and technological challenges. In this project we will study how to apply block chain technologies to e-commerce supply chain and logistics to improve traceability, security, and coordination.

Développement d’un logiciel d’analyse modale opérationnelle

L’Institut de recherche d’Hydro Québec (IREQ) est le leader en Amérique du nord sur des

recherches et développement en énergie. En collaboration avec L’École polytechnique de

Montréal et l’’École de technologie supérieure (ÉTS), un projet de recherche a déjà été

réalisé sur la vibration des turbines hydrauliques. À la suite du succès du projet, L’IREQ

souhaite développer une technique d’analyse modale opérationnelle sur des machines et

structures afin de faire le suivi modal de ses machines en assurant un fonctionnement

d’opération optimal

Apelin Analog Therapy as an Innovative Treatment for Cardiovascular Diseases

Apelin, an innate peptide, is a critical component of the apelin pathway, which is responsible for regulatory mechanisms of the cardiovascular system. Apelin is downregulated in patients with cardiovascular disease, therefore limiting the cardioprotective potential of the pathway. This project focuses on the optimization of a biological analog, able to withstand enzyme degradation with improved function that acts as a substitute for apelin. The intern involved in this project will have the opportunity to be a part of the development of a conceptual pharmaceutical into a biologic that can be used in clinical practice for patient treatment. Through the completion of this internship, PEARKO Therapeutics will have the assistance it needs to fully optimize its preclinical apelin analog formulations, bringing it a step closer to use in clinical practice.

Modélisation inverse de la charge de chauffage de l’eau d’un ménage

Les mesures d’équipements intelligents sont de plus en plus disponibles. Ces mesures permettent de caractériser le lien entre les habitudes des ménages et la consommation d’énergie du chauffage de l’eau. La meilleure connaissance de ce lien contribue au développement d’outils permettant d’anticiper la consommation d’énergie. Un réalisme accru de prévision permettrait à Hydro-Québec d’entrevoir d’autres méthodes pour gérer son réseau, évaluer ses programmes ou planifier ses activités. À terme, ceci permet d’augmenter la fiabilité de sa fourniture électrique tout en diminuant ses coûts de maintenances des infrastructures minimisant ainsi les impacts sur la tarification des clients.

Mechanical study and failure analysis on steel spirally tungsten inert gas (TIG) welded tubes

Spiral tubes and rings have been broadly used in the manufacturing sector, especially for the automobile industry. However, the failure of the rings will significantly shorten the service life of components, even leading to a disaster when the part is under operation. Generally, these tubes and rings are made from steel sheets spirally using the tungsten inert gas (TIG) welding method. Through the university-industry collaboration under the Mitacs program, the University of Toronto (U of T) team will give a fundamental understanding of failure mechanism of the (TIG) welded tube steels, and the partner company will improve their product quality and process stability by acquiring the study results from U of T on Process assessment, inspection method, and weld quality risk assessment.
This collaborative research provides theoretical knowledge in the failure mode from the TIG welding process and suggests a welding parameter window for the partner company to achieve a high-performance weld seam.

Experimental and numerical modeling of hydraulic fracturing in tight and light formations

Hydraulic fracturing technique has become an essential requirement in exploiting tight and light oil reserves in Saskatchewan and Alberta. The recovery in tight oil fields in these provinces is low with rapid production decline in hydraulically fractured wells. Also, it should be noted that fracturing horizontal wells can consume millions of gallons of water; a small portion of which is recovered after putting the wells on production. Considering the economic and environmental impacts of failed fractured wells, the need for research and development in the area of optimized fracturing design and fracture containment becomes evident. This research project aims at studying fracture initiation and propagation in tight formations as a function of various field and operational parameters. Results of this work will help in better design of fracturing jobs specific to Saskatchewan and neighboring provinces; with focus on increasing economic performance and reduction of environmental footprint of these stimulation operations.

How severe weather affects the auto insurance industry

In Canada, motorists are faced with a wide range of environmental conditions. Weather, in

the form of rain, snow, other frozen precipitation, fog or strong winds, occurs 10 to 20 percent

of the time, depending on the location and year. This project, which involves a three-way

partnership between State Farm Insurance, the Institute for Catastrophic Loss Reduction and

the University of Waterloo, explores weather-related driving risks in the Province of Ontario,

Canada, in order to better understand how risk is increased during inclement conditions. The

analysis is unique from previous studies in its focus on major storms, on urban versus rural

experiences of weather hazards, and in its exploration of accident characteristics and how

they may differ during inclement conditions versus clear, dry conditions.

Heat dissipation characteristics and ampacity analysis of three-phase underground cables with detailed soil thermal conductivity modeling

To satisfy the growing demand of power transmission in urban regions especially from the renewables such as
solar and wind, the three-phase underground cable lines have become one of the most attractive solutions
which fit both the space and landscaping requirements. The heat generation and energy dissipation
characteristics of these underground cable assemblies directly determine the cable ampacity and operation
performance. This project will create and validate a thermal model for three-phase cable assemblies in a
metallic ventilated enclosure; both in free air and within a concrete box. This study will benefit the partner
organization by allowing the design engineers to model variable types of cable assemblies that are not covered
in standards or electrical codes.

Hierarchical graph kernels for classification of molecules

The central problem of pharmaceutical research is to understand the effect of a certain molecule on human or animal biology. Many machine learning models have been developed in recent years and show great efficiency and accuracy for this kind of predictions. However, a problem common to many of the best algorithms is that they require huge amounts of data to be sure the models are well trained and make accurate predictions. This is a serious issue when such data volume is not available. We propose to adapt a family of methods called hierarchically defined kernels we belive is well suited to tackle the problem of molecule classification for small datasets. This method works by decomposing the objects of interest in a tree-like structure of sub-objects (like a picture can be split up into sub-pictures, each sub-pictures be decomposed into smaller sub-pictures and so on) and constructing iteratively a similarity measure starting with a similarity on the smallest sub-objects.

Novel Perovskite Nanoparticle Water Quality Sensor

The proposed research aims to manufacture smart water sensors for real-time monitoring of Canadian watersheds’ quality. The need for clean water is constant for communities across Canada. With growing concerns related to organic pollutants entering the water supply, the treatment of drinking water and water systems, and their health effects a need has been sown. The requirement for rapid, high accuracy and low cost water quality sensors is as prevalent now as at any point in the past. One pollutant source comes in the form of organic molecules, often hydrocarbon wastes from manufacturing, or hormones given off from animal excrement. Tracking the dissipation and sequestration of organic molecules in a water body is critical to watershed health. In cities, these systems help identify and treat some of the symptoms of urban stream syndrome. The research will increase Canada’s scientific and engineering capabilities in water quality monitoring. As a result, Canada will benefit of high-skilled interns to the workforce in the addition of its ability to compete in the global water marketplace.

Characterizing the sensory attributes of red and white wheat, their bransand whole grain products made using red or white wheats.

Red wheat is the most predominant wheat grown in Ontario. However, red wheats impart an

off-flavor to products when used in whole wheat formulations. The food industry is moving

towards developing a whole portfolio of whole wheat products in order to provide a healthier

alternative to consumers. However, issues related to the sensory characteristics of these

products have to be addressed first. There is a paucity of research on the subject of the

sensory attributes of red wheats compared to white wheats; what is the nature of off-taste,

what are the reasons for these; is the sensory attribute different based on the particle size of

the bran, etc. This collaborative project is the first step to establish clearly the nature of the

sensory attributes and its perception by consumers. The knowledge gained hereby will lead

to developing strategies to formulate whole grain products with improved sensory and textural

attributes.