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 […]

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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 […]

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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 […]

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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 […]

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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, […]

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Multi-institute domain adaptation by adversarial constrained medical time series representation learning

Hospitals strive to perform cutting edge medical treatment, treat all patients fairly, and reduce operating costs, while also enabling caregivers to spend more time interacting with patients. Artificial intelligence and machine learning promise these things. However, medical data provides unique challenges for machine learning. Currently, if a hospital wants to include an algorithm for automated […]

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Predicting Treatment Sensitivity in Hypotensive Patients

Anticoagulation with Warfarin is indicated and required for post-operative cardiovascular patients. However, it is a high-risk medication with a narrow therapeutic range where sub-optimal dosing can lead to complications and even death. While multiple risk factors have been associated to Warfarin sensitivity, the prediction of optimal Warfarin dosing strategies remains ineffective and requires trial and […]

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Application of Machine Learning to Vision-Based Pose Data for Exercise Classification

The research will be using visual information from the phone’s camera as well as demographic information from participants and implement various machine learning algorithms such as random forests, support vector machines, etc. to provide feedback regarding different exercises to the participant. Specifically, the algorithms will classify the exercise types. Furthermore, these algorithms will be optimized […]

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Mesurer les paléopressions des systèmes hydrothermaux aurifères le long de la faille Cadillac, Abitibi

Certains gisements riches en or de l’Abitibi sont associés à des veines de quartz formées à partir de fluides hydrothermaux à différentes profondeurs dans la croûte terrestre. La mesure des anciennes pressions enregistrées par ces veines, donc de la profondeur originelle des dépôts minéralisés est particulièrement importante en exploration minière. Elle permet notamment de déterminer […]

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Development, optimization and production of fiber-based strain sensors for aerospace, automotive and health

The project will employ three undergraduate coop students and one post-doctoral fellow to work with the MesoMat team to improve the sensing capabilities of the fiber technology that has been developed at MesoMat and develop robust production methods. MesoMat has developed a fiber-based sensor manufactured from plastics and nanoparticles. These materials change their resistance when […]

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A Survey on Application of Visualization and AI Algorithm-Driven Technology for Healthcare

Healthcare facilities collect and produce vast amounts of clinical-relevant data. Various AI-related methods (like computer-aided detection for mammography and the learning and visualization of clinical pathways) are applied to healthcare these days, and visualization techniques are also used to support clinicians due to the complexities of clinical data. This self-contained survey focuses on the assessment […]

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