Application de l’apprentissage automatique pour l’analyse de données dans le contexte Industrie 4.0

Le Centre de recherche industriel du Québec (CRIQ) a pour mission de contribuer à la compétitivité des secteurs industriels québécois et à la croissance des organismes en soutenant l’innovation, la productivité et les exportations. Dans le cadre de ces deux sous-projets MITACS, nous allons explorer comment construire et exploiter des modèles obtenus par apprentissage automatique […]

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Control Forecasting Feature

Control is a leader in mobile payment analytics and alerts for SaaS, subscription, and eCommerce businesses, enabling instant intelligence anywhere via its Android, iOS, and web-based products. We collect our customers’ payment data and provide them with their key business metrics that helps them monitor their performance. In order to improve our service to customers […]

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Conversion of low alcohols to high alcohols through continuous process with highly active multifunctional catalysts

In this project, a series of highly efficient and highly selective multifunctional Guerbet catalysts are developed and will be investigated for the condensation of low alcohols to high alcohols in a continuous-flow reactor. Low energy density bioethanol and methanol will be upgraded to n-butanol and iso-butanol with high energy content comparable to gasoline with high […]

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Développement d’une méthode intégrant la modélisation numérique et les résultats expérimentaux de nanoindentation permettant d’extraire les propriétés élastoplastiques des aciers de turbines hydrauliques

La fatigue des matériaux est un phénomène d’endommagement. Ce dernier a donc un impact négatif sur les équipements qui sont sollicités de telle sorte dont les turbines hydrauliques servant à produire l’hydro-électricité. Il devient donc nécessaire d’enrichir les connaissances dans ce domaine pour diminuer l’importance de cette dégradation sur des composants aussi critiques que les […]

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Real-time Quantitative Analysis of Cannabinoids in Cannabis

The medical marijuana industry has attracted significant attention recently due to its impending legalization in Canada in the coming year. Along with legalization comes the need for accurate and dependable characterization of the components in the product that is to be consumed by the end user. Keystone Labs is a certified cannabis analysis lab with […]

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PART A- Conversion of CO2 and H2O to Syngas Using Reversible Solid Oxide Fuel Cells (RSOFCs) Technology – Year two

The main objective of this project is to demonstrate the highly promising performance of our world-leading catalysts in a scaled-up solid oxide electrolysis cell (SOEC) system. SOECs can efficiently convert the greenhouse gas, CO2, or mixtures of CO2 and H2O, to useful chemicals and fuels, while running on excess electricity, thus serving to store intermittent […]

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Automated transaction classification using machine learning algorithm

The procurement process of an organization is key to understand company costs. Organizations gather large amounts of data coming from different sources (e.g. income statement, balance sheet, general ledger lines). This information is heterogeneous in nature as it is a mix of unstructured and structured data. Moreover, it needs to be cleaned and consolidated in […]

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Enhanced Techniques for History Matching and Forecasting of Petroleum Reservoir Data

History matching refers to calibrating numerical or analytical models by the observed data. However, this task can be very challenging in presence of complex geology and/or many unknown data . The purpose of this project is to introduce and apply the new techniques for efficient creation of predictive history-matched models for reservoir characterization of conventional […]

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Enhanced Techniques for History Matching and Forecasting of Petroleum Reservoir Data – Year Two

History matching refers to calibrating numerical or analytical models by the observed data. However, this task can be very challenging in presence of complex geology and/or many unknown data . The purpose of this project is to introduce and apply the new techniques for efficient creation of predictive history-matched models for reservoir characterization of conventional […]

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Evaluation of targeted alpha-therapy on patient-derived Glioblastoma cells

Glioblastoma multiforme (GBM) is the deadliest form of human brain tumors, systematically recurring despite multimodal treatment. As a consequence, the average patient survival is less than 15 months, and is thought to be linked with the presence of brain tumor stem cells (BTSCs) that are implicated in treatment resistance. GBM BTSCs are radiotherapy and chemotherapy […]

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