Modèle de prévision dynamique du comportement des renouvellements de polices d'assurance

Le département de Prévision et Analytique de TD Assurance est actuellement en charge de prédire les ventes et les revenues des différents produits d'assurance sur une base annuelle et mensuelle. Prédire les revenues, et ceci de manière précise, est crucial pour l’entreprise et son bon fonctionnement. Les modèles jusqu'alors utilisés ont étés construits il y a un peu plus de dix ans et ont été implémentés avec le logiciel Excel. Ces modèles sont complexes et requièrent trop de manipulations manuelles, engendrant non seulement des erreurs potentielles mais également une perte de temps.

Effect of influenza vaccination with high-dose antigen on geriatric population

Vaccination is an important preventive measure against influenza infection during both seasonal epidemics and pandemic outbreaks. This research aims to evaluate the health benefits and costs associated with a new vaccine developed by Sanofi for seasonal influenza. This vaccine provides better efficacy and higher protection for individuals over 65 years of age. The vaccine is expected to reduce severe illness and hospitalization in this age group.

Using Viral Dynamics to Connect Clinical Markers of Disease Progression to Sequence Evolution for HIV-1

HIV-1 remains a global health challenge, with over 35 million people infected. The high rates of turnover and evolutionary adaptability exhibited by HIV-1 pose a particular challenge to the use of antiretrovirals, as well as the development of a vaccine. Our focus is to understand the dynamics of two of the most commonly tracked clinical markers of an HIV-1 infection: CD4+ T cells/mm3 (CD4 count) and HIV-1 RNA/ml (viral load).

Advanced Simulation Methods for a Next Generation Computational Fluid Dynamics Solver Year One

Computational Fluid Dynamics (CFD) is a branch of fluid mechanics that is focused on using numerical methods to solve and analyze practical engineering problems involving fluid flow. The purpose of the proposed research project is to develop novel simulation methods directed at applications in sensitivity analysis and design optimization. Sensitivity and optimization studies are becoming more common as engineers are challenged to determine optimal operating configurations for their designs.

Developing efficient computational simulationtools for geophysical applications

Quantitative interpretation of magnetic data through inversion for general distributions of magnetic susceptibility has played an increasingly important role in mineral exploration in recent years. The goal of the proposed project is to develop efficient and robust computational simulation tools for the inversion of magnetization at a specified depth using ground/airborne magnetic data.

Development of an International consensual method for water use impact assessment in LCA

Cascades within the MITACS Elevation program are threefold: a. Ensure their industrial voice is represented on this international consensus building  process b. Being proactive, influence the process and anticipate the developments on the consensus around water footprinting methods c. Generate industry specific case studies to test  the method, ensure key problems are addressed and increase internal awareness Supporting the researcher that will lead the international process conducted under WULCA group is the mean of meeting the above mentioned objectives.

Optimizing the performance of the railway at AMIC by using data mining and advancedartificial intelligence techniques

This research project tackles a condition-based maintenance optimization problem in the railway equipment at ArcelorMittal Infrastructure Canada (AMIC). Logical Analysis of Data (LAD), a data mining technique, will be applied to exploit thousands of data records in order to identify and predict failure causes and degradation behavior of the equipment under study. New knowledge discovery approaches will be developed in order to deal with AMIC’s large scale databases. Mathematical programming and artificial intelligence techniques will be employed to develop these approaches.

Advanced Simulation Methods for a Next Generation Computational Fluid Dynamics Solver

Computational Fluid Dynamics (CFD) is a branch of fluid mechanics that is focused on using numerical methods to solve and analyze practical engineering problems involving fluid flow. The purpose of the proposed research project is to develop novel simulation methods directed at applications in sensitivity analysis and design optimization. Sensitivity and optimization studies are becoming more common as engineers are challenged to determine optimal operating configurations for their designs.

Algorithms and Software System for Analysis of Twitter Data using Apache Spark

The goal of this project is to develop a software system to collect, store, organize and query Twitter messages, and to develop algorithms that can process the Twitter data to extract value-added information, in particular, the geolocation of Tweets. First, we will design and implement a processing and analytics system for Twitter data using the Apache Spark environment. Second, we will research and extend advanced algorithms to infer the geolocation of Tweets from their contents.

Adaptation d’une modélisation statistique de l’érosion de cavitation à un autre type de turbine hydraulique et intégration d’un modèle physique

L’une des stratégies mise en oeuvre par Hydro-Québec pour accompagner la demande croissante d’électricité, consiste à caractériser les phénomènes contribuant à la dégradation des turbines hydrauliques. Dans cette optique, le phénomène de cavitation est étudié, car il est à l’origine de l’érosion et donc de l’endommagement des turbines. Ce phénomène correspond au passage de l’eau de l’état liquide à l’état gazeux sous l’effet d’une baisse de pression, engendrée par la rotation des aubes de la turbine.

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