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.
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.
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.
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.
Understanding the underlying factors that cause inherited diseases to develop is an important step in improving the health status of individuals, and identifying effective prevention and control measures. This project aims to apply fundamental know of genetics, genome sequence analysis, modeling and simulations, and bio-informatics to uncover the relationship between these factors and assess the risk of such diseases.
This project is to focus on building an application that can be used to perform a audiology-grade calibration of consumer headphones (and microphones) on a mobile device (such as an iPhone or iPad). The intern will use mathematical techniques (such as spectral analysis) to help gather and analyze user information more efficiently in order to provide a fast, accurate assessment of the user’s hardware capabilities for the purposes of hearing testing.
Flocking behavior is the behavior exhibited when a group of birds, called a flock, are foraging or in flight. There are parallels with the shoaling behavior of fish, the swarming behavior of insects, and herd behavior of land animals. What we want to do is to build the mathematics models and use these models to describe the flocking phenomenon. Many mathematics scientists have made great contribution to study the flocking phenomenon. We will use the knowledge of the differential dynamical system to study it.
Weather is a significant driver of daily natural gas and electricity price moves in various North American markets. Weather drives retail energy consumption, which in turn drives market prices through a supply and demand process.
The objective of the proposed research is to develop a statistical analysis framework that provides a reliable profile of Nova Scotia’s white-tailed deer population based on deer related data sources. This project is to support improvements to deer management in Nova Scotia. Improved management and conservation of Nova Scotia’s most important big game species supports wildlife habitat conservation by NS DNR, but is also of importance to the forestry industry, and stakeholders such as the NS Federation of Anglers and Hunters, and the Fur Institute of Canada.
Les données qu'on rencontre aujourd'hui sont souvent de grande dimension. Avec les données génétiques, les signaux et les images, des méthodes d'analyse qui tiennent compte de la taille des données est plus que jamais nécessaire. Chez Hydro-Québec, une nouvelle méthode de surveillance des équipements électriques a été développée, qui fait appel à la théorie de la communication. Cette méthode a mis en évidence l'utilité de tenir compte du comportement des données aléatoires dans un espace de grande dimension, bien connu en théorie des communications.