Radars are being used more and more in critical sites such as airports, military bases and borders for surveillance of huge areas to detect unwanted intrusions. Determination of the type of each target is essential for such systems to identify the nature of the intrusion and avoid false and nuisance alarms. This thesis is focused on the design of automatic target classification systems based on analysis of real radar data from different sites and environments.

This Mitacs Project’s aim is to calibrate and test a model to assess and improve the employee’s engagement. The work will focus in define a methodology to identify the necessary data for the calibration and the installation of a model (a set of equations) for improvement of a factory. This project will benefit both: the researchers with data for calibration and the factory with a new tool to improve productivity.

A critical issue in the oil and gas industry is to quantify the composition of fluids flowing back from the hydraulic fracturing process. This quantification is usually carried out by a manual process (frequently via a visual test) to estimate the water and oil produced from a well flow back process. A sample of these onsite tests are sent to laboratories for chemical analysis. This process has been the status quo for decades. This approach is manual, prone to error, and does not lend itself to sophisticated real time analysis.

Upcoming changes to financial regulation and oversight are creating increased demands for the accurate measurement of financial market risks and the provisioning of adequate economic capital to ensure that financial institutions can withstand market shocks and extreme events. The objective of this research project is to study issues related to the theory, performance, and practical implementation of standards and requirements for measuring and managing market risk set out by the Basel Committee on Banking Supervision.

Amid the tough challenge of dwindling oil prices, GE is seeking for new technology to create production forecasting and optimization tools that simulate the real operating environments and optimize across the entire process, providing actionable insights that help producers achieve their cost, production, and environmental goals. The objective of this project is to develop data driven models for optimizing bitumen production in SAGD reservoirs.

Due to the current economic downturn, especially the lower crude oil price, the drilling success rate become the most important goal for any oil/gas company. For a start-up company, any failure in drilling will be a disaster. To this end, the Deep Treasure Corp wishes that through the combination of mature hydrocarbon prediction techniques and new research results in seismic inversion,  the success rate of hydrocarbon prediction, the theoretical basis for well placement can be provided  in Roncott field, which will improve the success rate in drilling.

Wesgar is a factory that produces metal sheets for its customers. After a product is ready, it will be delivered to the customer. The objective of this project is to improve the On Time Delivery. At Wesgar they have different machines in their production system. These machines are able to process different products based on the shape, size and material. Each product must pass some specific machines to be processed through the production plan. A schedule that determines which product must pass which machine at what time is required for the production system at Wesgar.

Community hospitals in small towns or rural areas face challenges in delivering health care that will allow elderly members of their community to remain in the community that they helped to build. Using simulation modelling, this project will develop strategies for delivering complex continuing care in rural hospitals that is closely integrated with long-term care, residential care, and home care services. Small towns and rural communities have a tight-knit social fabric and the contributions that family support and community services provide to health care are important factors.

We are in the process of creating and growing a team of researchers expert in the field of machine learning and data-mining. Ultimately, our aim is to create solutions to eliminate the need to manually define personalization strategies. We are in the process of signing partnership agreements with retailers capable of collecting large-scale datasets of customer behaviour. Through a data-sharing/consulting partnership we plan to perform research on the design of recommender systems customized for the data-sets available to brick and mortar retailers.

Heart failure is among the causes of death in developed countries. Scientific and medical research has made improvements in treating this condition. Mathematical modelling and computer simulation would help in developing the necessary technologies to detect and treat heart blockages and also give a better understanding and protocols for ablation, the clinical procedure used to treat this condition.