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Science

Project Leader(s): 

Dr. Steven Easterbrook, (University of Toronto)

Project team: 
Dr. Marsha Chechik, (University of Toronto)
Dr. Mehrdad Sabetzabeh, (University of Toronto)
Dr. Shiva Nejati, (University of Toronto)
Non-academic participants: 

Bell Canada University Labs,  IBM Canada for Advanced Studies

Funding period: 
April 1, 2021 - March 31, 2021

Reactive Systems are formal systems that cause events in the physical world, in reaction to a set of monitored inputs. Examples include control systems for aircraft, medical devices, industrial processes, and consumer appliances. In many of these examples, safety (and often security) of the system is of paramount importance. To say anything at all about whether such a system is safe or secure, one has to be able to predict its behavior under the conditions that the system may encounter in use.

Project Leader(s): 

Dr. Holger H. Hoos , University of British Columbia

Project team: 
Dr. Kevin Leyton-Brown, University of British Columbia
Non-academic participants: 
Funding period: 
April 1, 2021 - March 31, 2021

Algorithms for solving difficult computational problems play a key role in many applications, including scheduling, resource allocation, computer-aided design, and software verification. In many cases, heuristic methods are the key to solving these problems effectively. However, the design of effective heuristic algorithms, particularly algorithms for solving computationally hard problems, is a difficult task that requires considerable expertise.

Project Leader(s): 

Dr. Kim McAuley, Queen's University

Project team: 
Dr. Thomas Harris, Queen’s University
Dr. James McLellan, Queen’s University
Dr. James Ramsay, McGill University
Dr. David Campbell, Simon Fraser University
Dr. Amos Ben-Zvi, University of Alberta
Dr. Carl Duchesne, Université Laval
Funding period: 
April 1, 2021 - March 31, 2021

Engineers use mathematical models to describe the production of plastics and other chemicals. The models contain unknown parameters that are estimated from plant data. In the past year, the research team analyzed several criteria that modelers use to decide how complex or how simplified their models should be. They showed that one popular model-selection criterion, the corrected Akaike Information Criterion, tends to select very simple models, and that another, the adjusted coefficient of determination, tends to select models with many parameters.

Project Leader(s): 

Dr. François Anctil, Université Laval

Project team: 
Dr. Anne-Catherine Favre, Université Laval
Dr. Vincent Fortin, Environment Canada
Dr. Christian Genes, Université Laval
Dr. Barbara Lence, University of British Columbia
Dr. Peter Yau, McGill University
Funding period: 
1 octobre 2008 – 31 mars 2010

The goal of this project is to evaluate if mesoscale (35 km) meteorological ensemble forecasts coupled to a short-range hydrological forecasting system can lead to improved forecasts, and thus help maximize hydropower production and minimize flood risks. Positive results would pave the way for a full project which would aim to design an efficient short-range hydrological ensemble forecasting system adapted to the climate and hydrology of the Great-Lakes and Saint Lawrence River basin.