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What's Happening This Week In Mathematics....

Tuesday September 30 1:30 - 2:30
Discrete Mathematics Seminar

Title: The structure of Costas Arrays
Speaker: Jonathan Jedwab, SFU

Regularly updated Discrete Math Seminar information can be found HERE.

Event: 56th annual meeting of the Canadian Operational Research Society (CORS) in Ottawa.

As in the past two years, we encouraged the undergraduates in Math 402W Operations Research Clinic to submit their projects to the CORS undergraduate student paper competition.  And, once again, they won both prizes.  This year, all 3 projects submitted were chosen as finalists, and presented their work at the meeting. (The fourth finalist was from the University of Alberta; nine entries were received.)  Congratulations go to:

Kishley Bhalla, Craig Mathews, W. Brett Robinson and Katie Sclater "Selecting Optimal Tolling Levels: A Case Study for the Fraser River in the Greater Vancouver Area"

Honourable Mention:
Nicole Mo, Alborz Namazi, Joyce Tai and Eric Yuen "Optimal Locations of Telecommunication Equipment: A Case Study for the City of Richmond, British Columbia, Canada"

Kingsley Cheang, Feiqi He, Sarah Lin and Ashlie Neufelt "The Community Mailbox Location-Routing Problem"

Additionally, Second Prize in the CORS Practice Competition went to Daniel Karapetyan (SFU Math postdoc 2011-13) and Abraham Punnen, for their paper "Operational Research Models and Algorithms for Fleet Size Planning and Schedule Optimisation for the British Columbia Ferry Services Inc."  Finalists for the practice competition included teams from the University of Toronto and IBM, first prize went to UOIT.

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Upcoming Events

  • CSC Seminar - Jakob Jorgensen
    2:30 PM - 3:30 PM
    October 3, 2014
    CSC Weekly Seminar Friday, October 3, 2014 TASC-2, Rm 8500 2:30 pm Speaker: Jakob Jorgensen Title: Sparsity-regularized image reconstruction in x-ray computed tomography Abstract: X-ray computed tomography (CT) is a widely used technique for non-invasive imaging, with the medical CT-scanner as the perhaps most well-known example. The underlying mathematical problem of reconstructing an image from the measured data is solved in modern scanners by methods involving analytic inversion of the Radon transform. Motivated by reducing the patient's x-ray dose as well as reducing scanning time for example in materials science applications, there is a large interest in reconstruction from reduced data, which is inherently difficult for the current methods. In recent years, a new class of methods based on incorprating prior knowledge into a variational formulation, has been studied intensely, in particular methods enforcing various forms of sparsity in the reconstructed image. A large number of studies demonstrate the potential for improved reconstruction from reduced data, however a fundamental understanding of conditions under which these methods can be expected to work is lacking. In this talk I will describe some of my recent work in this area. In particular, I will present empirical evidence of an average-case relation between image sparsity and the level of CT sampling sufficient for accurate reconstruction, and I will discuss conditions for ensuring uniqueness of the reconstructed image.
  • IRMACS Retreat
    October 6-7, 2014
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