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Download February 9th, 2016
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INFO SHEET QUEEN’S UNIVERSITY AT KINGSTON Department of Mathematics and Statistics http://www.mast.queensu.ca February 9, 2016 CALENDAR Wednesday, February 10 Curves Seminar Thursday, February 11 Time: 3:00 p.m. Place: Jeffery 319 Math Club Friday, February 12 Time: 5:30 p.m. Place: Jeffery 118 Number Theory Seminar Friday, February 12 Time: 11:00 a.m. Place: Jeffery 422 Graduate Seminar Friday, February 12 Time: 12:30 p.m. Place: Jeffery 319 Department Colloquium Monday, February 15 Time: 2:30 p.m. Place: Jeffery 234 Family Day Speaker: Mike Roth, Queen’s University Title: Introduction to Chern Classes II Abstract Attached Speaker: Peter Taylor, Queen’s University Title: A mysterious sequence Abstract Attached Speaker: Arunabha Biswas, Queen’s University Title: Gaussian polynomial analog of the multinomial coefficient Abstract Attached Speaker: François Marshall, Queen’s University Title: Robust Spectrum Estimation: Application to Relative Ionospheric Opacity Meters Abstract Attached Speaker: Scott Greenhalgh, Queen’s University Title: First principles and epidemiological applications of nonlinear recovery rates Abstract Attached University offices are closed Items for the Info Sheet should reach Anne ([email protected]) by noon on Monday. The Info Sheet is published every Tuesday. Wednesday, February 10, 3:00 p.m. Jeffery 319 Speaker: Mike Roth Title: Introduction to Chern Classes II Curves Seminar Abstract: We will start with the axiomatic definition of Chern classes, and see some elementary applications. Thursday, February 11, 5:30 p.m. Jeffery 118 Speaker: Peter Taylor Title: A mysterious sequence Math Club Abstract: If x1 is is the golden ratio, and x2 is the square root of 2, and x4 is one less than the square root of 5, … what on earth is x3 ? Friday, February 11, 11:00 a.m. Jeffery 422 Speaker: Arunabha Biswas Title: Gaussian polynomial analog of the multinomial coefficient Number Theory Seminar Abstract: We know that the binomial and multinomial coefficients are positive integers. In this talk we shall first define Gaussian polynomial analogs of the factorials and `generalized' multinomial coefficients; and then we shall talk about a conjecture related to `positivity' and `integrality' of these analogs. Friday, February 12, 12:30 p.m. Jeffery 319 Graduate Seminar Speaker: François Marshall Title: Robust Spectrum Estimation: Application to Relative Ionospheric Opacity Meters Abstract: Invariably, time series datasets are contaminated by such phenomena as colored noise processes, outliers, and significant data gaps. When a dataset is dense in such external phenomena, robust spectrum estimation is of primary importance. Robust estimation involves using the Welch estimation technique, jackknifing for computation of variances, and the determination of a mixture distribution. The talk will describe some cleaning techniques, and steps taken to make a spectrum estimate robust when confronted with a highly contaminated, non-stationary voltage signal for a relative ionospheric opacity meter (riometer). (The spectrum reveals if changes in the ionospheric electron density is correlated with solar-vibration normal modes.) Friday, February 12, 2:30 p.m. Jeffery 234 Department Colloquium Speaker: Scott Greenhalgh Title: First principles and epidemiological applications of nonlinear recovery rates Abstract: Differential equation models of infectious disease have undergone many theoretical extensions that have proved invaluable for the evaluation of disease spread. For instance, while one traditionally uses a bilinear term to describe the incidence rate of infection, physically more realistic nonlinear generalizations exist. However, such theoretical extensions of nonlinear recovery rates have yet to be developed. This is despite the fact that a constant recovery rate does not perfectly describe the dynamics of recovery, and that the recovery rate is arguably as important as any incidence rate in governing the dynamics of a system. In this talk, I will provide a first principle derivation of nonlinear recovery rates in differential equation models of infectious disease. To accomplish this, I will rely on an intimate connection between integral equations, stochastic processes, and differential equations. Finally, I will apply a novel nonlinear recovery rate, where infected individuals can only contribute to disease spread for a finite amount of time, to model the elimination of measles in Iceland.
