Upcoming Seminars:
Date: Friday, January 13, 2012, 1.30 p.m., FA 357
Speaker: Dr. Julia Johnson, Department of Mathematics & Computer Science, Laurentian University
Title:Rough Set Graphical User Interface (RSGUI)
Abstract:Rough Set Graphical User Interface (RSGUI) is an experimental tool for analyzing inconsistent and incomplete data. The system has been progressively developed, implemented, augmented with new algorithms, interfaced to a MySQL based data warehouser and turned into a web application by Laurentian Computer Science students over the last six years. The capabilities of RSGUI will be demonstrated and recent results discussed that establish the benefits of combining rough set decision making with stochastic analysis in mining exceedingly complex and difficult to interpret data sets.
Date: Friday, February 10, 2012, 1.30 p.m., FA 357
Speaker: Dr. Peter Adamic, Department of Mathematics & Computer Science, Laurentian University
Title: A deterministic model for pricing life insurance Abstract: In this seminar, we will illustrate some fundamental results used by actuaries to calculate the pure premium for a life insurance policy. A brief introduction to interest rate theory, with a subsequent introduction to life table methodology, will provide the necessary framework for deriving the actuarial present value of an annuity and/or future death benefit from which the life insurance premium can be obtained. The presentation will assume no prior knowledge of actuarial theory, and it is hoped that those who attend the seminar will walk away with a better understanding of what Actuarial Science is all about.
Date: Friday, February 17, 2012, 1.30 p.m., FA 357
Speaker: Dr. Amr Abdel-Dayem, Department of Mathematics & Computer Science, Laurentian University
Title: To Be Announced
Abstract:
Date: Friday, March 9, 2012, 1.30 p.m., FA 357
Speaker: Dr. Ralf Meyer, Department of Mathematics & Computer Science, Laurentian University
Title: Memory-optimized diagonalization of quantum systems using singular value decomposition
Abstract: Spin systems are an important subject in theoretical condensed matter physics. Several numerical methods have been developed to study the fascinating properties of quantum mechanical spin systems. Exact diagonalization is a method that uses numerical methods to calculate the lowest eigenvalues and eigenvectors of the systems Hamilton matrix. This method is strongly limited by the memory requirements of the vectors and matrices that need to be stored. In this presentation, a recently proposed method will be discussed [M. Weinstein et al., Phys. Rev. E 84, 056701 (2011)] that has the potential to dramatically reduce the amount of memory required in exact diagonalization calculations. The method artificially partitions the system into two subclusters and uses singular value decomposition to find an optimized representation of the eigenstates of the coupled system.
Date: Friday, March 23, 2012, 1.30 p.m., FA 357
Speaker: Nehme Bilal, PhD Student, Department of Computer and Software Engineering, École Polytechnique de Montréal. Software engineer at Objectivity
Title:An iterated tabu search heuristic for the partial set covering problem
Abstract:An optimization problem refers to maximizing or minimizing an objective function, subject to a set of constraints, by selecting the best configuration from a finite number of possibilities. Usually the number of possibilities is very large and cannot be enumerated in a reasonable computation time. In such cases, exact algorithms (like branch & bound) and heuristic algorithms (like genetic algorithms, tabu search, iterated local search) are used to reduce the search space by exploring only the promising configurations. The set covering problem is a very popular optimization problem and has been applied to a wide range of industrial applications, including scheduling, manufacturing, service planning and location problems. An introduction to optimization problems will be presented followed by a description of a new variant of the set covering problem and a hybrid heuristic algorithm to solve it. The developed algorithm is a combination of iterated local search and tabu search metaheuristics.
Date: Friday, March 30, 2012, 1.30 p.m., FA 357
Speaker: Dr. Fabrice Colin, Department of Mathematics & Computer Science, Laurentian University
Title: Mathematical Tools for Fluid Simulation in Computer Graphics
Abstract: To follow