In the road construction process, a civil engineer commonly uses software to outline the horizontal and vertical road alignment on a topographical map. The software then calculates the amount of earth that needs to be excavated, or filled, at certain points of the alignment as well as pavement costs, land costs and other expenses. Softree, the partner company, provides such software. There is currently no commercial software that offers the user an automated optimization of the alignment based on the total cost.
The project will develop methods for constructing profiles and predictive models for geo-spatial data. The socio-demographic profile will be developed for the geographical areas of interest. In addition, the models will be developed to identify areas with high potential; for acquiring new customers. The targeting of these areas may be conducted through unaddressed direct mail. Methods of testing effectiveness of marketing campaign and predictive models will be developed.
With the integration of once independent control systems into business networks there lies a major security risk that organizations may not be prepared to assess or manage effectively. Without proper testing, these real-time systems are vulnerable to attack which creates a significant risk to the reliability and integrity of these systems. With the use of a mathematical object, the Error Locating Array (ELA), we are able to detect errors in the system whenever the structure of the faulty interactions satisfies certain reasonable assumptions.
In this internship, the team proposes to develop high performance sequential and parallel algorithms for multiplication and division of multivariate polynomials. They propose to use a recursive data structure. One of the possible advantages of a recursive data structure is that we can also see how to parallelize polynomial division. Potentially high level algorithms such as computing polynomial GCDs and polynomial factorization will benefit from this speedup.
The computation of risk profiles for financial products and portfolios is an extremely important problem, both for regulatory and internal management purposes. For complex products whose value depends on a number of underlying risk factors and for which exercise decisions can be made prior to maturity, Monte Carlo simulation techniques are the only viable procedures. This project aims to adopt a simulation method used for pricing products, to computing risk exposures. Various ways of improving the computational speed will be explored.
This project will produce material, in the form of lesson plans, instructional guides and practice sheets, appropriate for a college-level foundational mathematics course and will monitor its effectiveness during an implementation at on Ontario college in the fall semester, 2009. Once completed, the material will become part of JUMP's growing body of course materials. It is hoped that the material will prove effective in addressing the mathematics requirement of college students and will be adopted at more institutions, fulfilling JUMP's goal of "[promoting] a numerate society".
The goal of this research project is to develop a management toolkit that will enable First Nation fisheries managers to select and employ appropriate mathematical population models based on management objectives and available data. The primary societal contribution of this research program is the development of a toolkit that will immediately enable access to ecological risk assessment (ERA) tools that target the appropriate level of biological organization (i.e. populations) in a transparent, accountable, and scientifically defensible manner.
Aptamers are single stranded DNA molecules that due to their sequence bind to specific target molecules. The process for the identification of aptamers for a specific target involves exposure of a large number of random sequences to the target followed by selection of sequences that bind. This process requires several several selection cycles for success. Selection is based on two overlapping factors, strengh of binding and specificity of binding.
Teck Metals Ltd. operates one of the world’s largest integrated lead-zinc smelting operations out of Trail, British Columbia. Every year, they report on atmospheric emissions of zinc and other contaminants through Environment Canada’s National Pollutant Release Inventory (NPRI). The purpose of this internship is to extend an existing inverse Gaussian plume model for estimating the emissions of zinc from point sources. The input to the algorithm is a collection of measurements of particulate material deposited on the ground in the area around the Trail smelter.
The research project is to investigate a multi]factor multi]asset extension of the Hestonf93 stochastic volatility model for comprehensive Credit Value Adjustment calculation and Commodity Counterparty Credit Risk methodology. The extended model covers counterparty hazard rates correlated with the underlying and interest rates in order to model wrong]way exposure.