A Mathematical Framework for Modelling Forest Fire Spread

Computer prediction models for forest fires are of great value to wildfire management. The goal of this project is to analyze the mathematical model used by the Wildfire Science Unit in their Prometheus fire prediction software package. In particular, the internship will work on the development of a robust software package which includes 3-D features such as valleys and ridges. Such a software extension will require a detailed analysis of the 3-D equations used in the package which govern fire propagation.

Building Information Model for the Automation of Residential Design and Construction

This research project will automate construction drawings for wood framing designs and apply them on site to residential facilities under construction by Landmark Master Builder. By utilizing 3D modelling, the intern will produce automatically-generated sets of construction drawings that can be easily read and understood by carpenters and framers who assemble wall panels, thus eliminating the drafting time involved in such operations. The intern will also provide an exact take-off list of materials required for construction and an optimization model.

Asset & Liability Management – Forecasting Volume and Duration of Core Demand Deposits

Demand deposits accounted for more than 27% of the total liabilities of Canadian Western Bank at the end of 2006. These deposits have no specific maturities and may behave as current liabilities or as longer maturing liabilities. The bank pays lower interest on the demand deposits than on the most part of fixed-term deposits. If we can estimate the portion of the demand deposits that act as longer-term liabilities, we can invest that amount in assets with a higher rate of return. This amount is referred to as “core deposits”.

A Statistical Model to Assess Cognitive Skills

Castle Rock Research provides quality curriculum-based educational resources to students, parents and educators, both online and in print. Assessment of learned knowledge needs to focus on two distinct aspects: knowledge retention and associated cognitive skills. Knowledge retention not only refers to the ability to recall learned facts but also the ability to understand the relationship between these facts (ie to understand the structure of the learned domain knowledge).

A Parameter-based Statistical Algorithm for Math Items in Multimedia Education

Castle Rock Research provides quality curriculum-based educational resources to students, parents and educators, both online and in print. This project involves the design of a parameter-based statistical algorithm to automatically generate math questions for multimedia education applications. Rather than relying on a curriculum designer to create questions one by one, multiple questions can be generated by the algorithm. By varying the parameter values, the model is able to control the difficulty level of the questions.

Residential Construction Material Waste Minimization

The objective of this research is to develop a comprehensive material waste minimization program in order to enhance sustainable development and promote innovation in the residential construction field. The scope of the research will include the identification and detailed examination of the factors that contribute to residential construction material wastes, the investigation of opportunities for automation of existing methods and processes as alternatives to current practices and the implementation of best practice concepts to minimize construction waste in the industry.

Optimization of Learning Performance on Multimedia Items using Machine-learning Methods

Castle Rock Research provides quality curriculum-based educational resources to students, parents and educators, both online and in print. Reinforcement has been well-studied in psychology and proven to be an efficient learning technique. However, learning behavior varies from one individual to another. It is important to understand one’s learning capabilities and response pattern so as to customize the reinforcement process and to optimize the performance of individual learners.

Numerical Weather Modelling for Predicting Hazardous Situations in Power Transmission Networks

The goal of this internship project is to develop a system for numerical modelling of the weather conditions contributing to the heightened risk of transmission system outages. A regular weather forecasting will be enhanced by specific models of the risk increasing factors, such as strong winds, freezing rain or lightening. The enhanced model will help to identify the time and location where hazardous situations are likely to occur, allowing users to make informed decisions regarding potential risk sectors and planning future expansions of existing transmission networks.

Modelling Body Composition with Special Attention to Visceral and Subcutaneous Adiposity

The internship research focuses on the regulation of human body composition as expressed by the ratio of lean body mass to total fat mass, a quantitative description of which is relevant to the management of obesity. Special attention will be paid to the distinction between visceral fat, which is associated with increased risk of heart disease and type 2 Diabetes, and subcutaneous fat, which imparts less risk for these conditions.

Calculation of the True Anisotrophic Distance Between Points

Geostatistics uses statistical modelling to assess the uncertainty inherent in natural resource problems. There is always a sparsity of data because of the cost of getting samples. Statistical models have emerged as the preferred method of quantifying the uncertainly in this situation. These models allow mining, petroleum and environmental companies to make better decisions when faced with sparse data. Thus, the intern’s research will develop a methodology to calculate the true distance between samples.

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