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.

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.

Kinematics Modelling and Trajectory Design for Arm and Shoulder Physical Therapies Performed by Rehabilitation Robots

This project involves studying the kinematics of the human body during physical therapies on the arm and shoulder. With guidance and assistance from Glenrose Hospital, the intern will collect a library of typically prescribed motions of the shoulder and arm during physical therapy. He will then develop a mathematical model to represent the kinematics of the arm and shoulder as well as a parameter identification routine to identify the model parameters using simple moves and coordinate measurement techniques.

Boreal Forest Mortality Modelling

The intern will collect data on tree mortality in the company's woodlands and develop equations to predict mortality rates from tree growth or forest age and composition. Mortality rates for white spruce have been particularly difficult to obtain due to overall low levels and sporadic occurrence of tree death. This project provides an interesting alternative broad survey approach to mortality compared to the present permanent sample plot (tag and re-measure) program. It will also aid the company with modelling the yield of mixed-wood forests.

Virtual Organ Modelling with Advanced Transport and Visualization Tools

Pharmacokinetics, the study of a drug’s course through the body, is an essential quantitative tool used in all stages of drug development and administration. The liver is the primary site of drug metabolism and elimination from the body, but it is difficult to model due to its complex structure. A virtual organ will be developed for the liver using modern mathematical techniques such as fractals in conjunction with flow reservoir modelling software developed by the Computer Modelling Group Inc.

Geostatistical Modelling of Variability and Uncertainty for Natural Attenuation at Upstream Oil & Gas Contaminated Sites

The intern will work on quantifying inherent uncertainties associated with natural attenuation of organic contaminants at upstream oil and gas contaminated sites. Uncertainty and variability in parameters such as hydraulic conductivity, biodegradation rate constant and spatial distribution of the source of contaminants may lead to highly uncertain results to be obtained from routine fate and transport models. Thus, there is a need to quantify these uncertainties and study their impact on the predicted plume size and clean up time.

Characterization and Prediction of Cancer Drug Resistance Markers Based on Data Mining of Microarray Profiles

The internship will concern studying the role and impact of specific proteins (in particular tubulin) in cancer, and the identification of prognostic markers of cancer progression and predictors of cancer response to existing and new compounds (mainly based on microarray data analysis and protein structure prediction).

Mathematical Modeling in Pharmaceutical Development

Microtubules are a key constituent of the cell's structural framework and are responsible for a diverse range of functions within the cell. They are cylindrical polymers, 25 nm in diameter and can grow to be several hundred micrometers in length. Tubulin, the protein which is the main component of microtubules, self-assembles to form the walls of the cylinder in a highly-ordered, helical lattice arrangement. Functionally, microtubules fill a wide variety of roles within the cell. The function often considered most important is the role played in cell division.