This symposium is an opportunity for students to present their scholarly and creative work.
- Dr. Maduka Rupasinghe, Assistant Professor of Mathematics, will sponsor Garrett Tresch. Garrett Tresch is a Mathematics and Actuarial Science major. Tresch will present Sieve Bootstrap-Based Prediction Intervals for GARCH Processes, during Oral Session III, 10:30 - 11:30 a.m. in the Faculty Room. Time Series deals with observing a variable - interest rates, exchange rates, rainfall, etc. - at regular intervals of time. The main objective of Time Series analysis are to understand the underlying processes and effects of external variables in order to predict future variables. This presentation uses the Sieve Bootstrap for computing prediction intervals.
- Dr. Paul Cao, Associate Professor of Computer Science, will sponsor Paul Pernici. Paul Pernici is a Computer Science and Mathematics major. Pernici will present Comparing Feature Extraction and Feature Selection Algorithms in Pattern Recognition, during Oral Session IV, 2:00 - 3:00 p.m. in the Trustees Room. Pattern recognition is the science of discovering the inherent properties of large sets of data. A popular approach used an artificial neural network (ANN), which is a biologically inspired machine learning model capable of mimicking human cognitive functions.
- Dr. Gordon Swain, Professor of Mathematics, will sponsor Joseph Scott Glorioso. Joseph Scott Glorioso is a Mathematics and Chemistry major. Glorioso will present Constant Speed or Constant Effort: Which is the More EfAcient Way to Run?", during Oral Session VI, 3:15 - 4:15 p.m. in the Trustees Room. The problem examined was whether it is more beneficial to run 5000 meters at constant speed or at constant effort while minimizing the time. The model, based on human data from literature, takes an input of runner's speed, wind speed, and incline and gives an output of volume of oxygen consumed. Using a simple conversion, VO2 was then converted to Calories expended.