Mathematical Model of Graphics Cards

Randall Pittman

The graphics card is a high-speed processor that is commonly used for video games, but can also be used for general purpose computation. Using the graphics card can increase performance if multiple computations can be done at once. However, sharing data between these computations can cause issues. This project develops a model to predict the effect of memory usage in programs that utilize the graphics card.

Robotic Localization and Mapping

Thomas Lux and Randall Pittman

Computing a map of an environment is relatively easy, if the location of the robot is perfectly known. Finding the location of a robot is easy, if a map of the environment is perfectly known. However, discovering both simultaneously is a much more difficult problem. Simultaneous localization and mapping (SLAM) is an algorithm to both map and pinpoint the mapping location at the same time. In this project, we explore multiple types of sensors, to discover which sensors are best suited for the SLAM process.

Computational Modeling of the pre-Bötzinger

Maya Shende

The part of the brainstem which controls breathing, the ventral respiratory column (VRC), contains a small region called the pre-Bötzinger complex (preBötc). The preBötc is vital in generating and regulating the breathing rhythm, but the details of how it accomplishes this feat are not well know. We created a simulation to explore the effect of different connectivity patterns within a computational model of the preBötc network, in order to better understand how connectivity influences the function of the preBötc.

Beat and Emotion Tracking Mobile Radio

John Guidry

While exercising, people are often too focused on their mobile devices. Their focus should be on their exercising. Helping people focus on their exercise, as opposed to their phones should lead to a better environment for everyone. To this end, we created an application that has the capability to chose songs based on their pace, as well as their emotion. The pace of the user is tracked via the accelerometer on the mobile device, while a survey is used to determine the mood of the user.