Projects

Pirate Detection 

Pirate DetectionSponsor: Johns Hopkins University Applied Physics LabCadet
Researchers: Stephen Mascioli, Cameron Armstrong, Ryan HarnerFaculty
Advisor: John David

This project was initiated to better understand the capabilities of naval sea and air assets off the Horn of Africa to be used as a tool against piracy in that region. A model was developed to simulate possible plane routes and pirate detection probabilities based off of realistic operating conditions in order to determine the maximum possible area coverage in a particular region over 7 days. Major factors in the model were the density of merchant ships in the region and the availability of patrolling assets.

Sponsor: Valley Program for Aging Services (VPAS)
Cadet Researcher: Alex Falcetti
High School Interns: Stevan Hall-Mejia
Advisors: Nate Axvig and John David

One of the services VPAS provides is a program in which hot meals are delivered to homebound senior citizens for their noon meal. Currently, over 400 meals are served each day.

Our task was to find a more efficient way to route delivery drivers given the daily fluctuations in both volunteer aid as well as meal demand. To accomplish this, we designed an easy-to-use piece of software that employs a combination of genetic algorithms, allowing VPAS to deliver their meals in a more efficient manner.

Sponsor: City of Lexington
Cadet Researcher: Robert “Chap” Michie
High School Interns: Kunal Ghandi and Stevan Hall-Mejia
Faculty Mentor: Geoffrey Cox

The City of Lexington is located in Rockbridge County, Virginia. The city owns and operates 27 buildings with 42 separate energy accounts: 13 natural gas and 29 electric. Prior to our project, all records of these accounts were handwritten documents kept within city hall, penciled in by a city employee.

The goals of the project were to first take this information and put it in a digital state and then provide a tool to analyze the data in question. Our tool allows the city to quickly access visual models of each building’s energy consumption so that improvements can be made and inefficiencies addressed. By looking at the visual models, the city can increase its overall sustainability, providing economic, environmental, and social benefits to the community. 

Sponsor: VMI Summer Undergraduate Research Initiative
Cadet Researcher: Will Lucas
Faculty Mentor: John David

Data Mining has become an increasingly popular technique in science, economics, business and sports, especially a sport with as rich data as baseball. In this project we mined millions of baseball statistics to predict which teams will win on a day to day basis as well as over entire seasons.

We focused on statistical techniques of regression, artificial neural networks and decision trees.