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Indiana University - Research Experience for Undergraduates - May 29 - July 24, 2016

2016Tangee Beverly


Poster PPT / JPG

Game Development with Big Data
Faculty Advisor: Geoffrey Fox, Ph.D., Distinguished Professor of Computer Science and Informatics and Physics
Graduate Student Advisors: Pulasthi Supun Wickramasinghe and Supun Kamburugamuve

Project Summary: My project is about researching how big data plays an important role in game development. Also, how python connects with big data and game development.

The game industry has come a long way from board games to extensive multi-player games with impressive graphics. Game developers create games for people's enjoyment. Big Data is a larger set of data that reveals set of patterns, trends, human behavior and interactions, so with the use of big data it plays a very important role with the gaming industry. It is used to collect the information about the gamer to keep them engaged of that particular game and use that data to help make the game better. Python is a well-known programming language that big data scientist uses to hold the big data. By learning to code with python we created a hangman game and a word counter to count the words in a text file. We are aimed in this paper to discuss the reasons and benefits for game developers to learn the python programming and understand the use of the Big Data in game development.


2016Charles Hockaday Jr.


Poster PPT / JPG

Python Tutorial for Big Data Scientists
Faculty Advisor: Geoffrey Fox, Ph.D., Distinguished Professor of Computer Science and Informatics and Physics and Physics
Graduate Student Advisor: Supan Kamburugamuve and Pulasthi Supun Wickramasinghe

Project Summary: Will display a tutorial on how Scientists would use Python in correspondence to Big Data. Basically discussing the basics of Python.

Python was established back in 1989 by Guido van Rossum at CWI in the Netherlands as a successor to the ABC programming language capable of exception handling and interfacing with the Amoeba operating system. For big data there is no specific thing that has to be “big” when it comes to discussing big data. Rather than that it comes down to the need for new techniques and tools in order to be able to process it. This project will determine how scientists will be able to use Python and extend it into using the program towards Big Data in the near future. People that developed Python were able to help make different tutorials and videos on how people can learn or even teach the program for others to learn at anytime. By stating this, the internet shows multiple online sources that someone can go by to learn this highly used program.


2016Hagan Hodgkins


Poster PPT / JPG

Ansible/devops in big data
Faculty Advisor: Geoffrey Fox, Ph.D., Distinguished Professor of Computer Science and Informatics and Physics

Project Summary: Creating ansilbe role that allow those working in big data to download and install prerequisites for their projects to machines without the need to have the roles located in each repository it is required in, potentially leading to duplicates.

When developers need to set up a new machine with the intent to use it as a development environment they must go through the hassle to create a list of what they need. They must then proceed to individually download each of the programs and dependencies that they would require for their machine to be viable for the development of projects. The creation of an automated system for downloading a preexisting list of programs and dependencies would allow a developer to skip this step entirely and relatively quickly delve into their development tasks. With this in mind we applied DevOps concepts and worked with ansible to create a role that did just this. We then applied the benefits of ansible role automation to a big data project which had several roles built into it that otherwise should be absent from the project's repository. As such we created individual repositories to host the roles and created an ansible document within the project that would call these roles should they be needed.


2016Nigel Pugh


Poster PPT / PDF

Counting Faces: Computer Vision and Privacy Application for the Visually Impaired Person
Faculty Advisor: Apu Kapadia, Ph.D., Associate Professor of Computer Science and Informatics
Graduate Student Advisor: Rakibul Hasan and Patrick Shaffer

Project Summary: The team developed a system that will inform a visually impaired person how many people are around them utilizing a Beaglebone Black. Our system uses an infrared camera to detect the presence of an individual based on body temperature and an HD camera to capture an image. The image is then processed and an output of the number of faces in the captured image is given.