Mentored Student Research
Dr. Hal Smith

2017 - Using IBM Watson in Academic Advising
Leanne Holder, Evan Shaffer, Zachary Sweeney

Investigated the use of various IBM Watson services to aid students in selecting an academic major. The prototype included the use NodeRED, analytics, and personality insights. The tool provided feedback on potential majors based on existing transcripts, writing samples, recommended academic plans, and campus charateristics.

This project was part of the 2017 Nittany Watson Challenge.

 

2016 - Effects of Heat on CPU Performance
Evan Shaffer

This project investigated the impact heat has on CPU performance.

This project was presented at the 2016 Penn State New Kensington Undergraduate Research and Creative Fair.

 

2014+2015 - Effects of Geomagnetic Storms on a GPS Unit
Nicholas Cirrincione

The intent of this project was to find a source for error in a GPS unit. The area of focus for this project was the effects of a geomagnetic storm that have been said to cause distrubances in the signal that is received by a GPS unit. To test the effect, measurements were taken twice daily with a handheld GPS unit and recording the presence and strength of any magnetic storms.

This project was presented at the 2014 and 2015 Penn State New Kensington Undergraduate Research and Creative Fair.

 

2013 - Interfacing Electroactive Polymers with Software for Capacitance Sensing
Matthew Peretic

This project was co-mentored with Dr. Robert Mathers, Prof. of Chemistry

Circuit boards have historically limited sensors to rigid materials; however, through the use of an Arduino microcontroller and electroactive polymers, this project seeks to enable touch detection on flexible services through capacitance sensing. As electrical current is run through a malleable conductive polymer, contact with outside surfaces drain the voltage from the surface. Custom developed software enables the Arduino to interpret these changes in current as a touch in the same manner as a push button switch and respond as desired.

This project was presented at the 2013 Penn State New Kensington Undergraduate Research and Creative Fair.

 

2013 - Automated Code Formatting and Standardization
Bradley Mayo

Developed a tool that performed realtime code formatting based on user settings. This enables code to be stored independent of specific formatting, even in a compressed format, and enhances readability for individual users. Providing for customizable formatting options reduces the need for defining extensive formatting requirements and having to consider them as part of a code review.

This project was presented at the 2013 Penn State New Kensington Undergraduate Research and Creative Fair.

 

2012 - Trek2Kili: A Business Plan for Web Presence
Jim Miller, Taylor Transue

Developed a business plan to help a Tanzanian start-up, Trek2Kili, who offers guiding services on Mt. Kilimanjaro, develop a web presence plan in order to promote their business. This included best practices for web design, payment transactions, search engine optimization, and leveraging social networks.

This project was presented at the 2012 Penn State New Kensington Undergraduate Research Fair.

 

2011 - A Comparison and Application of Data Visualization Techniques
Taylor Transue

The project involved comparing various techniques used to visualize data in information technology and implement a specific data visualization technique in a current project. The goal of the project was to enable users to answer questions about the data yielded by the project. The visualization techniques were implemented in Python using a variety of open source tools.

This project was presented at the 2011 Penn State New Kensington Undergraduate Research Fair.

 

2011 - A Framework for Single Sign-On
Tom Dalbo

The project enabled a user to maintain all of his or her passwords with ease, while keeping security a primary concern and flexibility among websites. Components from these open source projects were heavily used: Python, GNU's BASH, Apache HTTP server, and the GNU Privacy Guard (GPG).

This project was presented at the 2011 Penn State New Kensington Undergraduate Research Fair.

 

2009 - Distributed Component Framework - Java/C++ (DCF-JC++)
Don Virostek

A limitation of the DCF is that it is Java specific. For convenience, the framework, which was implemented in Java, used Java's built-in serialization to exchange messages between components. This project started the development of a C++ library that enabled C++ systems (not necessarily DCF-style systems) to receive/send messages to/from components in a DCF-based system. The approach was not to modify the existing DCF but rather create a C++ library to handle the decoded/encoding of the bit stream that was the serialized Java objects.

This project was presented at the 2009 Penn State New Kensington Undergraduate Research Fair and the 2009 Penn State Schreyer Honors College Undergraduate Research Exhibition.

 

2008 - Site Efficiency
Rob Grabowski, Drew Perriello

This project was an extension of a project the students pursued in IST 421. They implemented a system that crawled a web site, provided a visual representation of the interconnectivity and then computed the efficiency of the site: the average number of links needed to traverse from one page to any other page.

This project was presented at the 2008 Penn State New Kensington Undergraduate Research Fair and CCSC-MW 2008.

 

2007 - Distributed Component Framework - Multiprotocol (DCF-MPr)
Rob Grabowski, Drew Perriello

One limitation of the DCF is that it components had to use TCP/IP to send messages. The point of project was to extend the framework in such a way that other protocols could be supported and easily added by future users. Further, it was also desirable to provide for cross-protocol communication (e.g., TCP/IP-only components talking to Bluetooth-only components). The design for the extended framework was completed but not implemented.

This project was presented at the 2007 Penn State New Kensington Undergraduate Research Fair.

 

2006 - Distributed Component Framework (DCF)
Shawn Vause

To really make the search engines worthwhile, the search engines needed to be distributed. Realizing future systems would benefit from distribution as well, the Distributed Component Framework (DCF) project evolved to provide the building blocks for distributing component-oriented systems. The DCF provides location independent communication for event-driven, asynchronous components. In some sense, the DCF is a light-weight framework that provides a simple version of functionality found in full-blown industry products, such as implementations of the CORBA standard.

The DCF was an extension of ideas incorporated in IBSE-D. The distribution in that system, however, was specific to IBSE and would have required significant refactoring to be useful for other systems.

This project was presented at the 2006 Penn State New Kensington Undergraduate Research Fair and CCSC-NE 2006.

 

2006 - IBSE + DCF
Shawn Vause

This was not a formal project but rather a working example of the Distributed Component Framework. The single process version of IBSE from 2005 was refactored into a more formal component-oriented approach and layered on top of the DCF. The gain doing so is that the core image processing could be distributed of any number of nodes and nodes could be dynamically added or removed. This made an enormous performance improvement when performing web searches since a single keyword search with no subsequence crawling could and limiting the search to the first ten results returned by Google could result in hundreds of candidate images.

This example was included in the DCF presentation at the 2006 Penn State New Kensington Undergraduate Research Fair and CCSC-NE 2006.

 

2005 - Image Based Search Engine (IBSE)
Kevin Corace, Ken Kocon


For this project, the students evolved the (single process) IBSE to include the ability to perform active web searches by integrating the Google Search API. Rather than just specifying a directory which contains a static collection of images, the user can enter keywords that were used to perform a search with the Google Search API. The web pages returned by Google were then parsed for instances of the IMG tag, the location of the image reconstructed and the image downloaded and compared to the key image. The user could request that web crawling be performed as well. That is, the web pages returned from Google were combed for anchor tags, the URL reconstructed and the linked requested and searched. Crawling could be specified to be as deep as desired.

This project was presented at the 2005 Penn State New Kensington Undergraduate Research Fair. As well presented at CCSC-NE 2005.

 

2004 Image-Based Search Engine - Distributed (IBSE-D)
Mike Marcus

The original implementation of IBSE was as a single process. For searches that required examining than just a handful of candidate images, the system was extraordinarily inefficient. There is an obvious gain to be made if the search was distributed. This flavor of IBSE provided the distribution.

This project was presented at the CCSC-NE 2004.

 

2004 - Sound-Based Search Engine (SBSE)
Joe Kuhel, Luke Sadecky

Students developed a Sound-Based Search Engine (SBSE) by utilizing the technology of the Image-Based Search Engine (IBSE 2003). The input to the engine was a WAV file and was compared to WAV files contained in is a specified directory. The audio information contained in the WAV files were converted to an image and then fed into the image analysis engine of the IBSE system.

This project was presented at the 2004 Penn State New Kensington Undergraduate Research Fair.

 

2003 - Image-Based Search Engine (IBSE)
Justin Kofford, Mike Marcus, Ray Mastre

Students developed an Image-Based Search Engine (IBSE). Analogous to a text-based search engine the system accepted an image ("key image") and searched for instances of the image in a collection of other images. The search was done by first performing edge detection on the key image and candidate images. The "edged" key image was then raster scanned over the "edged" candidate images and a weight was assigned to the each comparison. The system returned the best match for each candidate images. The user was able to control the strength of the edge detection and also request that the system search for instances of the key image at 90- or 45-degree increments.

This project was presented at the 2003 Penn State New Kensington Undergraduate Research Fair.