2013 AMRE Annual Report

Developing an Assessment Framework for APEX

Student Researchers: Adam Donnelly, Varun Bhandari, Sebastian Weber
Faculty Advisor: Denise Byrnes (Computer Science) and Michelle Johnson (Communication)

Our project was a continuation of the 2011 AMRE project: College of Wooster Assessment, and related to the 2012 AMRE project: Experiential Learning Assessment. We were tasked with developing a framework for the assessment of the newly established center for Advising, Planning, and Experiential Learning (APEX). Our AMRE project was to renovate current assessment strategies that exist in the centers within APEX, and create a plan to incorporate the whole of APEX. Our tasks consisted of: 1) researching assessments implemented in organizations similar to APEX; 2) developing an understanding of current assessment structures at the Registrar, Learning Center, Advising Center, Career Planning, Experiential Learning, and Entrepreneurship; 3) working with an outside expert to prepare and implement an assessment workshop; 4) creating an APEX-wide mission, goal, and measures. This assessment plan will help APEX in increasing its effectiveness and assistance to students.

Agbioscience Marketing Research and Methodology Formation

Student Researchers: John Lanz, David Brew, Jeff May
Faculty Advisor: Peter Abramo, Center for Entrepreneurship

The purpose of the BioHio AMRE team was to conduct market research within the bioscience industries and to understand what industries could best be served at BioHio’s research park. The team created an entirely new research methodology that focused on Political, Economical, Social, Technological (PEST) trends. The findings will be used to help guide BioHio’s expansion and construction of the new research park.

Goodyear Tire Sales Forecasting

Student Researchers: Jai Kedia, Giang Nguyen, Ryan Snyder
Faculty Advisors: Denise Byrnes (CS) and Robert Wooster (Math)

The purpose of this project was to predict future quarterly industry tire sales. More specifically, there are three tire markets within the overall tire industry: consumer replacement, commercial replacement, and commercial original equipment. The interesting aspect of our project was the fact that we did not use historical tire sales to aid in our predictions, but rather only used economic indicators, such as the stock market, unemployment, and business inventories. The main challenge of this project was determining which economic factors were the optimal predictors for each market. We utilized regression techniques to choose the best indicators and artificial neural networks to make the predictions.

Performance Analysis of MPO and Related Optimization Tools

Student Researchers: Andrew Muller, Andrew Hoover, Torger Miller
Faculty Advisor: Sofia Visa (Computer Science) and Robert Wooster (Math)

The MPO Goodyear project entailed researching ways to speed up Goodyear’s Multi-Performance Optimization (MPO) software. The MPO tool allows its user to specify particular tire performance metrics and then an optimization is performed to produce an “optimal” tire. The team developed a multithreaded version of the MPO which achieves an average of 35% speedup. In addition to the multithreaded MPO tool, the team also developed ideas for future improvements on the MPO tool.

Using Lasers to Cut Plastic Film

Student Researchers: Deepika Sundarraman and Elliot Wainwright
Faculty Advisors: Drew Pasteur (Math) and Susan Lehman (Physics)

In this project students served as consultants for Kent Displays Incorporated in an attempt to help them better understand a CO2 laser cutting process of their polyethylene terephthalate (PET) film used to make Boogie Boards. Using Matlab, Excel, Mathematica, and other computational software, a model of the heat transfer process, including ablation of the material due to excessive energy from the laser, was written with the flexibility to change certain laser and material parameters and see the effect of the cutting. Welding strength of the heated material was also considered. The project involved knowledge of the physical and thermal processes, of numerical analysis, and the ability to quickly learn about a complicated process and computational techniques.

Undergraduate Research in Knot Theory

Student Researchers: Joseph Smith, Michael Bush, Katelynn French,
Faculty Advisors: John Ramsay and Jennifer Bowen (Mathematics)

Our research in knot theory was funded by HHMI Undergraduate Science Research Program and The College of Wooster’s Sophomore Research Program. Our team continued the College’s past research of Klein links. We focused on looking at the invariant of linking number for Klein links, as well as for torus links. With the use of braid words, we discovered equations that can calculate the linking numbers of Klein and torus links. We have written a paper on this subject, which we hope to publish. We have begun researching the P-colorability of Klein links and have found very interesting results. We hope to better understand these results in the future. Lastly, we have investigated the effect of Klein bottle hole placement on the created Klein links. We plan on finishing the write up of our conclusions and submitting them for publication.

Analysis of Sports Scheduling for the North Coast Athletic Conference

Student Researchers: Cal Thomay, Paula Trautvetter, Mike Ries
Faculty Advisors: Drew Pasteur and John Ramsay (Mathematics)

The goal of the project was to analyze the current methods used by the North Coast Athletic Conference in scheduling athletic contests in various sports. The primary objectives in scheduling are to minimize travel costs for NCAC member institutions and to minimize missed class times by student athletes. This optimization is subject to many sport-specific constraints. The team created a tool that will enable the NCAC to schedule athletic contests more efficiently as well as provide cost analysis of travel and missed class time to be used for comparison amongst different scheduling formats.

Finging transcription factor binding sites in the Solanum Lycopersicum genome

Student Researchers: Michelle Blackwood and Hunter Van Horn
Faculty Advisor: Sofia Visa (Computer Science)

We computationally identify potential transcription factor binding sites in Solanum Lycopersicum genome. For such an exhaustive search, an algorithm for Hadoop (a platform that supports distributed processing of large datasets across clusters of servers) is designed and implemented. Several potential motifs are identified in four different clusters of genes of interest. In addition, the Arabidopsis orthologs of the genes having these potential motifs are mapped into regulatory and co-expressed networks of genes.

OARDC Molecular and Cellular Imaging Center Integrating R Modules

Student Researchers: Doug Code, Liang Cheng, Dagmawi Zegeye
Faculty Advisor: Denise Byrnes (Computer Science)

R is a data analysis programming language widely used by statisticians. Integrating R modules directly into Galaxy (an application used by OARDC biologists) will simplify data analysis, making the process accessible to a larger audience.While R offers a broad range of functionality, the significant learning curve associated with R, particularly for individuals without programming backgrounds, can intimidate new users. The goal of this project is to build a graphical user interface that gives users with little to no R experience quick and easy access to the ggplot2 graphics package. The application uses RStudio’s Shiny package, which allows for the rapid development of R web applications. Shiny drastically decreases the amount of code and time needed to implement new features and build interface elements, making our R application easily maintainable and extendable.

Competitive Intelligence: Analyzing Agency Data

Student Researchers: Daniel Miller, Xiangyu Li, Anqi Huang
Faculty Advisors: Pam Pierce and Jennifer Bowen (Mathematics)

The purpose of this AMRE project was to analyze data collected from independent insurance agents to determine what characteristics or attributes determine whether a car insurance policy will be won or lost by Progressive Insurance. This analysis was done on comparisons between Progressive and six other insurance carriers.

Wayne County Children Services: Analysis of Recent Trends in Children Services Cases

Student Researchers: Annie Godonoga, Sheharyar Khushnood, Rebecca Wardrop, Andreja Siliunas
Faculty Advisor: Jim Burnell (Economics)

The goal of this project was to identify some possible factors that led to the increase in the number of children in the custody of Wayne County Children Services. The AMRE team approached this project in two ways. The first was a comparison between Wayne County and the other 87 counties in Ohio in 2007 and 2011. The purpose of this approach was to determine whether Wayne County was behaving differently than the state in some way and to analyze possible factors that could affect custody numbers on a statewide level. The second approach was an internal assessment of the classification of cases in Wayne County comparing 2008 and 2012. The team read over 200 individual cases and extracted variables of interest. Through this approach, the team was able to identify case characteristics that were more likely to lead to custody. The two years were then compared to determine any changes in the important characteristics. Together, these two approaches created a comprehensive picture of possible factors that led to the increase in custody numbers.

Market Segmentation Analysis of MIS Business Unit

Student Researchers: Jola Pham, Thanh Dang, Julia Land
Faculty Advisor: John Ramsay (Math) and Lisa Verdon (Economics)

The AMRE team performed an analysis of the manufacturing operations and product pricing data of Will-Burt’s MIS Business Unit. The project scope was to analyze data to determine “where Will-Burt loses money.” The team made recommendations to Will-Burt as to which items are least profitable and thus prime targets for focus and reassessment.