MICS Student Research: Gain Valuable Experience with Faculty

Students pursuing a major in the Department of Mathematical, Information & Computer Sciences have the unique opportunity to conduct real-world research alongside expert faculty. This student research involves the methodical formation of a scholarly honors project. The goal of this project and its process is to prepare students for the world of post-baccalaureate scholarship and research.

Work closely with a department faculty mentor to develop a project on a topic of your choosing and culminate research resulting in a presentation of your findings at a conference in spring semester. In preparation of presenting your findings, you will be coached through the various stages of conducting a research project and transforming your work into a scholarly presentation and paper. The Department of Mathematical, Information & Computer Sciences will strongly support you in your research, and you can look forward to working with your faculty mentor throughout the research, editing, and presentation processes with invaluable advice and guidance every step of the way.

Learn more about how students gain hands-on STEM experience through 国产剧麻豆剧鈥檚 summer research program

2021-22 Student Research

Sentiment Analysis: A Comparison of the Instagram Accounts of 国产剧麻豆剧 and Other Universities
Alexa Do
Mentor: Dr. Mike Leih

Sentiment analysis is a machine learning, Natural Language Processing technique that associates text with their given emotion. Marketers often use sentiment analysis to gain insights into their customers, especially in discovering areas that they can improve on or should continue doing. Sentiment analysis is often performed on social media platforms so that marketers can modify their content based on the positive sentiments found. Through a collaboration with 国产剧麻豆剧鈥檚 Marketing Department, sentiment analysis was conducted on the Instagram accounts of 国产剧麻豆剧 and their competitors. Using the VADER Python library, sentiment scores were created, ranging in numerical values from -1 to +1. These values were then translated as positive, negative, or neutral. By putting the Instagram Posts into categories, the colleges were ranked based on positive sentiment. Each category was then analyzed as to the reasons why a particular college received the top rank. Then sentiment scores were conducted for the universities collectively, demonstrating that Pepperdine received the highest sentiment overall.

Sequential Analysis of the Oncogenetic Proten E7 from High and Low Risk Human Papillomavirus
Camryn Marble and Isabel Garcia
Mentor: Dr. Heidi Woelbern

This study analyzes the impact of hydropathy on high- and low-risk serotypes of Human Papillomavirus (HPV). A review and categorization of HPV serotypes was performed alongside an investigation of epidemiological data. Preliminary hydropathy analysis using the R programming language suggests a correlation between increased hydrophilicity and oncogenic high-risk serotypes.

Anamnesis (short story)
Samuel Cheung
Mentor: Eddie Matthews

鈥淚 open my eyes and see the gray interior of my car. Squinting against the brightness, I see the lampposts, stray shopping carts, and evenly spaced diagonal lines of a parking lot. The passenger seat holds my backpack and a few loose sheets of paper with my handwriting scrawled on them. I turn in my seat and see that the backseat has a good number of my clothes haphazardly piled on top of each other.

I inhale and smell the metallic odor of dried blood. Panic shoots through my body as images of last night flood into my mind. I was in a rush to leave. No matter what, I couldn't stay in our apartment. Bella. I left a note on the kitchen table next to the salt and pepper.

I trace my steps backward as the fog of sleep lifts further. I had stared at the warning label on the visor that tells you about seat belts until my eyes ached and then drifted off to sleep. I parked here after driving for hours around town without a destination. I packed without thinking, it was more that I was just trying to get everything in my car. Before that, all that comes is the sight of our bedroom door closing. What happened?鈥� (Full story is on the 3rd floor bulletin board.)

2020-21 Student Research

Finding Renewable Energy Solutions Through GIS
Delaney Hanson
Mentor: Dr. Lori Carter

This project explores Esri's ArcGIS tool and uses its functionality to map out ideal renewable energy locations in specific areas in the United States. Depending on the type of energy source, different factors are considered to draw conclusions about the best places to implement renewable energy power plants. Research into GIS data and renewable energy factors helped guide the search for the datasets that this project required. This paper describes not only the results of ideal locations that were discovered, but also the process of learning and applying the various tools and techniques for the research. The tutorials provided for ArcGIS, demonstrated how the application displays datasets and uses processing tools to manipulate data on a map. The layers that were obtained provided insight to analyze the conditions which would create an ideal site for a solar or wind power plant.

Cloud Based Plasmid Annotation Tool
Leslie Smith
Mentor: Dr. Mike Leih

Plasmid genome analysis is a primary way biologists can study and infer characteristics about antibiotic-resistant bacteria. However, analysis of plasmid genomes has been hindered by inconsistent gene naming, various incomplete databases, and the need for many different tools to identify and analyze plasmid features. We aim to alleviate some of these challenges by providing a single, cloud-based web tool that can link the plasmid genome annotation workflow. With use of the genome analysis tool Prokka, AWS, and RShiny, we are able to provide a web tool for user-friendly plasmid genome upload, annotation, and visualization.

How to Build a Better Engineer: An Analysis of Integrated CS Ethics Modules
Morgan Wheeler
Mentor: Dr. Lori Carter

Starting in 2019, 国产剧麻豆剧 professors Dr. Lori Carter and Dr. Catherine Crockett recognized a need for integration of ethics into computer science (CS) and data science courses, so they have been developing a series of ethics modules to be embedded throughout CS curricula. These modules introduce four ethical frameworks 鈥� virtue ethics, analogies, utilitarianism, and deontology - for evaluating ethical dilemmas. Then, in upper-division courses, they are used to discuss relevant social issues pertaining to the topic of the class. Similar approaches to ethics have been made in other fields including medicine and business. Moral psychologists have long argued that practicing language-based reasoning through analyzing ethical dilemmas shapes a more ethical person; however, more recent work has shifted focus from the emphasis on moral reasoning to a development based more on quick emotions and intuitions as the proponents of moral action. To build moral development, those papers recommend having communities that foster moral behavior, learning from moral exemplars, and regularly practicing moral virtues. This paper evaluates the effectiveness of the CS ethics modules by analyzing the current responses from teachers and students, similar approaches to teaching ethics in accounting, and current developments in moral psychology. It is concluded that the modules could benefit by maximizing class discussion time by using pre-class activities, clarifying how the modules should taught, reframing the ethical frameworks in the introductory modules, and creating an additional open-ended module for students in internships.

Building a Cyber Range using Amazon Web Services
Josue Barragan
Mentor: Dr. Maria Zack
2021 Summer Research at 国产剧麻豆剧

Analysis and Graphical Representation of Complex Data
Jonathan Hake
Mentor: Dr. Greg Crow
2021 Summer Research at 国产剧麻豆剧

2019-20 Student Research

A Study in Securing the Internet of Things
Joey Tuttobene
Mentor: Dr. Mike Leih

Current Internet of Things (IoT) cybersecurity threats were investigated using current literature and direct examination of IoT devices including the 3D printer control software OctoPrint, the autonomous vehicle middleware MOOS-IvP, and a common consumer smart lightbulb. This research found that most IoT devices transmit in plaintext and that software controls alone are insufficient in control systems applications. Recommended best practices for organizations include segregating IoT devices on a network, using non-default credentials, and keeping devices up to date. Manufacturers need to include robust encryption and authentication of messages with their offerings, as well as provide methods to update devices easily and safely. Finally, physical fail-safes can complement imperfect software in IoT control system applications.

Big Data for Savings Groups: A Study and Application of Data Visualization
Maria Bolt
Mentor: Dr. Lori Carter

Big data, despite the inherent challenges it poses, has become more and more influential in recent years due to the ever-growing prominence of digital data as well as the constantly improving data management technologies. It has become a powerful tool for analysis in a wide range of industries and fields, even including applications to international development. However, the ability to gain insight from big data is dependent upon good data visualization. Similarly, the savings group model, an implementation of microfinance in developing countries, has risen in popularity in recent decades. This model has been successful by emphasizing local empowerment, but further advancement in the field is limited by the difficulty of data collection. In this study, it is argued that the application of big data analysis to savings group data could provide the needed support for the continuous improvement of the savings group model. Also, the DreamSave mobile application for savings groups, created by DreamStart Labs, provides a platform from which to begin synthesizing these fields. This research includes a theoretical examination of the aforementioned concepts, as well as a practical data visualization project using data from the DreamSave app. Finally, the study documents the challenges and lessons involved in the realization of the practical project, highlighting how they reflect common issues faced in the data-driven software development industry.

The History of the Cycloid Curve
Natalee Chavez
Mentor: Dr. Maria Zack

During the 17th century prominent mathematicians became fascinated with the cycloid curve. It was their favorite example to use in the development of their new ideas and theorems. They would use it to help them in their new discoveries because the unique properties aligned with the curve. Since it was used by most significant mathematicians of the 17th century, it is important to examine the history of it during this time period. This paper aims to examine mathematicians work with the curve, and similar methods used among mathematicians, and how the cycloid curve aided the development of calculus. In order to answer this question, proofs relating to finding general methods of tangents, areas, arc length to the curve and the brachistochrone problem were examined and analyzed. The methods used by mathematicians will be explained, compared, and contrasted. The relationship to the development of calculus will also be considered and explained. The goal of this paper is to illustrate the importance of the curve and why it must be studied will be demonstrated in this paper.

Using Machine Learning to Analyze Athletic Mechanics During Movement
Jacob Bell
Mentor: Dr. Ryan Botts
2020 Summer Research at 国产剧麻豆剧

Stitching Together a Decade of Survey Data
Sean Lovullo
Mentor: Dr. Greg Crow
2020 Summer Research at 国产剧麻豆剧

Applications of Abstract Algebra to Cryptography
Anthony Marciel
Mentor: Dr. Jesus Jimenez
2020 Summer Research at 国产剧麻豆剧

Integrating AWS Cloud Technologies into a Special Topics Course
Jasmine Yabut
Mentor: Dr. Mike Leih
2020 Summer Research at 国产剧麻豆剧

2018-19 Student Research

Homomorphic Encryption

Bryan Tapley
Mentor: Jes煤s Jim茅nez

We study a homomorphic encryption scheme, which allows operations to be performed on data while it is encrypted. This scheme is implemented using polynomial rings in SageMath. The construction of irreducible polynomials in a given field is considered. Isomorphisms between two fields are found, and the method is evaluated.

Torus Knots

Moyra Dyer
Mentor: Catherine Crockett

A knot is a closed curve in space that does not intersect itself. A double (triple) crossing is where two (three) strands of the knot meet. A specific family of knots, namely torus knots, is studied. The relationship between the number of double crossings and triple crossings is investigated for certain torus knots.

Computational Analysis of the Relationships Between Antibiotic Resistance and Plasmid Backbone Genes

Mariele Lensink
Mentor: Ryan Botts

Plasmid-encoded antibiotic resistance is a growing public health threat. Understanding relationships between antibiotic resistance genes (ARGs) and plasmid backbone structure would provide insight into how bacterial plasmids acquire such genes. This computational analysis characterizes plasmids by determining insertion patterns of ARGs most frequently associated with given plasmid backbones.

Predator-Prey Relationships for Coyote (Canis latrans), Ocelot (Leopardus pardalis), and Puma (Puma concolor) in Costa Rican Ecosystems

Amy Eppert
Mentor: Mike Mooring and Ryan Botts

Based on a camera trap survey in the Talamanca Cordillera of Costa Rica, we determined that Neotropical mammalian predators differed in their prey selection method: some species selected the most abundant prey, others preferred certain species regardless of abundance, and some used a combination of both methods.

Do you know what you just agreed to?

Briget Fortin and Allison Hale

Mentor: Lori Carter

We look at the transparency of large companies specifically regarding their user agreements. We evaluated user agreements based on word count, difficulty of words, sentence length etc using computational analysis.

How well does your computer know you?

Whitney Featherston and Mairele Lensink

Mentor: Lori Carter

Survey study analyzing the frequency and effectiveness of micro-targeted advertising. We used various skills and programs from our data management course, taught by Dr. Lori Carter, to collect and sort through data, discover and determine significant patterns, and present it in an intelligible way. Our study revealed that micro-targeted advertising is both frequent and effective in the lives of 国产剧麻豆剧 students - decreasing their focus and persuading them to deviate from their intended work.

Computational Analysis of the Relationships Between Mobile Genetic Elements, Accessory Genes and Plasmid Backbone Genes

Mariele Lensink

Mentor: Ryan Botts, Lori Carter, Dave Cummings, and Dawne Page

Honors project utilizing programming and bioinformatics methods to uncover the relationships between genes coding for antibiotic resistance and the backbone structure of plasmids found in bacteria. This new bioinformatics tool provides insight into how bacterial plasmids acquire such genes and makes data readily available for scientist to conduct more directed research in plasmid biology.

Crowdfunding Website Promotes Charitable Giving

Amy Eppert and Gabrielle Hovis

Mentor: Lori Carter

We analyzed fundraising campaigns from the website, gofundme, to evaluate the role of online and mobile giving platforms and the modern nature of charitable giving

Privacy Concerns Of Publicly Available Aircraft Data

Steven Dols

Mentor: Benjamin Mood