Carroll College Student Undergraduate Research Festival 2021

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https://carrollscholars.dspace7.dspace-express.com/handle/20.500.12647/10359

The Student Undergraduate Research Festival (SURF) is a celebration of the research done by Carroll College students. The event occurs every April, and everyone is invited to attend. SURF is seen as the highlight of the year for all of the students doing research, and it is a wonderful opportunity for other Carroll students, Carroll faculty and staff members, and community members to see the amazing work done by our students. Our students are very excited to share their research during this time of student-driven, inquiry-oriented learning.

2021 is a Digital SURF

Due to the worldwide COVID-19 pandemic, we are holding a Digital SURF event this year on Friday, April 23. Researchers have posted videos of their presentations on Carroll Scholars for the public and members of the Carroll community to view. These can be accessed using the links below.

Questions? Maria Larson at mjlarson@carroll.edu

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Now showing 1 - 5 of 94

A Deep Learning Approach to Dermatology
(2021-04-22) Norton, Madeline; Sullivan, Eric
Skin cancer is one of the most common cancers not only in the United States, but also worldwide, with almost 10,000 people in the U.S. being diagnosed with it every day. Early detection is important in order to save the lives of the affected patients. Computer aided diagnostic systems, such as Neural Networks, can drastically aid physicians to detect skin cancer in the early stages and avoid unnecessary biopsies, improving patient care and reducing cost. Moreover, portable systems and even mobile apps, without of course replacing physicians, assist people by providing suggested diagnoses that can act as a warning sign and lead to the early detection of skin lesions. With the goal of creating a portable system that is accessible to various health care facilities, I built upon a Convolutional Neural Network previously designed for the concept. In this, the system is able to take in images and assess what type of skin lesion is captured. This model is then compared to the diagnosis of a trained Physician to see how well it performs comparatively.
Autoencoders
(2021-04-22) Davidson, Shirley; Sullivan, Eric
A Neural Network is a statistical tool that aids in the classification of data points for machine learning. Autoencoders are a type of neural network that are capable of learning large amounts of data without being supervised by labeled training data. We use autoencoders to help with the curse of dimensionality, a common data science problem that involves an excess number of predicting variables. Autoencoders can build models while only using the most important information. In this presentation, we are going to look at three different types of autoencoders and analyze the results to see which performs better. The different methods we will explore are stacked, convolutional, and denoising. We will apply these autoencoders to an image classification problem, intending to achieve data compression.
Work and Labor Songs in 20th Century America
(2020-05) Duff, Arizona; Fregulia, Jeanette; Marchesini, Maren
Explore the relationship between labor and work songs and unionizing efforts in America from the industrial revolution to the present! How did song influence the formation of unions? What did the miners in Butte, Montana sing about, and how do we remember these songs today? In this presentation you’ll learn about the popular work songs sung in America, the roots of some of these songs, often stemming from unexpected places, and the role they played in the labor industry at the time.
Synthesis of Renewable Surfactants
(2021) Sablan, Olivia; Carpenter, Chrissie
Herbicides have been widely used for decades to kill off weeds and help crops thrive. The active ingredient in most commercially available herbicides is glyphosate, which works to eliminate plants by preventing protein synthesis. The wide use of herbicides has become a concern in recent years because of the potential to cause cancer. Although literature suggests that glyphosate is not carcinogenic, the surfactant which is used to disperse the herbicide may be toxic. Surfactants aid in dispersal of the herbicide by decreasing surface tension. The synthesis and characterization of broad-based herbicides, like Roundup® is not easily accessible, therefore the identity of the potentially harmful surfactants is unknown. The goal of this study was to synthesize a surfactant from natural materials to provide a less toxic, renewable alternative. The reagents used for the synthesis include carbohydrates and fatty acids, which are naturally occurring and easy to obtain from plants. The carbohydrates were used to form polar head groups, and the fatty acids were used to synthesize non polar tails. Multiple monosaccharides were attempted to convert to a surfactant, including galactose and xylose.
Expansion of Livingston Airport Turnarounds
(2021-04-11) Little, Lauren; Maccoun, Skyler; Fischer, Gary
The Livingston Airport (LVM) is located in Livingston, Montana in Park County. The population is roughly 8,000 people, however, due to its location, the airport has a high volume of tourist traffic. The high demand calls for the airport turnarounds to be expanded to accommodate larger aircraft. The expansion designs met all Federal Aviation Administration (FAA) requirements for aircraft loading up to 45,000 lbs for a single wheel and 99,999 lbs for dual wheels. The project meets design criteria while minimizing environmental impacts and providing a sustainable option. Four expansion alternatives were analyzed to ensure the needs of the airport were met. Calculations and designs were based on a current geotechnical report and site survey. The expansions and improvements to the turnarounds will allow for plane maneuvers to be in accordance with regulations while keeping all pilots and passengers safe. The turnaround improvements will help maintain and improve tourist numbers and provide revenue for the Livingston area.

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