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2023

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Articles 1 - 14 of 14

Full-Text Articles in Computer Sciences

Toxic Comment Classification Project, Brandon Solon Nov 2023

Toxic Comment Classification Project, Brandon Solon

Symposium of Student Scholars

The digital landscape has blossomed thanks to the surge of online platforms, boosting the variety and volume of user-created content. But it's not without its shadows; cyberbullying and hate speech have also proliferated, making web spaces less safe. At our project centerstage, we work on creating a machine learning model skilled at spotting toxic comments with precision - this way contributing towards an internet society free from fear or discomfort. We put well-documented datasets to good use along with careful preprocessing maneuvers while trialing diverse machina-learning protocols as part of constructing solid classification architecture for usages beyond current limitations within …

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Artificial Intelligence History, And Libraries: History And Legacy Of Library Contributions To Machine Learning, Wilhelmina Randtke Oct 2023

Artificial Intelligence History, And Libraries: History And Legacy Of Library Contributions To Machine Learning, Wilhelmina Randtke

Library Faculty Presentations

Machine learning seems to be newly everywhere. It's not new, so much as faster processing makes it newly useful. Imagine an automated cataloging program that takes 300 years to run, versus one that takes a week to run. Increased processing speed is a substantive change. This presentation overviews the history of libraries and artificial intelligence. First, teasing out past applications of machine learning in libraries. High quality results and concrete applications of artificial intelligence in libraries have been explored and published for decades. Over time, faster processing allows use at scale. Second, how library and metadata work contributes to machine …

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Sentiment Analysis Before And During The Covid-19 Pandemic, Emily Musgrove Jul 2023

Sentiment Analysis Before And During The Covid-19 Pandemic, Emily Musgrove

Mathematics Summer Fellows

This study examines the change in connotative language use before and during the Covid-19 pandemic. By analyzing news articles from several major US newspapers, we found that there is a statistically significant correlation between the sentiment of the text and the publication period. Specifically, we document a large, systematic, and statistically significant decline in the overall sentiment of articles published in major news outlets. While our results do not directly gauge the sentiment of the population, our findings have important implications regarding the social responsibility of journalists and media outlets especially in times of crisis.

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Blind Fighter – A Video Game For The Visually Impaired, Avery Wayne Harrah Apr 2023

Blind Fighter – A Video Game For The Visually Impaired, Avery Wayne Harrah

ATU Research Symposium

Blind Fighter is a video game made to be playable by anyone, regardless of any visual impairments the player may have. The game relies on auditory queues to allow players to understand what is happening in the game without ever having to see the screen. The project’s goal is to serve as a proof of concept that video games can be made inclusive with a few additions during development, without sacrificing overall quality. To do this, the game features full graphics in addition to testing many strategies for visually impaired players, including direction-based audio, unique sound effects for each game …

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Crime Prediction Using Machine Learning: The Case Of The City Of Little Rock, Zurab Sabakhtarishvili, Sijan Panday, Clayton Jensen Apr 2023

Crime Prediction Using Machine Learning: The Case Of The City Of Little Rock, Zurab Sabakhtarishvili, Sijan Panday, Clayton Jensen

ATU Research Symposium

Crime is a severe problem in the city of Little Rock, Arkansas. In this study, we aim to develop a machine-learning model to predict criminal activities in the city and provide insights into crime patterns. We will analyze publicly available crime datasets from Little Rock Police Department from January 2017 to March 2023 to identify trends and patterns in crime occurrence. We used data cleaning and exploratory data analysis techniques, such as figured-based visualizations, to prepare the data for machine learning. We will employ the Neural Prophet, a time-series machine learning model, to predict daily crime counts. The model will …

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Reworking Of The Arkansas Tech Human Resources Employee Records Software, Dalton J. George, Brayan Bonilla-Chavez, John Modica, Angelina Das Apr 2023

Reworking Of The Arkansas Tech Human Resources Employee Records Software, Dalton J. George, Brayan Bonilla-Chavez, John Modica, Angelina Das

ATU Research Symposium

Evisions Argos is a real-time reporting tool used by Arkansas Tech in many record-keeping departments. Reworking HR's software using this tool, security and database access concerns were negated, as Argos is already connected to the University's backend. Using Argos, we have made ATU HR's employee records software more user friendly and built a system that can be pushed to production for use by the university. As a secondary portion to this final project, we developed a proof-of-concept web application using the MEAN (Mongo, Express, Angular, Node) stack. This gave us the opportunity to produce a full-stack application from scratch as …

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The Ozark Getaway, Houston Barber, Marcus Gasca, Evan Reece Matlock, Avery Wayne Harrah Apr 2023

The Ozark Getaway, Houston Barber, Marcus Gasca, Evan Reece Matlock, Avery Wayne Harrah

ATU Research Symposium

Website designed for usage of renting AirBnb houses outside of the original website under the specific owner.

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Premium Wireless, Dakota Burkhart, Andrew Clark, Garrett Kenney, Brandon Monroe Apr 2023

Premium Wireless, Dakota Burkhart, Andrew Clark, Garrett Kenney, Brandon Monroe

ATU Research Symposium

Our work implements an inventory system and appointment system for the Premium Wireless phone company. It includes separate views for employees to manage inventory and view appointments for the day and the near future and allows customers to view all current inventory and set an appointment.

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Arkavalley Liquor: Simplifying Restaurant Alcohol Orders, Isaiah A. Kitts, Dayton Drilling, Bradlee Treece, Cameron Lumpkin Apr 2023

Arkavalley Liquor: Simplifying Restaurant Alcohol Orders, Isaiah A. Kitts, Dayton Drilling, Bradlee Treece, Cameron Lumpkin

ATU Research Symposium

The ArkaValley Liquor system is a web-based ordering platform designed to simplify the process of ordering alcohol for local restaurants. Currently, restaurants place orders by emailing the store, which makes it difficult to maintain a paper trail and track order details. With the ArkaValley Liquor system, the ordering process is automated, and all order details are saved in one central location. Each restaurant will have a login, ensuring only authorized individuals can place orders. The system will also provide a record of each restaurant's most recent order, making it easy to reorder if necessary. By using the ArkaValley Liquor system, …

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Nviz: Unraveling Neural Networks Through Visualization, Kevin Hoffman Apr 2023

Nviz: Unraveling Neural Networks Through Visualization, Kevin Hoffman

Mathematics and Computer Science Presentations

The growing utility of artificial intelligence (AI) is attributed to the development of neural networks. These networks are a class of models that make predictions based on previously observed data. While the inferential power of neural networks is great, the ability to explain their results is difficult because the underlying model is automatically generated. The AI community commonly refers to neural networks as black boxes because the patterns they learn from the data are not easily understood. This project aims to improve the visibility of patterns that neural networks identify in data. Through an interactive web application, NVIZ affords the …

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R Text Analysis For Adam Smith Cie Selected Works, Charlotte Grahame Apr 2023

R Text Analysis For Adam Smith Cie Selected Works, Charlotte Grahame

Mathematics and Computer Science Presentations

Text mining and text analysis is a way of understanding text documents using r coding that is more frequently used for numbered data. It helps with understanding portions of the text and drawing conclusions from there. This research looks specifically at the Adam Smith required documents that are used in the CIE course designated for freshmen. It looks at sentiments of the documents, including word sentiment, sentence sentiment, page and overall document sentiment as well. It provides visuals of word clouds to portray word frequency, tf-idf (which is explained in the presentation) and bigram analysis.

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Cie Text Analysis: Narrative Of The Life Of Frederick Douglass, The Declaration Of Independence, And The Declaration Of Sentiments, Arianna Knipe Apr 2023

Cie Text Analysis: Narrative Of The Life Of Frederick Douglass, The Declaration Of Independence, And The Declaration Of Sentiments, Arianna Knipe

Mathematics and Computer Science Presentations

Our STAT-451 class has worked with analyzing the words from CIE texts and assigning them to a sentiment or feeling and comparing them with one another using RStudio. This project analyzes texts from three sources: The Narrative of the Life of Frederick Douglass, The Declaration of Independence and the Declaration of Sentiments.

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Generation Z Cybersecurity Learners: The Identification Of Cybersecurity Instructor Strategies And Attributes That Maximize Student Engagement, Jeffrey Rice Apr 2023

Generation Z Cybersecurity Learners: The Identification Of Cybersecurity Instructor Strategies And Attributes That Maximize Student Engagement, Jeffrey Rice

Scholar Week 2016 - present

There exists a significant shortage of cybersecurity specialists in the workforce. Universities should endeavor to keep cybersecurity students engaged if they desire to be competitive and contribute graduates to the remediation efforts of this cybersecurity deficit. Instructors significantly contribute to student engagement and there is a correlation between student engagement and student retention. The purpose of this regional qualitative exploratory study was to identify attributes that Generation Z collegiate cybersecurity learners felt kept them engaged in their cybersecurity courses. The sample comprised 10 individuals identified as GenZ and used purposeful and snowball sampling to select participants. A semi-structured interview strategy …

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Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle Feb 2023

Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle

SDSU Data Science Symposium

In the era of big data, there is a need for forecasting high-dimensional time series that might be incomplete, sparse, and/or nonstationary. The current research aims to solve this problem for two-dimensional data through a combination of temporal matrix factorization (TMF) and low-rank tensor factorization. From this method, we propose an expansion of TMF to two-dimensional data: temporal tensor factorization (TTF). The current research aims to interpolate missing values via low-rank tensor factorization, which produces a latent space of the original multilinear time series. We then can perform forecasting in the latent space. We present experimental results of the proposed …

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