Other Computer Sciences Commons^™

A Case Study On Using Large Language Models To Drive Convergence-Oriented Literature Discovery In Critical Infrastructure Security, Caden J. Williamson

Electrical Engineering and Computer Science Undergraduate Honors Theses

In the world of cybersecurity, the rapid development of artificial intelligence proposes a constant challenge for researchers to defend critical infrastructure. Attacks on critical infrastructure can be catastrophic, and emerging strategies of cyber-adversaries that implement leading AI models can expose vulnerabilities in critical infrastructure much faster than previous tools. To defend against this emerging threat, the Cybersecurity Research Working Group at the University of Arkansas is aiming to develop a cross-domain and cross-discipline center of excellence. To support this effort, the group is writing a literature review on the topics of AI and critical systems security. Literature review is an …

Usage Of Natural Language Processing And Deep-Learning Techniques On Thematic Apperception Tests To Predict Big Five Personality Traits, Blayten Jones

Electrical Engineering and Computer Science Undergraduate Honors Theses

The usage of personality as a method of behavioral prediction and outcomes of success has grown considerably over the last few decades. This project explores predicting user personality profiles via the Big Five personality index through the integration of advanced natural language processing techniques as well as neural networks. Using a dataset provided by Dr. James W. Pennebaker, participants analyze an image—formally referred to as a thematic apperception test—and write a thorough paragraph describing the details. This free-form text, along with their personality test results, is captured in a structured dataset. Many deep-learning and machine learning models have been used …

Managing Graphical Fidelity With Stylized Shaders For Independent Game Development, Benjamin A. Edens

Electrical Engineering and Computer Science Undergraduate Honors Theses

This paper outlines work performed by the author within the Unity3D game engine to gain preliminary experience with technical art implementation and suggests design choices that could be useful to other students or independent game developers to manage complexity within their games while maintaining visual appeal. The final product of the discussed project is a small game consisting of an outdoor urban city environment as well as an interior aquarium environment. This paper begins with the author’s motivations and goals for the project before describing the implementation of specific aspects of technical art, including 3D modeling, rigging, animation, level design, …

An Exploration Of Procedural Methods In Game Level Design, Hector Salinas

Computer Science and Computer Engineering Undergraduate Honors Theses

Video games offer players immersive experiences within intricately crafted worlds, and the integration of procedural methods in game level designs extends this potential by introducing dynamic, algorithmically generated content that could stand on par with handcrafted environments. This research highlights the potential to provide players with engaging experiences through procedural level generation, while potentially reducing development time for game developers.

Through a focused exploration on two-dimensional cave generation techniques, this paper aims to provide efficient solutions tailored to this specific environment. This exploration encompasses several procedural generation methods, including Midpoint Displacement, Random Walk, Cellular Automata, Perlin Worms, and Binary Space …

A Survey And Comparative Study On Vulnerability Scanning Tools, Cassidy Khounborine

Computer Science and Computer Engineering Undergraduate Honors Theses

Vulnerability scanners are a tool used by many organizations and developers as part of their vulnerability management. These scanners aid in the security of applications, databases, networks, etc. There are many different options available for vulnerability scanners that vary in the analysis method they encompass or target for which they scan, among many other features. This thesis explores the different types of scanners available and aims to ease the burden of selecting the ideal vulnerability scanner for one’s needs by conducting a survey and comparative analysis of vulnerability scanners. Before diving into the vulnerability scanners available, background information is provided …

Universal Computation Using Self-Assembling, Crisscross Dna Slats, Jackson S. Bullard

Computer Science and Computer Engineering Undergraduate Honors Theses

I first give a brief introduction to formal models of computation. I then present three different approaches for computation in the aTAM. I later detail generating systems of crisscross slats given an arbitrary algorithm encoded in the form of a Turing machine. Crisscross slats show potential due to their high levels of cooperativity, so it is hoped that implementations utilizing slats are more robust to various growth errors compared to the aTAM. Finally, my software converts arbitrary crisscross slat systems into various physical representations that assist in analyzing their potential to be realized in experiments.

Linux Malware Obfuscation, Brian Roden

Computer Science and Computer Engineering Undergraduate Honors Theses

Many forms of malicious software use techniques and tools that make it harder for their functionality to be parsed, both by antivirus software and reverse-engineering methods. Historically, the vast majority of malware has been written for the Windows operating system due to its large user base. As such, most efforts made for malware detection and analysis have been performed on that platform. However, in recent years, we have seen an increase in malware targeting servers running Linux and other Unix-like operating systems resulting in more emphasis of malware research on these platforms. In this work, several obfuscation techniques for Linux …

Ransomware And Malware Sandboxing, Byron Denham

Computer Science and Computer Engineering Undergraduate Honors Theses

The threat of ransomware that encrypts data on a device and asks for payment to decrypt the data affects individual users, businesses, and vital systems including healthcare. This threat has become increasingly more prevalent in the past few years. To understand ransomware through malware analysis, care must be taken to sandbox the ransomware in an environment that allows for a detailed and comprehensive analysis while also preventing it from being able to further spread. Modern malware often takes measures to detect whether it has been placed into an analysis environment to prevent examination. In this work, several notable pieces of …

A Comparison Of Word Embedding Techniques For Similarity Analysis, Tyler Gerth

Computer Science and Computer Engineering Undergraduate Honors Theses

There have been a multitude of word embedding techniques developed that allow a computer to process natural language and compare the relationships between different words programmatically. In this paper, similarity analysis, or the testing of words for synonymic relations, is used to compare several of these techniques to see which performs the best. The techniques being compared all utilize the method of creating word vectors, reducing words down into a single vector of numerical values that denote how the word relates to other words that appear around it. In order to get a holistic comparison, multiple analyses were made, with …

Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi

Computer Science and Computer Engineering Undergraduate Honors Theses

Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated generation …

Applying Emotional Analysis For Automated Content Moderation, John Shelnutt

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing …

Trunctrimmer: A First Step Towards Automating Standard Bioinformatic Analysis, Z. Gunner Lawless, Dana Dittoe, Dale R. Thompson, Steven C. Ricke

Computer Science and Computer Engineering Undergraduate Honors Theses

Bioinformatic analysis is a time-consuming process for labs performing research on various microbiomes. Researchers use tools like Qiime2 to help standardize the bioinformatic analysis methods, but even large, extensible platforms like Qiime2 have drawbacks due to the attention required by researchers. In this project, we propose to automate additional standard lab bioinformatic procedures by eliminating the existing manual process of determining the trim and truncate locations for paired end 2 sequences. We introduce a new Qiime2 plugin called TruncTrimmer to automate the process that usually requires the researcher to make a decision on where to trim and truncate manually after …

An Exploration Of Methods For Classifying Air-Written Letters From The Spanish Alphabet, Manuel Serna-Aguilera

Computer Science and Computer Engineering Undergraduate Honors Theses

The ability to recognize human activity, especially air-writing, is an interesting challenge as one could identify any letter from many languages. I intend to investigate this problem of air-writing, but with the added twist of including the following letters from the Spanish alphabet: Á, É, Í, Ó, Ú, Ü, and Ñ. With this new alphabet, I set out to see what kinds of classifiers work best and on what kinds of data, since letters can be represented in multiple ways.

My tracking system will consist of a regular camera and a subject who will draw with a brightly colored marker …

Incorporating Word Order Explicitly In Glove Word Embedding, Brandon Cox

Computer Science and Computer Engineering Undergraduate Honors Theses

Word embedding is the process of representing words from a corpus of text as real number vectors. These vectors are often derived from frequency statistics from the source corpus. In the GloVe model as proposed by Pennington et al., these vectors are generated using a word-word cooccurrence matrix. However, the GloVe model fails to explicitly take into account the order in which words appear within the contexts of other words. In this paper, multiple methods of incorporating word order in GloVe word embeddings are proposed. The most successful method involves directly concatenating several word vector matrices for each position in …

Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang

Journal of the Arkansas Academy of Science

The purpose of this paper is to introduce deep learning-based framework LeNet-5 architecture and implement the experiments for functional MRI image classification of Autism spectrum disorder. We implement our experiments under the NVIDIA deep learning GPU Training Systems (DIGITS). By using the Convolutional Neural Network (CNN) LeNet-5 architecture, we successfully classified functional MRI image of Autism spectrum disorder from normal controls. The results show that we obtained satisfactory results for both sensitivity and specificity.

Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant

Journal of the Arkansas Academy of Science

This paper discusses data pertaining to space missions to astronomical bodies beyond earth. The analyses provide summarizing facts and graphs obtained by mining data about (1) missions launched by all countries that go to the moon and planets, and (2) Earth satellites obtained from a Union of Concerned Scientists (UCS) dataset and lists of publically available satellite data.

Simulating Foodborne Pathogens In Poultry Production And Processing To Defend Against Intentional Contamination, Silas B. Lankford

Computer Science and Computer Engineering Undergraduate Honors Theses

There is a lack of data in recent history of food terrorism attacks, and as such, it is difficult to predict its impact. The food supply industry is one of the most vulnerable industries for terrorist threats while the poultry industry is one of the largest food industries in the United States. A small food terrorism attack against just a single poultry processing center has the potential to affect a much larger population than its immediate consumers. In this work, the spread of foodborne pathogens is simulated in a poultry production and processing system to defend against intentional contamination. An …

Improving Electroencephalography-Based Imagined Speech Recognition With A Simultaneous Video Data Stream, Sarah J. Stolze

Computer Science and Computer Engineering Undergraduate Honors Theses

Electroencephalography (EEG) devices offer a non-invasive mechanism for implementing imagined speech recognition, the process of estimating words or commands that a person expresses only in thought. However, existing methods can only achieve limited predictive accuracy with very small vocabularies; and therefore are not yet sufficient to enable fluid communication between humans and machines. This project proposes a new method for improving the ability of a classifying algorithm to recognize imagined speech recognition, by collecting and analyzing a large dataset of simultaneous EEG and video data streams. The results from this project suggest confirmation that complementing high-dimensional EEG data with similarly …

Acceleration Of Ddscat Computation By Parallelization On A Supercomputer, Manoj V. Seeram

Chemical Engineering Undergraduate Honors Theses

The DDSCAT software is enabled for use of MPI or OpenMP to distribute calculation of different particle orientations amongst multiple processors on a high performance system. Run times for these simulations have been tested to take hours or days however and simulating varying orientations is not always necessary. If a simulation with only one particle orientation is submitted, DDSCAT could still potentially parallelize the simulation by wavelength calculations but it is unknown if this is the case. In this paper, we will be (i) quantifying the reduction in computation time that MPI provides relative to an equivalent MPI disabled simulation …

Neural Decomposition Of Time-Series Data For Effective Generalization, Luke Godfrey

Graduate Theses and Dissertations

We present a neural network technique for the analysis and extrapolation of time-series data called Neural Decomposition (ND). Units with a sinusoidal activation function are used to perform a Fourier-like decomposition of training samples into a sum of sinusoids, augmented by units with nonperiodic activation functions to capture linear trends and other nonperiodic components. We show how careful weight initialization can be combined with regularization to form a simple model that generalizes well. Our method generalizes effectively on the Mackey-Glass series, a dataset of unemployment rates as reported by the U.S. Department of Labor Statistics, a time-series of monthly international …

Overcoming Roadblocks In Introducing Virtual World Technology To High Schools, Casey Dylan Bailey

Graduate Theses and Dissertations

The EAST (Environmental And Spatial Technology) Initiative is a non-profit educational organization that provides students in over two hundred schools in eight states with access to advanced computing technologies for the purpose of enabling students to develop technical skills early and to produce solutions to local community problems. Although many high-end technologies are available through EAST, they are desktop solutions that individual students use and there are none that enable students within a school or between schools to collaborate.

This thesis is a saga that documents the identification and removal of many roadblocks to introducing a 3D multi-user virtual simulation …

A Comparison Of Dropout And Weight Decay For Regularizing Deep Neural Networks, Thomas Grant Slatton

Computer Science and Computer Engineering Undergraduate Honors Theses

In recent years, deep neural networks have become the state-of-the art in many machine learning domains. Despite many advances, these networks are still extremely prone to overfit. In neural networks, a main cause of overfit is coadaptation of neurons which allows noise in the data to be interpreted as meaningful features. Dropout is a technique to mitigate coadaptation of neurons, and thus stymie overfit. In this paper, we present data that suggests dropout is not always universally applicable. In particular, we show that dropout is useful when the ratio of network complexity to training data is very high, otherwise traditional …

A Bandwidth-Conserving Architecture For Crawling Virtual Worlds, Dipesh Gautam

Graduate Theses and Dissertations

A virtual world is a computer-based simulated environment intended for its users to inhabit via avatars. Content in virtual worlds such as Second Life or OpenSimulator is increasingly presented using three-dimensional (3D) dynamic presentation technologies that challenge traditional search technologies. As 3D environments become both more prevalent and more fragmented, the need for a data crawler and distributed search service will continue to grow. By increasing the visibility of content across virtual world servers in order to better collect and integrate the 3D data we can also improve the crawling and searching efficiency and accuracy by avoiding crawling unchanged regions …

Gesture Based Home Automation For The Physically Disabled, Alexander Hugh Nelson

Graduate Theses and Dissertations

Paralysis and motor-impairments can greatly reduce the autonomy and quality of life of a patient while presenting a major recurring cost in home-healthcare. Augmented with a non-invasive wearable sensor system and home-automation equipment, the patient can regain a level of autonomy at a fraction of the cost of home nurses. A system which utilizes sensor fusion, low-power digital components, and smartphone cellular capabilities can extend the usefulness of such a system to allow greater adaptivity for patients with various needs. This thesis develops such a system as a Bluetooth enabled glove device which communicates with a remote web server to …

An Introductory Educational Board Game For Use In Early Computer Science Education, Tyler Moore

Computer Science and Computer Engineering Undergraduate Honors Theses

Early computer science education should be necessary in high school curricula, but often it becomes inextricably linked to the act of programming instead of the study of the principles of computation. In order to divest computer science from programming a new teaching medium is needed, and early research into games as teaching tools shows some positive results when used properly. In order to find a better way to teach early computer science concepts I have designed and implemented a board game which illustrates and defines a few necessary computer science terms and mechanics. I had reasonable success in the classroom, …