Digital Commons Network^™

Phoneme Recognition For Pronunciation Improvement, Matthew Heywood

Theses/Capstones/Creative Projects

This project aims to improve English pronunciation by investigating speech errors and developing a tool to provide precise feedback. The study focuses on creating a new pronunciation tool that offers localized feedback, identifies specific errors, and suggests corrective measures. By addressing the shortcomings of current methods, this research seeks to enhance pronunciation refinement.

Utilizing cutting-edge technology, the tool leverages speech-to-phoneme AI models and modified lazy string matching algorithms to compare the user's spoken input with the intended pronunciation. This allows for a detailed analysis of discrepancies, providing users actionable insights into their phonetic errors. The speech-to-phoneme AI models mark a …

Enabling Iov Communication Through Secure Decentralized Clustering Using Federated Deep Reinforcement Learning, Chandler Scott

Electronic Theses and Dissertations

The Internet of Vehicles (IoV) holds immense potential for revolutionizing transporta- tion systems by facilitating seamless vehicle-to-vehicle and vehicle-to-infrastructure communication. However, challenges such as congestion, pollution, and security per- sist, particularly in rural areas with limited infrastructure. Existing centralized solu- tions are impractical in such environments due to latency and privacy concerns. To address these challenges, we propose a decentralized clustering algorithm enhanced with Federated Deep Reinforcement Learning (FDRL). Our approach enables low- latency communication, competitive packet delivery ratios, and cluster stability while preserving data privacy. Additionally, we introduce a trust-based security framework for IoV environments, integrating a central authority …

Creating A Virtual Hierarchy From A Relational Database, Yucong Mo

All Graduate Theses and Dissertations, Fall 2023 to Present

In data management and modeling, the value of the hierarchical model is that it does not require expensive JOIN operations at runtime; once the hierarchy is built, the relationships among data are embedded in the tree-like hierarchical structure, and thus querying data could be much faster than using a relational database. Today most data is stored in relational databases, but if the data were stored in hierarchies, what would these hierarchies look like? And more importantly, would this transition lead to a more efficient database? This thesis explores these questions by introducing a set of algorithms to convert a relational …

Context In Computer Vision: A Taxonomy, Multi-Stage Integration, And A General Framework, Xuan Wang

Dissertations, Theses, and Capstone Projects

Contextual information has been widely used in many computer vision tasks, such as object detection, video action detection, image classification, etc. Recognizing a single object or action out of context could be sometimes very challenging, and context information may help improve the understanding of a scene or an event greatly. However, existing approaches design specific contextual information mechanisms for different detection tasks.

In this research, we first present a comprehensive survey of context understanding in computer vision, with a taxonomy to describe context in different types and levels. Then we proposed MultiCLU, a new multi-stage context learning and utilization framework, …

Mending Trust In Ai: Trust Repair Policy Interventions For Large Language Models In Visual Data Journalism, Hangxiao Zhu

McKelvey School of Engineering Theses & Dissertations

Trust in Large Language Models (LLMs) emerged as a pivotal concern. This is because, despite the transformative potential of LLMs in enhancing the interpretability and interactivity of complex datasets, the opacity of these models and instances of inaccuracies or biases have led to a significant trust deficit among end-users. Moreover, there is a tendency for people to personify AI tools that utilize these LLMs, attributing abilities and sensibilities that they do not truly possess. This thesis exploits this personification and proposes a comprehensive framework of trust repair policies tailored to address the challenges inherent in LLM annotations within data journalism …

Companionship, Romance, And Self-Perception With Conversational Chatbots, Jonathan Windsor

Student Research Submissions

Serving as a metaphorical gateway transcending the communicative barriers of physical relationships in interpersonal dialogues, artificial imators of human behavior and speech, also known as conversational chatbots; a simulation of human knowledge and existence in a bi-directional conversation, functions as a rhetor of expression. Spanning from contexts of professional to romantic, I serve to dissect and critically analyze the nuances of human-machine relationships based on pre-established literature, inviting ethical considerations and biases in their design and marketing. Corporate influences spark pre-established servitude-esque relationships with conversational agents. Professional applications, both task-oriented and emotionally based alike, paint a mixed picture of …

A Nlp Approach To Automating The Generation Of Surveys For Market Research, Anav Chug

Honors College Theses

Market Research is vital but includes activities that are often laborious and time consuming. Survey questionnaires are one possible output of the process and market researchers spend a lot of time manually developing questions for focus groups. The proposed research aims to develop a software prototype that utilizes Natural Language Processing (NLP) to automate the process of generating survey questions for market research. The software uses a pre-trained Open AI language model to generate multiple choice survey questions based on a given product prompt, send it to a targeted email list, and also provides a real-time analysis of the responses …

The Impact Of Heterogeneous Voting Strategies And Candidate Issue Adaptation On Elections: An Agent-Based Model, Harmony Peura

Student Research Submissions

Political candidates in a democracy articulate positions on the issues of the day, but they are also highly aware of voter sentiment on those issues, and tailor their campaigns accordingly as they seek to win elections. Voters, too, adjust their political opinions based on (among other things) interactions with others in their social network. I present an agent-based simulation that models this dynamic interplay between candidates and voters, in order to shed light on what outcomes candidates can expect to result from a policy of “chasing” votes. The voters in the simulation differ from one another in the decision procedure …

Artificial Intelligence's Ability To Detect Online Predators, Olatilewa Osifeso

Electronic Theses, Projects, and Dissertations

Online child predators pose a danger to children who use the Internet. Children fall victim to online predators at an alarming rate, based on the data from the National Center of Missing and Exploited Children. When making online profiles and joining websites, you only need a name, an email and a password without identity verification. Studies have shown that online predators use a variety of methods and tools to manipulate and exploit children, such as blackmail, coercion, flattery, and deception. These issues have created an opportunity for skilled online predators to have fewer obstacles when it comes to contacting and …

Crash Detecting System Using Deep Learning, Yogesh Reddy Muddam

Electronic Theses, Projects, and Dissertations

Accidents pose a significant risk to both individual and property safety, requiring effective detection and response systems. This work introduces an accident detection system using a convolutional neural network (CNN), which provides an impressive accuracy of 86.40%. Trained on diverse data sets of images and videos from various online sources, the model exhibits complex accident detection and classification and is known for its prowess in image classification and visualization.

CNN ensures better accident detection in various scenarios and road conditions. This example shows its adaptability to a real-world accident scenario and enhances its effectiveness in detecting early events. A key …

Code For Care: Hypertension Prediction In Women Aged 18-39 Years, Kruti Sheth

Electronic Theses, Projects, and Dissertations

The longstanding prevalence of hypertension, often undiagnosed, poses significant risks of severe chronic and cardiovascular complications if left untreated. This study investigated the causes and underlying risks of hypertension in females aged between 18-39 years. The research questions were: (Q1.) What factors affect the occurrence of hypertension in females aged 18-39 years? (Q2.) What machine learning algorithms are suited for effectively predicting hypertension? (Q3.) How can SHAP values be leveraged to analyze the factors from model outputs? The findings are: (Q1.) Performing Feature selection using binary classification Logistic regression algorithm reveals an array of 30 most influential factors at an …

Guardians Of The Data: Government Use Of Ai And Iot In The Digital Age, Jannat Saeed

Honors Theses

The exponential growth of technology, epitomized by Moore's Law – “the observation that the number of transistors on an integrated circuit will double every two years”– has propelled the swift evolution of Artificial Intelligence (AI) and Internet of Things (IoT) technologies. This phenomenon has revolutionized various facets of daily life, from smart home devices to autonomous vehicles, reshaping how individuals interact with the world around them. However, as governments worldwide increasingly harness these innovations to monitor and collect personal data, profound privacy concerns have arisen among the general populace. Despite the ubiquity of AI and IoT in modern society, formal …

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 …

Evaluation Of An End-To-End Radiotherapy Treatment Planning Pipeline For Prostate Cancer, Mohammad Daniel El Basha, Court Laurence, Carlos Eduardo Cardenas, Julianne Pollard-Larkin, Steven Frank, David T. Fuentes, Falk Poenisch, Zhiqian H. Yu

Dissertations & Theses (Open Access)

Radiation treatment planning is a crucial and time-intensive process in radiation therapy. This planning involves carefully designing a treatment regimen tailored to a patient’s specific condition, including the type, location, and size of the tumor with reference to surrounding healthy tissues. For prostate cancer, this tumor may be either local, locally advanced with extracapsular involvement, or extend into the pelvic lymph node chain. Automating essential parts of this process would allow for the rapid development of effective treatment plans and better plan optimization to enhance tumor control for better outcomes.

The first objective of this work, to automate the treatment …

A Review Of Student Attitudes Towards Keystroke Logging And Plagiarism Detection In Introductory Computer Science Courses, Caleb Syndergaard

All Graduate Theses and Dissertations, Fall 2023 to Present

The following paper addresses student attitudes towards keystroke logging and plagiarism prevention measures. Specifically, the paper concerns itself with changes made to the “ShowYourWork” plugin, which was implemented to log the keystrokes of students in Utah State University’s introductory Computer Science course, CS1400. Recent work performed by the Edwards Lab provided insights into students’ feelings towards keystroke logging as a measure of deterring plagiarism. As a result of that research, we have concluded that measures need to be taken to enable students to have more control over their data and assist students to feel more comfortable with keystroke logging. This …

A Framework That Explores The Cognitive Load Of Cs1 Assignments Using Pausing Behavior, Joshua O. Urry

All Graduate Theses and Dissertations, Fall 2023 to Present

Pausing behavior in introductory Computer Science (CS1) courses has been related to a student’s performance in the course and could be linked to a student’s cognitive load, or assignment difficulty. Having an objective measure of the cognitive load would be beneficial to course instructors as it would help them design assignments that are not too difficult. Two studies are presented in this work. The first study uses Cognitive Load Theory and Vygotsky’s Zone of Proximal Development as a theoretical framework to analyze pause times between keystrokes to better understand what types of assignments need more educational support than others. The …

Inferring A Hierarchical Input Type For An Sql Query, Santosh Aryal

All Graduate Theses and Dissertations, Fall 2023 to Present

SQL queries are a common method to retrieve information from databases, much like asking a detailed question and getting a precise answer. Plug-and-play queries simplify the process of querying. In a Plug-and-play SQL query a programmer sketches the shape of the input to the query as a hierarchy. But the programmer could make a mistake in specifying the hierarchy and it takes programmer time and effort to specify the hierarchy. A better solution is to automatically infer the hierarchy from a query. This thesis presents a system to infer a hierarchical input type for an SQL query. We consider two …

Advancing Game Development And Ai Integration: An Extensible Game Engine With Integrated Ai Support For Real-World Deployment And Efficient Model Development, Ryan Anderson

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis introduces Acacia, a game engine with built-in artificial intelligence (AI) capabilities. Acacia allows game developers to effortlessly incorporate Reinforcement Learning (RL) algorithms into their creations. By tagging game elements to convey information about the game state or rewards, developers gain precise control over how RL algorithms interact with their games, mirroring real player behavior or providing full knowledge of the game world.

To showcase Acacia’s versatility, the thesis presents three games across different genres, each demonstrating the engine’s AI plugin. The goal is to establish Acacia as a preferred resource for creating 2D games with RL support without …

Analysis And Numerical Simulation Of Tumor Growth Models, Daniel Acosta Soba

Masters Theses and Doctoral Dissertations

In this dissertation we focus on the numerical analysis of tumor growth models. Due to the difficulty of developing physically meaningful approximations of such models, we divide the main problem into more simple pieces of work that are addressed in the different chapters. First, in Chapter 2 we present a new upwind discontinuous Galerkin (DG) scheme for the convective Cahn–Hilliard model with degenerate mobility which preserves the pointwise bounds and prevents non-physical spurious oscillations. These ideas are based on a well-suited piecewise constant approximation of convection equations. The proposed numerical scheme is contrasted with other approaches in several numerical experiments. …

Decentralized Unknown Building Exploration By Frontier Incentivization And Voronoi Segmentation In A Communication Restricted Domain, Huzeyfe M. Kocabas

All Graduate Theses and Dissertations, Fall 2023 to Present

Exploring unknown environments using multiple robots poses a complex challenge, particularly in situations where communication between robots is either impossible or limited. Existing exploration techniques exhibit research gaps due to unrealistic communication assumptions or the computational complexities associated with exploration strategies in unfamiliar domains. In our investigation of multi-robot exploration in unknown areas, we employed various exploration and coordination techniques, evaluating their performance in terms of robustness and efficiency across different levels of environmental complexity.

Our research is centered on optimizing the exploration process through strategic agent distribution. We initially address the challenge of city roadway coverage, aiming to minimize …

Exploring Decentralized Computing Using Solid And Ipfs For Social Media Applications, Pranav Balasubramanian Natarajan

Computer Science and Computer Engineering Undergraduate Honors Theses

As traditional centralized social media platforms face growing concerns over data privacy, censorship, and lack of user control, there has been an increasing interest in decentralized alternatives. This thesis explores the design and implementation of a decentralized social media application by integrating two key technologies: Solid and the InterPlanetary File System (IPFS). Solid, led by Sir Tim Berners-Lee, enables users to store and manage their personal data in decentralized "Pods," giving them ownership over their digital identities. IPFS, a peer-to-peer hypermedia protocol, facilitates decentralized file storage and sharing, ensuring content availability and resilience against censorship. By leveraging these technologies, the …

An Empirical Study On The Efficacy Of Llm-Powered Chatbots In Basic Information Retrieval Tasks, Naja Faysal

Electronic Theses, Projects, and Dissertations

The rise of conversational user interfaces (CUIs) powered by large language models (LLMs) is transforming human-computer interaction. This study evaluates the efficacy of LLM-powered chatbots, trained on website data, compared to browsing websites for finding information about organizations across diverse sectors. A within-subjects experiment with 165 participants was conducted, involving similar information retrieval (IR) tasks using both websites (GUIs) and chatbots (CUIs). The research questions are: (Q1) Which interface helps users find information faster: LLM chatbots or websites? (Q2) Which interface helps users find more accurate information: LLM chatbots or websites?. The findings are: (Q1) Participants found information significantly faster …

Investigating The Impact Of Human-Centered Interface Design On The User Experience Of Mobile Device Users, Ruchir Gupta

Theses and Dissertations

In order to investigate the intricate interaction between interface design, user technological proficiency, and other components of the user experience, this research study used a mixed-method approach. The beginner user group—those with little experience or expertise with technology - were the main target audience. The important discovery emphasizes the substantial influence that careful design can have on improving the effectiveness and usability of interfaces for non-tech-savvy individuals. When using the suggested Interface B instead of the current Interface A, beginner participants' task completion times significantly improved, according to the user study. This underlines the significance of creating with the needs …

Humanity Amid Innovation: Exploring Our Relationship To Technology, Sarah Durkee

Senior Theses and Projects

This thesis examines the impacts of technology on fundamental aspects of human nature and experience. Drawing on the works from Kant, Turing, Arendt, Benjamin, and Freud, it explores how rapid technological change is redefining human reason, intelligence, and creativity in the digital age. The first chapter analyzes whether modern online communication platforms realize or undermine Kant's vision of an enlightened public sphere fostering free discourse and critique. It argues that prioritizing engagement over substantive debate, these digital realms corrode the depth of interaction essential for cultivating human reason. The second chapter explores the pursuit of artificial intelligence as a reproduction …

Multi-Script Handwriting Identification By Fragmenting Strokes, Joshua Jude Thomas

<strong> Theses and Dissertations </strong>

This study tests the effectiveness of Multi-Script Handwriting Identification after simplifying character strokes, by segmenting them into sub-parts. Character simplification is performed through splitting the character by branching-points and end-points, a process called stroke fragmentation in this study. The resulting sub-parts of the character are called stroke fragments and are evaluated individually to identify the writer. This process shares similarities with the concept of stroke decomposition in Optical Character Recognition which attempts to recognize characters through the writing strokes that make them up. The main idea of this study is that the characters of different writing‑scripts (English, Chinese, etc.) may …

The Impact Of Ai On Ux: Challenges And Opportunities, Susan Stephanie Wells

Theses

Integrating artificial intelligence (AI) in user experience (UX) design is reshaping the field of UX, offering new opportunities and challenges for designers. This thesis project explores the multifaceted relationship between AI and UX design, focusing on the challenges, opportunities, and skills demanded of UX designers in the age of AI. Through a review of academic research and real-world experiences, this project studies the impact of AI on web design processes, UX testing, and data analysis. Key findings highlight the transformative potential of AI in enhancing user experiences, from suggesting website structures to facilitating UX testing and data analysis.

Comparative analysis …

White Cell Support Application For Expo Ops Tactical Wargame System, Zackery Joseph Milder

Theses

The purpose of this project was to create a support application for a tabletop wargame currently used for training and scenario simulation by the United States Marine Corps. The EXPO OPS Companion is meant to enhance the capabilities of the White Cell/table director, the unbiased third party responsible for running adjudication for the EXPO OPS Tactical Wargames System. EXPO OPS TWS is “…a table top wargame covering contemporary and future conflict at the platoon, company and battalion level. It is a wargame toolkit that enables wargaming scenarios in the 2020 to 2030 timeframe. The design centers on plans and decisions …

Improving The Scalability Of Neural Network Surface Code Decoders, Kevin Wu

Undergraduate Honors Theses

Quantum computers have recently gained significant recognition due to their ability to solve problems intractable to classical computers. However, due to difficulties in building actual quantum computers, they have large error rates. Thus, advancements in quantum error correction are urgently needed to improve both their reliability and scalability. Here, we first present a type of topological quantum error correction code called the surface code, and we discuss recent developments and challenges of creating neural network decoders for surface codes. In particular, the amount of training data needed to reach the performance of algorithmic decoders grows exponentially with the size of …

Code Syntax Understanding In Large Language Models, Cole Granger

Undergraduate Honors Theses

In recent years, tasks for automated software engineering have been achieved using Large Language Models trained on source code, such as Seq2Seq, LSTM, GPT, T5, BART and BERT. The inherent textual nature of source code allows it to be represented as a sequence of sub-words (or tokens), drawing parallels to prior work in NLP. Although these models have shown promising results according to established metrics (e.g., BLEU, CODEBLEU), there remains a deeper question about the extent of syntax knowledge they truly grasp when trained and fine-tuned for specific tasks.

To address this question, this thesis introduces a taxonomy of syntax …

Evaluating Large Language Model Performance On Haskell, Andrew Chen

Undergraduate Honors Theses

I introduce HaskellEval, a Haskell evaluation benchmark for Large Language Models. HaskellEval’s curation leverages a novel synthetic generation framework, streamlining the process of dataset curation by minimizing manual intervention. The core of this research is an extensive analysis of the trustworthiness of synthetic generations, ensuring accuracy, realism, and diversity. Additional, I provide a comprehensive evaluation of existing open-source models on HaskellEval.