Other Computer Sciences Commons^™

Optimizing Sensor Placement For Drone Detection According To A Grid Pattern, António Martinho Do Rosário Marçal

Masters Theses

In applications such as drone detection, it’s essential to place sensors efficiently, not only considering the cost of placement and operation, but also the maximization of the area covered.

This study presents an algorithmic approach to a placement strategy, which can be applied over any arbitrary area by defining the parameters of the grid according to which the sensors will be placed. The problem is framed as a multi-objective optimization task, considering trade-offs between sensor count and coverage.

One of the principal decision variables chosen is the shape of the cell blocks of the grid, for which two different values …

Predicting Music Origin With Deep Learning, Fruzsina Ladanyi

Electronic Theses, Projects, and Dissertations

This project explores the usage of a late fusion deep learning architecture to predict the geographic origin of music. Mel-Frequency Cepstral Coefficients (MFCCs) and the language of the music sample are used as features. MFCCs were extracted from audio files to capture sound features. The language was identified using OpenAI’s Whisper model to provide additional context. A late fusion neural network architecture combining Long Short-Term Memory (LSTM) layers for sequential MFCC input and dense layers for non-sequential language features were employed to support both classification and regression tasks. The classification model achieved an accuracy of 33.03% across 56 countries or …

Fact-Checker: A Web Application For Leveraging Large Language Models For Fact-Checking Youtube Videos, Andrew R. Craig

Electronic Theses, Projects, and Dissertations

Fact-Checker is a web application that allows users to fact-check YouTube videos. It feeds YouTube’s closed captioning transcript to a large language model (LLM) to extract claims. It then uses multiple LLMs, such as Gemini, Llama, and Claude, to verify these claims. The modular design makes it easy to change to a different LLM or model if needed. The application is built using Python for access to Application Programming Interfaces (APIs) and Streamlit as the front-end framework. The utilization of Docker and Dockerfiles enables easy distribution and deployment. It enables the application to be deployed on almost any hardware platform …

Out-Of-Band Anomaly Detection For Real Time Operating Systems, Jeffrey K. Holifield

Graduate Theses and Dissertations (2019 - present)

Real Time Operating Systems (RTOS) are increasing present throughout the industrial, business, defense, and healthcare spaces. These lightweight and efficient operating systems are designed to run on embedded, resource constrained devices, often within cyber-physical systems (CPS). A defining characteristic ofRTOSs is that they are deterministic. Tasks are scheduled to run on fixed timelines within guaranteed execution windows. In Industry 4.0 applications for example, sensors must receive and process inputs within a fixed schedule to ensure products are properly manufactured. This requires guaranteed service at fixed time periods. To accomplish this, RTOSs must conform to worst case execution times (WCETs) as …

Revolutionizing Digital Privacy Education For Older Adults: Enhanced Interventions And Ai-Assisted Learning Strategies, Heba Aly

All Dissertations

As older adults increasingly engage with digital platforms, they face unique privacy risks stemming from limited digital literacy, reduced trust in AI technologies, and constrained access—especially in rural or underserved communities. While digital tools offer benefits like social connection and information access, current privacy education efforts often neglect the needs of older adults. This dissertation addresses this gap by developing, testing, and refining digital privacy education interventions tailored for older adults, with a focus on trust, personalization, and AI-assisted learning.

Study 1 evaluates multiple instructional modalities across age groups, revealing older adults prefer structured videos and interactive tutorials, while younger …

Exploring Adversarial Threats To Neuralhash: A Perceptual Hashing Algorithm, Gurleen Kaur

Student Theses

Perceptual hashing algorithms are algorithms that generate content-based image hashes by extracting perceptual features from the images. Unlike cryptographic hashes, which exhibit significant changes with even slight input alterations, perceptual hashes do not change when modifications like compression, color correction and brightness are applied to the images. These hashes are designed to remain similar for inputs that are visually or perceptually alike, which has led to their widespread application in detecting duplicate images, finding similar images for reverse image search and to detecting inappropriate content of Child sexual abuse (CSAM) images by comparing image hashes with dataset of known perceptual …

Optimizing Distributed Boundary Exchanges For Benchmarks, Solvers And Sparse Matrix Operations, Gerald Collom

Computer Science ETDs

Boundary exchanges dominate the cost of both stenciled codes and those that rely on sparse matrix operations. The performance of large boundary exchanges is limited by synchronization overheads and injection bandwidth limitations. Irregular boundary exchanges incur additional overheads due to the large number of required messages. This thesis investigates multiple methods for improving the performance and scalability of both Cartesian and irregular boundary exchanges. Since boundary exchanges are typically performed iteratively, persistent communication presents an opportunity for optimization by sharing and amortizing setup costs. Partitioned communication is also explored to increase asynchrony, reducing bottlenecks from synchronization overheads and data congestion. …

Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope …

Legislative And Security Confrontation Of Crimes Artificial Intelligence In The State Of Kuwait (An Analytical Study), Rashid Mohammed Al Marri

Journal of Police and Legal Sciences

The study aimed to demonstrate the mechanisms of legislative and security confrontation of artificial intelligence crimes. The use of technologies associated with artificial intelligence may go beyond the imposed limits, whether by exploiting it through its program developers & specialists to commit crimes in the cyber field, or it may be with the growing capabilities of artificial intelligence to make decisions in the field. Many behaviors occur automatically. Our research also aims to study the criminal responsibility for these crimes, & determine it in order to hold the real perpetrator accountable in accordance with the legal rules in force to …

8-Page Zine Extra Credit Assignment, Ricaute Rogers

Open Educational Resources

This is an 8-page minizine extra credit assignment that put into practice the concepts learned in CIS100.

Pure And Strong Nash Equilibrium Computation In Compactly Representable Aggregate Games, Jared Soundy, Mohammad T. Irfan, Hau Chan

Research & Publications

Aggregate games model interdependent decision making when an agent’s utility depends on their own choice and the aggregation of everyone's choices. We define a compactly representable subclass of aggregate games we call additive aggregate games, which encompasses popular games like congestion games, anonymous games, Schelling games, etc. We study computational questions on pure Nash equilibrium (PNE) and pure strong Nash equilibrium (SNE). We show that PNE existence is NP-complete for very simple cases of additive aggregate games. We devise an efficient algorithmic scheme for deciding the existence of a PNE and computing one (if it exists) for bounded aggregate space. …

Full-Stack Web Applications: Infrastructure, Development Pipelines & Devsecops, Yassine Chahid, Patrick Slattery

Publications and Research

This research explores emerging development methodologies and technologies which facilitate the deployment and maintenance of software applications. It evaluates architectural styles for the development of software such as monolithic (legacy) and microservice models, with a focus on their key differences such as scalability or project structure through to the development of an application. By examining methodologies such as Agile and continuous integration/continuous development pipelines along with the deployment tools Docker and Git for version/release control, the study analyzes how these innovations speed up development, improve existing practices, and serve as the foundation for development operations. Cloud solutions for tasks such …

Advancements In Refreshable Braille Display Technology: A Comprehensive Survey, Maryam Etezad, Rajeev Joshi, Franceli L. Cibrian

Engineering Faculty Articles and Research

This paper provides a comprehensive mapping literature review of the advancements in refreshable Braille display (RBD) technology, which employs dynamically movable pins or dots to render Braille characters for individuals with blindness and visual impairment. This literature review, which includes 96 papers, aims to summarize the current evidence on six distinct types of RBDs: piezoelectric, electromagnetic, electroactive polymer (EAP), pneumatic, shape memory alloy (SMA), and microfluidic technologies. For each type, we discuss the underlying mechanisms, alongside the current trends and research opportunities. This comparative analysis aims to inform the selection of appropriate RBD technology based on specific user needs and …

Machine Learning: Neural Networking With Relu And Optimization, Aidan Redmond Brownell

Undergraduate Theses, Capstones, and Recitals

At its core, learning is an algorithmic process: it begins with input data, undergoes a series of transformations or computations, and yields an output intended to solve a specific task. This output is then compared against a target or desired result, and the internal mechanisms are updated based on how well the output aligns with expectations. While this feedback-driven process occurs almost effortlessly in humans, it is a far more structured, deliberate, and computationally intensive undertaking for machines.

Basic Theory And Implementations Of Quantum Error Correction, Derek Rodriguez

Undergraduate Theses, Capstones, and Recitals

The introduction of quantum computing has presented algorithmic solutions to computationally difficult challenges that are far more efficient than those of classical computers. These algorithms leverage the properties of quantum mechanics to manipulate the quantum properties of subatomic particles, requiring immense precision and stability. Current quantum hardware, however, is too noisy and introduces too many errors for these algorithms to be useful in practice, necessitating the use of error correction algorithms. This field survey seeks to introduce various principles of quantum mechanics relevant to quantum computing and quantum error correction (QEC), detail the implementation and motivations of a basic QEC …

The Critical Plastocapillary Number For A Newtonian Liquid Filament Embedded Into A Viscoplastic Fluid, Mohammad Tanver Hossain, Wonsik Eom, Arjun Shah, Andrew Lowe, Douglas Fudge, Sameh H. Tawfick, Randy Ewoldt

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The yield stress of a viscoplastic material can stabilize an embedded fluid tunnel against capillarity-induced breakup, enabling remarkable technologies such as embedded 3D printing of intricate, freeform, and small components. However, there is persistent disagreement in the published literature between the observed minimum stable diameter, 𝑑min, and the theoretical plastocapillary length 𝑝𝑐 = 2𝛤∕𝜎𝑦, with interfacial tension 𝛤 and bath yield stress 𝜎𝑦, leading to a prior hypothesis that the apparent surface tension 𝛤 is much smaller to enforce 𝑑min = 𝑝𝑐 . Here we introduce and experimentally test a new hypothesis that the critical diameter is set by the …

Tellings Of The Pacific Ocean: A Landscape-Based Approach For Multispecies Design And Hci, Maliheh Ghajargar

Engineering Faculty Articles and Research

Environmental disturbances induced by climate change have caused significant changes in our ecosystems and are threatening the health of our environments. As a response to this issue, a growing body of work has emerged in HCI and design, which seeks to foreground more-than-human stories in support of making more sustainable and just futures. This research contributes to this broad agenda by probing graphic novels as a multispecies storytelling method for design and HCI. Combining ideas from Anna Tsing’s adventures of landscape and from HCI and design’s use of sequential art (e.g., storyboards), we use landscape as the main protagonist of …

Video Game Hacking, A General Problem With Generalized Solutions, Luke Rowe

Master's Theses

As video games continue to get more popular and lucrative, the number of malicious actors seeking to exploit them grows with it. As this industry expands, so does the importance of securing games against cheating and abuse. This thesis aims to educate developers to help mitigate the abuse of video games by these malicious actors. The goal of this thesis is to provide a foundational framework for thinking like a hacker and how to make games harder to abuse once a hacker bypasses conventional anti-cheat software.

This thesis outlines some of the most common cheating methods and provides general context …

Optical Character Recognition For Early Handwriting Legibility Assessment, Franceli L. Cibrian, Kayla Anderson, Yingying 'Yuki' Chen, Lauren Min, Lizbeth Escobedo

Engineering Faculty Articles and Research

Monitoring children’s handwriting, such as avoiding writing assignments, displaying uneven letter formation, or showing slow writing speed, can help identify developmental and academic issues early. Poor handwriting affects up to 34% of children, leading to academic and self-esteem challenges. Handwriting assessments, typically conducted by teachers, are often delayed due to workload and could be subjective and inconsistent. This paper explores the potential of Optical Character Recognition (OCR) technology to augment and ease handwriting assessments. Based on an evaluation of 10 OCR algorithms using 33 handwriting samples assessed by two experts, the research indicates that Pen to Print and Google are …

Integrative Computational Modeling Of Distinct Binding Mechanisms For Broadly Neutralizing Antibodies Targeting Sars-Cov-2 Spike Omicron Variants: Balance Of Evolutionary And Dynamic Adaptability In Shaping Molecular Determinants Of Immune Escape, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this study, we conducted a comprehensive analysis of the interactions between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and four neutralizing antibodies—S309, S304, CYFN1006, and VIR-7229. Using integrative computational modeling that combined all-atom molecular dynamics (MD) simulations, mutational scanning, and MM-GBSA binding free energy calculations, we elucidated the structural, energetic, and dynamic determinants of antibody binding. Our findings reveal distinct dynamic binding mechanisms and evolutionary adaptation driving the broad neutralization effect of these antibodies. We show that S309 targets conserved residues near the ACE2 interface, leveraging synergistic van der Waals and electrostatic interactions, while S304 focuses on …

Towards Multi-Modal Multi-Document Understanding Capabilities In Foundation Models, Chuhan Li

Computer Science Theses

Contemporary foundation models are predominantly evaluated on isolated documentor image-understanding tasks, thereby overlooking the inherent multimodal multi-document reasoning that characterizes scientific inquiry. To bridge this gap, M3SCIQA is introduced, aMulti-Modal,Multi-document Scientific Question Answering benchmark crafted to test foundation models in practical scientific research settings. A comprehensive evaluation of 18 leading foundation models shows a substantial performance gap between models and human experts. Detailed error analysis reveals persistent deficiencies in both scientific visual reasoning tasks and long-range retrieval. Addressing the former, SPACECUE offers a concise yet effective visual prompting that overlays grid coordinates and Semantic-SAM masks …

Programming A More Efficient Onboarding Process For New Employees, Long H. Pham

Undergraduate Honors Theses

The current onboarding process for new hires in the University of San Diego’s Shiley-Marcos School of Engineering is inefficient. There is no central location where new hires and administrators can track onboarding progress. Both parties have to manage multiple email chains and write their own reminders to keep track of everything. This leads to delays, missing deadlines, and confusion for both parties. A web-based onboarding application has been developed recently to address these issues and streamline the onboarding process for new hires. However, this application contains several accessibility issues and does not follow all of the standards for effective employee …

Hybrid Graph-Recurrent Architecture For Citation Recommendation Via Future Embedding Forecasting, Mohammad Ausaf Ali Haqqani

Computer Science and Engineering Theses and Dissertations

The rapid expansion of scientific literature has intensified the challenge of identifying relevant citations, particularly for newly published or under-cited papers. Traditional citation recommendation systems typically model static relationships or respond to past citation activity, offering limited predictive power for emerging works. In response, this thesis presents a temporal modeling framework for citation recommendation that anticipates future scholarly relevance by forecasting the latent representations of academic papers.

Building on prior work that utilized Temporal Graph Networks (TGNs) to model dynamic citation flows, we propose Graph-Time, a hybrid architecture that integrates a Graph Transformer with a GRU-based time series predictor. The …

Real-World Implementation Of A Noninvasive, Ai-Augmented, Anemia-Screening Smartphone App And Personalization For Hemoglobin Level Self-Monitoring, Robert G. Mannino, Julie Sullivan, Jennifer K. Frediani, Paul George, Jeremy Whitson, James Tumlin, L. Andrew Lyon, Erika A. Tyburski, Wilbur A. Lam

Engineering Faculty Articles and Research

Anemia, characterized by low blood hemoglobin (Hgb) levels, afflicts >2 billion individuals worldwide. Here, we report real-world data generated by a smartphone app that noninvasively screens for anemia using only “fingernail selfies.” App data for anemia screening were obtained from >1.4 million uses across the United States enabling geographic mapping of Hgb levels. Of those, 9,061 users also self-reported complete blood count Hgb levels for comparison, resulting in accuracy and performance that match gold standard laboratory testing and a sensitivity and specificity of 89% and 93%, respectively, when using an anemia cutoff of 12.5 g/dL. Geotagged data enabled construction of …

Magic: The Gathering Deck Testing And Optimization, Ian B. Watson

Honors Theses

The goal of this project is to provide a tool for players of the trading card game Magic: the Gathering to determine whether or not a given deck is optimally built by outputting relevant information regarding its optimality. This is done through a simulator that plays a one-sided game, recording what cards are played, what turn they are played, and how much mana is left over at the end of every turn. The simulator was tested with both optimized and unoptimized decks to show how it can be used to diagnose both.

Optimizing Information Security In Cloud Environments: A Risk Management Approach And Guide For Enterprise Cloud Security, Joshua Olusegun Oyeniyi, Oluwashina Akinloye Oyeniran

Journal of Cybersecurity Education, Research and Practice

In recent years, cloud computing has become increasingly integral to organizational operations due to its scalability, accessibility and cost effectiveness in managing data and resources. However, the rise in security threats and attacks on cloud environments necessitates having robust measures in place to protect data confidentiality, integrity and availability. This paper presents an optimized approach to cloud information security management by reviewing the current threat landscape, evaluating key risk management frameworks, and provided practical solutions for enhancing enterprise cloud security. The study examined three leading cloud security frameworks: the Cloud Controls Matrix (CCM) known for its cloud-specific controls, the NIST …

Designing Ai-Driven Dining: A Ux Approach To Enhancing The Self-Service Experience, Kaylin Joung, Yuki Hayashi, Dailuaine Esguerra

Undergraduate Research Symposium Posters

Artificial intelligence has transformed many industries, yet its integration into self-dining experiences is still emerging. This research explores how AI can enhance self-dining by introducing technology like interactive kiosks and robot servers to improve efficiency, personalization, and customer convenience. By addressing current gaps, we aim to create a more seamless and engaging dining experience.

Supporting Novice Programmers With Scaffolded And Open-Ended Generative Ai Interfaces: Insights From A Design-Based Research Study, Justin Olmanson, Azadeh Hassani, Gretchen K. Larsen

Department of Teaching, Learning, and Teacher Education: Faculty Publications

In this study, we explore student experiences in coding and learning programming with scaffolded and unscaffolded generative AI interfaces. Specifically, we supported higher education students in using ChatGPT, an open ended interface for interacting with generative AI; and Giuseppe, a specialized interface with an OpenAI backend service that offers personalized supports specifically for helping students overcome early-stage challenges in learning to code, and working on education technology prototyping projects. This study contributes to the field by offering design insights for scaffolding initial learning interactions between generative AI interfaces and novice programmers. Our findings suggest that those new to coding welcome …

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, …