Digital Commons Network^™

Towards Breach Hypothesis Based Predictive Autonomous Cyber Defense Ecosystem: Proactive Prevention Of Imminent Threats And Productivity Losses, Yogesh Chavarkar

Master's Theses and Doctoral Dissertations

As cyberattack tools and techniques get sophisticated and persistent, reactive cybersecurity has been unable to effectively prevent breaches and compromises. Organizations and institutions with large complex environments have wide vulnerable exposure with higher chances of a cyberattack. This also increases overall security and financial risk. Possibility of repetitive attacks from cyber threats increases, too, despite the use of standard defense measures. Security tools and system vulnerabilities often need manual patching and updates to keep the environment secure and functioning effectively. Productivity suffers from manual trade-offs in keeping the systems secure from adverse impact. Persistent high-severity cyberattacks, despite continued reactive defensive …

Eeg And Imu Gait Signal Processing: A Comparative Assessment Of The "Reza" Exponential Filter And Classic Filters, Reza Pousti, Daniel M. Russell, Derek C. Monroe, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential "Reza" filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain-body imaging dataset with EEG and gait data from 49 healthy adults (EEG: 256-channel, 512 Hz; IMUs: six APDM Opals, 128 Hz). EEG channels were grand-averaged and band-pass filtered at 0.5-50 Hz, while IMU axes were averaged and band-pass filtered at 0.5-5 Hz. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD (EEG:0.5-50 Hz; IMU:0.5-5 …

Quantifying Uncertainty In Landscape Evolution And Provenance Analysis: Insights From Statistical And Numerical Modelling, Vivian Carmello Grom

LSU Doctoral Dissertations

Landscape evolution models (LEMs) and detrital zircon provenance are widely used to investigate Earth surface processes, yet both face challenges related to quantifying model behavior and interpreting sedimentary signals under realistic, heterogeneous conditions. This thesis addresses these challenges through analysis and case studies that develop and apply new approaches for analyzing landscape dynamics and assessing uncertainties in sediment provenance.

Chapter 1 introduces a quantitative framework for evaluating LEM outputs using Shannon Entropy, Moran’s I, and Geary’s C. Applied to simulations with steady uplift, periodic uplift, spatially variable uplift, and a timeseries of DEMs, these metrics capture spatial organization and information …

Crispr-Cas9 Unleashed: Gene-Slicing Adventures In The Cancer Battlefield, Shivakuma Sonnaila, Shilpi Agrawal

Chemistry & Biochemistry Faculty Publications and Presentations

Cancer, a global health menace, continues to pose significant challenges in terms of incidence and mortality, necessitating innovative therapeutic strategies. Despite existing treatments, the limitations persist, prompting a quest for novel approaches. The emergence of immunotherapy marked a transformative era in solid tumor treatments, yet its efficacy is constrained by adverse effects. Concurrently, the integration of advanced technologies into cancer treatment explores the vast potential residing at the molecular level through gene analysis and manipulation. This review articulates the role of state-of-the-art genome editing technology, notably clustered regularly interspaced short palindromic repeats (CRISPR-Cas9), in overcoming the constraints of immunotherapy for …

Lens: Llm-Enabled Narrative Synthesis For Mental Health By Aligning Multimodal Sensing With Language Models, Wenxuan Xu

Dartmouth College Master’s Theses

Multimodal health sensing offers rich behavioral signals for assessing mental health, yet translating these numerical time-series measurements into natural language remains challenging. Current LLMs cannot natively ingest long-duration sensor streams, and paired sensor–text datasets are scarce. To address these challenges, we introduce LENS, a framework that aligns multimodal sensing data with language models to generate clinically grounded mental-health narratives. LENS first constructs a large-scale dataset by transforming Ecological Momentary Assessment (EMA) responses related to depression and anxiety symptoms into natural-language descriptions, yielding over 100,000 sensor–text QA pairs from 258 participants. To enable native time-series integration, we train a patch-level encoder …

Recent Advances In Triboelectric Nanogenerators For Biomedical And Cardiovascular Monitoring, Amit Sarode, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, …

Advances And Challenges In Digitally Connected Point-Of-Care Biosensing, Abdellatif Ait Lahcen, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Point-of-care (POC) biosensors are undergoing a paradigm shift from isolated diagnostic tools to digitally connected, intelligent platforms that enable continuous and decentralized healthcare delivery. This review critically examines recent advances in wearable, implantable, and portable biosensors, highlighting how integration with wireless communication, the Internet of Medical Things (IoMT), and artificial intelligence is transforming their functionality and clinical utility. Particular attention is given to innovations such as smartphone-enabled interfaces, cloud-based analytics, and machine learning-assisted analysis, which collectively enhance sensitivity, specificity, and user accessibility across diverse healthcare settings, from personalized home monitoring and bedside diagnostics to deployment in resource-limited regions. The review …

Data Repository For: Dorsey Et Al., 'Rapid Transient Uplift Driven By Active Slab Tear, Southern Calabria, Italy', Rebecca J. Dorsey, Nathan D. Brown, Sergio G. Longhitano, Marco Meschis, Domenico Chiarella, Charles P. Ogle

Earth & Environmental Sciences Datasets

Southern Italy preserves a well-studied record of deformation and uplift related to migrating oblique collision, trench retreat, and tearing of subducted ocean slabs. However, the surface expression of these processes is incompletely understood due to a lack of reliable ages for marine terraces >200 m above sea level (masl). Here we use luminescence methods to date shallow marine sands from terraces ~ 100 to 1,000 masl in southern Calabria and interpolate the results with regional surface mapping. Burial ages overlap across the full range of sampled elevations with a weighted mean of 118.8 ± 8.7 thousand years before present (ka). …

Key-Point-Based Sign Language Translation With Multi-Stream Motion Modeling And Cross-Lingual Transfer, Alex Muchiri Kagozi

Dissertations and Theses

Automatic sign language translation remains challenging because models must recover linguistic structure from complex visual motion while relying on limited annotated data. This thesis investigates whether compact skeletal key-points can serve as an effective alternative to RGB video for continuous sign language recognition and translation, motivated by the privacy, computational efficiency, and transferability of skeletal representations. To address this problem, a segmented key-point-based framework is evaluated in continuous sign language recognition (Sign2Gloss), gloss-mediated translation (Sign2Gloss2Text), gloss-free translation (Sign2Text), and transfer learning within a common modeling pipeline. The proposed framework is a motion-aware multi-stream transformer encoder. Rather than processing the signer …

Nanostructured Cathode Catalysts For Aem Electrolysis: From Catalyst Design To Degradation And Hydrogen Dynamics, Yamini Kumaran

Electronic Theses & Dissertations (2024 - present)

Anion exchange membrane water electrolysis (AEMWE) presents a promising pathway toward cost-effective and sustainable hydrogen production by integrating the chemical robustness of alkaline systems with the compact, zero-gap design of proton exchange membrane electrolyzers. However, the widespread implementation of AEMWE is limited by the availability of highly active and durable platinum-group-metal (PGM)-free catalysts and by an incomplete understanding of their degradation behavior under realistic operating conditions.

This dissertation focuses on the development, characterization, and mechanistic investigation of nanostructured MoNi₄–MoO₂-based electrodes for efficient and stable hydrogen generation under alkaline and membrane-integrated environments. MoNi₄–MoO₂ nanorods …

Informationally-Optimal Measurements On Single-Qubit Systems, Adam V. Preston

Electronic Theses & Dissertations (2024 - present)

This thesis will focus on deriving informationally-optimal quantum state tomographic measurements on single-qubit systems, with the definition of informationally optimal to be defined as those measurements which maximize the average information gain. The informationally-optimal measurements that will be covered include projective measurements (formally building off of the work of [1] and putting it on firm, information-theoretic foundations), and more general types of quantum measurements called directional (also known as rank-one) positive operator-valued measure (POVM) measurements, and, finally, adaptive directional POVM measurements.

For projective measurements, we build on the work of Wootters and Fields ([1]) and show, via analytical methods and …

On Quantum Processes And The Epistemic Constraints, Varun Immanuel Premkumar Immanuel

Electronic Theses & Dissertations (2024 - present)

This doctoral dissertation on the foundations of quantum theory tells the story of a conceptual protagonist I have called “Epistemic Constraint.” Here, epistemic constraints are the definite, intersubjectively agreeable, ordinary-language conditions under which experiments are described.

The usual formulation of the quantum measurement problem, which I call the Schrodingerian measurement problem, has the structure of an anomaly: if we take quantum theory at face value, we expect no definite values, and yet we see definite values in experiments. The responses to this problem have been either to solve it or to dissolve it. These responses, which have taken the form …

The Predictability And Verification Of Precipitation From Landfalling Tropical Cyclones Using An Object-Based Framework, Melissa Piper

Electronic Theses & Dissertations (2024 - present)

Precipitation from landfalling tropical cyclones (TCs) poses a significant risk to life and property in both coastal and inland communities. Early warning systems can help mitigate the impacts of TC-induced flooding; however, this requires accurate quantitative precipitation forecasts (QPFs). Forecasting precipitation from landfalling TCs is a challenge, as the intensity, duration, and location of precipitation can be dependent on numerous storm-related and environmental factors. Previous studies have attempted to identify and correct NWP model deficiencies and reduce forecast uncertainty by applying traditional and advanced verification metrics to TC QPF. However, these studies have mostly used gridpoint verification metrics, limited samples …

On The Contribution Of The Gulf Stream To High Frequency Coastal Sea Level Variability, Tal Ezer

CCPO Publications

Long-term Atlantic Ocean and Gulf Stream (GS) variability were linked in past studies to coastal sea level (CSL) change along the U.S. East Coast - a weakening GS can lead to rise in CSL and increased coastal flooding. However, high frequency variability (HFV) in CSL is, in most cases, attributed to atmospheric weather events. This study is focused on HFV (intraseasonal variations with periods between similar to 1 week and similar to 2 months) in the GS and in CSL. First, wavelet and spectral analysis of observations of the Florida Current transport and CSL characterized the HFV in the data, …

Lessons For Transformative Ocean Science From The Integrated Marine Biosphere Research (Imber) Project, Deborah Santos Prado, Ella-Kari Muhl, Mia Strand, Derek Armitage, Nina Bednaršek, Stephanie Brodie, Christopher Cvitanovic, John Claydon, Sam Dupont, Karen Evans, Alistar Hobday, Eileen Hofmann, Raleigh Hood, Laura Kaikkonen, Dongyan Liu, Jessica Melbourne-Thomas, Franz Mueter, Eugene Murphy, Prateep Kumar Nayak, Alice Newton, Heidi Pethybridge, Carol Robinson, Samiya Selim, Rowan Trebilco, Micaela Trimble, Fang Zuo

CCPO Publications

This paper synthesizes the key contributions and lessons learned from Integrated Marine Biosphere Research (IMBeR), a large-scale global research project aimed at fostering ocean sustainability under global change for the benefit of society. The UN Decade of Ocean Science for Sustainable Development has catalyzed a renewed focus on the importance of transforming ocean science. IMBeR’s global activity over the past decade has focused on promoting transformative science by generating, mobilizing, and communicating the knowledge needed to support ocean governance. Key contributions from IMBeR participants include quantifying and comparing historic and present structure and functioning of linked ocean and human systems, …

Developing Collaboration And Community Through An Online Virtual Modality: Participatory Action Research, Jennifer Reed

Doctor of Education Dissertations

This action research study examined educators’ perceptions of collaboration and community within a virtual professional learning community and investigated how participation influenced collaborative actions over time. The study also compared the needs and goals of secondary and postsecondary educators participating in a shared VPLC model. Grounded in the Community of Inquiry and Online Collaborative Learning theoretical frameworks, this study addressed a growing need for effective, flexible professional learning structures that support collaboration across educational contexts. Data were collected from six educators, including three secondary and three postsecondary instructors, through pre- and post-administration of the Professional Learning Community Assessment–Revised, recorded virtual …

Ecological Feedbacks In The Earth System, Eugene J. Murphy, Jessica J. Williams, Isla H. Myers-Smith, Vivienne P. Groner, David M. P. Jacoby, Lester Kwiatkowski, Jess Melbourne-Thomas, Emma Ransome, Cristina Banks-Leite, Laurent Bopp, Marion Gehlen, Eileen E. Hofmann, Babette Hoogakker, Nadine M. Johnston, Yadvinder Malhi, Emma L. Cavan

CCPO Publications

Ecological feedbacks are fundamental features of the Earth system, affecting physical processes and chemical cycles. Our understanding of the interactions underlying these feedbacks at different spatial and temporal scales and the extent to which feedbacks affect Earth system functioning remains limited. Climate change and other anthropogenic pressures are already negatively affecting ecological processes in marine, freshwater, and terrestrial ecosystems. These will most likely be amplified in the coming decades under our current warming and socioeconomic pathways. The knock-on impacts on ecological feedbacks have the potential to cause rapid perturbations to the Earth system, and may significantly impact the structure and …

Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models …

Rockyou2024: What’S Your Password?, Yixuan Zhang

Honors Theses

Passwords remain a critical part of almost every account security system. As a result, password guessing attacks remain one of the most widespread yet profitable attacks possible. Setting a password resistant to attacks is thus an important task for account holders. In this paper, we use the RockYou2024 database, a collection of approximately 10 billion real-world passwords collected from data breaches, to analyze the characteristics of passwords found in real life. We start with basic statistical property analysis, such as length, distribution of digits and symbols, and proceed onto more complicated properties such as frequencies of combinations of characters, entropy …

From Shock To Routine: The Evolving Impact Of Shutdown-Related Sentiment On Stock Markets, Yiran Shao

Honors Theses

To address gaps in existing research, this paper selects two U.S. government shutdown periods, 2018-2019 and 2025, as research samples to explore the effect of policy uncertainty on sentiment. This paper primarily analyzes the following two research questions.

First, what is the correlation between government shutdown-related sentiment during the shutdown period and daily market fluctuations? Specifically, can the sentiment index constructed from shutdown-related news effectively predict the next-day stock return during the event period?

Second, does the market have a learning effect? That is, between 2018-2019 and 2025, has the relationship between shutdown-related emotions and market outcomes weakened, shortened the …

A Comparison Of Conversational Chatbots And The Internet For Consumer Information Search, Wondwesen Tafesse, Yoseph Mamo

STEMPS Faculty Publications

This study compares consumer perceptions of conversational chatbots and the internet for information search. While the internet is a mature platform, conversational chatbots represent an emerging technology, and insight into how consumers view them in relation to the internet for information search is lacking. Drawing on the information source utility perspective, the study builds a comparative model based on four key dimensions: information currency, information customisation, information trustworthiness, and media richness. Additionally, the study investigates consumers’ prior experience with conversational chatbots as a moderating factor. Data was collected from 191 respondents recruited through MTurk. Paired sample t-tests assessed mean differences …

Restoring Digital Trust: Decentralized Frameworks For Identity, Consent, And Media Provenance, Raghu N. Avula

Graduate Studies Theses and Dissertations 2026

Digital platforms are deeply embedded in modern society through centralized network architectures. As online interactions transition to the physical world handling sensitive data, user privacy and cryptographic security require enhancement beyond traditional limits. This dissertation presents a decentralized “Tri-Layer Trust Architecture” that leverages Verifiable Trust Registries, Cryptographic Binding, and Edge Verification to prioritize data sovereignty and local authentication. To demonstrate the architecture’s applicability across distinct operational environments, we implement three solutions: (1) Verifiable Presence for peer-to-peer ride-sharing via D-RideX, which encrypts biometric data on physical hardware (TEEs) and Soulbound Tokens (SBTs) to prevent impersonation without cloud database exposure; (2) Verifiable …

An Integrated Framework For Last-Mile Delivery Optimization Using Reinforcement Learning And Social Media-Based Traffic Prediction In Underdeveloped Megacities, Vasanth Bhat

Graduate Studies Theses and Dissertations 2026

Supply chain management has become increasingly critical as transportation costs rise and urban delivery systems place additional pressure on already congested networks. Last-mile delivery—the movement of goods from distribution centers to end users—represents the most expensive and operationally complex segment of the logistics process, particularly in underdeveloped megacities characterized by unpredictable traffic, limited infrastructure, and sparse real-time data. This dissertation proposes an integrated framework for optimizing last-mile delivery in such environments by combining social media–based traffic intelligence, machine learning, and deep reinforcement learning. The framework leverages unstructured, real-time data from social media platforms to enhance traffic prediction and incorporates these …

Aquatic Invasive Species Survey And Treatment On Lake Umatilla And Lake Celilo 2024-2025 Report, Jacob Rose, Gabriel E. Campbell

Center for Lakes and Reservoirs Publications and Presentations

Flowering Rush (Butomus umbellatus) is an invasive aquatic plant in the Pacific Northwest that threatens salmon habitat. The Center for Lakes and Reservoirs staff surveyed for this and other aquatic species from 2024 and 2025 in the Columbia River in Lake Umatilla and Lake Celilo. This document summarizes their survey efforts including their protocols, data, and small-scale removal efforts.

Fumigant Toxicity Of Essential Oils From Chemotypes Of Curry Tree (Murraya Koenigii) Against Adult African Malaria Mosquito (Anopheles Gambiae Sensu Stricto), Clarence M. Mang’Era, Fathiya M. Khamis, Ahmed Hassanali, Paul O. Mireji

All Peer-Reviewed Publications

The toxicity of fumigant formulations of essential oils (EOs) from curry tree (Murraya koenigii (L.) Spreng (Rutaceae)) against African malaria adult mosquito (Anopheles gambiae sensu stricto (Giles, 1902) (Diptera: Culicidae: Culicini)) was evaluated to identify most effective chemotype of the curry tree against the mosquitoes. Ninety-two compounds (91.78%–96.47% coverage) in the EO profiles were identified, among which EO isolated from curry tree chemotype from Kibwezi was most toxic. This chemotype had a median lethal dose (LD50) of 3.6 × 10⁻³ mg/cm³ (95% CI: 2.70–4.58) and a lethal time (Ti50) of 1.91 ± 0.086 h (p < 0.001). The equivalent LD50 of EOs of chemotypes from Mombasa, Makindu, and Malindi in Kenya was 4.9 × 10⁻³, 6.6 …

Remembering Right Relations: A Land-Centered Framework For Settler Teacher Transformation, Aimee E. De Ney

Antioch University Dissertations & Theses

Settler colonialism is based in the separation of peoples from Lands and from one another, producing ongoing harm to human and more-than-human communities as evidenced in climate collapse, racialized violence, war, and widening social inequities. These conditions are sustained by ideologies of human supremacy-specifically white, male, Christian human supremacy-that deny personhood to most humans and to all more-than-humans, while enabling the attempted erasure of Indigenous peoples and the nation-state enforcement of anti-Black and anti-Brown racism. Situated on the Lands of the Coast Salish Peoples in the Pacific Northwest of the United States, this multiparadigmatic innovation dissertation develops a Land-centered framework …

Sustainable Justice: A Critical Contemplative Approach To Sustainability In Higher Education, Jessica A. Reneau

Antioch University Dissertations & Theses

The field of sustainability studies increasingly asks students to confront ecological crises alongside considerations of power, privilege, and unequal environmental harm. This work can be emotionally challenging as well as intellectually complex. Contemplative practices, such as meditation and yoga, may offer meaningful pedagogical support, helping students cultivate the attention, reflection, and emotional capacity needed to stay engaged with justice-centered sustainability learning. Although the use of contemplative pedagogies is growing in higher education, little research has examined how these practices shape justice-orientated learning outcomes in sustainability education. This dissertation addresses that gap by exploring how both student and instructor experience contemplative …

The Pure Yang-Mills Field: I: Fixed Time Existence, James Glimm, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

The convergence of renormalized perturbation theory to all finite orders is defined and shown to be valid for the fixed time perturbation theory of a pure Yang-Mills field.

Two pure Yang-Mills quantum gauge field theories are constructed, one based on short distance asymptotics and the other based on long distance asymptotics.

The construction depends on an assumed principle of a maximum rate of entropy production.

Fairrfl: Fair And Robust Federated Learning In The Presence Of Selfish Clients, Andrea Augello, Ashish Gupta, Giuseppe Lo Re, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a paradigm that enables collaborative machine learning without disclosing the local data of the participants. However, in real-world FL deployment scenarios, some unscrupolous clients may alter the training process to skew the global model towards their local optimum, unfairly prioritizing their data distribution. Their influence can degrade overall model performance for normal clients and reduce fairness in the system. We call this novel category of misbehaving clients 'selfish'. This work proposes a Fair and Robust strategy for aggregation in the Federated Learning (FL) server to mitigate the effect of Selfish clients (FairRFL). FairRFL incorporates a novel …

Qura: Reinforcement Learning Based Routing For Quantum Networks, Tasdiqul Islam, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

Quantum routing deals with identifying a set of quantum repeaters to use to create entanglement between distant endpoints. Previous approaches proposed shortest-path and linear programming methods to find a solution to this problem. While the shortest path approach results in suboptimal performance, linear programming takes too long to find a solution as the network size and constraints increase. In this paper, we apply Deep Q-Reinforcement Learning (DQRL) to optimize routing in quantum networks both in terms of execution time and performance. The proposed Quantum Routing Algorithm (QuRA) first chooses which request to schedule among all requests. It then determines which …