Physical Sciences and Mathematics Commons^™

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 …

Bayesian Modelling On Periodically And Multiple Periodically Correlated Time Series Data, Jie Yao

Electronic Theses & Dissertations (2024 - present)

Time series with multiple periodically correlated (MPC) components present a complex challenge, with relatively limited prior research. Most existing models are designed for simpler periodically correlated (PC) components and often struggle with over-parameterization, optimization issues, and capturing complex PC patterns within a time series. Frequency separation techniques can help preserve the correlation structure of individual PC components, while Bayesian methods can integrate new and prior information to refine beliefs about these components. This study proposes a two-stage approach that combines frequency separation and Bayesian techniques to forecast PC and MPC time series data. This method aims to demonstrate improved effectiveness …

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, …

End-To-End Modeling For The Ross Sea Region Marine Protected Area: A Review Of Available Tools For Conservation Objectives, James R. Lovvorn, Cara Nissen, Alexis A. Bahl, Erik Behrens, Cassandra M. Brooks, Katy Christensen, Michael S. Dinniman, Lilian A. Dove, Alice K. Duvivier, Eileen E. Hofmann, Hayley Kwasniewski, Young Shin Kwon, Sharon E. Stammerjohn, Lei Xing

CCPO Publications

The challenge of protecting marine ecosystems, including biodiversity and manifold interactions in changing environments, has encouraged development of end-to-end models linking physical drivers through entire food webs to upper-level predators. Ideally such models should have temporal and spatial resolution adequate to capture important small-scale processes, while including scales large enough to encompass local food webs and movements of wide-ranging consumers. The need for component submodels to be manipulated and upgraded independently by scientists from different disciplines, and used selectively depending on questions addressed, favors modular structure allowing linkage of different submodels with varying strengths and weaknesses. As an example, this …

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 …

Basal Melting Variability Of The Ross Ice Shelf From Mixing Ratios Of Simulated Water Masses (1993-2018) And Potential Climatic Drivers, Enrico Pochini, Andrea Bergamasco, Florence Colleoni, Manuel Bensi, Giorgio Budillon, Pasquale Castagno, Michael S. Dinniman, Pierpaolo Falco, Emanuele Forte, Vedrana Kovačević, Stefanie L. Mack

CCPO Publications

Several water masses circulate under the Ross Ice Shelf (RIS), the largest ice shelf in Antarctica, each causing basal melting with a specific spatio-temporal pattern. To investigate these patterns and their variability, we applied a mixing ratio analysis to simulated water masses from a new numerical ocean model of the Ross Sea. The simulation, which was run over 26 years (1993–2018) and which includes the RIS cavity, shows good agreement with seaborne and mooring observations. The total RIS basal melt rate is 90 Gt/yr on average, and is caused mostly by High Salinity Shelf Water (HSSW) (68%), which enters the …

Agricultural Productivity Under Energy Development: Insights From California, Wai Yan Siu, Sherzod B. Akhundjanov

ODU Articles

This paper examines how agricultural productivity patterns in Kern County, California, a leading region for both agricultural production and oil and gas development, co-vary with the spatial and temporal expansion of hydraulic fracturing and associated energy infrastructure. Using parcel- and county-level analyses, we characterize how agricultural productivity differs across proximity to energy development and across spatial scales. The results reveal spatially heterogeneous and scale-dependent patterns: parcel-level evidence indicates lower Enhanced Vegetation Index-based vegetation productivity within the 20-mile proximity zone around fracking wells, while county-level results show heterogeneous crop-specific yield changes during the post-expansion period. Together, these findings highlight the importance …

Seeing The Invisible Load: Xr+ Multimodal Sensing For Cognitive Ergonomics In Industrial Training, Jessica M. Johnson, Andwele Grant

Virginia Digital Maritime Center (VDMC) Faculty Publications

Extended reality (XR) technologies are increasingly positioned as disruptive Industry 5.0 tools for human-centric industrial training and intelligent human–system integration. Coupled with multimodal sensing (eye tracking, EEG, HRV, GSR, and other physiological signals), XR environments promise to make otherwise invisible cognitive demands observable, especially for novice trainees entering complex industrial settings. Yet the evidence base is fragmented: (1) there is no quantitative synthesis of the cognitive ergonomics benefits of XR plus sensing; (2) little is known about which XR–sensor configurations yield the strongest effects; (3) prior reviews rarely focus on industrial and manufacturing tasks; (4) multimodal signals are used predominantly …

From Reviews To Value: Harnessing Crowdsourced Data To Capture Visitor Perceptions And Economic Benefits Of Recreation, Laura Costadone, Shan Zhang

ODU Articles

Quantifying the recreational value of protected natural areas is essential for sustainable management, conservation financing, and informed decision-making. Traditional approaches, such as on-site surveys, are often costly, spatially limited, and constrained by regulatory barriers. This study evaluates the potential of crowdsourced user-generated data to jointly assess visitor perceptions and the economic value of nature-based recreation, using Back Bay National Wildlife Refuge (Virginia, USA) as a case study. We integrated georeferenced photographs and textual content from four platforms (Flickr, TripAdvisor, Yelp, and AllTrails) with supplementary survey data to analyze visitation patterns, visitor sentiment, cultural ecosystem services, and recreational value using the …

Autonomous Float Data Reveal Decoupled Trends In Chlorophyll And Stratification In The Indian Ocean, Marufa Ishaque, Sophie Clayton, John Klinck

OES Faculty Publications

Recent studies have shown that the Indian Ocean is warming significantly, but how this warming impacts primary production is largely unresolved due to a relative lack of depth-resolved biological observations. In this study, we have used Biogeochemical-Argo data from 2013 to 2022, comprising over 9,000 individual profiles, to examine regional patterns and trends in depth-integrated chlorophyll, depth-integrated net primary production and stratification in the northern and Equatorial Indian Ocean. Our analysis shows that water column stratification is increasing in the majority of the study area, with the highest rate of increase observed in the western Bay of Bengal. At the …

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 …

Pursuer Evader Surveillance Game, Zijie Mu

Honors Theses

This thesis studies the pursuer evader surveillance game with a triangular obstacle in the short-term. In the game, the pursuer aims to maintain surveillance of the evader as long as possible while the evader aims to break surveillance in a finite time. We classify the player strategies into  ideal ones and best admissible ones. The outcome of the game is determined by line of sight. We reduce the 4D game to a 3D game with a boundary separating two different local regimes. When the evader starts inside the threshold, we show that there exists an admissible evader that maintains an …

Spillover Effects Of Medicare Advantage On Fee-For-Service Post-Acute Care Spending, Nyel Bangash

Honors Theses

Does the growth of Medicare Advantage reduce fee-for-service post-acute care spending through practice-pattern spillovers, or do observed spending differences primarily reflect favorable selection? Using a county-level panel of roughly 2,700 counties (2014–2023) and a two-way fixed effects specification, I find that a one percentage-point increase in MA penetration is associated with $9.54 less per-capita standardized FFS spending. Spending per episode falls while participation rates remain stable, consistent with practice-pattern spillovers rather than compositional changes from selection. Welfare indicators from County Health Rankings, CDC PLACES, and CMS Care Compare show no evidence that spending reductions harm health or care quality. The …

Education And The Maternal Childcare Gap: Evidence From The Uk Covid-19 Pandemic, Lara Bakhaya

Honors Theses

This paper examines whether college education shapes working mothers’ access to remote work, flexible working, and childcare hours in the United Kingdom, and whether COVID-19 school closures amplified these inequalities. Using data from the UK Time Use Survey (2016–2021), a repeated cross-sectional diary dataset spanning the pre-pandemic period and five COVID-19 waves, this paper estimates weighted logistic and ordinary least squares regressions on a sample of married or cohabiting, employed mothers. School closures serve as a natural experiment, providing an exogenous shock to caregiving demands that affected all mothers simultaneously regardless of education level. College education significantly predicted working from …

Net Carbonyl Ene Reactions Of Olefins With Aldehydes, Alexandra Mock

Honors Theses

Aldehydes and olefins react in the presence of base and TMSOTf to yield homoallylic alcohols. In this net ene reaction, TMSOTf acts as a Lewis acid to activate the aldehyde, leading to a strong oxygen-silicon bond that acts as a driving force in the reaction. In the proposed mechanism, the α-methylstyrene attacks the carbonyl carbon of the TMSOTf-activated aldehyde to produce a carbocationic intermediate. Elimination using a relatively bulky base (2,6-lutidine) provides the homoallylic alcohol. This reaction has proven robust in terms of the aldehyde and olefin scope.

Mechanisms Driving Disparities In Income Mobility Across The Income Distribution, Joe Larkins

Honors Theses

This study examines intergenerational income persistence across the income distribution, testing whether mechanisms driving inequality differ between families in the top and bottom halves of the income distribution. Using data from the National Education Longitudinal Study of 1988 (NELS:88), a nationally representative longitudinal survey of 8th grade students and their parents, this research estimates an interaction model comparing parental income effects for children in advantaged versus disadvantaged economic circumstances. The analysis reveals that a $1,000 increase in parental income yields eight times greater income gains for children in the bottom half of the distribution compared to those in the top …

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 …

Photo And Spatial Control Of Rna Structures And Functions: Exploring Positional Effects And Photo-Responsiveness Of Azobenzene Modified Nucleotides, Jinxi Du

Electronic Theses & Dissertations (2024 - present)

RNA molecules perform many important biological functions by forming complex three-dimensional structures stabilized by base pairing, tertiary interactions, and metal ion coordination. Because RNA function depends strongly on its structure, methods that allow reversible control of RNA conformation and activity are important for understanding RNA behavior and for potential therapeutic applications. However, achieving reversible and site-specific control of RNA structure, especially at the single-nucleotide level, remains challenging. In this dissertation, I developed and applied azobenzene-modified nucleotides as a chemical tool to enable optical and spatial control of RNA structure and function.

The first part of this dissertation focuses on establishing …

On The City-Scale Energy Balance Under Electrification And Renewable Generation: The New York City Case, Nour Elgalad

Electronic Theses & Dissertations (2024 - present)

Integration of renewable resources to meet the growing energy demand of dense urban regions is becoming a global priority under decarbonization mandates. This study contributes to these ongoing efforts by assessing the feasibility of using locally deployable urban renewable resources, namely offshore wind in the New York Bight region and rooftop photovoltaic (PV) systems over New York City, to meet the electricity demand of the city, and the grid vulnerabilities that emerge, during two contrasting extreme-weather periods: the intense heatwave of June 2025 and a fully electrified winter cold snap in January 2018. A unified, meteorologically driven modelling framework, based …

Impacts Of Segmenting Principle On Learner Performance And Attitude In A 3d Environment: A Mixed-Method Multiple Case Study, Kristin Herman, Mohan Yang, Jim Shifflet, Noah Glaser

STEMPS Faculty Publications

This study presents a conceptual replication of Moreno’s (Appl Cogn Psychol 21:765–781. 10.1002/acp.1348, 2007) study on the benefits of adhering to the segmentation principle when utilizing multimedia learning objects. Furthermore, this study expands upon the original by taking place in a low-immersive virtual reality environment, allowing for further understanding on the extent to which multimedia principles are still relevant. Both a synchronous and an asynchronous case are presented. Results indicate benefits for both cases in far transfer of learning. Furthermore, synchronous learners indicated a significant reduction in cognitive load and increased overall attitudes towards learning due to segmented instruction.

Drafting Policy To Address Academic Integrity: The Other Ai In Education, Elizabeth Burns

STEMPS Faculty Publications

The article focuses on the role of school librarians in drafting policies to address academic integrity amid the increasing use of artificial intelligence (AI) in K-12 education. It defines AI, including generative AI (GenAI), and discusses both the challenges and opportunities AI presents for teaching and learning, emphasizing the need for clear guidelines on ethical use. The article outlines three common AI policy models—permissive, hybrid, and restrictive—and stresses the importance of collaboration between librarians and teachers to establish consistent expectations, promote critical thinking, and ensure proper attribution of AI-generated content. School librarians are positioned as key facilitators in guiding students …

Students-Generative Ai Interaction Patterns And Its Impact On Academic Writing, Jinhee Kim, Sang-Soog Lee, Rita Detrick, Jialin Wang, Na Li

STEMPS Faculty Publications

Considering both the transformative opportunities and challenges presented by generative AI (GenAI) in academic writing, effectively integrating GenAI into the academic setting becomes a significant need requiring prioritization. Yet, there is limited understanding regarding the nature of interactions between different types of students, what behavioral patterns students exhibit during a student-GenAI interaction (SAI) on a given task, and how these different SAI patterns relate to the actual writing task performance. This study, therefore, aimed to identify SAI patterns of academic writing tasks depending on students’ level of AI literacy and examine the differences in academic writing performance between the identified …

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 …

Learning-Based Optimization For Collaborative Truck-Drone Routing And Scheduling, Ahmad A. Bany Abdelnabi

Graduate Studies Theses and Dissertations 2026

Modern delivery networks increasingly rely on innovative technologies such as drones working alongside trucks to meet rising demands for fast and efficient last–mile transportation. Hybrid truck–drone delivery offers strong potential, but its effectiveness depends on careful synchronization between trucks and drones. Although drones provide fast, direct travel, their limited endurance and the need to coordinate launch and recovery with trucks create tightly coupled routing and scheduling interactions. Poor dispatch decisions can cause truck waiting, reduce parallelism, and increase mission completion time. These challenges motivate decision frameworks that explicitly model synchronization and develop scalable methods for coordinated truck–drone operations. This dissertation …

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 …

Repeatability And Reproducibility Of Likelihood Ratio Estimation For Forensics Using Machine Learning: An Application To In-Silico Fire Debris Data, Cameron Ezazi

Graduate Studies Theses and Dissertations 2026

The importance of using statistical evidence to help inform the interpretation of forensic evidence has grown greater over time. This is especially evident in the field of forensic fire debris analysis, where the reliability and reproducibility of statistical results are crucial. This thesis investigates how the application of 5 different common machine learning methods on an in-silico fire debris dataset can be reduced to a univariate forensic score to create score-based likelihood ratios (SLRs), and how these ratios should be interpreted. These SLRs are crucial in supporting or rejecting a Prosecutor’s or Defense’s hypothesis, thus making the previously mentioned reliability …