Physical Sciences and Mathematics Commons^™

Coastal Flooding And Housing Market Liquidity: Policy Implications For Eastern U. S. Communities, Wai Yan Siu, Rex Sitti

ODU Articles

Coastal flooding poses an escalating threat to communities across the U.S East Coast, where rising sea levels and intensifying storms increasingly overwhelm existing infrastructure and natural defenses. These events generate complex economic consequences that extend beyond immediate property damage to affect community stability and long-term development patterns. The real estate industry in particular, faces increasing levels of flood risk. Existing research on climate risk and real estate markets focuses predominantly on price capitalization effects, overlooking the critical dimension of housing market liquidity. This study examines the causal impact of coastal flooding on days-on-market (DOM), a metric of liquidity in the …

Evaluating The Long-Term Effectiveness Of Marsh Terracing For Conservation With Integrated Geospatial And Wetland Simulation Modeling, Nick Carpenter, Laura Costadone, Thomas R. Allen

ODU Articles

Coastal marshes provide essential ecosystem services, yet they are vulnerable to anthropogenic stressors and climate change, particularly sea level rise (SLR). Restoration approaches like marsh terracing have emerged as nature-based strategies to enhance resilience and reduce habitat loss. This study applies the Sea Level Affecting Marshes Model (SLAMM) to assess the potential of marsh terraces to mitigate future losses, while also examining the model’s limitations, including its assumptions and capacity to reflect complex marsh processes. A geospatial approach was used to generate 3D representations of terraces through morphostatic modeling within digital elevation models (DEMs). Under a no-restoration scenario, SLAMM projections …

High-Resolution Modeling Of Extreme Heat Events With Socioeconomic Consideration: A Real-Case Wrf-Les Approach, Maryam Golbazi, Frank Liu, Yin-Hsuen Chen, Timothy W. Juliano, Heather Richter

ODU Articles

The overarching goals of this work is to explore best practices for micro-scale modeling of a real case, identify relevant phenomena by using high-resolution modeling, and to explore their implications for public health, and climate resilience strategies in Hampton Roads, VA, USA. This project employs the Weather Research and Forecasting (WRF) model to conduct a comprehensive study of Hampton Roads, utilizing a coupled mesoscale to microscale modeling capable of resolving boundary layer turbulence. This study has three primary objectives: (1) to establish the optimal mesoscale to Large-Eddy Simulation (LES) configurations for complex geographical regions such as the Hampton Roads (HR) …

Exploring Brent-Kung Adders In Balanced Ternary Cmos Logic, Astrea J.C. Rojas

Theses and Dissertations

The modern computer operates on a 64-bit architecture. These devices can store large numbers and precise decimals, but more advanced devices are needed to support progressing technologies every day. A more efficient system with higher speeds and larger operable numbers would be a key to optimization of computation as we know it. The ternary device, operating in base-3, has the potential to be that optimization. However, binary technology has such precedent and research that it is a difficult gap to span to compare the ternary system to the modern binary system. With a more advanced adder and optimized gates using …

Automorphism Groups Of N-Graded Vertex Algebras Associated With Cyclic Leibniz Algebras With Small Dimensions, Alexander M. Keene

Theses and Dissertations

A fundamental problem in the study of vertex (operator) algebras V is the determination of the group of (grading-preserving) N-graded vertex algebras associated with cyclic Leibniz algebras of dimensions 2 and 3 that were classified by C. Barnes, E. Martin, J. Service, and G. Yamskulna in [1].

In each case examined, investigation of the automorphism group relies on the key fact that the action of an automorphism σ is determined solely by its value at a single basis element b. Furthermore, we employ a result in [19] by H. Li and G. Yamskulna which states that we can determine the …

Neural Network Algorithm And Analysis For Multi-Label Ecg Data Classification, Akhil Raghava Kalal

Theses and Dissertations

Electrocardiogram (ECG) analysis is a fundamental diagnostic tool in cardiology, providing critical insights into cardiac function that directly impact patient care decisions and treatment outcomes. As healthcare systems face increasing demands, automated ECG interpretation using artificial intelligence offers promising solutions to improve diagnostic accuracy, reduce physicians workload, and enhance early detection of life threatening conditions.

This thesis compares two advanced deep learning architectures, CNN-GRU and Wide and Deep Transformer, for multi-label classification of 12-lead ECG data. Using data from the PhysioNet/Computing in Cardiology Challenge 2020, I evaluated both architectures across 27 different cardiac abnormalities. Results demonstrated that CNN-GRU architecture consistently …

The Impact Of Loss Function Topology On Gradient Descent, Robert B. Skudnig Jr.

Theses and Dissertations

Gradient descent is a popular optimization method that utilizes a model’s prediction error to iteratively improve its parameters for a given task. The functions that measure this error can be defined to align with the user’s goals and sometimes satisfy metric or norm properties. It is common for these functions to measure over Rn, but any differentiable space allows for gradient descent to occur. There has been some research investigating the influence of topological spaces on optimization methods, but it is a limited field of study. This thesis further explores this phenomenon by applying a transformation prediction model to multiple …

Centralized Deep Reinforcement Learning For Homogeneous Multi-Component Maintenance Optimization, Joseph W. Wittrock

Theses and Dissertations

This thesis explores an application of reinforcement learning (RL) in maintenance optimization. Recent advances in hardware-accelerated computation and deep learning have made RL a powerful tool for solving optimization problems which are too complex for traditional methods. Maintenance optimization involves improving the efficiency and effectiveness of maintenance activities through data-driven approaches, ultimately reducing costs and increasing asset availability. Making informed maintenance decisions is crucial to long-term sustainability.

A desirable maintenance policy maximizes a utility signal while minimizing the cost of maintenance. Techniques in sequential decision making such as dynamic programming (DP) and RL have found success in optimizing these maintenance …

Analyzing Factors Influencing Employee Turnover In Tech Companies: A Predictive Modeling Approach, Shinjon Ghosh

Theses and Dissertations

Employee turnover poses substantial challenges for technology firms, and understanding its key drivers through predictive modeling is essential for developing effective retention strategies. This study investigates factors influencing employee turnover in technology companies by implementing a predictive modeling approach on the IBM HR Analytics Employee Attrition dataset. The research aims were identifying key factors contributing to employee attrition, developing predictive models to forecast turnover risk, and analyzing interactions among significant predictors. By examining a range of features, the results highlight significant variables (Over Time, Monthly Income, Marital Status, etc.) of attrition and offer actionable insights for developing targeted employee retention …

Exploring Nitrate Reduction In A Saturated Riparian Buffer Through A Three-Dimensional Reactive Contaminant Transport Model In An Agricultural Area, Mcclean County Central Illinois, Franklin O. Ijigade

Theses and Dissertations

Saturated Riparian Buffers (SRBs) are engineered systems designed to remove nitrate and other pollutants from subsurface agricultural drainage water before it reaches a stream. This study utilizes a high-resolution coupled flow and reactive transport model to explore nitrate reduction and transformation in an SRB in glacial sediment. The influence of material heterogeneity on nitrate reduction and the effectiveness of the SRB was investigated. The study was conducted in an SRB located next to and receiving tile drainage water that ultimately drains into a 3^rd order stream (T3 stream) in central Illinois, USA. A three-dimensional steady groundwater flow model was …

Application Of Floating Wetlands To Improve Urban Stream Quality, Daniel Chukwunonso Chukwudi

Theses and Dissertations

Urban streams, impacted by urbanization, often exhibit degraded water quality due to elevated nutrient levels, a phenomenon known as urban stream syndrome. This study evaluates the effectiveness of a floating wetland (FW) system in reducing nitrate as nitrogen (NO₃-N) and phosphate (PO₄³⁻) concentrations in a side canal of the Chicago River’s North Branch, adjacent to Goose Island, Chicago, IL, from 2018 to 2023. Using a five-year dataset, including new sampling from May to December 2023, the research addresses two questions: (1) Do FWs lower NO₃-N and PO₄³⁻ concentrations in urban streams? and (2) Do FWs exhibit seasonal differences in nutrient …

Nature-Based Solutions For Urban Climate Resilience: Assessment Of Environmental Planning & Policy Perspective In New York City, Padmi R. Ranasinghe

Planning Dissertations - Archive

Climate change exerts a profound global influence, elevating the risk of disasters. Rapid urbanization and high population density make cities increasingly vulnerable to disasters. Climate impact is intense for cities in deltas and coastal regions, highlighting the importance of managing urban watersheds effectively. Often, climate change affects people unequally, with marginalized communities being extra vulnerable to climate-related disasters due to where they live (geographical vulnerability) and limited adaptive capacity. People often live in areas vulnerable to climate-related hazards, including flood zones and regions affected by environmental injustices. Enhancing city resilience is crucial, as it needs to reduce vulnerability and exposure …

The Algebra Behind Magic, Lois Carpenter

Undergraduate Research Awards

Card Tricks have long been a staple in the common magician’s repertoire, and while many tricks can be explained through sleight of hand alone, others rely on seemingly random shuffling methods that leave the magician with significant control over the deck. Applied card magic (frequently referred to as ‘cheating’) makes significant use of this ability. Thus, the utility of this topic is clear- anyone with basic mastery of perfect shuffles has complete control over the arrangement of cards in a deck, and with it a fundamental advantage against other players in any game of cards. While most perfect shuffles are …

Completing Multi-Latin Rectangles Via Factors With Prescribed Degrees In Bipartite Graphs, Amin Bahmanian

Faculty Publications – Mathematics

Let Q be an n x n array whose top left r x s sub‐array L is filled with a set of k different symbols such that each cell of L contains λ symbols. In this note, we find conditions under which each empty cell of Q can be filled with λ symbols in such a way that the total number of occurrences of each symbol is prescribed and that each symbol
occurs at most λ times in each row and column of Q. To prove this result, we establish a new criterion for a bipartite graph to have …

A Systematic Review And Taxonomy For Privacy Breach Classification: Trends, Gaps, And Future Directions, Clint Fuchs, John Hastings

Research & Publications

In response to the rising frequency and complexity of data breaches and evolving global privacy regulations, this study presents a comprehensive examination of academic literature on the classification of privacy breaches and violations between 2010-2024. Through a systematic literature review, a corpus of screened studies was assembled and analyzed to identify primary research themes, emerging trends, and gaps in the field. A novel taxonomy is introduced to guide efforts by categorizing research efforts into seven domains: breach classification, report classification, breach detection, threat detection, breach prediction, risk analysis, and threat classification. An analysis reveals that breach classification and detection dominate …

The Road Less Traveled: A Pathway Leading To Research At A Primarily Undergraduate Institution, Timothy D. Lash

Faculty Publications – Chemistry

Scholarly activities in primarily undergraduate institutions involve very different challenges from those in major research universities. In this essay, the author discusses how he initiated a research program involving undergraduates at Illinois State University following a number of missteps and false starts. Although undergraduate researchers have much to learn, and the levels of commitment vary considerably, they can nevertheless often make important contributions.

Unh/Noaa Joint Hydrographic Center 2025 Performance And Progress Report Executive Summary, Larry A. Mayer

Center for Coastal and Ocean Mapping

No abstract provided.

Developments On Quantum Phase Space Dynamics And Foundations, Gabriel Nowaskie

Mahurin Honors College Capstone Experience/Thesis Projects

This work explores the development and unification of quantum theory within phase space, with a particular focus on new mathematical structures and solution techniques that extend the standard quantum formalism. Building upon the Quantum Phase Space Representation (QPSR) introduced by Torres-Vega and Frederick, we present several advancements that address longstanding gaps in the formulation and solvability of quantum systems in this framework. We introduce the Half-Transform Ansatz, a novel method for solving the Time-Independent Schrodinger Equation by recasting it into a hypergeometric form, enabling the application of the Nikiforov-Uvarov method. This approach is demonstrated through the analysis of quarkonium systems …

Dynamics Of Thermalization In Classical Three-Dimensional Many-Body Systems: Non-Maxwellian Distributions And The Role Of Anisotropic Trapping, Roberto Onofrio, Bala Sundaram

Data and Datasets

The physics of interacting baths is of interest in a variety of contexts, ranging from ultracold atoms to ionized gases. While many features can already be captured in a one-dimensional model, others are speci c to the situation of two or three-dimensional systems. In this paper, we focus on three-dimensional features of a model for thermalization between two baths that we have explored in earlier publications. In contrast to the one-dimensional situation we show that, enroute to thermalization, deviations from the Maxwell-Boltzmann energy distributions more akin to  -distributions are observed. In three dimensions, these can be seen in changes at …

Private Property Vs. Public Access: Socio-Engineering Framework For Managing Non-Meandering Waters In South Dakota’S Prairie Pothole Region, Lydia Loken, Sushant Mehan

The Journal of Undergraduate Research

This study addresses the growing importance of balancing private ownership and public interest of Non-Meandering Waters (NMWs) overlaying private property in the South Dakota Prairie Pothole Region (PPR) through both a legal and socio-engineering lens. This study aims to develop an integrated management framework for Non-Meandering Waters in the South Dakota Prairie Pothole Region that combines water allocation principles, the Public Trust Doctrine, and water quality objectives to guide policy decisions, ensuring equitable access, long-term sustainability, and a balanced approach to both public and private interests. Data collection from October 2024 through February 2025 and included a literature review of …

Nonlinear Wave Dynamics In Asteroseismology With Application To Delta Scuti Stars, Mohammed Mourabit

Physics Dissertations - Archive

This thesis compiles the collection of works in nonlinear astroseismology and its implication to the δ Sct variable that we carried over the course of five years. With the advent of high-resolution space missions such as the Kepler and TESS telescopes, we were able to see significant progress in the field in recent years. Nonetheless the new technologies also brought an increasing number of observation that are seemingly contradictory to the linear theory of asteroseismology. In particular, we find the δ Sct variable, which eludes our models in terms of how varied we find they spectra for stars with very …

Algebra Structures For The Koszul Homology Of Minimal Intersections, Kathryn A. Grebel

Mathematics Dissertations - Archive

The Koszul homology of a local ring is a powerful tool in commutative algebra as it provides information on the structure and properties of the ring. In this research, we explore the relationship between quotients of regular local rings and their Koszul homology algebra. One such relationship is detailed by the Tate-Assmus theorem, which asserts, in part, that a ring is a complete intersection if and only if the Koszul homology is generated by its degree 1 homology elements. An objective of this research is to examine and identify the properties of a minimal intersection and its Koszul homology algebra. …

Minimizing Cpu Utilization For Job Scheduling Problems By The Advanced Round Robin Method: A Pragmatic Perspective, Haribhau R Bhapkar, Pankaj R Chandre, Parikshit Mahalle

ASEAN Journal on Science and Technology for Development

CPU scheduling issues include minimizing waiting time for processes, ensuring fairness in resource allocation, and optimizing throughput. Balancing these objectives can be challenging, as improving one aspect may negatively impact another, making it essential to design efficient scheduling algorithms. This work presents an innovative approach to enhance CPU utilization through the development of a Result-Based Round Robin Scheduling Algorithm. Traditional Round Robin Scheduling methods often face challenges in efficiently allocating CPU time, leading to suboptimal system performance. In response to these limitations, the proposed method introduces a result-oriented strategy that dynamically adjusts time quantum allocations based on the execution progress …

The Effect Of Blanching And Steaming Pretreatment On The Quality Of Durian (Durio Zibenthinus Murr.) Seed Flour, Nabilah Daniel, Rosnah Shamsudin, Mohd Sabri Pak Dek, Jhauharotul Muchlisyiyah, Masmunira Rambli

ASEAN Journal on Science and Technology for Development

Durian (Durio zibethinus Murr.), the "King of Fruits," has seeds that offer nutritional benefits, including high fiber for gut health and high protein for muscle growth. However, natural browning enzymes can limit its use in baking. This study investigates the comparative effects of blanching and steaming durations (5, 10, 15, 20, and 25 minutes) on the color and techno-functional properties of durian seed flour (DSF), providing an optimization-based approach rarely reported for this material.. Durian seeds were sourced from various stalls in Malaysia, washed, soaked in 0.6% sodium metabisulfite, and then blanched or steamed for for varying durations as …

Fiber Optic Distributed Acoustic Sensing For Surface Wave Inversion In Terrestrial And Marine Environments, Constantine Coclin

Open Access Master's Theses

The use of distributed acoustic sensing (DAS) has gained popularity for a variety of seismic sensing applications due to its capability to sense broadband frequency ranges on spatial scales unattainable with conventional point sensors. The ability to sense and characterize vibrational surface waves in the near-surface can provide valuable information about the subsurface structure of an environment. The objective of this study is to evaluate the use of DAS to sense surface wave propagation for the multi-channel analysis of surface waves (MASW) methodology, such that a sub-surface shear wave velocity profile can be obtained in both a terrestrial and near-shore …

Semi-Empirical Prediction Of Wave Runup During Nor’Easters In New England, Pranav Sai

Open Access Master's Theses

Wave runup amplifies the impact of storm events on coastal beaches, accelerating erosion and threatening infrastructure. Accurate quantification of extreme runup during storms is critical for improving coastal hazard predictions and informing resilience strategies. Field measurements of wave and water levels enable empirically derived formulas to calculate runup, parameterizing setup, incident swash, and infragravity swash separately. This study predicts extreme runup across Napatree Point, a sandy barrier at Rhode Island’s westernmost point, known for its dissipative beach morphology and exposure to intense storm activity. Using the ADCIRC+SWAN hydrodynamic and wave models, mean sea level and surface wave parameters were simulated …

Design And Evaluation Of A Compiler Architecture For First-Class Pattern Matching, Timothy Colaneri

Open Access Master's Theses

This thesis presents the design, implementation, and evaluation of a compiler for Asteroid, a multi-paradigm programming language that introduces first-class pattern matching as a core feature. Unlike conventional pattern matching systems - typically restricted to syntactic constructs like match or case expressions - Asteroid elevates patterns to first-class entities, enabling them to be assigned to variables, passed as arguments, returned from functions, and composed dynamically.

To support this novel abstraction, the compiler is structured as a two-phase system: a Python-based frontend for parsing and syntax analysis, and a Rust-based backend that compiles the language into executable code via a custom …

Metabarcoding-Biomass Relationships And Internal Standards For Quantitative Dna Metabarcoding, Frances Webber

Open Access Master's Theses

DNA metabarcoding has been widely adopted due to its power in investigating the composition of protistan communities, accurately identifying even small and cryptic taxa. However, the compositional nature of DNA metabarcoding results, and the distortion of natural abundances due to variation of the often-used 18S rRNA gene copy number over several orders of magnitude, renders these results semi-quantitative at best, limiting the application of DNA metabarcoding to ecological study. Here, we constructed mock communities from uni-algal cultures of taxonomically diverse phytoplankton and conducted metabarcoding using multiple primer sets and both DNA and cDNA as PCR templates. For each culture, chlorophyll …

A Compact Frequency Comb Generator For Large-Format Superconducting Microwave Kinetic Inductance Detectors, Sungyoun Seo

Open Access Master's Theses

Microwave Kinetic Inductance Detectors (MKIDs) are promising superconducting detectors that achieve superior sensitivity to silicon-based photo detectors by leveraging a small bandgap of superconductors. They are advantageous for sensitive imaging instruments, particularly space telescopes. However, a large-format array with several hundreds of thousands of detectors is required for large-scale observations in space, and it encounters multiple challenges. The biggest challenge is the absence of compact, energy-efficient, and radiation-tolerant readout solutions. Of multiple functions in the MKID readout, the new frequency comb generator is presented in this thesis. It features a low on-chip memory requirement while promising the relaxed frequency resolution …

Big Cells, Big Impact: Unravelling Seasonal Patterns Of Net Primary Production In Narragansett Bay, Dominique Jae Lockwood

Open Access Master's Theses

Net primary production is a measurement of available energy, or the amount of biomass that phytoplankton produce during photosynthesis that fuels marine food webs and drives carbon cycling. Despite its ecological importance, net primary production is relatively understudied in comparison to chlorophyll-a, which is often used as a proxy for biomass rather than productivity. In this study, we measured size-fractionated net primary production and chlorophyll-a concentrations in Narragansett Bay over a 14-month period from January 2022 to February 2023. Weekly surface water samples were collected and filtered to distinguish between small (> 10 μm) and large ( …