Physical Sciences and Mathematics Commons^™

Flexible Membrane Electrodes For Use In High-Capacity Lithium-Ion Batteries, David A. Denemark

College of Graduate Studies: Theses & Dissertations

Wearable electronic devices require high-capacity flexible batteries to improve user comfort and increase usage time per charge. In this thesis, flexible lithium-ion battery (LIB) electrodes are prepared using a novel and scalable phase inversion method, embedding one-dimensional SnO₂ nanowires and double-walled carbon nanotubes within a porous polyacrylonitrile asymmetric membrane. The optimized electrode delivered an initial specific discharge capacity of 915.93 mAh g⁻¹, approximately 2.5 times greater than conventional graphite anodes, with 61.99% capacity retention after 45 cycles. The incorporation of a carbon mesh substrate further enhanced both electrochemical and mechanical performance, achieving 89.46% capacity retention after 45 cycles and a …

Purified Zero-Shot Sketch-Based Image Retrieval, Yang Zhou, Jingru Yang, Jin Wang, Kaixiang Huang, Guodong Lu, Shengfeng He

Research Collection School Of Computing and Information Systems

Sketches, as a new solution in multimedia systems that can replace natural language, are characterized by sparse visual cues such as simple strokes that differ significantly from natural images containing complex elements such as background, foreground, and texture. This misalignment poses substantial challenges for zero-shot sketch-based image retrieval (ZS-SBIR). Prior approaches match sketches to full images and tend to overlook redundant elements in natural images, leading to model distraction and semantic ambiguity. To address this issue, we introduce a distraction-agnostic framework, purified cross-domain matching (PuXIM), which operates on a straightforward principle: masking and matching. We devise a visual-cross-linguistic (VxL) sampler …

Assessing Climate Change Impacts On Wildfire Risk In Central Appalachian Forests Of The Eastern United States, Imiya Mudiyanselage Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

Wildfire risk is increasing in the eastern U.S., yet spatial and climate-driven assessments remain limited. This study evaluates climate change impacts on wildfire risk in the Upper James Watershed (UJW) using baseline (2000–2019), near-future (2021–2040), and far-future (2061–2080) projections from a 12-model CMIP6 global climate model (GCM) ensemble under SSP2–4.5 and SSP5–8.5. A wildfire risk model was developed in ArcGIS Pro using nine key factors and validated with MODIS hotspot data, showing good agreement between modeled risk patterns and observed fire occurrences (NOF = 0.21, RMSE = 4.20, MAE = 3.37). Baseline risk was primarily driven by land cover, fire-lookout …

Integrative Machine Learning Of Genetic And Lifestyle Factors For Personalized Skin Health, Yassine Benachour, Lina Maloukh, Barbara Geusens

All Works

Objective: To develop an AI framework that combines genetic, phenotypic, and lifestyle data for profiling skin-health patterns and generating hypothesis-supporting summaries for potential decision support. Methods and procedures: A dataset of 5,254 individuals integrates six genes (FLG, AQP3, MMP-1, MMP-3, SOD2, GPX), six phenotype severities, and 20+ lifestyle factors. Mutation burden and interactions are tested by ANOVA. K-modes clustering identifies four interpretable dermatological profiles within the cohort and is embedded in leakage-free nested cross-validation (train-only selection; test labels from training centroids). Subtypes are predicted from genetics plus lifestyle using an XGBoost (XGB) classifier; explainability uses gain, permutation importance, and SHAP …

A Novel Bernstein Operational Matrix Approach For Tempered Fractional Differential Equations: Convergence And Stability Analysis, Jalal Al Hallak, Mohammed Alshbool, Ishak Hashim, Eddie Shahril Ismail, Shaher Momani

All Works

Tempered fractional differential equations (TFDEs) incorporate exponential decay into fractional operators to account for truncated memory and semi-long-range dependence in a variety of applications, including anomalous diffusion, viscoelasticity, transport phenomena, geophysical processes, and financial dynamics. In this work, a tempered fractional Bernstein method (TFBM) was proposed for the numerical solution of TFDEs involving Caputo-type derivatives. The proposed formulation combined a Bernstein polynomial approximation with an analytic representation of the Caputo–tempered fractional derivative through operational matrices. On this basis, two collocation-based variants were developed, namely, a Chebyshev-type method (TFBM-C) and a Legendre-type method (TFBM-L). For the linear setting, a convergence analysis …

Empirically Evaluating The Accessibility Of A Pon-Enable Feature Diagrams Notation By The Red-Green Colorblind Community, Mohamed El-Attar, Sarah Kohail, Rima Grati

All Works

In 2016, an enhanced version of a feature diagram notation developed using the Physics of Notations (PoN) framework was introduced. Empirical evidence demonstrated that this revised notation was more cognitively effective than the original. However, the new notation relies on color, specifically red, which poses accessibility challenges for individuals with red–green color vision deficiency, as they cannot perceive the notation as originally intended. Consequently, the cognitive effectiveness of a red–green–deficient (RGD) version of the new notation relative to the original notation remained unknown. Although the PoN framework specifies several principles that may be satisfied with or without the use of …

Rumooz Aljareemah: An Intelligent Search System For Uae Criminal Law With Case Correlation Framework For Forensic Investigators, Rahaf Alnuaimi, Maryam Almarzooqi

All Works

Digital forensic investigations in the UAE encounter dual challenges: effectively correlating data across cases and complying with local legal frameworks. Conventional methods create information silos that hide connections between instances and increase the probability of procedural errors. This paper presents RUMOOZ ALJAREEMAH, a prototype platform for case correlation designed for cybersecurity experts and forensic investigators in the UAE. The approach integrates a correlation engine with a UAE-specific legal compliance framework, using authentication protocols, bilingual assistance, and text-based search algorithms. Our theoretical framework suggests enhancements in investigative efficiency, including reduced case resolution durations, improved identification of cross-case relationships, and a decrease …

Escher: Efficient And Scalable Hypergraph Evolution Representation With Application To Triad Counting, S. M. Shovan, Arindam Khanda, Sanjukta Bhowmick, Sajal K. Das

Computer Science Faculty Research & Creative Works

Higher-order interactions beyond pairwise relationships in large complex networks are often modeled as hypergraphs. Analyzing hypergraph properties such as triad counts is essential, as hypergraphs can reveal intricate group interaction patterns that conventional graphs fail to capture. In realworld scenarios, these networks are often large and dynamic, introducing significant computational challenges. Due to the absence of specialized software packages and data structures, the analysis of large dynamic hypergraphs remains largely unexplored. Motivated by this gap, we propose ESCHER, a GPU-centric parallel data structure for Efficient and Scalable Hypergraph Evolution Representation, designed to manage largescale hypergraph dynamics efficiently. We also design …

Real-Time Isolated Asl Recognition: Evaluating Spatial-Temporal Networks And Multimodal Llms, Raga Mouni Batchu

West Chester University Graduate Theses, Dissertations, and Final Projects

This thesis investigates the deployment of high-accuracy Isolated ASL Recognition (ISLR) in resource-constrained edge environments. We train a lightweight Spatio-Temporal Attention Network (SSTAN,∼2.7 M parameters,∼10 MB) on the WLASL-100 benchmark, achieving 75.25% Top-1 and 88.24% Top-5 accuracy with 139 ms CPU-only inference. A systematic comparison against frontier multimodal LLMs (Gemini 3 Flash, Gemini 3.1 Pro, Qwen 3 VL) shows SSTAN outperforms the best LLM baseline by∼1.85×in accuracy while being 22–230×faster and up to 40×cheaper annually. The LLMs’ core limitation is a lack of fine-grained temporal perception; they impose English-language semantic priors rather than learning the articulatory distinctions that define ASL …

Climate Resilience In Action: Process-Based Equity For Co-Governed, Socially Cohesive, Ecologically Integrated Democracies Through The Design And Implementation Of Nature-Based Solutions, Donna Choih

Antioch University Dissertations & Theses

Nature-based Solutions (NbS) governance and behavior have the potential to become more equitable, beginning with a closer examination of what equity entails. Governance and behavior together are the actions manifest from internal dispositions and thoughts that facilitate the process of decision-making, in this case, for equitable NbS. This critical review seeks to (1) address the gap in literature on human development and behavioral dimensions of procedural justice for NbS by further defining process-based equity (PbE), and (2) present a framework of best practices for equitable NbS. This framework, along with a complementary conceptual model, was developed using the Preferred Reporting …

Green Space: Investigation Into The Role Pocket Parks Play In Biodiversity And Human Well-Being, Jacalyn Speicher

Antioch University Dissertations & Theses

Natural communities and the birds that inhabit them are essential to the physical and emotional well-being of human residents in urban settings. The action research undertaken in this study addresses the social and environmental justice issues of equity, accessibility, and diversity afforded avian and human communities in the design of pocket parks within the urban landscape. As urbanization consumes the natural landscape, people and birds must adapt to the novel challenges of a changing environment. I studied 10 pocket parks identified in Center City, Philadelphia, Pennsylvania between January and June 2026. This time frame spanned the seasons from winter to …

Mathematicly Rigorous Quantum General Relativity, I: Pure, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A pure general relativity (quantum or classical) is one lacking in matter. Such a field has a Lorentzian space time geometry. A renormalization perturbative expansion, truncated to all finite orders, establishes both the quantum and the general relativity theory with full mathematical rigor.

The Pure Yang-Mills Field, \, Iia: The Mass Gap, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

No abstract provided.

The Pure Yang-Mills Field, \, Iia: The Axioms, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A previously constructed pure Yang-Mills quantum gauge field theory is shown to satisfy all Osterwalder Schrader axioms.

General Relativity: Existence, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A mathematically rigorous renormalized perturbative expansion, truncated to all finite orders, establishes the existence of quantum general relativity theories with Fermion matter fields. The expansion is initialized with the selection of a vacuum state. Distinct infrared (IR) and ultraviolet (UV) vacuum states are considered. The IR vacuum state defines cosmology model. The UV vacuum state defines a black hole model. The vacuum state is initialized with a o3 gauge Lie algebra defining a quark-gluon plasma. With this choice, string theory is avoided. Finite order renormalized perturbation theory, defined using Bosons to avoid Fermion sign cancellation, is convergent to all finite …

Scaling Laws, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A mathematically rigorous renormalized perturbative expansion, truncated to all finite orders, establishes the existence of quantum general relativity theories with Fermion matter fields. The expansion is initialized with the selection of a vacuum state. Distinct infrared (IR) and ultraviolet (UV) vacuum states are considered. The IR vacuum state defines a cosmology model. The UV vacuum state defines a black hole model. The vacuum state is initialized with a o3 gauge Lie algebra defining a quark-gluon plasma. With this choice, string theory is avoided. Finite order renormalized perturbation theory, defined using Bosons to avoid Fermion sign cancellation, is convergent to all …

High-Resolution Mapping Of Soil Moisture Variation Using Uas Thermal And Multispectral Imagery, Jackline Amma Timah

Theses and Dissertations

In agricultural landscapes, soil moisture regulates hydrologic partitioning, nutrient transport and water quality, land-atmosphere energy exchange that shapes local climate, and ecosystem resilience. However, traditional monitoring approaches, such as in-situ sensors and satellite imagery, often lack the spatial resolution required to capture fine-scale soil moisture variability. This study evaluated whether unmanned aerial system (UAS)-derived thermal, multispectral, and terrain variables can capture fine-scale spatial variability in volumetric water content (VWC) within an SRB in central Illinois.

High-resolution imagery was collected and paired with 50 field-measured VWC observations. Land surface temperature (LST), vegetation indices (NDVI and NDRE), spectral bands, and slope were …

Advancing Food Equity Through Explainable Ai (Xai): Identifying Place-Based Factors And Conditions Of Food Security, Leslie Hoglund, Hyoshin Park

Health Behavior, Policy & Management Faculty Publications

Food behaviors, food security, and their association with socioeconomic factors constitute a critical area of study with implications for public health, economic stability, and social equity. Understanding these relationships are essential for developing effective policies and interventions that promote sustainable, healthy food systems and greater food equity. This paper employs explainable artificial intelligence (XAI) methods to identify key features influencing household food behaviors. The insights gained from the XAI analysis are further utilized in conjunction with inverse reinforcement learning (IRL) to examine expert behaviors related to eating habits satisfaction. The XAI results reveal that household health conditions, spending patterns, and …

Large Language Model-Assisted Research Question Development In Public Health: A Case Study In The Special Supplemental Nutrition Program For Women, Infants, And Children (Wic), Qi Zhang, Bidusha Neupane, Priyanka Patel, Futun N. Alkhalifah, Yi He, Leslie Hodges

Health Behavior, Policy & Management Faculty Publications

Objective:

To assess the feasibility of using large language models (LLMs) to develop research questions about changes to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) food packages.

Design:

We conducted a controlled experiment using ChatGPT-4 and its plugin, MixerBox Scholarly, to generate research questions based on a section of the USDA summary of the final public comments on the WIC revision. Five questions weekly for three weeks were generated using LLMs under two conditions: fed with or without relevant literature. The experiment generated 90 questions, which were evaluated using the FINER criteria (Feasibility, Innovation, Novelty, Ethics, …

Performance Of Numerical Methods Applied To The Black–Scholes Model, Scott Cameron Williams

UNF Graduate Theses and Dissertations

We compare five numerical approaches for approximating solutions to the Black–Scholes partial differential equation for pricing European call options: FTCS, BTCS, Crank– Nicolson, Monte Carlo simulation, and a physics–informed neural network (PINN). These methods span finite difference techniques, probabilistic simulation, and machine learning. Performance is evaluated based on computational efficiency and accuracy relative to the analytical Black–Scholes solution.

Among the methods, Crank–Nicolson and the PINN demonstrated the strongest overall performance. Crank–Nicolson achieved the highest accuracy but exhibited increased runtime as the number of underlying stock price grid points grew. In contrast, the PINN produced slightly less accurate results but with …

A Comparative Evaluation Of Data Imbalance Handling Techniques In Machine Learning Models For One-Year Mortality Prediction In Liver Cirrhosis, Sumiya Hasan Trisha

UNF Graduate Theses and Dissertations

Liver cirrhosis is associated with substantial morbidity and mortality, making one-year mortality prediction a clinically relevant problem. Using a liver cirrhosis dataset as the motivating application, this thesis evaluates five machine learning classifiers—Logistic Regression, Random Forest, XGBoost, LightGBM, and CatBoost—under five class-imbalance handling strategies: Baseline learning, Random Oversampling, SMOTE-NC, ADASYN, and Cost-Sensitive Learning. Hyperparameter tuning was conducted using randomized search, and predictive performance was assessed over 200 iterations of Monte Carlo Cross-Validation using Accuracy, Precision, Recall, Fl-score, and ROC-AUC.

The results suggest that imbalance-handling strategies can materially affect predictive performance, particularly recall. Because the outcome of interest is death within …

A Comparative Study Of Classification Methods For Healthcare Analytics, Xueting Zhao

UNF Graduate Theses and Dissertations

This thesis presents a comparative study of logistic regression, Linear Discriminant Analy- sis (LDA), and Quadratic Discriminant Analysis (QDA) for binary classification in healthcare analytics, integrating theoretical derivation, simulation, and real-data application. A facto- rial simulation study crosses the covariance structure (equal vs. unequal), predictor correla- tion (ρ ∈ {0, 0.5, 0.9}), dimensionality (p ∈ {2, 5, 10}) and sample size (n ∈ {50, 100, 200}) across 54 scenarios with 1,000 Monte Carlo replicates each. Three main findings emerge. Logistic regression and LDA are nearly interchangeable when the assumption of equal-covariance holds. QDA achieves substantially better discrimi- nation when class-specific …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

The Second Minimum Size Of A Finite Subspace Partition, Esmeralda Năstase, Papa Sissokho

Faculty Publications – Mathematics

Let V = V (d, q) denote the vector space of dimension d over Fq . A subspace partition P of V , also known as a vector space partition, is a collection of nonempty subspaces of V such that each nonzero vector of V is in exactly one subspace of P. Motivated by applications of minimum blocking sets and maximal partial t-spreads, Beutelspacher (Geom Dedic 9:425– 449, 1980) determined in a lemma the minimum possible size δ(d) over all (nontrivial) subspace partitions of V . In Heden et al. (Des Codes Cryptogr 64:265–274, 2012) and N˘astase …

Second And Fifth Graders’ Changes In Strategies For Integer Addition, Mahtob Aqazade, Laura Bofferding

Faculty Publications – Mathematics

Research on integer addition often attributes students’ performance to their grade level while ignoring the role of prior whole number knowledge in influencing their learning difficulties. To explore whether these difficulties are related to their grade level or persistence in using rules based on their whole-number experiences, we first paired three second-grade students with three fifth-grade students who had similar integer addition strategies on their pretest. Then, we compared their strategy changes and performance after small-group sessions and whole-class activities around integer addition (i.e., instructional intervention). Although all pairs gained from the pretest to posttest, one fifth grader still relied …

Histochemical Alteration, Protein Nitration, And Antioxidant Expression In Oysters As Early Warning Indicators For Microplastic Contamination In The Texas Gulf Coast, Rebecca Muñiz, Md Faisal Amin, Md. Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Microplastics are widely distributed in aquatic environments and have been detected in numerous organisms. Marine bivalves are among the most affected aquatic organisms by microplastics due to their filter-feeding behavior. In this study, 60 oysters were collected from two sites along the Texas Gulf Coast. Fourier transform infrared (FTIR) spectroscopy and Nile red staining were used to detect microplastics in oyster (Crassostrea virginica) tissues. We compared field and laboratory samples collected after a two-week depuration period to identify differences in the shape and size of microplastics in oyster tissues. Results from the field sites showed a large number of microplastics, …

Chesapeake Bay Water Clarity: Challenges And Successes, Jessica S. Turner, Carl T. Friedrichs, David B. Parrish, Kelsey A. Fall

OES Faculty Publications

The Chesapeake Bay is a large estuarine system spanning multiple jurisdictions and serves as a model for estuarine health worldwide. Historically, nutrient loading degraded water quality, prompting the need for regulation. Water clarity, one component of water quality, is vital for benthic communities and serves as a key indicator of overall ecosystem health. Here, physical resuspension and salinity gradients, nutrient and sediment inputs, production of organic detritus by phytoplankton, and benthic communities all interact to drive clarity patterns, with high spatial variability. Trends over the last 50 years show improvement, though with a temporary increase in organic detritus in response …

A Tale Of Two Microbialities: Stromatolites And Microbially Induced Sedimentary Structures, Nora Noffke, Stanley M. Awramik

OES Faculty Publications

Microbialites are biosedimentary structures built by microbial mats. Five microbialite groups are distinguished: stromatolites, thrombolites, dendrolites, leiloites and microbially induced sedimentary structures (MISS). This contribution discusses the two most abundant microbialite groups in marine settings, stromatolites and MISS. Microbial interactions with clastic sediment are very similar in both stromatolite and MISS formation. However, in stromatolites, syngenetic carbonate production caused by photoautotrophic and heterotrophic metabolisms and by calcimicrobes also takes place. More so, carbonate may precipitate within the extracellular polymeric substances. Due to the various carbonate forming processes as well as recrystallisation, the microscopic mat fabrics within stromatolite laminae are rarely …

Characterizing The Unique Chemical Imprint Of On-Axis, Lower-Temperature Hydrothermal Flow To The Deep Ocean (Southern East Pacific Rise, 16.5°-18.0°S), Laura E. Moore, Randelle M. Bundy, Joseph A. Resing, Scott White, Tamara Baumberger, Peter N. Sedwick, Nathaniel J. Buck, Anson M. Antriasian, Isaac Keohane, Bettina M. Sohst, Sharon L. Walker, Christopher R. German

OES Faculty Publications

In addition to high-temperature vents, lower-temperature flow (LTF) (< 300°C) is abundant along mid-ocean ridges and contributes globally-important fluxes of heat and water along with largely-unconstrained geochemical influences on the ocean. We examined the impact of on-axis LTF on the chemical composition of the overlying water column (< 40 m above seafloor) along the 16.5°-18.0°S sector of the ultrafast-spreading southern East Pacific Rise using autonomous underwater vehicle Sentry surveys and conductivity-temperature-depth rosette casts. LTF sites were typically spatially isolated from high-temperature systems and imparted unique chemical signatures to the overlying ocean. Water column samples impacted by LTF exhibited low particulate iron:sulfur ratios and high methane: total-dissolvable manganese ratios, whereas samples influenced by high-temperature venting exhibited opposite trends. We confirmed that LTF imparts a distinct and measurable chemical signature to the water column, independent from high-temperature vents. Isolated, on-axis LTF will be important to consider when assessing hydrothermal circulation impacts upon ocean biogeochemistry.

Contribution Of Non-Linear Internal Waves To Marine Net Primary Production Has Been Underestimated, Xiaoju Pan, Tung-Yuan Ho, George T. F. Wong, Jen-Hua Tai, Shoude Guan, Fuh-Kuo Shiah

OES Faculty Publications

Field observations in the northern South China Sea (NSCS) indicate that elevated concentrations of chlorophyll a (Chl_a) associated with non-linear internal waves (NIWs) were more pronounced in the subsurface than at the sea-surface. At a given surface Chl_a, the vertically integrated Chl_a in an NIW-active area was 45% higher than that in an area where the NIW activities were minimal. As a result, net primary production (PP_eu) estimated from surface Chl_a from remote sensing by using the current Chl_a-based PP_eu model (e.g. VGPM) would have underestimated the true value by the same amount. If this correction is …