Digital Commons Network^™

Signature-Based Attribution Of Images Generated By Stable Diffusion, Bella White

Master's Theses

Generative AI is powerful yet controversial technology capable of spreading misinformation, non-consensual imagery, and offensive materials when not properly safeguarded against such abuse. Synthetic image alteration and generation have always been abused, from photo editing software to Generative Adversarial Nets, and now Diffusion Models. The Internet Watch Foundation and the National Center for Missing and Endangered Children have reported a consistent increase in reported AI generated child sexual assault materials (CSAM) and sextortion scams since the introduction of DMs. New digital forensics tools must evolve to adapt to the ever-changing landscape of AIG CSAM abuse. This work provides a comprehensive …

Why The Long Face? The Distribution And Niche Of The Imperiled Narrow-Faced Kangaroo Rat (Dipodomys Venustus), Garrett L. Gimbel

Master's Theses

Distribution models provide a practical use case of connecting ecological niche theory with species’ occurrence and assemblages. By explicitly linking Hutchinson’s “niche space” with geographic space researchers can gain valuable information on a species’ niche characteristics and interactions, thereby informing conservation and management practices. The narrow-faced kangaroo rat (Dipodomys venustus) is a highly understudied kangaroo rat species endemic to the central coast of California and is an ideal species to explore niche theory in distribution modeling. Three subspecies are currently recognized: The Santa Cruz kangaroo rat (D. v. venustus), the elephant-eared kangaroo rat (D. v. …

Using Hydraulic And Hydrologic Modeling To Determine Scour At Toro Creek Under Climate Change Conditions, Gabriel E. Alaniz

Master's Theses

ABSTRACT

This study evaluates bridge scour at the Toro Creek crossing of Highway 1 in Morro Bay, California, under present conditions and future climate conditions with more frequent extreme rainfall events. California infrastructure is becoming increasingly vulnerable to extreme storm events and increased intense precipitation events brought by climate change. This analysis focuses on the calculation of scour for both the northbound and southbound spans. Highway 1 plays a vital role in California’s coastal transportation infrastructure by carrying more than 20,000 vehicles daily (Caltrans, 2017). In this thesis, a hydrological model (HEC-HMS) is used to simulate runoff under present-day and …

The Moderating Effect Of Income Inequality On The Income–Emissions Relationship In G20 Countries, Zahra Rizky Fadilah, Budiasih Budiasih

Economics and Finance in Indonesia

This study analyzes the moderating effect of income inequality on the income–emissions relationship in the environmental Kuznets curve (EKC) framework. Findings indicate that the relationship is inverted U-shaped in middle-income G20 countries, but monotonically increasing in high-income G20 countries. Interestingly, income inequality moderates this relationship only in the latter group. These findings suggest that middle-income G20 countries should focus on raising income per capita to mitigate environmental degradation, while their high-income counterparts need to prioritize reducing income inequality to effectively decouple income from emissions.

Creating A Growth Mindset: A Mixed-Methods Program Review Research Study On The Effects Of Social–Emotional Learning On Retained Third-Grade Students, Casshaunda Davis

Electronic Theses and Dissertations

In Mississippi’s public elementary schools, third-grade students are faced with promotion–retention decisions from the third-grade state assessment and, when retention is the outcome, students often experience negative emotional outcomes. In our school setting, the challenge is how better to help our retained, third-grade students to cope with retention and to grow a strong mindset of self-efficacy towards academic achievement after experiencing retention. This mixed-methods program review research study was conducted to institute a social–emotional learning intervention program in our existing MTSS behavioral program offered to Tier III (at-risk) students. I followed an intervention program to foster a growth mindset for …

Numerical Calculations Of The Electromagnetic And Gravitational Wave Signatures Of Unequal Mass Black Hole Binary Inspirals, Madeline Clyburn

All Dissertations

In 2015, the Laser Interferometer Gravitational-Wave Observatory (LIGO) measured the first gravitational waves (GWs) from the coalescence of two stellar-mass black holes. This detection marked a historic milestone in astrophysics, confirming general relativity and establishing the existence of gravitationally bound black holes. Since then, researchers have extended the search to even more massive black hole mergers. Recently, the International Pulsar Timing Array (IPTA), including the North American Nanohertz Observatory for Gravitational Waves (NANOGrav), detected a nanohertz GW background from supermassive black hole binaries (SMBHBs), black holes with masses M ≃10^7−10^9 M⊙ orbiting throughout the universe. However, a single SMBHB has …

Dual-Model Approach For Accurate Chest Disease Detection Using Gvit And Swin Transformer V2, Kamal Ahmad, Hafeez Ur Rehman, Babar Shah, Farman Ali, Irfan Hussain

All Works

The precise detection and localization of abnormalities in radiological images are very crucial for clinical diagnosis and treatment planning. To build reliable models, large and annotated datasets are required that contain disease labels and abnormality locations. Most of the time, radiologists face challenges in identifying and segmenting thoracic diseases such as COVID-19, Pneumonia, Tuberculosis, and lung cancer due to overlapping visual patterns in X-ray images. This study proposes a dual-model approach: Gated Vision Transformers (GViT) for classification and Swin Transformer V2 for segmentation and localization. GViT successfully identifies thoracic diseases that exhibit similar radiographic features, while Swin Transformer V2 maps …

Curvilinear Image Segmentation Using Multiscale Variational U-Net, Rebekah Fortes

LSU New Orleans Theses and Dissertations

Segmentation of curvilinear structures such as water contours, cracks in cement, and vascular networks in biomedical imaging, poses unique challenges due to extreme class imbalance, irregular morphology, low contrast against complex backgrounds, and the need to preserve global connectivity while detecting fine-scale details. We propose a Multiscale Variational U-Net (MSVU-Net) architecture designed specifically to address these challenges. The model integrates multiscale convolutional filters to capture both global context and local detail, while embedding a variational model in the bottleneck layer to enhance structural representation. To mitigate class imbalance and improve fidelity, the network optimizes a hybrid loss function that combines …

Coupled Machine Learning Models: Combining Observations And Numerical Analysis In A Physics-Regularized Approach, Austin B. Schmidt

LSU New Orleans Theses and Dissertations

This dissertation investigates surrogate modeling for fixed-location environmental forecasting using novel data-combination techniques. The work surveys the landscape of observational measurements and numerically generated data, identifying similar research and gaps in current methodologies. The ratio-coupled training framework is introduced to combine two data sources per predicted feature through a tunable parameter that weights training signal strength. An optimization scheme is developed to simultaneously tune surrogate weights and the coupled signal ratio, allowing relative influence between signals to act as an explicit regularizer. Three case studies demonstrate the methodology and approach in a variety of contexts. The first study is based …

Peptoid-Based Molecular Analysis Utilizing High-Speed Molecular Dynamics Methods, In Chul Hwang

LSU New Orleans Theses and Dissertations

Polypeptoids are N-substituted glycine polymers, which differ from peptides in the placement of the side chain being present on the amide nitrogen rather than the backbone C_α. While both peptoids and peptides are composed of linked amino acids, the structural changes resulting from the differing origin of the side chain leads to distinct backbone structure, as well as remove the chirality found in the peptide structure. These differences lead peptoids to have different physiochemical and biological properties, such as being resistant to proteolysis and diverse three-dimensional structures that are not observed in peptides. With the shifting of the …

G2pdeep-V2: A Web-Based Deep-Learning Framework For Phenotype Prediction And Biomarker Discovery For All Organisms Using Multi-Omics Data, Shuai Zeng, Trinath Adusumilli, Sania Zafar Awan, Manish Sridhar Immadi, Dong Xu, Trupti Joshi

Biomedical Sciences

Multi-omics data offers rich insights into complex traits across organisms, yet integrating and analyzing these datasets for phenotype prediction and marker discovery remains challenging. Researchers need accessible tools that combine deep learning, hyperparameter optimization, visualization, and downstream analysis in a unified web platform. To address this, we developed G2PDeep-v2, a web-based platform powered by deep learning for phenotype prediction and marker discovery from multi-omics data across a wide range of organisms, including humans and plants. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm …

Development And Validation Of A Thermal Model For An Electric Vehicle Transmission, Ghazal Rajabikhorasani

Dissertations

This research investigates the thermal behavior of a high-speed electric vehicle (EV) helical gearbox with the goal of improving the prediction accuracy of component temperatures and total power losses under a range of operating conditions. The study focuses on developing a physics-based lumped-parameter thermal network model capable of capturing the main heat generation and dissipation mechanisms within the transmission. The model integrates experimentally validated loss correlations for gears, bearings, seals, and churning, as well as convective and radiative heat transfer paths.

The thermal network model was coded in MATLAB and validated through a series of controlled experiments performed on an …

Development Of The Hydrogeology Concept Inventory And Exploration Of Its Embedded Spatial Thinking Components, Oluwarotimi Akindele Popoola

Dissertations

Hydrogeology is a sub-discipline of geoscience that deals with the occurrence and movement of water and possible contaminants within the subsurface. Understanding basic principles of hydrogeology is important for applying practical solutions to hydrogeology problems. Hydrogeology is a visuospatial discipline in which spatial thinking skills play a significant role. To assess the hydrogeology knowledge of students, a valid and reliable assessment instrument with spatial components is required.

This research was conducted as a series of quantitative studies with three goals: (1) to develop the Hydrogeology Concept Inventory (HCI), a valid and reliable measure of upper-level undergraduate students’ hydrogeology knowledge, (2) …

Realization Of Deterministic Quantum Circuits For Non-Deterministic Or Incompletely Specified Quantum State Machines, Manjith Kumar, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In classical logic design, there are machine learning methods based on converting a set of input-output traces to non-deterministic automata that are then converted to deterministic automata and synthesized using logic gates. This approach has not yet been extended to quantum automata. In this paper, we present a method to convert a set of input-output traces to a non-deterministic automaton, which is then converted to an incompletely specified multi-output Boolean function. The existing logic synthesis approaches for designing quantum circuits are insufficient to handle incompletely specified functions. So, we present a novel algorithm to synthesize logic functions with don’t cares …

Development Of A Handy Tool For The Selection Of Urban Stormwater Best Management Practices, Aaron T. Kenny

Civil & Environmental Engineering Theses & Dissertations

The City of Norfolk, Virginia faces substantial stormwater management challenges due to shallow groundwater, tidal influence, dense urban development, and limited right-of-way. These constraints limit the applicability of many Best Management Practices (BMPs) and require the early identification of feasible practices before detailed hydrologic modeling. This thesis introduces a decision-support tool that quickly and systematically identifies and prioritizes BMPs that are both feasible and well-suited to Norfolk’s Municipal Separate Storm Sewer System (MS4) program, streamlining early-stage selection and saving time and resources.

The tool implements a two-stage methodology. First, feasibility gates are applied using catalog attributes derived from the Virginia …

Relativistic Three Particle Scattering, Md Habib E Islam

Physics Theses & Dissertations

In this dissertation, we develop and apply a relativistic framework for studying three-body scattering amplitudes, their analytic structure, and the emergence of universal phenomena such as the Efimov effect. The work integrates three complementary components.

First, we introduce a systematically improvable numerical method for solving relativistic three-body integral equations in momentum space. By discretizing the continuum problem into finite matrix equations and extrapolating to the continuum limit, we obtain stable partial-wave amplitudes in the presence of a two-body bound state. Two complementary treatments of the pole contribution are implemented and shown to reproduce previous finite volume results, with controlled estimates …

Piezoelectric Energy Harvesting From Roadways: Challenges, Advances, And Future Directions, Heba Gaber, Mohamed Abdelraheem

Faculty Publications

As the global demand for renewable energy intensifies, piezoelectric energy harvesting from roadways has emerged as a promising avenue for sustainable power generation. This systematic literature review analyzes 61 peer-reviewed studies to assess the feasibility, performance, and potential of integrating piezoelectric systems into roadway infrastructure. While technology faces challenges, such as high installation costs, limited energy output, and a scarcity of thorough economic evaluations, findings suggest it holds considerable promise as a supplementary renewable energy source. The review analyzes the operational characteristics and efficiencies of various piezoelectric transducers, identifies key factors influencing system performance, and evaluates recent technological advances. It …

(R2115) Analysis Of Single Server Queueing System With Differentiated Vacations And Differentiated Breakdowns, V. Karthick, V. Suvitha

Applications and Applied Mathematics: An International Journal (AAM)

This research work considers a single server queueing model with differentiated vacations. In addition there is a possibility of two types of failures when the server is in a busy period; namely hard failure and soft failure. In the time of soft failure server may work with a slow service rate. We analyzed as a Quasi-Birth-and-Death (QBD) process, using the matrix geometric method, the steady state probability vector of the number of customers in the queue and the stability conditions are produced. Busy period analysis of the proposed model in given. The effects of various parameters on the system performance …

(R2132) A Multi Server Markovian Working Vacation Queue With Randomly Varying Environment, A. Sundaramoorthy, R. Kalyanaraman

Applications and Applied Mathematics: An International Journal (AAM)

In this article, we consider a multi server Markovian queueing system with working vacation. During busy period, the arrival and service completion are generated by K distinct randomly varying environments. At a service completion epoch, if no customer in the system, the servers take vacation, the vacation policy is multiple vacation policy and the vacation period follows negative exponential distribution. In addition, during vacation period the servers serve customers if they arrive. Based on the vacation termination point we define two Models. For the two models, the steady state probability vector of number of customers in the queue, the stability …

(R2135) System Dynamical Analysis For Ann-Based Numerical Solutions Of A Compartmental Model: A Bio-Mathematical Model Of Drug Diffusion Through The Compartments Of Blood And Tissue, Rakesh Kumar, Sudarshan Dhua

Applications and Applied Mathematics: An International Journal (AAM)

This paper provides a considerably efficient numerical approach to acquire the solutions of a biomathematical model administrating oral and intravenous distribution of pharmaceuticals in the human body. The proposed numerical approach based on an artificial neural network is employed to extract numerical solutions for a detailed set of ordinary differential equations and analyze the change in concentration of drug diffusion via the compartments of blood and tissue medium. We primarily focus on analyzing three different models established on the diffusion process, exercising laws of mass action and Fick’s principle. In this work, the existing model is reformulated as an optimization …

(R2107) Analysis Of A Bivalent Vaccine Model With Peer Influence Effect On Testing, Manoj Kumar Singh, Anjali .

Applications and Applied Mathematics: An International Journal (AAM)

The coronavirus caused havoc around the world. There was a terrible situation in villages and cities, and no one knew how to deal with it. Although the governments of each country tried their best to save the common people, vaccination programs and testing centers were built everywhere. However, people were not utilizing it due to fear. Because of this, the infection spread rapidly. The qualitative study of the mathematical model here is in context with the situation when bivalent vaccination and testing are available for an epidemic. The mathematical model combines the exposed period and influenza model with vaccination included …

Triple-Parametric Autoencoder For 2d Reparameterization Via Bézier, B-Spline, And Nurbs Representations, Shaoliang Yang, Jun Wang

Mechanical Engineering

This paper proposes a sample-wise triple-parametric deep learning framework (TPDLF) for 2D curve parameterization. The proposed framework integrates Bézier, B-spline, and Non-Uniform Rational B-spline (NURBS) curve formulations within a unified neural network architecture, enabling the reconstruction of smooth and closed 2D curves such as real-world airfoil and synthetic Superformula shapes (with -fold symmetry). An encoder compresses the input curve shape into a latent space, while three distinct decoders untangle the latent space by inferring corresponding governing parameters for each parameterization (i.e., Bézier/B-spline/NURBS). The corresponding reconstruction modules are then deployed to ensure smooth curve generation using the governing parameters …

Topic Modeling And Culturomic Analysis Of 30,000 Books Over 100 Years Using Gensim, Michael A. Freeman

Electronic Theses and Dissertations

This thesis explores the cultural influence of historical events on English-language fiction published between 1820 and 1929. Using a corpus of 30,256 digitized books from Project Gutenberg, Latent Dirichlet Allocation (LDA) topic modeling was applied to identify recurring themes across eleven decades. The study sought to determine whether historically significant events could be detected within fictional narratives. One clear instance emerged: Napoleon Bonaparte and the Napoleonic Wars appeared explicitly in the 1820s corpus. Beyond this, several thematic patterns were observed—such as maritime language in the 1840s, national identity in the 1880s, and youth-oriented dialogue in the early 20th century—that plausibly …

A Deep Learning And Causal Modeling System For Retinal Disease Diagnosis, Shiyu Tian

Dissertations (1934 -)

Vision-threatening retinal diseases, such as diabetic retinopathy (DR) and diabetic macular edema (DME), are major causes of preventable blindness worldwide. Early screening and follow-up are essential, but advanced imaging like Optical Coherence Tomography (OCT) is expensive and not always available outside large clinics. In contrast, color fundus photography is inexpensive and common, yet it only shows a surface view and can miss subtle changes inside the retina. These practical limits make it hard to deliver timely, high-quality eye care in many settings. As AI is increasingly used in healthcare, retinal disease diagnosis has benefited as well. This work combines deep …

Isolation Of The 2019 Bonnet Carré Spillway Effects On The Habitat Suitability Of Brown Shrimp (Farfantepenaeus Aztecus) And Blue Crab (Callinectes Sapidus) Using A Modeling Approach, Mallory Dyson

Master's Theses

In 2019, an unprecedented flood year, the Bonnet Carré Spillway (BCS) was opened on two separate occasions (February 27^th to April 11^th, and May 10^th through July 27^th) diverting a volume 6 times the volume of Lake Pontchartrain into the surrounding coastal waters of Louisiana, Mississippi, and Alabama. The goal of this research was to determine the spatio-temporal influence of these freshwater releases on two economically and ecologically important species (Farfantepenaeus aztecus and Callinectes sapidus) with variable responses to salinity and temperature depending on the age class. The Habitat Suitability Index (HSI) …

Early Career Setback And Future Achievement In Professional Sports, Suman Kalyan Maity, Yang Wang, Nima Dehmamy, Victoria Medvec, Brian Uzzi, Dashun Wang

Computer Science Faculty Research & Creative Works

A central tenet of human performance posits that past success is a key predictor of future outcomes. This principle underpins selection processes in various human endeavors, shaping opportunity, wage, and winner-take-all inequalities. Here we systematically examine the future performance of previous winners and non-winners across two sports contexts using two different empirical strategies. First, we track young athletes participating in world-class track and field competitions and compare the future performance of bronze medalists to those finishing just shy of the podium. Next, we study a novel natural experiment in tennis, where we compare future performances of 'lucky losers'—players who advanced …

Real-Time Estimated Sequential Organ Failure Assessment (Sofa) Score With Intervals: Improved Risk Monitoring With Estimated Uncertainty In Health Condition For Patients In Intensive Care Units, Yan He, Qian Luo, Hai Wang, Zhichao Zheng, Haidong Luo, Oon Cheong Ooi

Research Collection Lee Kong Chian School Of Business

Purpose: Real-time risk monitoring is critical but challenging in intensive care units (ICUs) due to the lack of real-time updates for most clinical variables. Although real-time predictions have been integrated into various risk-scoring systems to aid monitoring, existing systems do not address uncertainties in risk assessments. We developed an enhanced risk monitoring framework based on commonly used systems like the Sequential Organ Failure Assessment (SOFA) score by incorporating uncertainties to improve the effectiveness of real-time risk monitoring in ICUs.Methods: This study included 5,351 patients admitted to the Cardiothoracic ICU in the National University Hospital in Singapore. We developed machine learning …

By The Numbers: Numeracy, Religion, And The Quantitative Transformation Of Early Modern England (Book Review), Calvin Jongsma

Faculty Work Comprehensive List

Reviewed Title: By the Numbers: Numeracy, Religion, and the Quantitative Transformation of Early Modern England by Jessica Marie Otis. New York, NY: Oxford University Press, 2024. 264 pp. ISBN: 9780197608777.

Visual Simultaneous Localization And Mapping For Multi-Robot Collaboration, Aidan O’Hare

Electrical and Computer Engineering Master's Theses

As society continues to progress with robotics and automation, the significance of multi-robot systems continues to increase. Single robot systems are limited in their capacity to carry out certain types of tasks, similar to how one person is limited. When it comes to carrying large, cumbersome objects that would require multiple entities to move in a coordinated manner, it is very apparent that implementing a multi-robot system is necessary. Multi-robot systems have become a sector of robotics of increasing interest due to the multitude of use cases they are able to fulfill. However, scalability is a large part of the …

Host-Intrinsic Factors Determine Anti-Tumor Efficacy Of Exercise In Pancreatic Ductal Adenocarcinoma, Sumedha Pareek

Dissertations and Theses (Open Access)

Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths with a low 5-year relative survival rate of approximately 13.3% for all stages combined. We have previously shown that exercise can improve quality of life and enhance functional capacity among patients with PDAC. Exercise induces a variety of changes in the tumor microenvironment with beneficial effects in several tumor types. However, our understanding of the clinical effects of exercise and the mechanisms that mediate anti-tumor effects are limited in pancreatic cancer.

In this project, using C57BL/6 mice from Taconic Biosciences (Tac) and Jackson Laboratories (Jax), we established a …