Digital Commons Network^™

Optimizing Power Grids In Uae Using Data Analytics For Improved Efficiency And Reliability, Khalid Bukhashem

Theses

The United Arab Emirates (UAE) has aims to triple its renewable energy capacity to 14 GW to attain the objective of 30% contribution of clean energy by 2031. Energy consumption, on the other hand, will increase from 5.2 to 5.8 exajoules by 2028. The grid infrastructure for which was developed to facilitate the centralized generation of power, is not conducive to dealing with the variability of the decentralized renewable resources that lead to inefficiencies in operation and reliability problems. The Dubai power grid is analyzed using historical data of 105,120 residential, commercial and industrial supplies. In this analysis machine learning …

An Examination Of High-Entropy Alternatives Of Connectionist Temporal Classification Loss For Optical Music Recognition Using Convolutional Recurrent Neural Networks, Hritik Saynganthone

Theses

The Connectionist Temporal Classification (CTC) loss function is the most commonly used loss function in the field of Optical Music Recognition (OMR). However, OMR suffers from a massive class imbalance problem, exacerbated by the fact that CTC loss is subject to the spiky distribution problem, wherein the blank token introduced by CTC is vastly overpredicted and appears in timesteps where it would make more sense to predict a non-blank token, since CTC will collapse repeated tokens into a single token. This work posits that alternative loss functions to CTC that optimize for an increase in entropy of the prior probability …

Mixed-Integer Linear Programming (Milp) Model For Transportation Cost Optimization, Yasmen Ghonim

Theses

Motivated by a request from a real company, this study presents a mixed integer linear programming (MILP) model for labor transportation at real company located in Dubai (BSG). The study integrates routing, assignment, and environmental pricing into one model, with the focus on fixed shift worker transport and featuring several dorms and sites. It also tests the model with the real company data from the UAE service sector. The model assigns workers from dormitories to the client sites by busses in a manner that minimizes daily transport cost and monetized CO₂ emissions, subject to capacity, routing, and utilization constraints. The …

Assessing Large Language Models As An Interpretive Layer In Marketing Mix Modeling: Implications For Marketing Analytics, Mohammad Bin Haider

Theses

Marketing mix modelling (MMM) remains a core technique for guiding budget allocation, yet its outputs are often difficult for non-technical planners to interpret and govern. At the same time, large language models (LLMs) offer new possibilities for translating complex model artefacts into narrative guidance, but raise concerns about hallucination, reproducibility, and alignment with model-risk governance. This thesis examines whether an open-source MMM framework can be engineered as a repro- ducible, governance-ready pipeline and then augmented with a tightly constrained LLM interpretive layer. The empirical setting is a multi-brand, multi-country retail portfolio with several years of digital marketing and outcome data …

Same Data, Different Analysts: Variation In Effect Sizes Due To Analytical Decisions In Ecology And Evolutionary Biology, Elliot Gould, Hannah S. Fraser, Timothy H. Parker, Shinichi Nakagawa, Simon C. Griffith, Peter A. Vesk, Fiona Fidler, Daniel G. Hamilton, Robin N. Abbey-Lee, Jessica K. Abbott, Luis A. Aguirre, Carles Alcaraz, Irith Aloni, Drew Altschul, Kunal Arekar, Jeff W. Atkins, Joe Atkinson, Christopher M. Baker, Meghan Barrett

Faculty Research, Scholarly, and Creative Activity

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope …

Geochemical Analysis Of The Eagle Ford Shale In Webb And Dimmit Counties, Tx, Natalie G. Girlinghouse

Electronic Theses and Dissertations

The Late Cretaceous Eagle Ford Shale of South Texas is a mixed carbonate–siliciclastic succession that serves as both a prolific hydrocarbon source and reservoir. This study integrates chemostratigraphy, mineralogical analysis, and elemental ratio proxies to reconstruct depositional environments and assess controls on detrital influx, paleoproductivity, and redox conditions across multiple cores in Webb and Dimmit counties. Major, trace, and redox-sensitive elements were evaluated alongside Total Organic Content (TOC) and carbonate content to identify stratigraphic trends and environmental shifts.

Results reveal distinct geochemical signatures between the Upper and Lower Eagle Ford Shale, with the Lower Eagle Ford characterized by elevated Al-rich …

Structural Geology Of The Brady Mountain Area, Ouachita Mountains, Arkansas: Integrating Field Mapping, Geospatial Techniques, Photogrammetry And 3d Modeling For Structural Analysis, Emmanuel Darko, Zachariah Fleming

Electronic Theses and Dissertations

Much of the Ouachita orogenic belt, representing the deformed Paleozoic rocks flanking the southern margin of the North American craton, is buried beneath post-orogenic Mesozoic and Tertiary sediments composing the Gulf Coastal Plain. The Ouachita Mountains of Arkansas and Oklahoma are the largest areas of outcrop for the Pennsylvanian-age Ouachita orogenic belt, making it an ideal place to study the orogeny. This study focuses on the Brady Mountain area within the Benton Uplift, the orogenic core of the Ouachita Mountains in western Arkansas. The region is comprised of numerous ridges trending nearly east-west and are for the most part densely …

Glacial Deposits, Vol. 50, 2025, Illinois State University

Glacial Deposits

Newsletter of the Illinois State University Department of Geography, Geology, and the Environment

Fractional Order Hierarchical Decompositions Using Multigrid Components, Panayot S. Vassilevski

Mathematics and Statistics Faculty Publications and Presentations

Motivated by the fractional order multilevel decompositions of finite element spaces developed previously, we exploit additive representations of popular multigrid (MG) cycles to design fractional order MG decompositions. The additive representations enable us to scale the individual hierarchical components thus ending up with fractional order hierarchical decompositions that are based on the readily available MG components. This results in a highly efficient and scalable (in terms of high-performance) fractional order hierarchical MG decompositions that we tested in the setting of finite element white noise sampling as an alternative to PDE-based white noise sampling using fractional order shifted Laplacians.

Navigating Seismic Anisotropy, With Applications To Alaska, Aakash Gupta

Geosciences

Seismic anisotropy characterizes how elastic waves travel through solid materials with different speeds, depending on the direction of the waves and the direction of particle motion of the waves. Evidence of seismic anisotropy in the Earth is widespread, from seismic waves sampling the crust, mantle and even the core, to active-source, industry-scale seismic experiments, to laboratory mea­ surements of rock samples from boreholes or at the surface. Global models of the Earth provide a highly averaged image of anisotropy. Studies based on shear wave splitting measurements from local and global earthquakes indicate that the anisotropy in the Earth is much …

Examination Of Differences Of Similar-Sized Martian Craters At The Simple-Complex Transition As Revealed By High-Resolution Imaging And Stereo-Derived Topography, Lindsey Dorn

Geosciences

Impact craters on Mars have a wide range of morphologies, and the relationship between the mechanics of their formation and their eventual morphologies is still not completely understood. By examining craters within a narrow diameter range, impact energies are constrained to similar values - enabling focused investigation of target properties and their influence on crater excavation and modification. There is a transition from simple bowl-shaped depressions to complex craters with terraced walls and central floor structures with increasing crater diameter. We analyzed target influences on morphology by examining eleven well-preserved craters of varying morphologies in the 7 to 9 km …

Ice Surface Change And Flow Dynamics Analysis Of Sít’ Tlein (Malaspina Glacier) Through Remote Sensing, Victor Devaux-Chupin

Geosciences

Sít’ Tlein, located in southeast Alaska, is the largest piedmont glacier in the world. Periglacial lake expansion, low-lying bed, and proximity to the Pacific Ocean put its glacier lobe at risk of rapid retreat. Its disappearance would equate to removing an area of land about half the size of Rhode Island. Sít’ Tlein exhibits complex ice flow responsible for its iconic folded moraines, and for its heterogeneous ice resupply in its lobe, which occasionally surges. This lobe is gradually mantled by debris and vegetation as the ice flow fades towards its margins, protecting it from melting. This the­ sis is …

Multi-Scale Insar Investigations Of Anthropogenic And Natural Processes In The American Southwest, Emily Jo Graves

Geosciences

Arid regions in the American Southwest undergo measurable surface deformation driven by variations in subsurface fluid pressure, and other natural and anthropogenic processes. These processes range from regional scale aquifer dynamics to local oil and gas wellsite activities. This dissertation produces and then utilizes InSAR-derived average velocity fields and displacement time series to reveal and understand these multi-scale processes, their interactions, and impacts for a portion of the American Southwest. Chapter 1 discusses the climate and natural and anthropogenic processes present in our study area. In Chapter 2, we generate detailed large scale average velocity maps that reveal deformation associated …

Security Vulnerabilities And Defense Tactics For Generative Ai Application Development, Kyle Klein

University Honors Theses

Generative AI (GenAI) applications such as OpenAI's ChatGPT leverage large language models (LLMs) trained on enormous amounts of data to accomplish tasks such as document editing, summarization, and query response. Chatbots and LLM programs that are equipped with retrieval-augmented generation (RAG) have the ability to draw upon data provided by developers and users to improve the quality of the program's responses. LLM technology has even expanded to generate images, audio, and video from user instructions. Designed around unpredictable user input and typically composed of many opaque components, LLM software products face a paradigm shift of new, constantly evolving security challenges. …

Muc15 Ectodomain Architecture Regulates Integrin Clustering To Control Cancer Metastasis, Simei Zhang, Guy M Genin, Et Al.

2020-Current year OA Pubs

Cancer metastasis is governed by physical cues at the cell-matrix interface, with matrix stiffness, ligand density, and topography established as key determinants. Here, a fourth critical factor in cancer metastasis, the architecture of the cell-surface glycocalyx is identified. Using MUC15 as a representative small glycoprotein, mathematical modeling and domain truncation experiments are combined to show that glycoprotein size distribution governs integrin adhesion states and metastatic outcomes. MUC15 localizes to focal adhesions and interact with integrins, while larger glycoproteins such as MUC1 are sterically excluded. These physical effects, rather than intracellular signaling, dictate adhesion state transitions: removing MUC15's ectodomain eliminated its …

Does Health Insurance Coverage Improve Cardiometabolic Risk Factor Levels? Quasi-Experimental Evidence From India, Kavita Singh, Anubha Agarwal, Mark D Huffman, Et Al.

2020-Current year OA Pubs

BACKGROUND: Chronic conditions cause notable health and economic burdens. While health insurance enables access to healthcare, its effects on chronic care outcomes remain under-explored.

OBJECTIVE: To examine the association between health insurance coverage and cardiometabolic risk factors among people with chronic conditions in India.

METHODS: Data from the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) and Solan studies, including 2,926 adults with chronic conditions were analyzed using propensity score weighting to evaluate the associations between health insurance and cardiometabolic risk factors (HbA1c, low-density lipoprotein cholesterol [LDLc], and blood pressure [BP]) and self-reported health status (measured using European Quality …

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 …

Studies On Curcumin-Glucoside In The Prevention Of Alpha-Synuclein Aggregation, Lakshmi Sowmya Emani, Jayanth K. Rao, Jagadeesha Kumar Dasappa, Marisín Pecchio, Johant Lakey-Beitia, Hansapani Rodrigo, Jessica Cruz-Mora, Priya Narayan, Nikhilesh Anand, Bharathi Gadad

School of Medicine Publications

Background: α-synuclein (α-syn) deposition in the mid-brain region is one of the hallmark pathologies of Parkinson's disease (PD). The key steps involve the transformation of α-synuclein into a toxic oligomer and insoluble fibrillar aggregates.

Objective: To understand the role of curcumin-glucoside in the prevention of α-syn aggregation, a mechanistic approach.

Methods: In the present study, we synthesized a novel molecule, curcumin-glucoside (Curc-gluc), to improve the water solubility and partition coefficient, making the molecule with high bioavailability. The present study is focused on understanding the α-syn aggregation kinetics in the presence and absence of Curc-gluc, curcumin (Cur), copper (Cu), and iron …

Terrestrial And Lacustrine Organic Matter Biomolecular Transformations Via Thermal Maturation And Oxidative Degradation, Louis Connor Bondurant

Chemistry & Biochemistry Theses & Dissertations

The most abundant source of fossil fuel-forming kerogen on Earth is classified as Type II kerogen, believed to originate from marine biomass. However, a significant amount of lacustrine and terrigenous carbon is transported to the ocean through fluvial discharge. Less than half of the exported organic carbon is observed in coastal regions and the open ocean. There is a great need for an explanation of what is happening to this organic carbon during transport and deposition. Traditionally, the marine organic matter in coastal regions accumulates to eventually be buried and transformed into petroleum over millions of years due to its …

Sciteuq: Toward Uncertainty-Aware Complex Scientific Table Data Extraction And Understanding, Kehinde Ajayi

Computer Science Theses & Dissertations

Scientific tables report critical research insights, data, and findings for scientific progress. Because Portable Document Format (PDF) is the de facto standard format for scientific paper publishing, there has been an emerging need for an automatic method to extract data from PDF files. A significant fraction of scientific tables exhibit complex structure and content, making it challenging for machine learning tools to accurately extract the content directly from PDF files. Despite the advancements in Table Structure Recognition (TSR), automated extraction of data from complex scientific tables remains a challenge due to variations in table structures and contents. In this dissertation, …

Exploring Student Confidence And Calibration Accuracy In College Algebra: A Mixed-Methods Explanatory Sequential Study, Courtney T. Hill

STEMPS Theses & Dissertations

Calibration, or students’ ability to predict and postdict their performance on an academic task, has important implications for academic performance. It can influence students' decision making processes concerning learning activities, as well as their levels of motivation and self-regulation (Kolovelonis, 2023). The literature on calibration is clear, often indicating that students are not great at these judgements (Lin et. al, 2001). While this phenomenon is well documented, it is not an easy one to explain. Therefore, a two-phase explanatory-sequential mixed method design was used to examine undergraduate students’ calibration judgements on a college algebra exam. To further contribute to the …

The Paradox Of Discipline: Equity, Standardization, And Black Student Outcomes In Public Schools, Latricia T. Davenport

Educational Leadership & Workforce Development Theses & Dissertations

Despite efforts to address profound discipline disparities impacting Black students, the implementation of alternative disciplinary approaches like Positive Behavioral Interventions and Supports (PBIS) and Restorative Justice (RJ) has failed to eliminate significant disproportionality in school discipline. This study investigates how teachers navigate the challenges of disciplining Black students within a paradoxical school environment that juxtaposes equitable, human-centered methods with a historically rooted managerial paradigm emphasizing uniformity and zero tolerance. Drawing upon systemic racism and the concept of 'apprenticeship of observation,' this study explores how teachers' implicit biases about Black students are formed by long-held institutional norms and personal experiences. It …

Examining The Perceptions Of Economics And Personal Finance Teachers' Preparedness To Teach Financial Literacy, Tasha L. Wearren

Educational Leadership & Workforce Development Theses & Dissertations

Financial literacy has become an important topic in our society. Despite an increased focus in financial literacy education, there is limited research assessing teachers’ ability to teach financial literacy by examining their endorsement area. According to Soroko (2021), research is limited regarding teachers’ beliefs and practices as it relates to financial literacy. As O’Neill and Hensley (2016) indicated, “Teachers cannot teach personal finance well if they do not understand it themselves and/or cannot engage their students” (p. 639). This qualitative multiple case study examined how Economics and Personal Finance teachers perceive their preparedness to teach financial literacy with different endorsements. …

Design And Assessment Of A Single-Blade Rotary Wing For Use In Vertical Takeoff And Landing (Vtol) Aircraft, William C. Mcmasters

Mechanical & Aerospace Engineering Theses & Dissertations

A single-bladed propeller was designed to determine its efficacy in increasing efficiency of quadplane aircraft in the cruise configuration while still providing sufficient vertical lift for the vertical takeoff portion of flight. Aerodynamic theory predicts higher efficiency for single-blade propellers, resulting in a lower power requirement. A counter-weighted single-blade was modeled after a 10x5 model aircraft propeller used in small unmanned vehicles with a steel counterweight to balance centrifugal forces. The propeller was tested in the ODU wind tunnel to determine performance at various Advance Ratios (J). The research suggests that single-blade propellers show comparable performance compared to two-bladed propellers …

Making Explanations Make Sense: Xai For Smishing Detection, Eleni Alexandra Katsarakes

Psychology Theses & Dissertations

Explainable Artificial Intelligence (XAI) is a key component of effective human-AI collaboration, particularly in high-stakes domains such as cybersecurity. While AI tools hold promise for mitigating threats such as SMS-based phishing (SMiShing), their real-world effectiveness may hinge not just on detection accuracy, but on whether users can make sense of the system’s outputs. As SMiShing attacks grow in both frequency and sophistication, so does the urgency of designing human-centered AI systems that support user decision-making under uncertainty. This study examined how four distinct AI explanation types - Normative (rule-based), Attributive (feature-based), Exemplar (case-based), and Recommendation-Only - influence user performance, confidence, …

Comparative Analysis Of Emergent Behaviors Of Three Drone Swarm System Models For Targeting Using Agent-Based Modeling And Simulation, Arsenio T. Gumahad Ii

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation introduces a novel computational simulation framework for evaluating the emergent behaviors of three swarm drone models using Agent-Based Modeling and Simulation (ABMS). The three swarm models are a Leader-Follower swarm model based on Bruckstein's antline theory, a Flocking model based on a simplified Reynolds 'Boids’ model, and a Stigmergic model with pheromone-based coordination. The primary objective of the simulation is to evaluate the performance of these models in delivering a user-defined number of drones of each type to a target area of interest in four separate scenarios, resulting in 50,000 separate simulation trials. Each scenario was structured to …

A Kinematic, Data-Parameterized Approach To Constrain Subducted Seafloor During The Emplacement Of Shatsky Rise, Alexzandrya Katrina Shotorban

OES Theses and Dissertations

This study investigates ridge spreading rates and plate boundary geometry in interactions between large igneous provinces and mid ocean ridges, and their role in the kinematics of Shatsky Rise, an undersea volcanic plateau in the western Pacific Ocean that is roughly the size of the state of California. Shatsky Rise formed at a ridge-ridge-ridge (RRR) triple junction (TJ) (Hilde et al., 1976; Sager et al., 1988), at the intersection of the Pacific-Izanagi, Pacific-Farallon, and Izanagi-Farallon ridges, beginning at approximately 147 Ma. Investigations into Shatsky Rise’s formation are limited by the fact that two-thirds of the seafloor data has subducted with …

Component Model Development Of Heat Exchangers, Expanders, And Control Valves For Autonomous Cryogenics Plant Cool-Down, William Harris Buhrig Iv

Mechanical & Aerospace Engineering Theses & Dissertations

The traditional method of cryogenic plant cool-down involves having continuous on-call staff to head into the office at any time to modify the existing multi-layered PID control systems if the on-call staff member detects a significant deviation from the cool-down plan. This thesis aims to outline an effective method for modeling the structure of systems with performance characteristics that deviate from design requirements and from ideal inlet-outlet correspondence, enabling the adjustment and modification of existing control structures across all Thomas Jefferson National Accelerator Facility (JLab) cryogenic refrigeration plants. Analytical Modeling and Gaussian Process Regression (GPR) are applied to model the …

Human Identification And Action Recognition Using Small Data And Deep Domain Adaptation, Alexander M. Glandon

Electrical & Computer Engineering Theses & Dissertations

Human identification and human action recognition problems are two important research areas for real-world security and surveillance applications. In both human identification and action recognition, it is necessary to operate by collecting small datasets in the field, possibly in a short time window of observation. This dissertation studies and develops computational modeling and high-performance machine learning (ML) and deep learning (DL) models for human identification and human action recognition using small amounts of data. These methods and computational models may be useful for different security and surveillance applications.

This dissertation on human recognition develops a ML computational model to estimate …

Toward Personalizing Quantum Computing Education: An Evolutionary Llm-Powered Approach, Iizalaarab Elhaimeur

Computer Science Theses & Dissertations

Quantum computing education faces significant challenges due to its complexity and the limitations of current tools. This thesis introduces a novel Intelligent Teaching Assistant for quantum computing education and details its evolutionary design process. The system combines a knowledge-graph-augmented architecture with two specialized LLM agents: a Teaching Agent for dynamic interaction and a Lesson Planning Agent for lesson generation. The system is designed to adapt to individual student needs, with interactions meticulously tracked and stored in a knowledge graph. This graph represents student actions, learning resources, and their relationships, aiming to enable reasoning about effective learning pathways. We describe the …