Digital Commons Network^™

Experimental Investigation Of Thermosyphon Thermal Performance Using Different Filling Ratio, Talib Z. Farge, Samar J. Ismael, Rawad M.Thyab

Engineering and Technology Journal

The present work investigated the thermal performance of thermosyphon by using distilled water as a working fluid at different filling ratios (50%, 60%, and 70 %). The thermosyphon was manufactured from a copper tube with outer and inner diameters (26 and 24) mm, respectively. The thermosyphon was tested experimentally at different input power (100, 200 and 300) Watt. The operating temperature of the oil was chosen below 85°C. Experimental results revealed that the filling ratio of 60% exhibited the best heat dissipation at the highest operating temperature. While the low operating temperature and 50 % filling ratio show better heat …

Direct Shear Strength Of Rpc Member, Shahad Q. Madhlom, Hussein A. Aziz, Ammar A. Ali

Engineering and Technology Journal

In this research paper, results are obtained from Reactive Powder Concrete (RPC) push-off specimens - double L shape subjected to direct shear loading. Different parameters considered are compressive strength, percentages of steel fiber, presence of aggregate and shear reinforcement. The results show that increasing in steel fiber content starting from 0.0% and ending with 1.5% leads to increases in the shear strength by (261%) and attempt to decrease its brittleness. The presence of steel fiber content enhances and improves the tensile strength and the shear strength. Using RPC in constructing the specimens enhances the shear strength by 29.6% compared with …

Novel Dynamic Batch-Sensitive Adam Optimiser For Vehicular Accident Injury Severity Prediction, Daniel Asare Kyei, Alimatu Saadia-Yussiff, Maame G. Asante-Mensah, Abdul Lateef-Yussiff, Charles Roland Haruna, Derry Emmanuel

Iraqi Journal for Computer Science and Mathematics

The choice of optimiser is important in deep learning, as it strongly influences model efficiency and speed of convergence. However, many commonly used optimisers encounter difficulties when applied to imbalanced and sequential datasets, limiting their ability to capture patterns of minority classes. In this study, we propose Dynamic Batch-Sensitive Adam (DBS-Adam), an optimiser that dynamically scales the learning rate using a batch difficulty score derived from exponential moving averages of gradient norms and batch loss. DBS-Adam improves training stability and accelerates convergence by increasing updates for difficult batches and reducing them for easier ones. We evaluate DBS-Adam by integrating it …

Genpix: A Diverse Dataset For Fake Image Detection, Guessoum Dalila, Benblidia Nadjia, Boumahdi Fatima, Remmide Mohamed Abdelkarim, Nouri Tarek-Amine, Bataouche Azeddine-Lotfi

Iraqi Journal for Computer Science and Mathematics

The rapid advancement of sophisticated generative models has intensified the need for robust fake image detection systems. However, many existing benchmark datasets suffer from limited diversity in content types and generation techniques, constraining the generalization ability of detection models. To address these limitations, we introduce GenPix (Generalized Pixels), a comprehensive dataset encompassing over 80,000 images spanning diverse categories, including faces, objects, and scenes, generated by multiple state-of-the-art models such as Generative Adversarial Networks (GANs) and diffusion-based architectures. The dataset includes samples from different generation methods to ensure broad coverage of fake image characteristics.

GenPix provides a realistic evaluation environment that …

Eyolov8-Msaff: An Enhanced Object Detection Algorithm With Multi-Scale Attention And Feature Fusion For Small And Dense Object Detection In Uav Applications, Mohammed Hasan Mutar, Morteza Valizadeh, Alaa Hussein Abdulaal, Mehdi Chehel Amirani

Iraqi Journal for Computer Science and Mathematics

The proliferation of unmanned aerial vehicles (UAVs) has necessitated the development of sophisticated object detection algorithms capable of handling the unique challenges posed by aerial imagery. Traditional detection methods often struggle with small object sizes, dense distributions, and complex backgrounds characteristic of UAV-captured scenes. This research presents EYOLOv8-MSAFF (Enhanced YOLOv8 with Multi-Scale Attention and Feature Fusion), a novel deep learning architecture specifically engineered for superior performance in UAV-based object detection tasks. The proposed methodology integrates four innovative components: a Hybrid Spatial-Channel Attention Mechanism (HSCAM) that processes attention information in parallel rather than sequentially, an Adaptive Multi-Scale Feature Fusion Module (AMSFFM) …

A Novel Hierarchical Multi-Scale Attention Mechanism For Enhanced Yolov8 Performance In Unmanned Aerial Vehicle-Based Small Object Detection, Mohammed Hasan Mutar, Morteza Valizadeh, Alaa Hussein Abdulaal, Mehdi Chehel Amirani

Iraqi Journal for Computer Science and Mathematics

Object detection in Unmanned Aerial Vehicle (UAV) images presents significant challenges due to the prevalence of small and densely packed objects, as well as variations in scale, orientation, and lighting conditions. This paper introduces a novel object detection algorithm, Hierarchical Multi-Scale Attention YOLO (HMSA-YOLO), which is an improved version of YOLOv8 designed to address these challenges. The proposed method incorporates a novel Hierarchical Multi-Scale Attention (HMSA) module, a Bidirectional Feature Pyramid Network (BiFPN) for enhanced feature fusion, a modified loss function, and an adaptive anchor optimization technique. The HMSA module effectively captures both channel and spatial dependencies at multiple scales, …

Comparative Performance Evaluation Of A Gpu-Accelerated Watershed Model For Flood Inundation Mapping, Maliha Ali

Electronic Theses and Dissertations 2020 - Present

This study evaluates PyWMP (Python-based Watershed Modeling and Planning), which is a flood modeling framework developed by the Center for Water Resiliency and Risk Reduction (CWR3) at Florida Atlantic University (FAU). The framework includes a 2D Rain-on-Mesh (ROM) solver, which is an explicit finite-volume shallow-water equation model. PyWMP is compared against HEC-RAS 2D and Flood Modeller for their rain-on-grid capabilities for watershed-scale flood inundation mapping under three design storm scenarios. The performance of PyWMP was evaluated using both quantitative and spatial metrics. Mean absolute error values showed that the average depth difference between each model is under 1 foot. Percent …

Analysis Of Flood Modeling For The Replication Of An Extreme Rainfall Event In South Florida, Lusnel Fritznel Ferdinand

Electronic Theses and Dissertations 2020 - Present

Flooding is the most common natural disaster in the United States, and trends show an increase in flood risk for the foreseeable future. Florida averages 45 flood disasters per year, at an annual cost of $86 million. Communities in Florida are susceptible to a variety of flood-inducing sources, including tropical cyclones, extreme rainfall, and rising sea levels, which can impact the tourism industry and the economic well-being of residents. The first objective of the thesis was to use flood modeling to replicate the extreme rainfall event that caused heavy flooding in Broward County, Florida, from April 12-13, 2023. A commercial …

Multiscale Network Modeling Of Native And Modified Photosynthetic Light-Harvesting Complexes, Zane E. Armijo

Chemical and Biological Engineering ETDs

Photosynthetic light-harvesting complexes harvest solar energy and direct electronic excitations toward reaction centers with exceptional efficiency. This dissertation models the Fenna--Matthews--Olson complex of green sulfur bacteria, coupled to the PscA1 reaction center, as a chromophoric network. Forster resonance energy transfer theory, validated against numerically exact hierarchical equations of motion, was implemented in kinetic Monte Carlo simulations to resolve fine-grained excitation-transport pathways. The predicted charge-transfer efficiency of 77\% agrees with experiment, with the FMO2 monomer and its gateway pigment governing interfacial transfer. Systematic single, multi, and symmetry-preserving site removals, interpreted through Mobius inversion, identify critical pigments and show that cooperative effects …

Developing Simulation To Improve G3p3 Efficiencies, Andrew Gaudette

Mechanical Engineering ETDs

Concentrated solar power (CSP) systems offer a promising method of renewable energy generation by using heliostats to focus sunlight onto a falling particle receiver. At the National Solar Thermal Testing Facility (NSTTF), particles absorb and store solar energy for later power generation. A major source of efficiency loss is wind-driven particle escape through the receiver aperture. This thesis develops computational fluid dynamics (CFD) simulations to characterize wind flow around the G3P3 falling particle receiver and support future wind mitigation strategies. Numerical studies were conducted to establish an appropriate simulation methodology. Iteration studies showed that 2,000 iterations were sufficient for convergence, …

Simulations Of Atmospheric Pressure Streamer Discharges: Mechanisms Of Streamer Propagation And Related Physics, Dejan Nikic

Electrical and Computer Engineering ETDs

Gas discharge simulations are performed with particular focus on photoionization process in a positive streamer discharge. The effects of this process are investigated by isolating the change in photoionization mean free path (MFP) and keeping the additional processes constant. Furthermore, comparison are made between various effects of simulation parameters, such as initial conditions, geometry extent, simula- tion particle count etc. All of these simulations are performed using a modern Direct Simulation Monte Carlo Particle-in-Cell (DSMC-PIC) code developed by Sandia Na- tional Laboratories. Large scale simulations including 1 cm and 5 cm electrode gaps are performed under standard atmospheric condition air. …

Computationally Tractable Methods For Constrained Optimal Control And Reachability Analysis Of Nonlinear Stochastic Dynamical Systems, Karthik Sivaramakrishnan

Electrical and Computer Engineering ETDs

Autonomous systems operating in uncertain environments require methods that can rigorously quantify safety, predict future behavior, and compute optimal decisions tractably. The unifying challenge is reasoning about uncertainty propagation in constrained dynamical systems. Motivated by autonomous spacecraft inspection, this dissertation develops model-based and data-driven methods for stochastic optimal control and stochastic reachability. First, it studies optimal on-orbit inspection of an uncertain tumbling spacecraft in both single-agent and multi-agent settings, and derives computationally efficient reformulations for exploring trade-offs among sensing, trajectory deviation, and fuel use. Second, it develops a probabilistically safe penalty-based reinforcement learning method that preserves gradient information during training …

Dynamic Reconstruction Engineering Of Anti-Corrosion Ni-Based Anodes For Alkaline Seawater Electrolysis, Yi-Gang Zhang, Wen-Wen Xu, Tian-Yu Zhang, Zhi-Yi Lu

Journal of Electrochemistry

Green hydrogen production via alkaline seawater electrolysis offers an environmentally sustainable and potentially cost-effective route to address both energy and climate challenges. Achieving long-term anode stability under complex ionic environments and industrial current densities remains a central bottleneck. Specifically, Ni-based anodes exhibit intense surface reconstruction during the oxygen evolution reaction, necessitating dynamic anti-corrosion strategies. This mini review systematically summarizes reconstruction engineering approaches to develop anti-corrosion Ni-based anodes of alkaline seawater electrolysis across increasingly complex ionic environments from simulated seawater to real seawater: (i) Cl^– dominated; (ii) Cl^– with co-existing oxyanions, and (iii) Cl^–  with co-existing Br^{– …}

Preparation And Performance Study Of In-Situ Self-Assembled Biphasic Smmn2O5-Nimn2O4 Composite Cathode, Neng-Chu Xia, Yu Zhou, Qin Wang, Jia-You Zhang, Chun Yu, Yang Zhang, Wan-Bing Guan, Jian-Xin Wang

Journal of Electrochemistry

Mullite-structured oxides exhibit excellent oxygen reduction reaction activity, possess a low thermal expansion coefficient due to their unique crystal structure, and can eliminate the need for a barrier layer and simplify the preparation process as they contain no alkaline earth elements. Thus, they hold great promise as novel cathode materials for solid oxide fuel cells. In this work, a mullite-spinel-structured SmMn₂O₅-NiMn₂O₄ (SMO-NMO) composite cathode was one-step synthesized via a solid-liquid composite route, and its in-situ self-assembly enabled good compatibility with the electrolyte without any barrier layer. Characterization results showed that the SMO:NMO = …

In-Situ Stm Visualization Of Molecular Structural Evolution During Electrochemical Oxidation Coupling Of Para-Aminothiophenol On Au(111), Zi-Wei Ma, Tai-Rui Wu, An-Ni Zheng, Lai-Ke Chen, Yuan-Hui Xiao, Zhao-Bin Chen, Qing-Na Zheng, Jian-Zhang Zhou, Jia-Wei Yan, De-Yin Wu

Journal of Electrochemistry

Para-aminothiophenol (PATP) is not only a widely-used probe molecule in the field of surface-enhanced Raman spectroscopy (SERS), but also an important model molecule for interfacial reactions, exhibiting distinct photo- and electro-oxidation pathways, so that PATP is selectively activated under different external fields. The evolution of products and intermediates during electrochemical oxidative coupling remains unknown. In this study, we have investigated the dynamic electrochemical oxidation process of PATP on the Au(111) surface using cyclic voltammetry, electrochemical (EC)-SERS, and in situ electrochemical scanning tunneling microscopy (EC-STM). The results showed that PATP forms an unsaturated adsorption coverage on Au(111) in an acidic solution. …

Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby

Civil Engineering ETDs

Wildfires alter the water quantity and quality in downstream river networks. Fires promote biodiversity, maintain habitat, and provide many ecosystem services in a fire-adapted landscape. However, changes in the natural fire regimes can alter ecosystem function and threaten the water security of impacted downstream communities. The magnitude, timing, and persistence of these impacts are difficult to predict due to the lack of high-resolution datasets with adequate coverage to evaluate spatiotemporal trends after a fire. This dissertation moves us beyond the status quo to evaluate post-fire fluvial responses across scales, from the event-scale impacts after the Hermit’s Peak-Calf Canyon wildfire in …

Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman

Biomedical Sciences ETDs

Early life adversity (ELA) increases lifelong neuropsychiatric vulnerability. Yet how ELA reorganizes brain-wide activity and circuit coordination across later experience remains unclear. This dissertation tests the hypothesis that ELA alters adult brain-wide activity and responses to threat through disrupted coordination among neural systems that regulate emotional experience, including prefrontal-limbic and monoaminergic systems. Longitudinal manganese-enhanced MRI of adult mice exposed to standard or fragmented early care, combined with computational processing and statistical modeling, quantified brain states before, during, and long after innate predator threat. These studies established that acute threat evokes large-scale, distributed brain activity that evolves over time. ELA potentiates …

Helmholtz Reciprocity In Bidirectional Y-Junction Couplers, Hosuk Lee

Optical Science and Engineering ETDs

This thesis explores the light propagation characteristics in Y-junction couplers based on the Helmholtz reciprocity principle. The Helmholtz reciprocity principle is a crucial concept in optical system design, and it has primarily been understood based on input-output symmetry. However, this study emphasizes reciprocity needs to consider the entire system, beyond the traditional input-output symmetry reciprocity interpretation. For this study, we specifically examined the direction-dependent asymmetrical outputs, in the Whistle-geometry Ring Laser (WRL) structure. And the WRL results cannot be fully explained by simple input-output symmetry for reciprocity. The Y-junction coupler in the WRL structure makes different output characteristics based on …

Algorithmic Sculpting Of Complex Fused Silica Surfaces For Nondestructive, Mode-Matched Cavity Quantum Electrodynamics: Adaptive Co2 Milling And Simulation-Guided Ultrafast Inscription, From Fiber Fabry-Perot Cavities To Monolithic Architectures, Meagan E. Parker

Optical Science and Engineering ETDs

Quantum sensors achieve exceptional measurement sensitivity through coherent, well-isolated quantum systems, but practical deployment is hindered by destructive readouts that require repeated state preparation and create long system dead times. Optical cavities enable continuous, nondestructive measurements with minimal back-action, yet integrating high-finesse cavities into scalable quantum devices remains limited by existing fabrication methods. To overcome these constraints, an adaptive CO₂ laser-milling platform was developed. Guided by glass thermodynamics and melt dynamics, this closed-loop system uses in-situ phase-shifting interferometry to sculpt complex fused-silica surfaces with sub-nanometer root-mean-square roughness. The platform was validated by fabricating extended-length fiber Fabry–Pérot cavities and monolithic micro-cavity …

Non-Traditional Rare-Earth-Doped Oxide Glass As A Gain Medium, Jared S. Tolliver

Optical Science and Engineering ETDs

There is a need for mid-infrared(MIR) lasers in defense, medical, and environmental monitoring. A large part of this technological development is the study of gain media. One class of materials of special interest is glasses with a low maximum phonon energy. These have the fiberization and broad spectral features of glass, whereas glasses with high maximum phonon energy exhibit higher rates of multi-phonon relaxation and can be opaque in the MIR, both of which are detrimental to laser operation. Recent advances in container-less processing have allowed for the study of new glasses that aren’t possible with conventional fabrication techniques. One …

3d Electromagnetic Simulations Of A 1.6 Cell S-Band Photoinjector: Emittance Studies For Electron Microscopy, Trudy Bolin

Electrical and Computer Engineering ETDs

Modern beam-based materials research demands electron sources with increasingly precise time resolution, high brightness, and stability. For example, there are various instruments across the U.S. dedicated to ultrafast electron diffraction (UED), but fewer are dedicated to ultrafast electron microscopy (UEM), which demands beam stability. Modeling femtosecond electron bunches with ultra-low emittance < 50 nm-rad inside a 1.6-cell S-band (2856 MHz) rf photoinjector with full 3D electromagnetic simulations can require high-performance computing (HPC) environments due to the scale disparity between the macroscopic cavity geometry and the femtosecond-scale bunch kinematics. To enable optimization in a desktop computing environment, this work presents a streamlined 3D electromagnetic Particle-in-Cell (PIC) simulation framework optimized for 400-femtosecond bunch regimes. The covariance method was employed to study emittance properties for electron bunch counts ranging from thousands to millions and has successfully resolved highly transient, pure rf phase-space rotations, such as a localized energy-spread minimum occurring at the gun exit iris. To overcome the computational cost of these simulations, a machine-learning-based Bayesian optimization approach was deployed to construct multi-objective Pareto fronts from sparse datasets. Because the simulation software is scalable from desktop to HPC facilities, the framework is ready for experiments at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL).

Real-Time Waveform Synthesis For Rfsoc-Based Quantum Control Systems, Tiamike I. Dudley

Electrical and Computer Engineering ETDs

RFSoCs are gaining adoption in many labs for quantum control systems thanks to their compactness and affordability. Making full use of the many components on an RFSoC evaluation board is a challenging engineering problem that must be solved to realize scalable control systems. In this dissertation, I evaluate the performance of various RFSoC components in the context of quantum information science. I present two custom FPGA engines that accelerate and parallelize arbitrary waveform generation. The first engine can be instantiated many times to power low-speed DACs for ion-shuttling trap electrodes. The second engine synthesizes CPMG-XY8n dynamical decoupling pulse sequences on …

Modeling For You: A Personalized Approach To Residential Energy Simulation And Distributional Reinforcement Learning, Nestor Gabriel Pereira

Electrical and Computer Engineering ETDs

The growing complexity and uncertainty of residential energy use, driven by electric

vehicles and renewable technologies, demand more intelligent and robust

management systems. Traditional methods often fail when faced with unpredictable

electricity prices and user behavior. This dissertation addresses this gap by presenting

a novel personalized framework combining detailed household energy modeling with

a risk-aware reinforcement learning agent for appliance scheduling.

The first contribution is a probabilistic, bottom-up simulation model that captures

the interdependent behaviors of occupants, appliances, and electric vehicles to

generate realistic, high-fidelity load profiles. The second contribution is a lightweight,

tabular Distributional Q-Learning (D-QL) algorithm that schedules …

Enhanced Computational Modeling Of Photoionization And Streamer Formation, Anahita Alibalazadeh

Electrical and Computer Engineering ETDs

Photoionization is a key mechanism governing the formation and propagation of streamer discharges in air by generating electron-ion pairs ahead of the streamer front. Accurate and computationally efficient modeling of this non-local process is essential for reliable plasma simulations. However, the widely used Zheleznyak photoionization model relies on empirical assumptions and requires computationally expensive domain-wide integration.

This dissertation advances photoionization modeling in three ways. First, the classical integral model is enhanced by incorporating experimentally measured vacuum ultraviolet (VUV) emission spectra together with photoabsorption and photoionization cross-section data, enabling direct calculation of the photoionization source term as a function of pressure …

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

Integrated Construction Risk Assessment Framework, Felix Delmonte

Mechanical and Civil Engineering Faculty Publications

An integrated risk assessment architecture for construction projects synthesizes data governance, BIM, Digital Twins, and hybrid analytics into a continuous feedback loop that links sensing, semantic modelling, probabilistic simulation, and organizational learning. The framework distinguishes aleatory from cognitive uncertainty and prescribes layered methods: Monte Carlo and Bayesian updating for measurable variability; fuzzy inference and consensus aggregation for linguistic and expert judgements; and graph-based discovery for dynamic cyber-physical topologies represented as time-varying graphs 𝐺𝑡. Governance primitives, aligned with ISO 19650, enforce provenance, interoperability, and staged readiness thresholds that prevent premature prescriptive outputs until model convergence criteria are met. BIM and GIS …

The Zeal Instruction Set Architecture, Joseph A. Gerani

Master's Theses

The Instruction Set Architecture of a CPU (Central Processing Unit) determines what type of instructions the CPU is able to understand, how those instructions are encoded, and what it should output upon receiving those instructions as input. There are currently three popular ISAs meant for the consumer market: x86, RISC-V, and ARM, as well as a fourth that mostly now exists in the server market by the name of Power. One of the most important parts of an ISA is for engineers to be able to understand it and make use of it. If an ISA is too complicated, nobody …

Pipeline Optimization Of Agentic Llms For Text-To-Sql, Peter Conant

Master's Theses

Current database interfaces limit users’ interaction to those with technical skills, creating timely roadblocks for non-technical professionals. Text-to-SQL aims to simplify database interactions by translating natural language questions into database queries, but long-standing challenges like question understanding, question-schema linking, and SQL generation have held the field back. In the AI era, foundational LLMs prove to be very capable of question understanding SQL, perform well in Schema Linking, Generation, and Evaluation tasks. However the cost to run these model is a hurdle for many organization with low funds and resources. Text-to-SQL solutions often operate across large enterprise size databases with, and …

Development Of Proposed Airworthiness Certification Criteria For Interference-Tolerant Radio Altimeter Systems, Matheus B. Furstenberger

Student Works

Radio altimeters provide height-above-ground information to flight deck displays and multiple safety-critical aircraft systems, however legacy certification standards were not developed for high-power terrestrial wireless services operating in adjacent C-Band spectrum. This study addressed the absence of a consolidated airworthiness certification framework for interference-tolerant radio altimeter systems installed on Title 14 Code of Federal Regulations Part 25 transport category airplanes. An archival research synthesis was conducted using publicly available regulations, proposed and final rules, technical standard orders, advisory circulars, airworthiness directives, industry standards, spectrum-management documents, technical studies, and stakeholder comments. Qualitative content analysis and source triangulation were used to identify …

Table Of Contents, The Editors

Coal Geology & Exploration

No abstract provided.