Digital Commons Network^™

A Robust And Energy-Efficient Federated Ids For Iiot Using Spiking Neural Networks And Differential Evolution With Adversarial Resilience, Mohammad Othman Nassar

Iraqi Journal for Computer Science and Mathematics

The Industrial Internet of Things (IIoT) is faced with increasing cybersecurity threats that require lightweight, fast, and resilient intrusion detection systems (IDS). This study presents a novel federated IDS framework that integrates federated learning (FL), Spiking Neural Networks (SNNs), and differential evolution (DE). The use of SNNs within a federated context is a rare and innovative contribution that enables effective temporal feature extraction from IIoT traffic. DE is employed as a global optimization mechanism, enhancing robustness and generalization beyond conventional federated aggregation. To further strengthen resilience, synthetic adversarial noise is injected during training, allowing evaluation in realistic poisoning scenarios. The …

Deep Reinforcement Learning Based Control For Enhanced Frequency Response With Multi-Energy Storage Systems, Abu Shouaib Hasan, Rui Fan, Wei Gao, Di Wu

Electrical and Computer Engineering: Faculty Scholarship

This paper proposes an advanced strategy for managing multiple battery energy storage systems (BESS) to enhance frequency support during contingencies. A novel deep reinforcement learning (DRL) framework based on a guided surrogate-gradient-based evolutionary strategy (GSES) was developed to dynamically regulate BESS outputs for rapid power injection or absorption. This approach effectively mitigates the rate of change of frequency (ROCOF) and stabilizes the system frequency under varying operating conditions. Parallel computing techniques are employed to accelerate training and ensure robust performance. In addition, a genetic algorithm is implemented to determine the placement of BESS within the grid network, strategically minimizing ROCOF …

New Collaborative Water Accounting Proposals To Protect Lake Powell And Lake Mead During Extreme Low Reservoir Storage And River Flow (Protect And Flexible During Crisis), David Rosenberg, Anabelle Myers, Brittany Fager, Erik Porse

Civil and Environmental Engineering Faculty Publications

Low Colorado River flows threaten to draw down Lake Powell and Lake Mead below their minimum power pool elevations. Additionally, the U.S. Federal Government through its Bureau of Reclamation (Reclamation) has set a new deadline for November 11, 2025 for new proposals to operate Lake Powell and Lake Mead after existing operations expire at the end of 2026. In a prior April 2025 post, we shared 13 reasons why we have hope for consensus on new operations (Rosenberg et al., 2026). One reason was that during crisis, rapid changes in policies and operations are possible. More recently, we asked the …

Site Specific Reliability-Targeted Snow Loads And Winter Wind Parameters Across The World, Brennan Bean, Nicholas Brimhall, Bikram Bhusal, Marc Maguire, Maha Moussa

Mathematics and Statistics Faculty Publications

This report presents a framework for estimating Reliability Targeted Snow Loads (RTSLs) and Winter Wind Parameters (WWPs) at locations outside the Conterminous United States (OCONUS). The methodology integrates ground-based in-situmeasurements with gridded global climate products to generate spatially continuous RTSL estimates for nearly any location in OCONUS. RTSLs are computed at qualifying in-situ stations, and predictive models relating gridded climate products to in-situRTSLs enable estimation at locations lacking direct measurements. This report describes the development of the in-situ annual maximum snow load database, the construction of global gridded climate summaries, the estimation of site-specific RTSLs and Service Targeted …

Thermal Properties Of Novel Materials, Wilarachchige D.C. Bhagya Gunatilleke

USF Tampa Graduate Theses and Dissertations

Thermal properties play an important role in various aspects of applications of technology startingfrom the materials property determinations to device performance improvements and their safety and stability. Measurements of the thermal properties of such materials of interest pose challenges due to the demands of these measurements for determination of intrinsic materials properties. The research included in this dissertation involved both synthesis of novel materials and their measurement of thermal properties. Solid-state materials synthesis involves various synthesis and processing techniques, while specific technological applications demand synthesis of defect-free single crystals. Such synthesis techniques were explored for the research included in this …

Experimental Investigation: Performance Of Ranque-Hilsch Vortex Tubes Under Various Surface Boundary Conditions, Ahmad Al-Najjar

Thesis/ Dissertation Defenses

The Ranque–Hilsch vortex tube (RHVT) is a passive thermos-fluid device that splits compressed gas into simultaneous cold and hot streams through strong swirling flow inside a slender tube, without moving parts. This study experimentally examines how external boundary conditions applied to the tube wall influence RHVT performance. Three wall conditions were imposed: (i) externally cooled (cooling), (ii) externally heated (heating), and (iii) adiabatic (insulated). Tests were conducted with air over an inlet pressure range of 2–6 bar. The primary objective was to understand the extent to which wall thermal condition modifies temperature separation and energy efficiency. Performance was quantified using …

Evaluating Tire-Pavement Noise Reduction Of Porous Asphalt Using Close Proximity Tests: Comparative Performance And Long-Term Effectiveness, Jin Hwan Kim, Kyungnam Kim, Oh Sun Kwon, Woo Young Cho, Youngguk Seo

Faculty Articles

The objective of this study was to understand the long-term noise reduction effect of Porous Asphalt (PA) in an expressway environment. To this end, PA was compared with that of Stone Mastic Asphalt (SMA), tined concrete, and Next-Generation Concrete Surface (NGCS) at the time of construction. Then, the evolution of PA’s acoustic performance was characterized on 82 pavement sections over the period of 1–18 years. The Close Proximity (CPX) method was used to measure tire-pavement noise at three cruising speeds: 80, 100, and 120 km/h. Mean Profile Depth (MPD) and permeability time were considered as key functional measures of PA …

Elucidating The Effects Of Water Activity On The Hydration Kinetics And Thermodynamics Of Ye’Elimite–Calcium Sulfate Hydrate Systems, Godwin I. Ogbuehi, Rupack R. Halder, Aditya Kumar, Gaurav Sant, Monday U. Okoronkwo

Materials Science and Engineering Faculty Research & Creative Works

Relative humidity and water activity (aH) reductions have been known to suppress the hydration of anhydrous cement clinker phases. However, the relationship between ye'elimite (C4A3$) hydration kinetics and water activity remain unclear. This study employs experimental and thermodynamic modeling approaches to investigate the influence of water activity on ye'elimite hydration in the "C4A3$ + water", and "C4A3$ + gypsum + water" systems. Experimental findings indicate that as water activity decreases, C4A3$ hydration diminishes until the reaction is brought to a halt at a threshold aH. The critical aHand corresponding solubility constant of C4A3$ (KC4A3S¯) estimated from thermodynamic analysis are 0.46 …

A Hybrid Data Assimilation Approach For Parameter Estimation In Dynamical Systems, Xuejian Li

Math Department Colloquium Series

In this talk, we present a hybrid data assimilation (DA) method that integrates continuous data assimilation (CDA) with particle filtering to estimate parameters in dynamical systems. Parameter estimation in such systems is particularly challenging because it involves both determining the parameters and estimating the often high-dimensional physical state. To address this difficulty, we decouple the estimation of states and parameters by employing CDA for state estimation and particle filtering for parameter estimation, with information exchanged alternately between the two. This hybrid framework leverages the strengths of CDA in handling high-dimensional state estimation and the efficiency of particle filters in estimating …

A Fully Automated Drilling Machine For Printed Circuit Boards With Superior Path Optimization, Mohamed Mammdouh, Ahmed Khaled, Reem Mahmoud, Osama Desouki, Sameh O. Abdellatif

Electrical Engineering

This paper addresses a critical challenge in Printed Circuit Board (PCB) manufacturing by proposing an AI-driven, fully automated drilling machine that employs sophisticated path-planning techniques. Current methodologies often fail to adequately assess designs with varying hole sizes, diverse component placements, and complex geometries, leading to compromised precision and increased manufacturing times. Our innovative approach leverages advanced algorithms to intelligently analyze PCB designs and optimize drilling paths, significantly reducing production time and minimizing errors. By automating the drilling process, we enhance overall productivity while ensuring precise hole placement, essential for maintaining high-quality circuit boards. Utilizing KiCAD EDA software, we automate the …

Toward Autonomous Pavement Inspection: An End-To-End Vision-Based Framework For Pci Computation And Robotic Deployment, Nada El Desouky, Ahmed Torky, Mohamed Elbheiri, Mohamed Eid, Mohamed Ibrahim

Civil Engineering

Advancements in robotics and computer vision are transforming how infrastructure is monitored and maintained. This paper presents a novel, fully automated pipeline for pavement condition assessment that integrates real-time image analysis with PCI (Pavement Condition Index) computation, which is specifically designed for deployment on mobile and robotic platforms. Unlike traditional methods that rely on costly equipment or manual input, the proposed system uses deep learning-based object detection and ensemble segmentation to identify and measure multiple types of road distress directly from 2D imagery, including surface weathering, a key precursor to pothole formation often overlooked in previous studies. Depth estimation is …

Preparing Tomorrow’S Professionals: Industry-Informed Ai Integration, Brent A. Terwilliger Ph.D, John Faraca

Publications

As AI reshapes operations across aviation and aerospace, organizations are investing in ways to preserve data integrity, safeguard proprietary knowledge, and uphold critical professional competencies. This presentation shares emerging findings from a study that surveys and interviews industry professionals about their use of AI tools, their concerns about misuse, and the importance of secure, enterprise-controlled “walled garden” environments. The work explores how employers define appropriate, effective, and innovative AI adoption, particularly in roles requiring high-stakes decision-making, compliance, and technical acumen.

By analyzing organizational expectations around AI-related knowledge, skills, and abilities (KSAs), this research offers practical guidance for academic programs seeking …

Student Perspectives On Ai-Enabled Tools For Adaptive Learning, John Faraca

Publications

Artificial Intelligence (AI) is increasingly influencing the delivery of higher education, especially in aviation technical disciplines. From AI-assisted gimbals and video production tools to generative AI platforms, these technologies are helping learners to engage with course material, accomplish objectives, and connect academic concepts with professional applications. By offering pathways for personalization, streamlining resource access, and supporting interactive instruction, AI tools expand opportunities for effective learning. This work builds on a current collaborative research project with a faculty researcher to explore the student perspective in the active review and application of these tools to highlight their potential to improve usability, address …

“How Can Ai Data Centers In The U.S. Meet Projected Electricity Demands By 2030?, Aiden M. Matano

Sustainable Supply Chain Management

The rapid expansion of artificial intelligence is driving a sharp increase in U.S. electricity demand, with AI-driven data centers emerging as a central contributor through 2030. This paper asks how U.S. AI data centers can meet projected electricity needs while simultaneously reducing carbon emissions. Using a supply-chain and systems perspective, it analyzes the full energy chain of AI data centers: upstream electricity supply and grid deliverability, midstream facility design and grid interaction, and downstream operational practices, waste management, and disclosure. Drawing on recent projections from the International Energy Agency, Lawrence Berkeley National Laboratory, and U.S. federal guidance, the paper shows …

A Fragility Framework For Surface Erosion With Application To Earthen Dam Breaching, Ege C. Kurter, Ayman Mokhtar Nemnem, M. Hanif Chaudhry, Jasim Imran

Faculty Publications

Overtopping failures of earthen dams are a growing concern under intensifying extreme rainfall. This study introduces a probabilistic fragility framework that combines hydrologic modeling, hydraulic analysis, and soil erodibility to assess erosion risk under uncertain load and resistance. Fragility curves derived from Monte Carlo simulations quantify erosion initiation and severity as functions of rainfall depth and excess shear stress. Application to multiple dams affected during the 2015 South Carolina floods reproduces observed outcomes ranging from complete breach to no damage. The framework also captures cascading effects, where failure of an upstream structure increases downstream loading and erosion potential. Compared with …

A Study Of Nonlinear Duffing Equations Using The Haar Wavelet Method, Kumbinarasaiah S., Yeshwanth R., Nandeesh K C.

Mansoura Engineering Journal

The main goal of this study is to solve Duffing equations, which are nonlinear differential equations (DEs), using the Haar wavelet technique. The solutions to this equation for an externally pushed and damped oscillator show intriguing dynamic behavior. Mathematicians have recently become more interested in wavelet analysis because of its real-world applications. A few real-world problems have been considered to assess the current methodology. Here, the (OMI) Operational Matrix of Integration and collocation points transform the non-linear ODEs into a system of nonlinear algebraic equations. The resulting system of algebraic equations is then solved using the Newton-Raphson technique to retrieve …

Design Considerations For Conversational Agents To Assess The Social-Emotional Well-Being Of Young Children In Low-Income South African Communities, Lucretia A. Williams, Elizabeth A. Ankrah, Catherine E. Draper, Caylee J. Cook, Franceli L. Cibrian, Jesus A. Beltran, Kimberley D. Lakes, Gillian R. Hayes

Engineering Faculty Articles and Research

A variety of digital technologies have been used to support early childhood development (ECD) programs in low-income South African communities. Even though technology has provided opportunities to increase access to health interventions, the lack of trust and socio-economic constraints under which these tools would need to work pose complex challenges. We examine home visitors’ work processes, experiences, and preferences of a conversational agent to support their work of administering social-emotional well-being assessments to young children ages 0-5. Analysis of the results of focus groups with 51 home visitors indicates the need for designing conversational agents that support ECD in the …

Enhancing Nitrogen Removal In High Permeability Bioretention Media: The Combined Role Of Biochar, Wood Chips And Hydraulic Design, Joshelyn Guimaray

USF Tampa Graduate Theses and Dissertations

Urban stormwater runoff can transport high nutrient loads to receiving waters, leading toeutrophication, harmful algal blooms, and the formation of hypoxic zones. Bioretention systems are a form of green infrastructure designed to mitigate these impacts, but their application in dense, ultra-urban environments is often limited by large land area requirements. This has led to the adoption of high permeability media (HPM) to accommodate higher hydraulic loading rates (HLRs) and reduce the system footprint. However, conventional HPM systems often show inconsistent removal of dissolved nitrogen species due to short hydraulic retention times (HRTs), a lack of organic carbon, and insufficient anoxic …

The Science And Economics Of 3d-Printed Filament Recycling, Michael Domingo, Dane Freund, John Mcswiggin, Adam Meadows

Sustainability Conference

In recent years, 3D printing has grown rapidly, both in homes and commercially. This has led to increased demand for plastic filaments, many of which contribute to plastic waste. This project explores the potential of recycling household plastics into 3D printing filament, promoting sustainability and creating a circular economy. Materials like PLA, PETG, ABS, and polypropylene can be recycled or even composted. Existing research has shown that recycled filaments can maintain comparable tensile strength to their virgin counterparts, depending on the recycling process. Furthermore, implementing circular economy practices for plastics could save billions annually by mitigating pollution and reducing landfill …

Localized Nuclear Utility For Erau Environmental Improvement, Timothy Schroeder, Jacob Blanton, Christopher Anderson

Sustainability Conference

The reliance of Embry Riddle Aeronautical University (ERAU) on energy supplied by Florida Power & Light (FPL), which currently draws large amounts of power from fossil fuel sources, is continuously suboptimal both environmentally and financially. This study proposes assessing the feasibility of deploying a campus scale nuclear reactor tailored to ERAU’s power consumption profile. This serves as a path toward reducing greenhouse gas emissions and limiting dependence on external fossil fuel generation. The methods used are primarily literature review(s), and numerical analysis on comparable use cases. The literature reviews focused on design theory and yield of nuclear reactors on a …

Aura Aero, A Perspective On Sustainability And Resilience, Mattia Padulo

Sustainability Conference

Since its foundation, AURA AERO has committed to tackle aviation related environmental impacts, through an incremental industrial approach that has allowed the company to become the first fully fledged aircraft manufacturer among the new players in the field of Advanced Air Mobility. AURA AERO product policy has been gradually shaped to scale-up towards bigger, smarter, greener products, and is now enriched by unmanned technologies, as an adaptation to newer societal demands induced by the current geopolitical context. The presentation will give an update on the latest company and product developments, and particularly those related to the INTEGRAL E - the …

Advancing Power System Reliability And Security With Efficient And Resilient Graph Neural Network Frameworks, Seyed Hamed Haghshenas

USF Tampa Graduate Theses and Dissertations

Enhancing the reliability and security of smart grids is critical for ensuring their seamless operation and resilience against disruptions. The increasing integration of distributed energy resources, advanced measurement devices, and cyber-physical elements introduces both opportunities and challenges for grid management. While these advancements provide enhanced visibility and operational control, they also expose the grid to vulnerabilities from cyber-physical stresses, such as cyber-attacks, equipment failures, and fluctuating power demands. Traditional methods for reliability assessment and threat detection often rely on model-based approaches that struggle to adapt to the complexity and dynamic nature of modern smart grids. These limitations necessitate novel data-driven …

Abdominal Ultrasound Image Dataset For Organ Classification And Disease Detection, Sifat Zina Karim

Research Data

This is a dataset of Ultrasound (US) images of abdominal organs. US imaging is widely accessible and a very common diagnostic tool, as it is non-invasive and does not involve radiation risk. This dataset was curated solely for research in deep learning, with potential applications in supervised, semi-supervised, and unsupervised learning to support disease detection in resource-constrained settings.

The dataset comprises 5,468 unique images organized into ten anatomical categories: Abdominal Aorta (0), Gallbladder (1), Hepatic Vein (2), Kidneys (3), Liver (4), Ovaries (5), Pancreas (6), Portal Vein (7), Spleen (8), and a composite Pelvic Urinary/Reproductive category (9), comprising the Urinary …

Optimizing Driving Waveforms To Enhance Inkjet Printing Speed, Chao Jan Sui, Wenchao A. Zhou

Mechanical Engineering Faculty Publications and Presentations

Inkjet printing has been extensively employed across various industrial applications due to its capability to produce high-resolution outputs and accommodate a diverse range of materials. However, its printing speed (volumetric printing rate or volumetric productivity) has remained a bottleneck for large-scale manufacturing. This study introduces a new strategy aimed at enhancing the speed of piezoelectric inkjet printing by optimizing waveform parameters. Expanding on our prior work, which analyzed the relationship between driving signal parameters and key factors like droplet volume and jetting frequency, we now focus on optimizing these parameters to maximize printing speed. To establish a fair comparison across …

Utilizing A Virtual Firewall Appliance For Introducing And Reinforcing The Concepts And Implementation Of Devices To Improve Security In A Computing Environment, Stanley Mierzwa, Christopher Eng

Center for Cybersecurity

The educational realm of higher education cybersecurity curriculum continues to evolve to provide more opportunities for experiential hands-on and work role-related practical applications of technology solutions. Gaining greater competencies is quickly becoming a normal requirement for such programs that are designated by the National Security Agency Center of Academic Excellence programs. The work roles of cybersecurity include a variety of knowledge, skills, and abilities, depending on the category of the activity or task. Firewalls have been a staple cybersecurity, network security, and information security device and strategy to protect organization networks and computing environments. This paper will provide details and …

The Functional Efficiency Of Healing Gardens Elements And Its Impact On The Functional Aspect Of Hospitals, Menna Allah Hesham Mohammed, Heba Mohamed Abdou

Mansoura Engineering Journal

Communication with nature has a positive effect on human health and well-being in different civilizations all time. But technological development caused the production of purely functional buildings that are far from communicating with nature, although some buildings contain gardens to achieve communication with nature, their elements are poor. Therefore, healing gardens are considered one of the main elements to raise the efficiency of the functional performance of the health building because they contain the resting places and healing departments. Therefore, this study focuses on determining the functional criteria for the elements of the garden that must be considered when designing …

Effects Of Yttrium And Barium Trace Impurities On The Dielectric Properties Of  Srtio3 (111) Single Crystals At Cryogenic Temperatures, Hung Trinh, Alan Devoe, Fatih Dogan

Materials Science and Engineering Faculty Research & Creative Works

Commercially available single crystals of (111) SrTiO₃ were found to contain impurities of varying amounts that strongly affected their dielectric performance at cryogenic temperatures. Three crystals with total impurities of 111, 126, and 625 ppm, primarily of barium and yttrium, were analyzed. Relative permittivity (εr) and loss tangent were investigated with high resolution as a function of temperature (4 K to 100 K), DC voltage (0 V/cm to 800 V/cm), and frequency (100 Hz to 1 MHz). An impurity level as low as ≈500 ppm barium resulted in an increase of the maximum permittivity (εm) to approximately 50,000 at …

Lithological Modeling And Aquifer Characterization Of The Coastal Lowlands Aquifer System In Texas, Emmanuel Egyin Hayford

LSU Master's Theses

The Texas Coastal Lowlands Aquifer System (CLAS) is a crucial water resource for the Gulf Coast, serving millions through municipal, agricultural, and industrial supplies. However, its sustainability is increasingly threatened by factors such as population growth, saltwater intrusion, land subsidence, and climate change. A significant limitation is the absence of a comprehensive, data-rich, three-dimensional lithologic model that accurately represents the intricate structure and geometry of the aquifer. Existing models are overly simplistic, treating the hydrogeologic unit as laterally uniform and failing to capture its true hydrogeologic complexity. This study addresses this gap by developing the first high-resolution 3D lithologic model …

Preparation, High-Temperature And Low-Temperature Performance Evaluation Of Bio-Based Polyurethane Modified Asphalt, Junfeng Gao, Guixiu Guo, Hainian Wang, Chonghui Wang, Dongzhao Jin

Michigan Tech Publications

To achieve sustainable and environmentally friendly development of pavement materials, it is essential to identify alternative materials to reduce dependence on petroleum resources. This study aims to functionalize castor oil (CO) with isocyanates to prepare bio-based polyurethane-modified asphalt (Bio-PUMA), determine its optimal preparation parameters, and evaluate the effects of Bio-PU content and isocyanate index (R) on the high- and low-temperature performance of Bio-PUMA. The orthogonal experimental design (OED), grey correlation grade analysis (GCGA), penetration, softening point, ductility, and viscosity were conducted to determine the preparation process and evaluate the performances of Bio-PUMA. The results show that the preparation factors affecting …

Seeing What Matters: Safety-Critical Semantic Segmentation Via Transfer Learning On Construction Sites, Obiora J. Odugu

LSU Master's Theses

Autonomous robots are increasingly deployed on construction sites for tasks such as progress monitoring, inspection, and safety assessment. For these robots to operate effectively, they must perceive and interpret complex, dynamic environments populated by workers, machinery, and unstructured terrain. Achieving reliable perception depends on high performing semantic segmentation models trained on large volumes of annotated data—an expensive and logistically challenging requirement in construction due to privacy restrictions, variable site access, and slow digitalization. This research addresses the challenge of limited labeled data by investigating transfer learning as a label-efficient approach for construction-site segmentation. Specifically, it explores whether road construction imagery—abundant …