Digital Commons Network^™

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models …

Autonomous Weapons And Strategic Stability, Chick Edmond

Political Science & Geography Faculty Publications

The increasing number of artificial intelligence (AI) elements within military systems has introduced new forms of security dilemmas related to speed, level of secrecy, and transfer of responsibility from humans to machines. This article addresses the question of whether or how AI enabled autonomous weapons can lead to greater levels of strategic instability. Three causal mechanisms were determined by this study to potentially create destabilizing effects due to the introduction of autonomy; the first mechanism is a reduction in time available for decision making. The second mechanism involves the creation of multiple pathways of escalation. The third mechanism is the …

The Fox Versus The Hedgehog: Firm Survival During Unprecedented Crises, Sheng Fang, Shaomin Li, Liu Wang

Management Faculty Publications

This paper examines how sales channel diversification influences firm resilience during the COVID crisis. Drawing on a series of logit regressions analyzing 11,662 firms across 31 developing countries, we find that firms embodying an open mind-set and a diverse array of sales channels, akin to foxes, are more likely to survive, as compared to their hedgehog counterparts, which focus on one particular task. Our mediation analysis suggests that this is mainly due to their faster growth in sales and exports. Moreover, we find that the impact of fox-like traits on firm survival is moderated by female leadership and corporate innovation.

Frequency And Phase Synchronization Of Antenna Arrays With Phase Incoherent Microcontrollers, Harley W. Byrd

University of Kentucky Master's Theses

The construction of phased array antennas has traditionally been an expensive and complex task. It has recently been claimed that it is possible to construct high-performance Wi Fi antenna arrays using inexpensive consumer components. Motivated by some limited data available from online presentations of such devices, this thesis covers an attempt to construct a phased-array Wi-Fi antenna using several ESP32 chips, which have native Wi-Fi modulation and demodulation capabilities. While there are many positive aspects associated with utilizing ESP32 chips for this purpose, a key challenge is the inherent phase incoherence of their internal Phase Locked Loops (PLLs). The approach …

Exploring Undergraduate Women’S Experiences Of Collaborative Learning In Engineering Education: A Phenomenological Study Of The Social World, Sandra Ireri Cruz Morena

Doctoral

The persistent underrepresentation of women in engineering education remains a concern across global and national contexts, despite rising overall enrolment of women in higher education. In Ireland, the national average of women entering Engineering, Manufacturing, and Construction (EMC) programmes has gradually increased; however, the rate at Technological University Dublin (TU Dublin) has stayed at approximately 15% since 2016. This study seeks to better understand the gendered challenges underlying such trends by exploring the lived experiences of female undergraduate engineering students at TU Dublin, particularly in relation to collaborative learning environments such as project- and problem-based learning (PBL).

Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra

Theses and Dissertations (Comprehensive)

Effective and interpretable classification of medical images remains a critical challenge in computer-aided diagnosis, particularly in data-scarce and resource-constrained clinical settings where traditional deep learning models prove impractical. This study addresses the fundamental barrier to Vision Transformer adoption in medical imaging—massive parameter counts and data requirements—through a systematic two-phase methodology. Phase 1 evaluates three spline-based Kolmogorov–Arnold Network (KAN) variants to identify the optimal nonlinear approximation function for parameter-efficient medical image classification: SBTAYLOR-KAN (B-splines with Taylor series), SBRBF-KAN (B-splines with Radial Basis Functions), and SBWAVELET-KAN (B-splines with Morlet wavelets). Comprehensive experiments across brain MRI, chest X-rays, and tuberculosis datasets—without any image …

Assessing Dissolved Organic Matter Sources And Dynamics In Urban Stormwater: Implications For Greenhouse Gases, Harper W. Schmalz

Theses and Dissertations (Comprehensive)

Stormwater management ponds (SWMPs) are important aspects of land-use planning and increasingly recognized as active sites of biogeochemical processing that influence carbon cycling; however, little research has investigated the controls on dissolved organic and dissolved inorganic carbon (DOC and DIC) within these systems. This thesis examined the processing and transformations of dissolved carbon between three compartments to support the development of a greenhouse gas (GHG) box-model for urban stormwater ponds, including SWMP sediment, surface water, and vegetation. The objective of this thesis was to assess the biogeochemical processes that govern the rate and transformation of DOC and DIC between these …

Flexible Cu Nanostructured Laser-Induced Graphene Electrodes For Highly Sensitive And Non-Invasive Lactate Detection In Saliva, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

A scalable and facile fabrication strategy is presented for developing a flexible, nanostructured, non-enzymatic electrochemical sensor for lactate detection based on copper-modified laser-induced graphene (CuNPs/LIG). A one-step electrodeposition process was employed to uniformly decorate the porous LIG framework with copper nanostructures, offering a cost-effective and reproducible approach for constructing enzyme-free sensing platforms. Scanning electron microscopy and energy-dispersive X-ray spectroscopy confirmed dense Cu nanostructure loading and efficient interfacial integration across the conductive LIG surface. The resulting CuNPs/LIG electrode exhibited excellent electrocatalytic performance, achieving a sensitivity of 8.56 μA µM⁻¹ cm⁻² with a low detection limit of 42.65 …

A Scalable Paper-Based Electrochemical Sensor Employing Mwcnts For Isoniazid Detection, Sri Ramulu Torati, Gymama Slaughter

Center for Bioelectronics Publications

Isoniazid (INZ) is an antimicrobial agent that treats tuberculosis by inhibiting the InhA enzyme in Mycobacterium tuberculosis, making sensitive and reliable methods for routine monitoring essential to ensure safe and effective therapy. We report the development of a novel paper-based electrochemical sensor for the sensitive and selective detection of isoniazid. The sensor is constructed using a gold inkjet-printed electrode (GIPE) modified with gold nanoparticles (AuNPs), chitosan (CH), and multi-walled carbon nanotubes (MWCNTs), forming a GIPE/AuNPs/CH/MWCNTs sensor. Electrochemical deposition of AuNPs effectively addressed insulating gaps generated during the sintering of the gold ink, enhancing electrical conductivity and surface uniformity. The …

Recent Advances In Triboelectric Nanogenerators For Biomedical And Cardiovascular Monitoring, Amit Sarode, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, …

A Portable Potentiostat Integrated With A Pt/Zno/Lig Electrode For Non-Enzymatic Glucose Detection, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Continuous glucose monitoring is critical for effective diabetes management; however, conventional benchtop potentiostats are bulky, costly, and unsuitable for decentralized point-of-care (PoC) applications. To address these limitations, this work presents a miniaturized, low-cost electrochemical sensing platform integrating a non-enzymatic glucose sensor with a portable potentiostat. The sensing electrode is based on laser-induced graphene modified with zinc oxide and platinum nanostructures via electrodeposition to enable sensitive glucose detection under physiological conditions. A custom-designed portable potentiostat was developed to control electrode potentials and perform electrochemical measurements, and its performance was experimentally validated against a commercial Metrohm system. Glucose detection was evaluated using …

Modern Potentiostat Architectures For Electrochemical Sensing: Design, Integration, And Future Directions, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Potentiostats are essential to electrochemical sensing, enabling precise control of electrode potentials and measurement of current responses. As demand grows for portable, wearable, and point-of-care systems, potentiostat design has evolved from benchtop instruments to compact, low-power, and wirelessly connected platforms. This review provides a comprehensive, system-level perspective on modern potentiostat architectures, covering operational principles, analog front-end design, signal generation and acquisition, communication protocols, and software integration. Unlike prior reviews that treat these aspects independently, this work integrates electrochemical theory with electronic design and data communication frameworks. Key components, including operational amplifiers, transimpedance amplifiers, DAC/ADC subsystems, and microcontroller-based control, are examined …

Nanofibrous Materials And Nanoparticles For Combating Antimicrobial Resistance: Synthesis, Integration, And Translational Perspectives, Rewati Raman Ujjwal, Ashish Dilip Sutar, Rahul Shukla, Gymama Slaughter

Center for Bioelectronics Publications

Antimicrobial resistance (AMR) is a major global health challenge driven by mechanisms such as biofilm formation, efflux pumps, and genetic mutations. Nanoparticulate and fibrous materials have emerged as promising strategies to overcome these limitations through multimodal antimicrobial action and controlled drug delivery. This review highlights recent advances in electrospun nanofibrous systems, including natural and synthetic polymer-based scaffolds, stimuli-responsive nanofibers, and functionalized patches. Nanoparticle-loaded nanofiber systems demonstrate enhanced performance, including bacterial eradication, sustained drug release, and significant biofilm disruption. Multifunctional systems combining antimicrobial, antioxidant, and immunomodulatory properties further show synergism. Emerging innovations, such as piezoelectric and smart sensing systems, enable self-powered …

Electrochemical Hemoglobin Biosensors For Point-Of-Care Diagnostics, Ashwini Dantanarayana, Gymama Slaughter

Center for Bioelectronics Publications

Hemoglobin (Hb) and its glycated variant (HbA1c) are essential clinical biomarkers for diagnosing anemia, acute hemorrhage, and long-term glycemic control. The growing demand for decentralized point-of-care (POC) testing has accelerated the development of rapid, inexpensive, and portable electrochemical sensing platforms. These technologies exploit the intrinsic redox activity of the heme prosthetic group, yet achieving efficient direct electron transfer (DET) remains a fundamental challenge because the electroactive iron center is deeply embedded within the globin structure. This review critically examines recent advances in electrochemical Hb sensing, tracing the evolution of electrode architectures from conventional carbon substrates to nanostructured materials, including graphene, …

The Efficacy Of Hybrid Manufacturing For High Stress Automotive Parts, Logan Trimmer

Harrisburg University Other Works

Presentation covering the broad strokes of the project. The goal was to prove the viability of hybrid/additive manufacturing for high stress automotive applications. This project focused on recreating a piston from an old engine to examine if hybrid manufacturing could be used for such applications. On a small scale, hybrid manufacturing was able to be more cost effective if the costs of the equipment and electricity were ignored. The decision to ignore those costs came from the inability to find accurate prices for industrial casting.

Impact Of Bubble-Induced Turbulence On Two-Phase Flow Dynamics At High Void Fraction In A Large Diameter Channel, Sungje Hong, Joshua P. Schlegel, Subash L. Sharma

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

This study represents the first investigation into the influence of bubble-induced turbulence (BIT) on interfacial area transport mechanisms in gas–liquid two-phase flows under conditions of high void fraction and high velocity in a large diameter channel. Given the unique characteristics of bubble flow in larger channels, the turbulent effects induced by bubbles differ from those observed in smaller channels. However, limited research exists regarding the impact of BIT beyond bubbly flows in large-diameter channels. To address this gap, two approaches for implementing the BIT model are explored: a direct method and an indirect method. This paper assesses both the general …

Lift And Drag Benefits Of Morphing Aircraft, Joseph Lombardi

Master’s Theses

Aircraft use the ability to change the geometry of their wings to produce lift and drag as needed to maintain flight conditions. While the wings themselves are not physically changing shape, flaps and ailerons are used to alter the lift and drag coefficients experienced. Flaps have been used and changed over the years in order to produce better lift to drag ratios. The most commonly used flaps have been plain, slotted, and double slotted. Each type features slightly different mechanical structures, thus producing differing amounts of lift and drag. The introduction of new materials allow for a morphing flap to …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …

Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain

Journal of Marine Science and Technology–Taiwan

In terms of aerial robotics, stable and precise formation control is a significant challenge for tilting multi-quadrotors during disturbances. This paper proposes a fixed-time formation control strategy for tilting multi-quadrotors to address the effect of external wind gusts. The observer accurately predicts environmental disturbances and an adaptive backstepping sliding-mode control (ABSMC) method with an output recurrent fuzzy broad learning system (ORFBLS) addresses these disturbances within a finite time. ORFBLS dynamically adjusts its structure through a growing ORFBLS structure to allow nodes to be added as needed. The method's stability is validated using Lyapunov stability theory and ensures the convergence of …

Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou

Journal of Marine Science and Technology–Taiwan

Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.

This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …

Autonomous Uav Mission Planning Under Threat Using Model Predictive Control With Proportional-Navigation Pursuers, Mehmet B. Ozcelik

Mechanical and Aerospace Engineering Theses

Autonomous unmanned aerial vehicles (UAVs) operating in contested environments must

complete mission objectives while avoiding restricted regions, radar exposure, and pos-

sible interception. This thesis develops a MATLAB-based simulation framework for

two-dimensional UAV mission planning under threat using model predictive control and

proportional-navigation chasers. The mission requires the UAV to travel from a start

location to a goal while visiting required checkpoints and avoiding no-fly zones and radar

regions. A chaser attempts to intercept the UAV using either a basic pure-pursuit-style

law or a proportional-navigation guidance law.

The framework integrates environment generation, augmented visibility-graph rout-

ing, waypoint management, UAV kinematic …

Llm-Driven Closed-Loop Uav Control With Obstacle-Aware Model Predictive Control, Halimcan Yasar

Mechanical and Aerospace Engineering Theses

This thesis presents a closed-loop control architecture for uncrewed aerial vehicles (UAVs) in which a large language model (LLM) serves as a high-level decision module operating over a persistent, metric 3D world model.

Rather than generating low-level commands or open-loop plans, the LLM selects one parameterized maneuver per decision step from a small, verified library of flight primitives conditioned on a structured representation of the drone state, tracked object positions, and mission specification.

Translational motion is executed by a planar model predictive controller (MPC) with soft obstacle avoidance, using obstacle hypotheses provided by the LLM, so that safety-critical constraint handling …

Hall Current And Nth Order Chemical Reaction Effects On Unsteady 3d Mhd Williamson Nanofluid Flow With Thermophoresis And Brownian Motion Over An Inclined Stretching Sheet, Polavarapu Sudheer, Ramachandra Reddy Vaddemani, Raghunath Kodi

Mansoura Engineering Journal

This study examines the influence of Hall current and nth-order chemical reaction on unsteady three-dimensional magnetohydrodynamic (MHD) Williamson nanofluid flow over an inclined stretching sheet. The model incorporates thermal radiation, heat source, Brownian motion, and thermophoresis effects. The governing nonlinear partial differential equations are transformed into a system of ordinary differential equations using similarity transformations and solved numerically using the shooting method with a fourth-order Runge–Kutta scheme. The results indicate that an increase in the magnetic parameter significantly reduces velocity profiles while enhancing temperature and concentration distributions. The Hall parameter reduces surface drag and improves heat transfer, while decreasing mass …

Preserving The Identity Of Historic Coptic Orthodox Monasteries In Egypt Under Contemporary Pressures: Case Studies Of St. Bishoy And St. Anthony Monasteries, George Medhat Adeeb, Mohamed Khairy Amin, Mohamed Ahmed Al-Sherbiny

Mansoura Engineering Journal

Historic Coptic Orthodox monasteries in Egypt (HCOMEs) represent an important component of Christian heritage, integrating architectural value with enduring spiritual traditions that reflect both tangible and intangible dimensions. However, contemporary development and changing functional demands are generating transformations that may affect their identity if not carefully managed. Despite extensive scholarship, limited research has systematically examined these transformations through a structured evaluative approach. This study addresses this gap by developing and applying an analytical and evaluation framework to examine how contemporary pressures influence the historical, architectural-spatial, and spiritual identity of HCOMEs, and to assess the effectiveness of monastic responses. The framework …

Optimization Of Mechanical Properties Of Copper Nanofiller Reinforced Banana Fiber Polyester Composites Using Grey–Taguchi Method, Nikhil Janardan Rathod, Mayur Jayant Gitay, Markala Karthik, Harshwardhan Ghongade, Upendra Rajak, Rajendra Sopan Narkhede

Mansoura Engineering Journal

Mechanical performance of banana fiber-reinforced polyester composites maximized using a composite Taguchi and a Grey Relational Analysis (GRA) process. This will aim at enhancing dispensation limits to enhance better tensile, flexural and impact belongings. The hand lay-up method was used to create composites by variable three key limits and they included banana fiber content (30 wt%), copper nanoparticle content (15 wt%), and curing temperature (80 o C). Trial design and mechanical properties were being measured in form of ASTM values on a L9 orthogonal array.

The multi-response optimization was performed with the help of the Grey Relational Analysis, which was …

Evaluating Matching Frontier Methods For Crash Modification Factor Estimation, Usama Elrawy Shahdah, Eman K . Ali, Sania Reyad Elagamy

Mansoura Engineering Journal

This study evaluates "matching frontier" methods against conventional approaches for estimating Crash Modification Factors (CMFs). Thirty-four method-model combinations were tested, including 16 frontier variants, 8 propensity-score-matching algorithms with negative binomial and mixed-effects models, and two benchmarks (empirical Bayes and cross-sectional), across multiple sample sizes and three true CMF values (0.80, 1.00, and 1.30). Of these, 30 converged successfully; 4 mixed-effects models with replacement-based matching failed due to duplicate control observations. Each scenario was evaluated across 10 Monte Carlo replications to quantify performance uncertainty.

Synthetic crash data were generated with known treatment effects, examining scenarios ranging from ideal (386 treated, 21,000 …

Remote Sensing-Based Rice Detection: Novel Indices From Optical And Sar Synergy, Kaifi Chomani

Mansoura Engineering Journal

Accurate rice mapping is challenging due to the lack of a simple, efficient approach and the complexity and limited ability of existing methods to distinguish rice fields from non-rice fields. This study proposes two novel indices: the Multispectral Rice Detection Index (MRDI), which utilises optical imagery, and the OptiRadar Rice Index (ORRI), which incorporates both optical and Synthetic Aperture Radar (SAR) data. Ground-truth data from the Cropland Cropping Systems (CROS) were used to assess the performance of both indices. The findings indicated that MRDI achieved an overall accuracy of 97.97% with perfect recall (100%) but lower precision (78.65%). However, the …

An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare

Mansoura Engineering Journal

The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …

Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy

Mansoura Engineering Journal

Concrete is essential for construction due to its high strength and durability. It supports most modern infrastructure globally. Cement production is a major source of CO₂ emissions, posing serious environmental concerns. Additionally, the rising demand for concrete is straining the limited supply of essential raw materials, such as aggregates. Researchers are examining alternative materials to improve Sustainability while maintaining structural strength to address these issues. This research aims to improve concrete performance by enhancing cement durability with nano-silica. Coconut shell, an agricultural by-product, functions as an eco-friendly alternative to conventional coarse aggregates, alleviating their scarcity. Microbiologically induced calcium carbonate precipitation …