Digital Commons Network^™

Simultaneous Observations Of Irregular Sporadic E Structures Using The Lwa And A Dps4d, Kenneth S. Obenberger, C. A. Taylor, Jonah J. Colman, Eugene Dao, J. Dowell, J. D. Eccles, Daniel J. Emmons, C. T. Fallen, J. M. Holmes, G. B. Taylor

Faculty Publications

Multi-instrument studies have recently shed new light on the morphology of sporadic E, especially intense sporadic E. Here we present simultaneous observations of dense sporadic E (E_s) structures using the Long Wavelength Array (LWA) radio telescopes and a Digisonde Portable Sounder 4D (DPS4D). Our coordinated observations show that the LWA radio telescopes in central New Mexico can reliably locate regions of dense Es structures as they pass over a Digisonde located over 500 km away in Texas. The LWA appears to be most sensitive to the densest E_s structures, which also appear to contain irregularities with vertical …

Scalable Cyber-Physical Testbed For Cybersecurity Evaluation Of Synchrophasors In Power Systems, Shuvangkar Chandra Das, Tuyen Vu, Hebert L. Ginn Iii

Faculty Publications

This paper presents a synchrophasor-based real-time cyber-physical power system testbed with a novel security evaluation tool, pySynphasor, that can emulate different real attack scenarios on the phasor measurement unit (PMU). The testbed focuses on real-time cyber-security emulation using different components, including a real-time digital simulator, virtual machines (VM), a communication network emulator, and a packet manipulation tool. The script-based VM deployment and software-defined network emulation facilitate a highly scalable cyber-physical testbed, which enables emulations of a real power system under different attack scenarios such as address resolution protocol (ARP) poisoning attack, man-in-the-middle (MITM) attack, false data injection attack (FDIA), and …

Graphtreemed: A Hybrid Graph-Tree Rag Architecture For Mission-Critical Medical Applications, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Studies within engineering management indicate that decision-making is often based on the cognitive processing of grouped and pictographic information clusters entangled with high-level pattern recognition. Similarly, graph-based retrieval-augmented generation (RAG) architectures substantially improve diagnostic accuracy and interpretability, while tree-structured systems reduce critical misses through hierarchical reasoning. However, existing solutions often lack a unified framework that seamlessly integrates these two paradigms to address the multifaceted demands of mission-critical healthcare settings. This proposal introduces GraphTreeMed, a novel hybrid RAG architecture designed to harness the complementary strengths of graph-based and tree-based retrieval mechanisms, thereby advancing the safety and efficacy of clinical decision support …

Rf Emission From Partial Breakdown Events And Their Classification, Torin Sammeth

Electrical and Computer Engineering ETDs

Electrical breakdown is a core component of Pulse Power both in its utilization and as a failure point in systems. This research is investigating the feasibility of D-dot antennas to detect and potentially identify different forms of partial electrical breakdown in a point-to-plane gap geometry. In this work, the RF emission detected by a D-dot probe during a partial breakdown event is shown to correlate with the presence of light and current using a fast-current transformer and photomultiplier tube. Additionally, the frequency components of the RF signal were measured with the use of a fast Fourier transform. Identifying these frequencies …

Antenna Analysis Using Mixed Computer Platforms (Aacp), Keith H. Bova

Electrical and Computer Engineering ETDs

This thesis reviews the design, implementation, and benchmarking of commercially available, previous generation (CAPG) computer systems, and how they can be used with computational electromagnetics. The thesis focuses on their architecture, performance, and practical applications. It begins with an overview of CAPG system components, including different node types such as login/controllers, compute nodes, block storage, and object storage. The process of assembling these systems is outlined. The conjugate gradient method and direct linear solvers were benchmarked. The performance of CAPG systems is compared with modern computing architectures. A detailed analysis provides recommendations for designing CAPG systems around the performance of …

Enhancing Frequency Event Detection In Power Systems Using Two Optimization Methods With Variable Weighted Metrics, Hussain A. Alghamdi, Midrar A. Adham, Umar Farooq, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

This research presents a novel technique that refines the performance of a frequency event detection algorithm with four adjustable parameters based on signal processing and statistical methods. The algorithm parameters were optimized using two well-established optimization techniques: Grey Wolf Optimization and Particle Swarm Optimization. Unlike conventional approaches that apply equally weighted metrics within the objective function, this work implements variable weighted metrics that prioritize specificity, thereby strengthening detection accuracy by minimizing false-positive events. Realistic small- and large-scale frequency datasets were processed and analyzed, incorporating various events, quasi-events, and non-events obtained from a phasor measurement unit in the Western Interconnection. An …

Securing Biometric Data, Alyssa F. Carroll

Cybersecurity Undergraduate Research Showcase

Biometric data has been widely adopted across various sectors, including digital identity, artificial intelligence (AI), border control, digital wallets, and national identification systems. While biometric identifiers—such as fingerprints, retina scans, and facial recognition—offer reliable and convenient authentication, they also raise significant concerns regarding privacy and security. This paper examines how biometric data is stored, the vulnerabilities it faces, and the most effective methods for safeguarding it. By highlighting the critical importance of biometric data protection, this study reviews current research on approaches, strategies, and policies that enhance security while preserving the functionality and efficiency of biometric systems.

Utilizing Machine Learning To Predict The Charge Storage Capability Of Lithium-Ion Battery Materials, Manoj Chhetri, Karen S. Martirosyan

Physics & Astronomy Faculty Publications

With the increasing demand for high-performance batteries in applications such as electric vehicles and portable electronics, accurately predicting the charge storage capacity of battery materials is crucial for developing more efficient and reliable energy storage systems. Machine Learning (ML) and data-driven approaches, plays a vital role in enhancing our understanding of Li-ion battery performance, guiding materials design, optimizing system efficiency, and accelerating innovation in energy storage technologies. In this study, an ML-based approach was applied to a dataset of 2345 rechargeable Li-ion battery materials, obtained from the Materials Project online portal, to predict gravimetric charge storage capacity ─ a key …

Electric Field Profiles Under High Voltage Overhead Transmission Lines With Under-Build Distribution Circuit, Aminu Haruna

Electrical Engineering Theses

The increasing use of underbuilt lines in recent transmission projects alters electric field profile under transmission lines. By assessing electric field intensity in these transmission and distribution network configurations, the study identifies regions with high electric fields that may exceed standard exposure limits, posing potential risks. This work employs the charge simulation method and the method of imaging to analyze electric fields beneath transmission lines with underbuilt distribution networks. Key objectives include calculating the electric fields at 1 meter above ground, and evaluating the field at conductor surfaces. The study considers transmission line voltages of 69kV, 161kV, 220kV, 345kV and …

A Reliable And Efficient Detection Pipeline For Rodent Ultrasonic Vocalizations, Sabah Shahnoor Anis, Devin Mark Kellis, Kris Ford Kaigler, Marlene A. Wilson, Christian O'Reilly

Faculty Publications

Analyzing ultrasonic vocalizations (USVs) is crucial for understanding rodents' affective states and social behaviors, but the manual analysis is time-consuming and prone to errors. Automated USV detection systems have been developed to address these challenges. Yet, these systems often rely on machine learning and fail to generalize effectively to new datasets. To tackle these shortcomings, we introduce ContourUSV, an efficient automated system for detecting USVs from audio recordings. Our pipeline includes spectrogram generation, cleaning, pre-processing, contour detection, post-processing, and evaluation against manual annotations. To ensure robustness and reliability, we compared ContourUSV with three state-of-the-art systems using an existing open-access USV …

An Effective Genetic Algorithm For Mixed Precision, Wanyu Zhang, Yu Shang, Min Tsao, Yiwei Li, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

The precision of floating-point numbers is a critical task in high-performance computing. Many scientific applications rely on floating-point arithmetic, but excessive precision can lead to unnecessary computational overhead. Reducing precision may introduce unacceptable errors. Addressing this trade-off is essential for optimizing performance while ensuring numerical accuracy. In this paper, we present a genetic algorithm-based approach for tuning the precision of floating-point computations. Our method leverages algorithmic differentiation and first-order Taylor series approximation to assess the impact of precision variations efficiently. We employ stochastic partitioning algorithms with multiple precision combinations that meet the error requirements. Moreover, we present a genetic heuristic …

From Adversarial Attacks To Robust Classifiers - A Study In Social Media Spam Detection - Black Box & White Box, Jonathan Jose Penaloza Rumie

Undergraduate Theses

Adversarial attacks pose a significant threat to the reliability of machine learning-based spam detection systems in social media. This undergraduate thesis, "From Adversarial Attacks to Robust Classifiers: A Study in Social Media Spam Detection – Black Box & White Box," systematically examines the impact of both black-box and white-box adversarial attacks on a range of spam classifiers, including Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Bagging, Gradient Boosting, and Support Vector Machines. Leveraging a novel dataset derived from Twitter spam messages and enhanced with adversarial perturbations such as synonym replacement and character-level modifications, this study evaluates classifier performance under …

On The Robustness Of Adaptive Resonance Theory Neural Networks, Shane Cairns, Leonardo Enzo Brito Da Silva, Sasha Petrenko, Donald C. Wunsch

Miners Solving for Tomorrow Research Conference

No abstract provided.

Impulse, Spring 2025, Jill Fier, Micayla Standish, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

2 | Faculty, Staff Honored
4 | The State of Lithium
6 | 100 Years of Ag and Biosystems Engineering
8 | Major Milestones
12 | Distinguished Engineer Geldert-Murphy
14 | Distinguished Engineering Heitkamp
16 | By the Numbers
18 | Space Grant Consortium at SDSU
20 | Healthcare Systems Engineering Program
22 | Ridgway Three-Peat
23 | Aerospace Club Launches
24 | Power and Energy Scholarships
25 | More Take Part in Nasa Challenges
26 | Weber Recognized as Student Leader
30 | Wild Hare Racing Ready
32| Sebern’s Success as Sole Operator
34 | Meink: From Prairie to …

Amplification In Mems Rlc Circuits For Enhanced Sensitivity And Mems Applications, Mutaz Mohd Hamdi Al Fayad

Durham School of Architectural Engineering and Construction: Dissertations, Theses, and Student Research

Micro-electro-mechanical systems (MEMS) have garnered significant attention due to their unique characteristics, including small size, high sensitivity, and cost-effective mass production. While electrostatic actuation offers low power consumption, it requires high voltage to move the MEMS structure, posing a challenge for applications such as RF switches and MEMS resonator-based sensors. Reducing the required input voltage for electrostatic MEMS remains a key research focus.

This thesis investigates voltage amplification in electrostatic MEMS through integration with resonant RLC circuits. By leveraging resonance, optimized configurations are designed to maximize voltage gain and enhance the signal-to-noise ratio. Through theoretical modeling and simulations using MATLAB …

Developing Fixed-Bias Langmuir Probes For Multi-Point Constellation Deployments, Henry Carter Valentine

Doctoral Dissertations and Master's Theses

Since their initial development in the early 20th century, electrostatic Langmuir probes have proved invaluable in terrestrial and interplanetary ionospheric sounding applications. When deployed aboard rocket and satellite platforms, these probes yield high-cadence, in-situ measurements of key plasma parameters such as electron density, ion density, and electron temperature. Furthermore, the efficacy of Langmuir probes in characterizing the three-dimensional structure and dynamics of ionospheric plasmas can be augmented by the technique of multi-payload deployments. In this work, we discuss the design, development, and analysis of fixed-bias Langmuir probes constructed for two multi-point science campaigns: the Mars-bound, dual-satellite Escape and Plasma Acceleration …

Analytical Dispatch Strategies For Pumped Storage Hydro: A Conditional Dynamic Programming Approach To Discontinuous Multi-Period Optimization Problems, Jian Liu, Jianwen Zhang, Zaiwu Gong, Donald C. Wunsch, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing integration of renewable energy sources like wind and solar poses significant challenges to secure and stable grid operation. Energy storage systems, particularly pumped storage hydro (PSH), play a crucial role in balancing power supply and demand. Traditional analytical studies of PSH economic dispatch problems often assume zero lower bounds for generating and pumping rates to simplify analysis and derive analytical solutions for multi-period optimization problems. However, the inherent mechanical design constraints of PSH require non-zero minimum flow rates for efficient operation. We analyze two scenarios, merchants having PSH only and merchants having both PSH and wind farms. In …

Transforming Optical Vernier Effect Into Coherent Microwave Interference Towards Highly Sensitive Optical Fiber Sensing, Ruimin Jie, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

The optical Vernier effect has garnered significant research attention and found widespread applications in enhancing the measurement sensitivity of optical fiber interferometric sensors. Typically, Vernier sensor interrogation involves measuring its optical spectrum across a wide wavelength range using a high-precision spectrometer. This process is further complicated by the intricate signal processing required for accurately extracting the Vernier envelope, which can inadvertently introduce errors that compromise sensing performance. In this work, we introduce a novel approach to interrogating Vernier sensors based on a coherent microwave interference-assisted measurement technique. Instead of measuring the optical spectrum, we acquire the frequency response of the …

Smart Traffic Intersections: Leveraging Isac And Millimeter-Waves For Advanced Vehicle Platooning, Mohammed Risal Thadathil

Theses

The rapid advancement of self-driving cars is reshaping the transportation industry and accelerating the development of smart cities. Vehicle platooning, a key capability of autonomous vehicles, has the potential to enhance traffic efficiency, reduce congestion, and improve safety at intersections. However, maintaining platoon cohesion, minimizing latency, and optimizing traffic signal interactions remain significant challenges. This study addresses these issues by leveraging Integrated Sensing and Communication (ISAC) technology with millimeter-Waves (mmWaves) signals to optimize platooning performance at traffic signal intersections.

The research identifies gaps in existing Vehicle-to-Everything (V2X) communication frameworks, particularly in managing platoon movements in urban traffic intersections. To bridge …

Enhancing Iot Security Using Lightweight Machine Learning Algorithms: A Comprehensive Approach Using Ensemble Learning, Feature Selection, And Federated Transfer Learning, Khawlah Harahsheh

Electrical & Computer Engineering Theses & Dissertations

The rapid expansion of the Internet of Things (IoT) has introduced significant security vulnerabilities due to the resource-constrained nature of IoT devices and their exposure to cyber threats. Traditional security solutions are often infeasible due to the high computational and storage demands they impose. This dissertation presents a lightweight, AI-driven security framework that enhances IoT network resilience by integrating feature selection, ensemble learning, and federated transfer learning while maintaining data privacy and minimizing computational overhead.

The proposed framework consists of three primary components: Feature Selection for Intrusion Detection, which optimizes performance by reducing redundant data and improving detection accuracy with …

Streamer Discharge Simulation For Plasma-Assisted Combustion, Stuart Jairo Reyes

Electrical & Computer Engineering Theses & Dissertations

A common and successful method to achieve atmospheric pressure fuel-air plasma-assisted combustion is through repetitive ns pulsed discharges and dielectric-barrier discharge. The transient phase in these discharges is dominated by transport influenced by strong space charges produced by ionization fronts, this can be best represented by the streamer model. The function of non-thermal plasma in these discharges is to excite the species in the fuel-air mixture to produce radicals which accelerate the chemical conversion reactions which directly lead to temperature rise, ultimately culminating in ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to developing a …

Painting Rich Six-Dimensional Pictures Using Polarized Fluorescence Microscopy, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

No abstract provided.

Adaptive Control System Of Nonlinear Dynamic Object On The Basis Of Neuro-Fuzzy Networks, Isomiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Technical science and innovation

The presented paper is devoted to the development of an adaptive control system for a nonlinear dynamic object using neuro-fuzzy networks. The authors note that in real conditions dynamic objects function under conditions of uncertainty, which are characterised by complex and poorly understood relationships between technological variables, the presence of perturbing and random disturbances, as well as nonlinear elements. This makes it difficult to apply traditional linear adaptive control algorithms. The use of self-organising adaptive control is proposed, in which the mathematical model of the controlled system is formed by operational identification during system operation. It is shown that linear …

Development Of Analytical Dependencies For Determining Kinematic Parameters Of The Drive Of The Working Engine Of The Mixing Machine, N. A. Maksudova

Technical science and innovation

The requirement of any technological process of product preparation is intensive mixing. This ensures uniform distribution of components. At the initial stage of designing planetary mechanisms, special attention is paid to determining the kinematic parameters. The dimensions, weight and design of the mechanism depend on the value of these parameters. The main criterion for assessing the scheme of the planetary mechanism is the kinematic parameters of the gear wheels of the mechanism. The article presents a kinematic scheme of the planetary mechanism of the kneading machine. The principle of rotation of the gear wheels of the planetary mechanism of the …

Development And Analysis Of The Kinematic-Dynamic Model Of The Rehabilitation Exoskeleton System, Umidjon Abdumutalipovich Takabaev, Zafar Botirovich Juraev

Technical science and innovation

Designing modern rehabilitation exoskeleton systems requires a comprehensive study of human-machine interactions. In this process, creating kinematic and dynamic mathematical models of the system is extremely important. In this paper, we develop mathematical models that describe rehabilitation exoskeleton systems' kinematic and dynamic properties. Based on the Denavit-Hartenberg method we construct kinematic model of the exoskeleton system. The method gave us to determine the coordinate system for each joint. Furthermore, we also study the motion range of joints of the exoskeleton. Modeling the dynamic properties of the system performed with the second-order Lagrange equation. The exoskeleton construction consisting of knee, thigh, …

Design And Development Of A Low-Cost Educational Robot: A Scalable And Affordable Software Learning Platform, Diana Refaat Henry Jacob, Mohamed Tarek Elawa, Ashraf Mohamed Hafez

Journal of Engineering Research

This study presents the design and development of a low-cost educational robot to enhance learning experiences in robotics and programming. The system integrates robust software development, ensuring seamless interaction between sensors, actuators, and a custom-designed graphical user interface (GUI). The robot is equipped with various sensors and actuators to support a broad range of experiments and educational applications. The software architecture is detailed, focusing on its modularity and ease of use, enabling students to intuitively program and interact with the robot. Additionally, a series of experiments were conducted to evaluate the performance of the sensors and actuators, providing insights into …

Non-Orthogonal Multiple Access Empowered Physical Layer Security Systems: Review, Issues And Challenges, Aml Fawzy, Mahmoud Selim, Maha Elsabrouty, Sameh Napoleon, Mustafa M. Abd Elnaby

Journal of Engineering Research

As 5G networks advance, the demand for higher data rates, enhanced spectral efficiency, and increased connectivity intensify. Non-orthogonal multiple Access (NOMA) addresses these needs by allowing multiple users to share the same time and frequency resources, thus optimizing network resource utilization and significantly boosting system capacity and throughput. NOMA's influence extends beyond traditional communication scenarios, impacting various vertical industries that require extensive connectivity, such as the Internet of Things (IoT). This transformative approach is crucial for industrial and critical mission applications. Given the importance of safeguarding these communications from potential eavesdroppers, Physical Layer Security (PLS) emerges as a vital tool. …

Comprehensive Sensing Analysis Of Ofdm Waveform For Future Jrc And Radar Systems, Mehmet Yazgan

USF Tampa Graduate Theses and Dissertations

In today’s interconnected world, sensing is one of the indispensable parts of wireless systems.The need to optimize and diversify the use of the radio frequency spectrum has reached unprecedented importance. Cutting-edge applications, including autonomous technologies, intelligent urban systems, and advanced monitoring, require solutions that can effectively merge communication and sensing functions within limited bandwidth. Orthogonal frequency division multiplexing (OFDM) has emerged as a leading contender in this field due to its superior ability to maximize spectral usage, resilience to multipath interference, and versatile signal configuration options. Reconsidering the use of the OFDM waveform for sensing purposes is undeniably essential due …

Role Of Eye-Tracking Technology And Software Algorithms In Enhancing Adhd Detection And Diagnosis: A Systematic Literature Review, Lauren E. Perkins

Honors College Theses

This systematic literature review explores the role of eye-tracking technology and software algorithms in enhancing the detection and diagnosis of ADHD. ADHD, a neurodevelopmental disorder affecting both children and adults, is traditionally diagnosed through behavioral assessments, which may lack objectivity. Recent studies suggest that eye-tracking, specifically focusing on saccades, fixations, and blink rates, offers the potential for more accurate and objective measures of ADHD. The review examines clinical trials, observational studies, and machine learning research to assess the correlation between ADHD and eye movement patterns. Results indicate that individuals with ADHD exhibit distinct eye movement patterns, which can be quantified …

The Impact Of Solar Angle And Cloud Shadows On 3d Reconstruction Of Rolling Stock Cargo, Carlina M. Ostrand, Adam D. Reiman, Frank W. Ciarallo, Scott L. Nykl, Clark N. Taylor, Joshua F. Krutz

Faculty Publications

Meeting the relentless demand for more efficient air cargo transportation is of paramount importance for commercial needs and military missions. This study describes an experiment to test an innovative approach that harnesses cutting-edge stereoscopic vision technology to create 3D point clouds of rolling stock cargo across varying solar angles and cloud shadow conditions. Virtual cargo point clouds are generated by calibrating and systematically organizing the depth and location points from an RGB-D camera and then reprojecting them in a virtual environment. Measurement accuracy was rigorously tested across six camera positions in various combinations of weather conditions against physical ground truth …