Digital Commons Network^™

Securing Distributed Energy Resources: A Dnp3 Master Station With Semantic Web Integration For Decentralized Der Data Sovereignty, Ethan J. Coffman

Electrical Engineering and Computer Science Undergraduate Honors Theses

As current electrical grids trend toward a heavier reliance on DERs, there is a growing need to secure DER communications while maintaining data sovereignty for device owners. Previously, work by Donna Thakadipuram established the foundation for a decentralized framework using Solid by implementing a prototype that used a Raspberry Pi and a DSP to simulate Modbus traffic and upload the data to a Solid server. This thesis extends her work to simulate multiple DERs using Typhoon HIL and communicate to each device over DNP3/TCP. The system uses a Python-based DNP3 master to collect telemetry from all 12 DERs before transforming …

Low-Cost Rf Exposure Monitoring With Tinyml Prediction, Sanad Sahawneh

Nanoscale Science & Engineering (discontinued with class year 2014)

The proliferation of wireless technologies has produced a dense, increasingly heterogeneous radio-frequency (RF) environment that surrounds modern life. While regulatory bodies such as the Federal Communications Commission (FCC) and the World Health Organization (WHO) maintain exposure guidelines, the tools that ordinary people, educators, and small institutions can use to actually observe RF exposure in their own spaces remain expensive, specialized, and largely confined to professional laboratories. Spectrum analyzers and calibrated field probes routinely cost between five hundred and one hundred thousand dollars per unit, placing continuous local monitoring out of reach for most environments where exposure questions are most natural …

The Role Of Operational Context In Shaping Energy Management Portfolios: A Comparative Case Study Of Two Manufacturing Facilities, Cynthia Aranda

Theses and Dissertations

Using two facilities as illustrative examples, this research investigates how a manufacturing plant's operational and financial context may influence its investment decisions in energy-efficiency measures. This challenges the primacy of the simple payback period (SPP) as a screening tool and instead demonstrates the role of operational context in investment decision-making. To this extent, this study is anchored to a qualitative comparative case study analysis of two ITAC energy assessments for two manufacturing plants in Texas: a higher value-added aerospace MRO plant (GE Aerospace, TR0060) versus a cost-sensitive automotive stamping plant (UMP Metal Stamping, TR0061). The two cases illustrate two different …

Sub-Ghz Propagation Along Freight Trains For Wireless Onboard Communications, Dario Hinojosa

Theses and Dissertations

With the increasing length of freight trains, maintaining reliable wireless communication for onboard sensors has become increasingly challenging. Sub-GHz communication bands are a promising solution due to their long-range capability and suitability for rural railway environments. This study analyzes radio wave propagation around freight railcars to evaluate path loss and determine how antenna polarization affects wireless communication performance.

Time-domain full-wave electromagnetic simulations were performed using simplified railcar models and later validated through field testing using a vector signal generator, vector network analyzer (VNA), and spectrum analyzer. Various antenna polarization configurations were evaluated within the Sub-GHz Long Range (LoRa) frequency band …

Robust Hardware Trojan Detection Leveraging Dual‑Domain Features And Stacked Ensemble Learning, Sefatun-Noor Puspa

All Theses

In Cyber-physical systems rely on sensors, communication, and computing, all powered by integrated circuits (ICs). These ICs are vulnerable to malicious hardware attacks, with hardware Trojans being one of the stealthiest threats. Trojans are malicious implants in the circuitry, which are often inserted during design or fabrication stages. This stealthy addition remains dormant until triggered and might cause functional disruptions or sensitive information leakage once triggered. Traditional IC validation methods, such as functional testing and logic analysis, usually fail to capture these subtle anomalies because hardware Trojans are intentionally designed to mimic normal circuit behavior. They often remain dormant under …

Transient Mitigation In Dual Active Bridge Converter Using An Auxiliary Converter With High-Frequency Selective Control For Load Step-Down Condition, Sachith Dilshan Wijesooriya

Masters Theses

Dual Active Bridge (DAB) converters are widely utilized in applications such as electric vehicles, renewable energy systems, and solid-state transformers due to their high efficiency, galvanic isolation, and bidirectional power transfer capability. However, during rapid load transitions, DAB converters frequently exhibit significant output voltage overshoot and prolonged settling times, which increase device stress and adversely affect system reliability. This thesis proposes an auxiliary-circuit-based transient mitigation method to address these limitations. The auxiliary circuit, implemented as a bidirectional Buck–Boost stage, operates in Boost mode during load step-down events to absorb excess energy and suppress the resulting voltage overshoot. The design of …

Enhancing Reliable Performance Of Microgrids With Autonomous Control Of Distributed Energy Resources, Sahand Liasi

All Dissertations

This dissertation presents a comprehensive investigation into enhancing the reliability, efficiency, and autonomous operation of modern power networks through advanced microgrid integration and control strategies. The research addresses critical challenges across three interconnected domains: microgrid control, thermodynamic modeling of heat recovery system (HRS), and optimal distribution network reliability.

In the realm of microgrid control, this work introduces novel methodologies for grid forming inverter-based resources (IBRs). A significant contribution is the development and validation of an "Auto Frequency Change" controller, which drastically reduces microgrid synchronization time with the main grid from several minutes to approximately four seconds, with theoretical potential for …

Safe Control Design For Quadruped Locomotion In Unstructured Environments Using Linear Transfer Operators, Sriram Sundar Krishnamoorthy Shankara Narayanan

All Dissertations

Deploying quadruped robots in unstructured, obstacle-rich environments requires control and planning methods that remain safe and reliable despite complex terrain geometry, limited sensing, and inevitable modeling errors. This thesis develops operator-theoretic tools for safe control design of robotic systems using linear transfer operators, with a focus on quadruped locomotion in unstructured environments. The central goal is to develop a unified operator-theoretic framework for safe control design based on the Perron–Frobenius (P–F) and Koopman operators. In particular, the thesis leverages \emph{density functions} to develop safe navigation frameworks in the dual space of densities. In the operator-theoretic perspective, the P–F operator governs …

Design And Reliability Analysis Of A Radiation-Tolerant On-Board Computer System For Martian Surface Missions, Jack Ryan

Master's Theses

Space environments present complex challenges for electronic devices, perhaps most notably in the form of radiation effects; the natural protections provided by Earth’s atmosphere and magnetosphere are largely absent in deep space and extraterrestrial environments, making single-event effects (SEE) a critical concern. Although radiation-hardened components offer near-immunity to SEE, they possess tremendous drawbacks in both cost and performance. To circumvent such issues, this thesis investigates the feasibility of leveraging a commercial-off-the-shelf (COTS) device, the AMD KRIA K24 system-on-module (SOM), for use in Martian surface missions.

Detailed models were used to predict SEE rates in the system, and system-level fault tree …

A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small satellites often lack the ability to analyze their data in real time, relying instead on downlinking raw measurements to Earth before any scientific interpretation can occur. This delay restricts missions that require rapid awareness of environmental or space-weather events. This thesis presents the Low-power Array for Cubesat Edge Computing Architecture, Algorithms, and Applications (LACE-C3A), a hardware platform designed to enable in-orbit data processing within the power and volume limits of CubeSat-class spacecraft. 

LACE-C3A uses a modular cluster of flash-based FPGAs, which offer low power consumption, radiation resilience, and in-flight reconfigurability. The system consists of a Controller board responsible …

Ionospheric Plasma Electron Density Measurement And Theory Using Impedance Probe Techniques, Justin Wellington

All Graduate Theses and Dissertations, Fall 2023 to Present

The ionosphere plays a critical role in how radio frequency (RF) signals, like those used in Global Position System (GPS) satellite communications, travel through space. Disturbances in the ionosphere, such as equatorial plasma bubbles (EPB), scatter these signals and cause communication dropouts or navigational errors. To study these conditions, spacecraft use instruments that measure the surrounding plasma directly. One of these instruments is an impedance probe, which applies a small electrical signal to a sensor and determines electron density from the measured impedance.

This thesis improves the modeling and interpretation of impedance probe measurements. A numerical method is developed that …

Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio

All Graduate Theses and Dissertations, Fall 2023 to Present

Measuring magnetic fields in space helps scientists understand phenomena that can affect satellite communications and navigation systems on Earth. This research develops a new low-power magnetic field sensor for spacecraft that improves upon existing designs by moving the sensitive parts away from electrical interference and using energy-efficient digital electronics for precise measurements. The sensor’s power-efficient design is particularly important for small satellites, where power is limited and must be carefully managed. It will fly on future NASA missions to study disturbances in Earth’s upper atmosphere that can disrupt radio signals and GPS. This work contributes to our ability to better …

Design And Optimization To Advance Silicon Carbide Modules For Medium Voltage High Power Applications, Ahmed Ismail

Graduate Theses and Dissertations

The commercial availability of the first 10 kV silicon carbide (SiC) MOSFET removes the principal semiconductor barrier to medium-voltage power conversion, enabling converter topologies that are structurally inaccessible to silicon IGBT solutions at this voltage class. This dissertation presents the characterization infrastructure, device-level data, and preliminary system-level validation needed to advance the deployment of the third-generation 10 kV SiC MOSFET in converter applications. A custom-built 10 kV double-pulse test platform is developed with a fully documented component-sizing methodology, custom medium-voltage magnetics, and a measurement infrastructure capable of high bandwidth waveform capture at kilovolt common-mode potentials. On this platform, the third-generation …

Mitigating Inertial Measurement Unit Drift In Quadcopter Trajectory Tracking Using Kalman Filter Sensor Fusion With Global Positioning Measurements, Juan Sandro Caballero Aguilar

Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) like quadcopters are widely used in civilian and military applications such as farming, photography, search and rescue missions, and autonomous navigation and motion. The performance and stability of these systems depend on accurate state estimation, which provides real-time information about the vehicle’s position, velocity, and orientation. However, achieving reliable state estimation is challenging due to sensor noise, measurement uncertainty, and inaccurate modeling. Common navigation sensors such as the Global Positioning System (GPS) and Inertial Measurement Units (IMUs) exhibit complementary characteristics. GPS provides absolute position measurements but suffers from noise, multipath effects, and low update rates, while …

Versatile Exoskeleton Control Paradigms For Agile Human Locomotion: Task-Agnostic And Stability-Augmented Assistance, Miao Yu

All Dissertations

Lower-limb exoskeletons have shown great potential for assisting human locomotion, but designing controllers that provide assistance across diverse locomotor tasks and under external perturbations remains a major challenge. Many existing controllers for steady-state walking rely on pre-defined reference trajectories, which constrain voluntary human motion and limit adaptability across tasks. Moreover, they usually assume stable walking, while their performance under unstable conditions remains largely unexplored. In addition, existing gait stability augmentation controllers are often reactive rather than proactive to unstable conditions. In this dissertation, we propose control frameworks that preserve voluntary human motion while addressing two major challenges: providing task-agnostic assistance …

Data-Driven Multimodal Mri Representation Learning For Subtype Discovery And Disease Progression Modeling In Parkinson’S Disease, Zihan Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Parkinson’s disease (PD) exhibits substantial clinical and neuroanatomical heterogeneity, limiting robust patient stratification and clinically meaningful progression modeling from MRI. We propose a unified multimodal 3D generative representation-learning framework that learns an interpretable latent space from co-registered baseline T1/T2 MRI with an edge-aware channel. Confound-corrected latent embeddings support unsupervised subtype discovery, while disease duration provides weak supervision to orient a continuous progression axis. On an independent external cohort (PPMI, N=171), the discovery-trained subtype structure shows significant partial replication (ARI=0.35; permutation test p=0.001) and enables longitudinal clinical stratification: mixed-effects modeling reveals subtype-dependent MDS-UPDRS III progression, with the strongest effect in subtype …

Design Of An Extensible And Scalable Data Acquisition System For Pulse Shape Discrimination, Prince John

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis presents the design and development of a highly scalable, end-to-end data acquisition (DAQ) system for nuclear physics experiments that can be deployed in configurations ranging from a few to thousands of detector channels. The system is built as an extensible platform composed of modular 16-channel chipboards that support a wide range of scintillator and detector types and perform real-time, on-board data sparsification and pulse-shape processing. Three versions of the chipboard have been fabricated to date.

The DAQ architecture is based on a family of analog pulse-shape-processing application- specific integrated circuits (ASICs) developed by the IC Design Laboratory at …

Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton

McKelvey School of Engineering Graduate Student Theses & Dissertations

As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …

Temporal Logic Planning In Semantic Maps Of Unknown Environments Using Tl-Rrt, Dongrui Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Autonomous mobile robots are increasingly expected to perform complex missions in unstructured environments. Traditional path planning approaches handle simple point-to-point navigation, but struggle with complex tasks that involve temporal and logical orderings of objectives. Linear Temporal Logic (LTL) provides a method for complex missions (e.g., sequential visits to multiple targets or surveillance tasks) in a strict way. This thesis presents an integrated planning framework that enables a robot to satisfy LTL-based task specifications in an unknown environment by combining a Temporal Logic RRT* (TL-RRT*) planner with semantic mapping. The robot builds a semantic map of its environment online using simultaneous …

A Study Of Visualized Diagnostics In Early Stage Digital Twin Implementation Of An Industrial Control System, Michael R. Kinzel

All-Inclusive List of Electronic Theses and Dissertations

Industrial Control Systems (ICS) are used for process control in almost all industries. An ICS combines Operational Technologies (OT) with Information Technologies (IT) to allow human supervision of a process through surveillance of process variables and manipulation of controlling elements such as valves to maintain stable process conditions. ICSs have been in-service for several decades and may remain operational past their technological service life. Organizational personnel interact with the ICS through visual displays that both indicate the process variables and also the controlling elements. The Human Machine Interface (HMI) allows visibility of the process and the ability to manipulate controlling …

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …

Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd

Chemical Technology, Control and Management

For solving this issue, the paper considers a hierarchical multi-criteria decision-making problem, where the choice of a company that corresponds best to the criteria is required. Data used in this problem are presented in the form of intervals, which makes it possible to cope with uncertainty in the problem solution. Several companies working in missile production industry are chosen as alternatives for analysis. Evaluation of the selected alternatives is made based on five criteria clusters. More than twenty criteria are taken into account during evaluation.

Solving this problem is achieved with the help of the technique based on computation of …

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.

Molecular Catalysts For Electrochemical Nitrogen Activation Toward Sustainable Ammonia Synthesis, Jin-Xiu Han, Hao Xue, Xian-Biao Fu

Journal of Electrochemistry

Homogeneous electrocatalytic nitrogen reduction reaction (NRR) provides a powerful framework to interrogate molecular nitrogen-fixation pathways under mild conditions. By tuning the metal center, ligand architecture, and reaction medium, these systems enable capturing key intermediates and delivering mechanistic insight at the molecular-level resolution. Nevertheless, advances remain constrained by highly reduced operating potentials, intense competition from the hydrogen evolution reaction (HER), limited durability in turnover, and inadequate long-term stability.

In this review, we take electron delivery to the molecular active site as the guiding principle for organizing homogeneous electrochemical N₂ activation and transformation. We classify reported systems into direct electron transfer …

Water-Driven Solid Electrolyte Interphase Governs Continuous-Flow Ammonia Electrosynthesis, Peng-Bo Liu, Sheng-Liang Zhai, Ji Huang, Zhong-Shuo Zhang, Jie Zeng, Shao-Feng Li

Journal of Electrochemistry

Flow-cell architectures have emerged as a powerful platform for continuous and stable lithium-mediated nitrogen reduction (Li-NRR), enabling ambient-condition electrochemical ammonia synthesis and offering a promising alternative to Haber-Bosch processes. However, Li-NRR is exceptionally sensitive to trace water, and even minor variations in water content can profoundly alter interfacial chemistry. Here, we systematically investigate how initial water concentration affects Li-NRR performance in a continuous-flow cell. Excess water drives the formation of a thick solid electrolyte interphase (SEI) layer, which may impede nitrogen access to metallic lithium and hinder lithium-ion transport. As a result, the ammonia Faradaic efficiency collapses from ~61% to …

Insertion Of Noble Metal Free Cathodic Catalyst Layer With Fe-N-C Catalyst For Boosted Performance Of Pemfc, Shi Zhou, Muhammad Tariq, Asif Nadeem Tabish, Muhammad Salman, Fan-Di Ning, Muhammad Rayyan Tayyab, Ran-Ran Peng, Meng-Geng Hao, Wen-Mu Li, Xiao-Chun Zhou

Journal of Electrochemistry

Economical Fe-N-C catalysts are considered as promising alternatives to platinum group metal catalysts for proton exchange membrane fuel cells (PEMFCs). Despite exhibiting robust activity on rotating disk electrodes, their performance within membrane electrode assemblies often experiences limitations, such as decreased O₂ diffusion, high H₂O₂ formation, low proton conduction, and a lower electron transfer number. In this study, key factors, including proton transport, electron conduction, and gas diffusion within air-breathing PEMFCs, have been investigated by adjusting cathode catalyst layer (CCL) compositions. From the experimental results, the optimal peak power density was obtained when the loading of Fe-N-C …

A Machine Learning Framework For Ddos Attack Detection In Sdn-Enabled Mobile Wireless Networks, Ishita Sharma, Satyam Agarwai, Shashi Shekhar Jha, Sumit Chakravarty

Faculty Articles

Attacks on network components and devices pose a significant threat to service continuity, necessitating robust detection mechanisms. This paper presents a Distributed Denial of Service (DDoS) attack detection framework tailored for heterogeneous mobile wireless networks within a Software-Defined Networking architecture. A two-tier model is proposed: localized attack detection at access points (APs) using a Multi-Layer Perceptron (MLP) classifier, and centralized detection under mobility at the controller using a Long Short-Term Memory (LSTM) model. The system incorporates novel traffic features such as flow count, speed of source IP, source and destination IP address entropy, proportion of bidirectional flows, and handover frequency, …

Nocap: Article Fact-Checking With Ai, Thomas Chamberlain, Anthony Ciero, Varun Doddapaneni, Joshua Pechan

Electrical Engineering and Computer Science Student Publications

Fact checking media is important for properly obtaining information

Create a website that uses AI knowledge to allow users to fact check an article

Give these articles an authenticity score and report on what is fact or fiction

Aggregate scores of articles by the same publisher in a database allowing users to view their scores and article authenticity reports

Ortega Observatory Weather Station, L. Collins, B. Erskine, L. Houck, E. Kornbau

Electrical Engineering and Computer Science Student Publications

The team’s mission was to create an automated weather station with a convenient display to give information on conditions that affect the ability to observe such as rain and wind, in addition to performing necessary maintenance or repair on the Ortega Observatory and aiding in the construction of the PCB that will control the telescope movement arms.