Electrical and Computer Engineering Commons^™

Integration Of Bayesian Networks And Neural Networks For High-Dimensional Data Analysis, Cooper Schmer

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

High-dimensional biomedical datasets, such as omics data, present significant challenges for predictive modeling due to noise, redundancy, and computational complexity. This thesis proposes a hybrid framework that integrates Bayesian Networks (BNs) and Artificial Neural Networks (NNs) to improve classification performance of such data sets while reducing input dimensionality. Central to this work is a novel feature selection method based on d-separation, a structural property of Bayesian networks that encodes conditional independence relationships.

The proposed approach introduces a count-based d-separation metric to quantify the relevance of variables to a target outcome, along with a thresholding scheme to balance feature selection robustness …

A Software-Defined Radio Testbed For Mimo-Ofdm Communications, Chaz G. Maschman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we implement a testbed for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems via GNU Radio. Specifically, we implement a configurable framework for the construction of MIMO-OFDM software-defined radio (SDR) systems as a GNU Radio module. The GNU Radio MIMO-OFDM module consists of multiple algorithmic blocks necessary for implementation of a MIMO-OFDM system. This includes a library for the generation of orthogonal or pseudo-random pilot sequences, amendments to the Schmidl-Cox protocol for MIMO synchronization, and the creation of click-and-drag GNU Radio blocks implementing the conversion of arbitrary data sent via external programs to MIMO-OFDM frames, the initial …

A Low-Power Mixed-Signal Potentiostat System-On-Chip With Integrated Dual-Slope Adc, Seth Mcrobert

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This thesis presents the design and characterization of a low-power mixed-signal potentiostat that was integrated with a 65 nm core in a SoC for low-power electrochemical sensing applications. The system integrates a low-noise transimpedance-based potentiostat front end with a 12-bit dual-slope analog-to-digital converter (ADC) for accurate current-to-digital conversion. The potentiostat core—comprising the control amplifier, current-mirror network, and transimpedance amplifier—consumes 38.2 µA from a 2.5 V supply (95.5 µW) and achieves an input-referred noise floor of 113 µVRMS over a 330 Hz bandwidth, while having an input current range from 1 nA to 20 µA and a noise-limited sensitivity of 56.4 …

Reinforcement Learning Based Security Schemes For Distributed Ai Systems, Ashan Chamath Gunawardena

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Distributed machine learning (DML) is a component of modern intelligent systems, enabling collaborative training across devices such as mobile clients, vehicles, and edge networks. However, the decentralized nature of these systems introduces vulnerabilities, particularly data poisoning attacks that compromise model integrity and degrade performance. Traditional defenses, such as statistical filtering, robust aggregation, and privacy-preserving techniques, often struggle to adapt to overwhelming adversaries or operate under strict privacy and real-time constraints. This dissertation proposes the use of reinforcement learning (RL) and deep reinforcement learning (DRL) based misbehavior detection schemes that dynamically identify poisoning attempts in distributed AI systems, including federated learning, …

Rapid State-Of-Health Estimation Of Batteries Using Machine Learning With Limited Eearly-Discharge Voltage Data, Mohammad Bakhtiari

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

The utilization of lithium-ion batteries has been rapidly expanding across diverse sectors, including electric transportation, stationary energy storage systems, and the built environment. Ensuring a high level of reliability in these applications is essential, as the performance and safety of such systems depend strongly on the accurate assessment of the battery’s State of Health (SOH). Conventional SOH estimation techniques—often based on complex electrochemical models or extensive laboratory testing—tend to require a large number of measurements, advanced instrumentation, and high computational cost. These factors make them impractical for large-scale deployment or real-time monitoring. This study introduces a simplified machine-learning-based approach for …

Study Of Ai Applications In Biomedical Data Acquisition, Communication, And Analysis: Cest Mri Acceleration And Ecg Transmissions, Adarsha Bhattarai

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation investigates the application of artificial intelligence in biomedical data acquisition, communication, and analysis to advance neurological research and to enable the early detection of cardiovascular conditions. Despite significant advances in imaging and physiological modalities, challenges persist. Imaging modalities, such as the chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) technique are challenged by a prolonged data acquisition time and high operational costs. In addition, physiological modalities such as electrocardiogram (ECG) sensors face constraints in providing uninterrupted signal monitoring which is crucial for the timely detection of premature cardiac abnormalities. The primary goal of this work is to …

Analysis Of Vision Transformers And Domain Adaptation In Long-Range Facial Recognition, Zachary Michael Swanson

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Atmospheric turbulence presents a significant barrier to long-range facial recognition, introducing severe geometric distortions and blur that degrade image quality. This thesis investigates deep learning approaches for mitigating these effects, with a focus on transformer based architectures and domain adaptation strategies.

An in-depth benchmarking study was performed using convolutional neural networks (CNNs) and vision transformers (ViTs) on the Husker BRIAR Research Collection from up to 500m (HBRC-500) face dataset. The results demonstrated that vision transformers, particularly hierarchical vision transformers like the shifted-window (Swin) transformer, outperform CNN-based models at long distances due to their ability to model global spatial relationships and …

Conversion Of Thermal Energy Stored In Conductive Concrete To Electricity With Thermoelectric Generators, Moustafa M. Al Adawi

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This paper presents a proof-of-concept experimental study on the use of conductive concrete as thermal energy storage and its conversion into electricity. The conductive concrete is heated to 100°C by supplying electricity, and the stored thermal energy is converted back into electricity using thermoelectric generators (TEGs). Measurement results demonstrate that the conductive concrete effectively stores thermal energy up to 100°C, and this energy can be successfully converted into electricity. The findings highlight the potential of conductive concrete as a reliable medium for thermal energy storage.

Advisor: Lim Nguyen

Physics Embedded Neural Network: A Novel Data-Free Numerical Method For Solving Computational Physics Problems, Pawan Gaire

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

A novel approach for solving partial differential equations (PDEs) using neural networks for scientific computing is introduced. The proposed approach, referred to as physics-embedded neural network (PENN), features a unique architecture that incorporates the PDE and boundary conditions information directly within the final fully-connected layer of the feed-forward neural network (NN). The key aspect of PENN is the parallel numerical embedding of a differential equation associated with physical problems within the activation function of the network’s final layer. This integration leads to a new class of computational solvers competitive with classical methods like the Finite Element Method (FEM) and capable …

Modeling Degradation In Li-Ion Batteries: Analyzing Single-Cell Degradation And Applying It To Customized Pack-Level, Mohannad Y. Alkhalil

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

The rapid expansion of lithium-ion (Li-ion) battery applications in areas such as electric vehicles (EVs), renewable energy storage, and portable electronics has drawn attention to the need for improving their performance, safety, and longevity. As Li-ion batteries become essential across technologies, understanding degradation mechanisms is critical for optimizing design and ensuring reliable operation. This work provides a detailed overview of modeling degradation in Li-ion batteries, focusing on single-cell behavior and its implications for pack-level performance.

The PyBaMM (Python Battery Mathematical Modeling) package, an open-source battery simulation tool written in Python, is used for single-cell simulations. Liionpack, another Python-based library, is …

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 …

Investigation Of Conductive Die-Top Thermal Capacitors During Short Circuit Operation Of Silicon Carbide Devices, Youssef Abotaleb

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Silicon carbide (SiC) power devices have garnered significant attention in recent years due to their superior thermal and electrical properties compared to traditional silicon devices. However, SiC power devices suffer from severe reliability issues arising from their mechanical properties. This is because the Young's modulus of SiC is about three times larger than that of silicon, which correspondingly raises the mechanical stresses acting on the bonding structure, often leading to device failure under power shock events.

Traditional packaging materials and designs tend to constrain SiC performance, as hot-spot temperature resulting from a power shock is one of the key factors …

Virtual Control: A Comparison Of Methods For Hand-Tracking Implementation, Nathan Roberts

Honors Program: Senior Projects (Public)

This thesis examines the design philosophy of modern virtual reality applications that utilize hand-tracking as a primary form of user input. The analysis presented hopes to provide ideas for future implementations of this technology so that more immersive experiences are developed. This analysis starts with the discussion of a modern example of successful hand-tracking implementation, then comparing that implementation to a recent senior design project. This comparison is primarily based on each experience’s ability to create interactivity and immediacy. Interactivity is the degree to which the user can quickly and reliably make changes to their virtual environment, while immediacy is …

Patterning Synthesis Of Lead Halide Perovskites Toward Photonic Application, S. M. Nayeem Arefin

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Lead halide perovskites (LHPs) are a fascinating class of photonic materials with the potential to revolutionize various optoelectronic applications. Their diverse crystal structures, ranging from 0D to 3D configurations, offer a unique combination of properties, including high tunability and ease of synthesis. However, their inherent instability and the difficulty of patterning them into sophisticated photonic structures using conventional methods present a significant hurdle to their widespread applications. This thesis addresses these challenges by proposing a novel synthesis method that combines soft lithography and self-assembly. By utilizing a patterned template with controlled wettability, precise manipulation of LHP crystal formation is achieved, …

Ultrashort Pulsed Laser Treatment Is Effective At Sterilizing Metal Surfaces For Planetary Protection, Kaleb Mcquillan

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

To prevent forward contamination from microbes aboard spacecraft intended for exploration of solar system bodies there is a need for effective sterilization methods. However, current techniques are both time-consuming and expensive. For example, dry heat sterilization requires removal from the assembly site and several days of treatment. Furthermore, some components such as optics and electronics are not compatible with current sterilization techniques. In this thesis, a novel femtosecond laser surface processing technique for the rapid sterilization of spacecraft hardware is reported. Femtosecond lasers produce extremely high photon fluxes (10²⁹ photons/s*cm², ~0.03 J/cm²) in extremely short …

Applying Circuit Theory To Describe Changes In Structural Landscape Connectivity In Response To Wildfire, Christian Ross Nielsen

School of Natural Resources: Dissertations, Theses, and Student Research

Understanding and conserving ecological connectivity is critical to the preservation of vulnerable landscapes. Circuit theory, in which landscapes are imagined as circuit boards with varying resistances to the flow of current, is being increasingly used to model spatially explicit connectivity of landscapes and to inform land management and conservation decision-making. Utilizing continuous, quantitative estimates of percent cover by five land cover functional groups to create a conductance surface, this study expanded upon an established application of circuit theory that used the open-source software Circuitscape to model species-agnostic, omnidirectional connectivity. This model was automated using Python to create time-series connectivity maps …

Integrated Multi-Omics Analysis Of Cerebrospinal Fluid In Postoperative Delirium, Bridget A. Tripp, Simon T. Dillon, Min Yuan, John M. Asara, Sarinnapha M. Vasunilashorn, Tamara G. Fong, Sharon K. Inouye, Long H. Ngo, Edward R. Marcantonio, Zhongcong Xie, Towia A. Libermann, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Preoperative risk biomarkers for delirium may aid in identifying high-risk patients and developing intervention therapies, which would minimize the health and economic burden of postoperative delirium. Previous studies have typically used single omics approaches to identify such biomarkers. Preoperative cerebrospinal fluid (CSF) from the Healthier Postoperative Recovery study of adults ≥ 63 years old undergoing elective major orthopedic surgery was used in a matched pair delirium case–no delirium control design. We performed metabolomics and lipidomics, which were combined with our previously reported proteomics results on the same samples. Differential expression, clustering, classification, and systems biology analyses were applied to individual …

Development And Evaluation Of An Expedited System For Creation Of Single Walled Carbon Nanotube Platforms, Ivon Acosta Ramirez, Omer Sadak, Wali Sohail, Xi Huang, Yongfeng Lu, Nicole M. Iverson

Department of Electrical and Computer Engineering: Faculty Publications

Single-walled carbon nanotubes (SWNT) have a strong and stable near-infrared (nIR) fluorescence that can be used to selectively detect target analytes, even at the single molecule level, through changes in either their fluorescence intensity or emission peak wavelength. SWNTs have been employed as NIR optical sensors for detecting a variety of analytes. However, high costs, long fabrication times, and poor distributions limit the current methods for immobilizing SWNT sensors on solid substrates. Recently, our group reported a protocol for SWNT immobilization with high fluorescence yield, longevity, fluorescence distribution, and sensor response, unfortunately this process takes 5 days to complete. Herein …

Growth And Simulation Of Dielectric-Metal Nanoheterostructured Thin Films By Ballistic Deposition, Shawn Wimer

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This thesis is divided into two related topics: the structural and chemical characterization of dielectric-metal nanoheterostructured thin films grown by glancing angle deposition (GLAD) and the results of the simulated growth of films and structures by GLAD with discrete-space and continuous-space Monte Carlo ballistic simulation.

Individual structures comprising films grown by GLAD were investigated by S/TEM and SEM imaging, electron diffraction, and chemical characterization and mapping by EDX. Different intermolecular interactions within and between different materials, including Si, Ag, Au, and ZrO₂, are linked to differences in the shapes of individual materials in heterostructures, the shape of heterostructures …

Electronic Properties Of Group-Iii Nitride Semiconductors And Device Structures Probed By Thz Optical Hall, Nerijus Armakavicius, Philipp Kühne, Alexis Papamichail, Hengfang Zhang, Sean Knight, Axel Persson, Vallery Stanishev, Jr-Tai Chen, Plamen Paskov, Mathias Schubert, Vanya Darakchieva

Department of Electrical and Computer Engineering: Faculty Publications

Group-III nitrides have transformed solid-state lighting and are strategically positioned to revolutionize high-power and high-frequency electronics. To drive this development forward, a deep understanding of fundamental material properties, such as charge carrier behavior, is essential and can also unveil new and unforeseen applications. This underscores the necessity for novel characterization tools to study group-III nitride materials and devices. The optical Hall effect (OHE) emerges as a contactless method for exploring the transport and electronic properties of semiconductor materials, simultaneously offering insights into their dielectric function. This nondestructive technique employs spectroscopic ellipsometry at long wavelengths in the presence of a magnetic …

Scalability And Connectivity Challenges For The Future Of Digital Radio Communication, Christopher Bayliss

Honors Program: Senior Projects (Public)

This thesis explores future challenges in digital radio communication, particularly focusing on scalability and connectivity issues that could impede technological advancements. With the increasing production of digital technology and reliance on radio frequencies, there is a need for innovative solutions to overcome limitations in spectrum availability, interference management, and bandwidth constraints. This work evaluates current modulation techniques, spectrum allocation strategies, and advanced communication technologies such as cognitive radio systems and reconfigurable intelligent surfaces. Through a comprehensive literature review and analysis, this thesis identifies promising developments, including dynamic spectrum sharing and symbiotic radio systems, that could significantly enhance spectrum efficiency and …

Chiroptical Second-Harmonic Tyndall Scattering From Silicon Nanohelices, Ben J. Olohan, Emilija Petronijevic, Ufuk Kilic, Shawn Wimer, Matthew Hilfiker, Mathias Schubert, Christos Argyropoulos, Eva Schubert, Samuel R. Clowes, G. Dan Pantoş, David L. Andrews, Ventsislav K. Valev

Department of Electrical and Computer Engineering: Faculty Publications

Chirality is omnipresent in the living world. As biomimetic nanotechnology and self-assembly advance, they too need chirality. Accordingly, there is a pressing need to develop general methods to characterize chiral building blocks at the nanoscale in liquids such as water-the medium of life. Here, we demonstrate the chiroptical second-harmonic Tyndall scattering effect. The effect was observed in Si nanohelices, an example of a high-refractive-index dielectric nanomaterial. For three wavelengths of illumination, we observe a clear difference in the second-harmonic scattered light that depends on the chirality of the nanohelices and the handedness of circularly polarized light. Importantly, we provide a …

Star-Based Reachability Analysis Of Binary Neural Networks On Continuous Input, Mykhailo Ivashchenko

School of Computing: Dissertations, Theses, and Student Research

Deep Neural Networks (DNNs) have become a popular instrument for solving various real-world problems. DNNs’ sophisticated structure allows them to learn complex representations and features. However, architecture specifics and floating-point number usage result in increased computational operations complexity. For this reason, a more lightweight type of neural networks is widely used when it comes to edge devices, such as microcomputers or microcontrollers – Binary Neural Networks (BNNs). Like other DNNs, BNNs are vulnerable to adversarial attacks; even a small perturbation to the input set may lead to an errant output. Unfortunately, only a few approaches have been proposed for verifying …

Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The …

Development Of A Multi-Use Modular Microfluidic Platform Using 3d Printing, Carson Emeigh

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Microfluidic lab-on-a-chip (LoC) technology has driven numerous innovations due to their ability to perform laboratory-scale experiments on a single chip using microchannels. Although LoC technology has been innovative, it still suffers from limitations related to its fabrication and design flexibility. Typical LoC fabrication, with photolithography, is time consuming, expensive, and inflexible. To overcome the limitations of LoC devices, modular microfluidic platforms have been developed where multiple microfluidic modules, each with a specific function or group of functions, can be combined on a single platform. Modular microfluidics have overcome some of the limitations of LoC devices, but currently, their fabrication is …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …

Design And Optimization Of A Novel Monolithic Spring For High-Frequency Press-Pack Sic Fet Modules, Bogac Canbaz

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Silicon Carbide (SiC) Field-Effect Transistor (FET) modules lead the way in power electronics, being superior in efficiency and robustness for high-frequency applications. The shift towards SiC from traditional silicon (Si)-based devices is driven by its superior thermal conductivity, higher electric field strength, and operational efficiency at elevated temperatures. These features are critical for the development of next-generation, grid-oriented power converters aimed at enhancing the reliability and sustainability of power systems. This research focuses on high-frequency press-pack (HFPP) SiC FET modules, addressing the primary challenge of miniaturizing SiC FET dies without compromising performance, through an innovative press-contact design essential for increased …

An Investigation Of Information Structures In Dna, Joel Mohrmann

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The information-containing nature of the DNA molecule has been long known and observed. One technique for quantifying the relationships existing within the information contained in DNA sequences is an entity from information theory known as the average mutual information (AMI) profile. This investigation sought to use principally the AMI profile along with a few other metrics to explore the structure of the information contained in DNA sequences.

Treating DNA sequences as an information source, several computational methods were employed to model their information structure. Maximum likelihood and maximum a posteriori estimators were used to predict missing bases in DNA sequences. …

Surface Chemistry Of Femtosecond Laser Processed Surfaces, Graham Kaufman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Micromachining and surface functionalization with femtosecond lasers is a rapidly developing technology in the field of materials and interfacial sciences due to its flexibility towards materials, tunability in surface features, and prospects for scalability. Many interfacial applications have been shown to be enhanced with femtosecond laser-induced surface texturing including two-phase heat transfer, antimicrobial properties, electrochemical systems and more. However, without ideal surface chemistry, the enhancements cannot be optimized for a given application. Surfaces functionalized by femtosecond lasers tend to have transient surface chemistries when exposed to the atmosphere, changing important interfacial properties like the interaction of the solid surfaces and …

Controlling The Broadband Enhanced Light Chirality With L-Shaped Dielectric Metamaterials, Ufuk Kilic, Matthew Hilfiker, Shawn Wimer, Alexander Ruder, Eva Schubert, Mathias Schubert, Christos Argyropoulos

Department of Electrical and Computer Engineering: Faculty Publications

The inherently weak chiroptical responses of natural materials limit their usage for controlling and enhancing chiral light-matter interactions. Recently, several nanostructures with subwavelength scale dimensions were demonstrated, mainly due to the advent of nanofabrication technologies, as a potential alternative to efficiently enhance chirality. However, the intrinsic lossy nature of metals and the inherent narrowband response of dielectric planar thin films or metasurface structures pose severe limitations toward the practical realization of broadband and tailorable chiral systems. Here, we tackle these problems by designing all-dielectric silicon-based L-shaped optical metamaterials based on tilted nanopillars that exhibit broadband and enhanced chiroptical response in …