Digital Commons Network^™

Effects Of Spent Coffee Grounds On Improvement Of Resistive Switching Characteristics In Natural Rubber-Based Memory, Muhammad Awais, Nadras Othman, Mohamad Danial Shafiq, Feng Zhao, Kuan Yew Cheong

Electrical and Computer Engineering Faculty Research & Creative Works

The recent upsurge in environmental awareness provokes the widespread usage of green materials in sustainable electronic applications. Herein, the effects of spent coffee grounds (SCGs) on natural rubber (NR)-based resistive switching (RS) memory are systematically investigated. This study presents the fabrication of a metal-insulator-metal (MIM) structure using NR incorporated with SCGs (0 to 8 wt.%) as a memristive layer and sandwiched between electrodes. A significant improvement in the ON/OFF ratio from 10⁴ for pure NR to 10⁷, read memory window increased from 2.03 to 2.45 V with improved stability even after 130 cycles of switching is achieved …

Improving Particle-Phase Nitrate Measurement In Pm2.5 Filter Sampling: Evaluation Of A Denuder–Nylon Filter Modification In The Spartan Network, Wenyu Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Accurate measurement of PM_2.5 composition is of global importance. Evaporation-induced mass loss introduces potential bias in filter-based PM_2.5 measurements, with ammonium nitrate volatilization from Teflon filters being a major contributor to negative mass artifacts. Previous studies have demonstrated that using an acid gas denuder in combination with nylon filters can help recover the nitrate mass. This study evaluates design modifications to the AirPhoton sampling station setup within the globally distributed Surface Particulate Matter Network (SPARTAN) incorporating an additional acid gas denuder upstream and a nylon filter downstream of the existing Teflon filter.

Two co-located AirPhoton Sampling stations were …

Safe Real-Time Obstacle Detection And Navigation Using Cbf–Clf And Cbf–Pid Control, Nicolas M. Hernandez

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traditional robotic navigation pipelines typically follow a three stage architecture: obstacle detection, path planning, and low-level control for trajectory tracking. While effective in static environments, these methods often introduce latency and lack formal guarantees of safety in dynamic or unplanned for scenarios. Our work addresses these limitations by developing a real-time controller grounded in Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs), unified through a Quadratic Program (QP). We first investigate a hybrid CBF-PID-QP controller on a 1/10 scale car, where the CBF serves as a real-time safety filter, modifying the PID output to prevent constraint violations. While this …

Characterizing And Modeling The Nonlinear Behavior Of Additively Manufactured Trapped-Powder Dampers, Jonathan Knight Black

Theses and Dissertations

Laser Powder Bed Fusion (LPBF) can be used to create metal parts with pockets of retained, unfused powder that serve as mechanical dampers. These trapped-powder dampers show promise for reducing the amplitude of vibrations at resonance by orders of magnitude. However, little is currently understood about the nonlinearity and repeatability of trapped-powder dampers, meaning that the design process currently consists of expensive trial-and-error prototyping and iteration. The present work contributes a corpus of experimental measurements for rectangular beams with trapped-powder dampers of various dimensions and locations. Preliminary testing revealed the presence of a memory effect which we hypothesize to be …

Investigating Radiation Induced Rowhammer And Retention Failures In Dram, Tyler Ricks

Theses and Dissertations

It is desirable for DRAM devices to be used in harsh radiation environments. Exposure to radiation causes DRAM cells to lose their retention time as their ability to store charge effectively declines. Exposure also worsens the effect of disturbance that causes neighboring cells to flip when a row is opened multiple times: an effect known as the Row Hammer Effect. This thesis evaluates the impact of radiation-induced memory cell degradation by comparing memory cell's retention time and their resilience to the row hammer vulnerability. Three generations of DRAM were placed under a neutron radiation beam. Sections of the irradiated devices …

Understanding And Evaluating Genomic Language Models, Aadit Kapoor

Master's Theses

Large Language Models (LLMs) have shown remarkable capabilities in interpreting complex patterns across various domains, yet their application to genomic data remains limited. We see great potential in leveraging LLMs for vital biological tasks, such as predicting transcription factor binding sites and identifying antibiotic-resistant genes. This emergent behavior positions LLMs as powerful tools for enhancing our understanding of intricate biological language. LLMs trained specifically on genomic data, such as DNA sequences, operate distinctly compared to those trained on natural language. This difference is evident not only in the architectural landscape of the models but also in the methodologies employed by …

Integrated Algorithm And Hardware Design For Hybrid Neuromorphic Systems, James Seekings, Mahsa Ardakani, Peyton Chandarana, Arshia Eslami, Mohammadreza Mohammadi, Ramtin Zand

Faculty Publications

This paper investigates the combined potential of neuromorphic and edge computing to develop a flexible machine learning (ML) system designed for processing data from dynamic vision sensors. We build and train hybrid models that integrate spiking neural networks (SNNs) and artificial neural networks (ANNs) using the PyTorch and Lava frameworks. We explore the effects of quantization on ANN models to assess its impact on both accuracy and energy efficiency. Additionally, we address the challenges of deploying hybrid models on hardware by implementing individual components on specific edge platforms. We also propose an accumulator circuit to bridge the spiking and non-spiking …

Digital Trading Platform Selection Under Neutrosophic Numbers And Multi-Criteria Decision-Making Methodology: An Illustrative Example, Eman Sayed, Karam M. Sallam, Ibrahim Alrashdi

Neutrosophic Systems with Applications

Uncertainty, vagueness, and incomplete information are pervasive in real-world decision-making scenarios, particularly in multi-criteria decision-making (MCDM) contexts involving expert judgments. To address these challenges, this study introduces a comprehensive decision-making framework that integrates Triangular Neutrosophic Numbers (TNNs) with the Weighted Aggregated Sum Product Assessment (WASPAS) method. The framework begins by capturing expert evaluations using TNNs, which effectively represent the degrees of truth, indeterminacy, and falsity inherent in subjective assessments. These evaluations are then transformed into crisp values using a novel score function that preserves the embedded uncertainty. The resulting decision matrices are aggregated into a unified structure to ensure consistency …

Land8fire: A Complete Study On Wildfire Segmentation Through Comprehensive Review, Human-Annotated Multispectral Dataset, And Extensive Benchmarking, Anh Tran, Minh Tran, Esteban Marti, Jackson Cothren, Chase Rainwater, Sandra Eksioglu, Ngan Le

Electrical Engineering and Computer Science Faculty Publications and Presentations

Early and accurate wildfire detection is critical for minimizing environmental damage and ensuring a timely response. However, existing satellite-based wildfire datasets suffer from limitations such as coarse ground truth, poor spectral coverage, and class imbalance, which hinder progress in developing robust segmentation models. In this paper, we introduce Land8Fire, a new large-scale wildfire segmentation dataset composed of over 20,000 multispectral image patches derived from Landsat 8 and manually annotated for high-quality fire masks. Building on the ActiveFire dataset, Land8Fire improves ground truth reliability and offers predefined splits for consistent benchmarking. We evaluate a range of state-of-the-art convolutional and transformer-based models, …

Compact Heterogeneous Architectures And Algorithmic Methods For Enhanced Real-Time Digital True Time Delay Beamforming And Radar Applications, Nathan Lynn Burnett

Theses and Dissertations

Modern radar and signal processing systems require efficient computational architectures to handle increasing data rates while still being able to maintain dynamic configurability and complex tasks. This thesis presents and explores hardware and algorithmic approaches addressing these demands across several different applications. First, a low-cost tracking platform and architecture for unmanned aerial vehicles (UAVs) is developed, which provides detection and tracking capabilities, compliant with new FAA remote ID regulations. Second, a GPU-FPGA based digital true time delay beamformer is implemented to achieve real-time wideband radio frequency interference (RFI) mitigation. Specifically this beamformer explores weight calculation and calibration through particle swarm …

Versatile Waveform Generation And Clocking Techniques For Rfsoc-Based Digital Designs, Michael David Jones

Theses and Dissertations

Within an ever-evolving radio-frequency (RF) environment, designers are required to adapt systems to increasingly constricted parameters. The available tools continually grow to match this need, but so does the complexity in using them. The radio-frequency system-on-chip (RFSoC) is an innovation that combines a field-programmable gate array (FPGA) with an integrated RF chain. Designing with an RFSoC allows for high-precision data transmission, sampling, and processing, but it can be difficult and time-consuming to develop specialized circuits. The open-source CASPER project aims to provide a library of abstracted block-design components to simplify the design process. An arbitrary waveform generator (AWG) is created …

Accelerating Gnn Inference On Multi-Core Systems, Binglin Ji

McKelvey School of Engineering Graduate Student Theses & Dissertations

Graph Neural Networks (GNNs) are becoming increasingly popular, with their applications expanding across diverse domains. As the scale of graph data continues to grow, including larger numbers of nodes, edges, and higher embedding dimensions, standardized libraries such as DGL and PyG have been developed to facilitate GNN computation. However, with the rapid increase in the number of processor cores and the evolution of multi-core architectures, these libraries often show poor scalability and fail to execute GNN inference efficiently on the latest multi-core systems, particularly those with upwards of a hundred cores. To address this limitation, we present FGI, a Fast …

Development And Optimization Of Gradient Pore Structured Porous Ceramics: Modeling, Properties, And Potential For Industrial Production In Thermal Insulation Engineering, Gang Qi, Minghui Li, Ruoyu Chen, Haichuan Wang, Haiming Wen, Yi Ding, Xiaoyu Xia, Dixin Yan, Can Chen, Saisai Li

Materials Science and Engineering Faculty Research & Creative Works

This study prepared gradient pore structure ceramics from silica fume through direct foaming. The rheological behavior of the slurry was improved by varying the solids content. Physical and mathematical models were developed to describe the longitudinal movement of foam in the ceramic slurry and the mechanism of gradient pore formation. These models were used to predict the pore sizes at different heights within the ceramic. Insulation and mechanical properties were enhanced by optimizing the gradient pore structure. The gradient pore structure resulted in significant directional differences in specimen properties. Additionally, suitable sintering-temperatures for gradient pore structure ceramics are discussed. The …

Development Of Numerical Tools And Performance Metrics For Analysis Of Optical Particle Counters, Doug Webb

Theses and Dissertations

Monitoring air quality is essential for understanding and mitigating the health impacts of airborne particulate matter (PM), which is linked to respiratory and cardiovascular disease. Optical particle counters (OPCs) are widely used for air quality monitoring, yet their precision and accuracy remain uncertain due to inconsistent performance evaluations. In this thesis, performance metrics are developed that can be used to assess the accuracy of OPCs in measuring PM concentrations and size distributions. Computational fluid dynamics (CFD) simulations are employed to analyze the behavior of particle-laden air streams through representative OPC models. The impact of design parameters is quantified using newly …

Demystifying The Discharge Coefficient For Flow Over Thin Weirs And Sills, Joseph E. Pugh, Subhas Karan Venayagamoorthy, Timothy K. Gates

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

A revised derivation of the discharge coefficient for flows over thin weirs and sills in the limits of wall overflow to a free overfall is given. Using dimensional analysis, we show that the discharge coefficient, (Formula presented), in the classical weir-discharge equation is best understood as a weir Froude number, (Formula presented), which accounts for the combined effects of inertia, contraction and viscous energy losses within the flow field. A comprehensive set of experimental data from historical studies is complimented by new data from the authors, featuring both laboratory flume experiments and three-dimensional numerical simulations of weir flows. Synthesis of …

Tracing Tremor: From Upper-Limb Neuromusculoskeletal Dynamics To Movement Signatures In Essential Tremor, Landon J. Beutler

Theses and Dissertations

Tremor is a common neurological condition that significantly impairs the quality of life for millions. Despite this prevalence, the underlying mechanisms of its propagation remain poorly understood, and current treatment options often rely on trial-and-error methods. Moreover, the most common type, Essential Tremor (ET), presents a unique challenge due to its heterogeneity--patients exhibit a wide range of symptoms, severities, and responses to treatment. This thesis primarily advances tremor understanding through computational modeling, with a secondary focus on data-driven subtyping of ET via cluster analysis. These parallel paths aim to improve both mechanistic insight and clinical classification. Tremor propagation refers to …

Development Of Low-Cost Small-Batch Flibe Filtration, And A Comparison Of Uranium Tetrafluoride And Ionic Oxygen Oxidation In Flibe, Jacob D. Christensen

Theses and Dissertations

Low-cost benchtop-scale molten fluoride salt cleaning was investigated in FLiBe (LiF-BeF2), focusing on electrochemical cleaning and filtration. FLiBe filtration was demonstrated using both pressurized and open filtration systems. Copper and 400 Monel meshes were effective and reusable. Wetting appears to be the primary obstacle to FLiBe filtration. Oxygen oxidation behavior in FLiBe was examined using cyclic voltammetry (CV) and cyclic square wave voltammetry (CSWV) techniques. Standard addition height measurement was used to determine electrode surface area. Results support a single-step 2-electron process, matching observations in literature. Pt electrodes may be prone to oxidative side reactions, although more investigation is required. …

Seasonal Variation In Modulus Of Cement-Treated Base Layers And Untreated Base Layers In Utah, Mason Robert Kessler Millard

Theses and Dissertations

The objective of this research was to compare the stiffness of cement-treated base (CTB) layers and untreated base course (UTBC) layers in a cold region through a typical year. The scope of work included testing of three residential pavement segments comprising CTB layers and two comparable pavement segments comprising UTBC layers in northern Utah. Design thicknesses were verified through drilling and dynamic cone penetrometer testing in September 2024. Following 3 to 15 years of service, the sites were evaluated using portable falling-weight deflectometer (PFWD) testing in May 2024, July 2024, September 2024, November 2024, January 2025, and March 2025. After …

Emergence Of Norms In The Presence Of Social Network Structure In A Stochastic Evolutionary Game Theory Model, Parker Foresman

Dissertations and Theses

In their 2000 paper, The Emergence of Classes in a Multi-Agent Bargaining Model, Axtell, Epstein, and Young introduced an agent-based bargaining model to study how social norms can emerge and persist from the decentralized, asynchronous interactions of individual agents in the presence of noise, even when these agents have no predefined preferences or advantages. This thesis extends their model by incorporating structured interaction networks, allowing us to investigate how the topology of agent interactions influences long-run dynamics and norm formation. Using a custom simulation package built in the Julia programming language, we replicate the original results under a complete …

Iraqi’S Car License Plate Recognition Based On Deep Learning, Mushreq Abdulhussain Shuriji, Husam Al-Behadili, Hadel A. Hussain

Iraqi Journal for Computer Science and Mathematics

Vehicle license plate recognition is essential due to the rising number of operational cars, which leads to an increasing difficulty of this task even for humans. Systems for car license recognition normally consist of two branch systems, namely, license plate recognition and license plate detection. The aim of the detection part is to pinpoint the car and the position of its license plate, while the objective of the recognition part is to recognize characters on that plate. In this work, the emphasis is on Arabic car license plates. In this category of plates, there are three lines containing numerals and …

Rotor Interaction Aerodynamics: Influence Of Phase And Spacing On Wake And Pressure Behavior, Nathan D. Welker

Theses and Dissertations

This dissertation explores the aerodynamic behavior and interactions in the flow-fields of dual rotor systems. The experiments used Particle Image Velocimetry (PIV) combined with pressure and force measurements to characterize the flow with an emphasis on side-by-side rotor flows at small separation distances. This work is separated into six main chapters: first, the topic is introduced with a thorough literature review in Chapter 1, the methodology and details of the experiments are discussed in detail in Chapter 2; the effects of phase offset on dual-rotor rotor flows is explored in Chapter 3; the influence of separation distance on the side-by-side …

Solvent- And Binder-Free Additive Manufacturing Of Polymer-Derived Ceramics: Rheological Tuning And Structural Performance, Laxmi Sai Viswanadha, Jeremy Watts, Mohammad Naraghi

Materials Science and Engineering Faculty Research & Creative Works

Silicon carbide (SiC) ceramic matrix composites are widely used in aerospace applications due to their high strength, heat resistance, and corrosion resistance. However, traditional machining methods make it challenging to fabricate complex shapes. This study presents a solvent-free and binder-free direct ink writing (DIW) method for producing SiC/SiOC composites using polycarbosilane SMP-10, a preceramic polymer that acts as both the ceramic precursor and the liquid phase, thereby eliminating the need for volatile solvents and sacrificial binders. By adjusting the SiC content, printable ink formulations were developed, and their flow properties were analyzed. The influence of geometric factors, such as inter-wall …

Coding For Nonstandard Channels: A Capacity-Oriented Approach, J Daniel Harman

Theses and Dissertations

This work addresses the issue of coding for non-standard channel models with an emphasis on capacity-oriented channel analysis and system design. The first channel studied is the Wyner wiretap channel. Channel sounding results were obtained to calculate the capacity for the multi-antenna case of the Wyner wiretap channel to ascertain the potential for secure communication via secrecy coding. The second channel studied is an asymmetric binary crossover erasure channel (ABCEC) with a short-blocklength constraint. The capacity for this channel was derived, and linear codes were chosen and tested. Another study was conducted on the ABCEC within a degraded wiretap channel …

Predicting The Yield Strength Of Aluminum Alloys Based On Composition, Clinton K. Waite

Theses and Dissertations

This work describes a model to predict the yield strength of aluminum alloys, in either an annealed or T6 (peak aged) state, based solely on its composition. This is accomplished through the analyses of strengthening mechanisms common to aluminum, of which a novel semi-empirical model to predict precipitation strengthening is discussed. Solid solution strengthening and grain boundary strengthening are more simplistically considered but with significant accuracy. It is shown that by combining the strength contributions of each strengthening mechanism, the overall yield strength can be predicted by its composition in any of the 1xxx-7xxx series alloys. This allows the model …

Volumetric Imaging Of Cellular Dynamics Using Light-Sheet Microscopy: From Subcellular Structures To Whole Organisms, Md Nasful Huda Prince

Optical Science and Engineering ETDs

Advancing biomedical imaging requires platforms that combine high-resolution, speed, and stability across biological scales. This dissertation presents three innovations designed to address limitations of conventional light-sheet and oblique plane imaging. First, we introduce Reflected Inline Detection in Epi-Oblique Plane Microscopy (RIDE-OPM), a compact and drift-resistant system that eliminates a tertiary detection path while maintaining alignment flexibility, enabling robust long-term live imaging. Second, we present a high-speed Axially Swept Light-Sheet Microscopy (ASLM) platform for cleared tissues, using dual foci and synchronized sweeping to achieve isotropic sub-micron resolution at up to 40 frames-per-second, a fourfold improvement over standard ASLM. Integrated with a …

Recent Advances In Developing Cell-Free Protein Synthesis Biosensors For Medical Diagnostics And Environmental Monitoring, Tyler P. Green, Joseph P. Talley, Bradley Charles Bundy

Faculty Publications

Cell-free biosensors harness the selectivity of cellular machinery without living cells’ constraints, offering advantages in environmental monitoring, medical diagnostics, and biotechnological applications. This review examines recent advances in cell-free biosensor development, highlighting their ability to detect diverse analytes including heavy metals, organic pollutants, pathogens, and clinical biomarkers with high sensitivity and specificity. We analyze technological innovations in cell-free protein synthesis optimization, preservation strategies, and field deployment methods that have enhanced sensitivity, and practical applicability. The integration of synthetic biology approaches has enabled complex signal processing, multiplexed detection, and novel sensor designs including riboswitches, split reporter systems, and metabolic sensing modules. …

International Comparison Of Weather And Emission Predictive Building Control, Christian Hepf, Ben Gottkehaskamp, Clayton Miller, Thomas Auer

Research Collection College of Integrative Studies

Building operational energy alone accounts for 28% of global carbon emissions. A sustainable building operation promises enormous savings, especially under the increasing concern of climate change and the rising trends of the digitalization and electrification of buildings. Intelligent control strategies play a crucial role in building systems and electrical energy grids to reach the EU goal of carbon neutrality in 2050 and to manage the rising availability of regenerative energy. This study aims to prove that one can create energy and emission savings with simple weather and emission predictive control (WEPC). Furthermore, this should prove that the simplicity of this …

Developing An Integrated Risk Assessment Framework To Quantify The Resilience Of Critical Railway Infrastructure: Characterization Of Risks And Hazards To The U.S. Rail Network Through Empirical Data And Past Events, Haizhong Wang, Brian M. Staes, Benyamin Ghoreishi

Mineta Transportation Institute

To improve understanding of the impact of natural hazards on the U.S. railway system, this project developed a comprehensive, geospatially precise dataset that maps historical hazard events to specific rail segments. The project provides insight into when, where, and how much damage natural hazards have inflicted on rail infrastructure across the country. While a rail-specific hazard database did not previously exist, this research combines data from the Geological Survey (USGS) Flood Events Database, Hydrologic Unit Codes (HUC), the National Centers for Environmental Information (NCEI) from the National Oceanic and Atmospheric Administration (NOAA), and the National Weather Service (NWS) forecast zones. …

Mae Enewsbrief Apr- June 2025, Department Of Mechanical And Aerospace Engineering, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

Predicting Miner Localization In Underground Mine Emergencies Using A Hybrid Cnn-Lstm Model With Data From Delay-Tolerant Network Databases, Patrick Nonguin, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mining environments are highly hazardous, often prone to gas explosions, cave-ins, and fires that may trap miners during emergencies. The accurate, real-time localization of miners is vital for effective self-escape and rescue operations. Although the Mine Improvement and New Emergency Response (MINER) Act of 2006 mandates communication and tracking systems, most current solutions rely on low-power devices and line-of-sight methods that are ineffective in GPS-denied, dynamic subsurface conditions. Delay-Tolerant Networking (DTN) has emerged as a promising alternative by supporting message relay through intermittent links. In this work, we propose a deep learning framework that combines Convolutional Neural Networks (CNNs) …