Digital Commons Network^™

Simulation- And Machine Learning-Based Methods For Inland Waterway Operation And Maintenance Decision-Making, Maryam Aghamohammadghasem

Graduate Theses and Dissertations

The U.S. inland waterway transportation system (IWTS) is an essential part of the country's multimodal freight transportation network. In addition to seasonal droughts and floods, the operations of the IWTS may be disrupted by random malfunctions and scheduled maintenance of its critical components. Among these critical components, locks play a key role in the operation of navigable inland waterways, and lock-induced disruptions to the supply chains of related industries, such as agriculture and manufacturing, often result in significant economic losses. To assess the performance of the U.S. IWTS, we develop a PyNetLogo simulation tool to capture the movements and delays …

Trauma Network Design Considering Patient Safety And Cost., Lin Lin

Electronic Theses and Dissertations

Trauma, as the leading cause of mortality and morbidity for those under the age of 45 in the US, incurs trillions in annual economic costs. The time-sensitive nature of trauma treatment necessitates an effective, coordinated regional trauma system to optimize patient safety. However, the financial burden associated with trauma care, especially due to low-insured population, presents a significant challenge to the financial health of trauma centers (TCs). To address critical challenges in this domain and provide much-needed insights to trauma decision-makers regarding their trauma system cost, network design, and subsidy policy, this dissertation proposes 3 contributions. First, we introduce an …

Analysis On Plasma Propulsion Thruster Material Reconfiguration For Thrust Stabilization, Chinedumu Chidiebere Okafo

Mechanical & Aerospace Engineering Theses & Dissertations

Rocket propulsion has been a primary focus for scientific and technical advancement supporting space exploration. For long-duration, low-thrust space missions, propulsion systems designed with plasma energy as the primary source for generating thrust are of high interest. Plasma energy, like electric propulsion, involves the excited state of ionized atoms, where the ionized particles are separated and then act as a propellant to push a spacecraft in the intended direction for flight. Although more energy efficient compared to traditional rocket systems, plasma propulsion has the deficiency of consistent erosion of the metallic containment substrate, as plasma is being generated and released …

Input Structure Based Optimization For Privacy Preserving Ai Systems, Feng Yizhou

Electrical & Computer Engineering Theses & Dissertations

As Artificial Intelligence (AI) systems become increasingly integrated into critical domains, ensuring privacy-preserving model design and system deployment has become a pressing priority. Safeguarding both sensitive user data and proprietary model parameters is critical throughout the AI model and system, from data acquisition and pre-processing to model inference and deployment. However, existing privacy-preserving frameworks face several limitations, including fragmented data ownership, incomplete protection across system stages, substantial computational overhead, and poor scalability to modern architectures such as large language models. This dissertation explores a unifying optimization strategy centered on input structure design to address these challenges. The core idea is …

Failure Study Of Silicon Gated Field Emitter Arrays: Experiment And Simulation, Rushmita Bhattacharjee

Boise State University Theses and Dissertations

Silicon-based Gated Field Emitter Arrays (Si-GFEAs) are among the most well-developed field emitters. They are being actively explored for vacuum transistors and microwave vacuum electron devices due to their high-frequency performance, radiation resistance, and thermal stability up to 400 °C. However, their long-term reliability is limited by sudden failure events, resulting in cathodic vacuum arcs. This dissertation presents a combined experimental and simulation-based investigation into arc initiation mechanisms in Si-GFEAs. Different device arrays were tested under normal operation in vacuum at 10^-7 Torr with gate voltages of 50-70 V and emission currents from tens of nA to tens of µA. …

From Waste To Solution: Modeling And Characterization Of Grape Seed Bio-Waste For Phosphate Removal From Wastewater, Abeer Al-Bsoul, Zakaria Al-Qodah, Muhammad Tawalbeh, Khalid Bani-Melhem, Khalideh Al Bkoor Alrawashdeh, Mohammad Hailat, Ahmed A. Al-Taani, Eid Gul

All Works

In this study, particles of ground grape seeds were utilized to adsorb phosphate ions from a prepared solution, aiming to reduce phosphate concentration. Through a series of adsorption experiments, the effects of the adsorbent concentration, initial phosphate ion concentration, temperature, and pH on the phosphate ion uptake were studied. The removal efficiency of the phosphate ion decreased from 77 to 61% as a 25 to 45 °C increment in temperature was observed, which indicated the exothermicity in the adsorption process. The phosphate ion movement onto the adsorbent surface that exhibited the highest uptake value favored a neutral reaction environment with …

Mathematical Modeling Of Effects Of Tumor Location On Lung Function., Lamargaret Temukisa Johnson

Master of Engineering Theses

Lung cancer has the highest rates of incidence and mortality of all cancers. Most lung cancer tumors are Non-Small Cell Lung Cancer (NSCLC). NSCLC patients with lesions in the upper lobes are found to have better prognosis compared to those with lesions in the middle and lower lobes. Previous studies have suggested various causes for this discrepancy at both the organ-scale and tissue-scale. To model NSCLC growth in different locations within the lung, an organ scale lung model and tissue scale tumor model were coupled through the tissue pressure, and oxygen and carbon dioxide partial pressures. The coupling was used …

Internet Of Things And Modern Digital Evidence Collection, Muhammad T. Haider

Student Theses

The ever-evolving landscape of technology and its innovations are populating our houses, streets and all kinds of industries. The use of smart devices is booming from most developed nations to underdeveloped countries. The complications which come with the use of the Internet of Things has been an active discussion for the past many years. If we look around in a room of 30 people, we will most likely find double the amount of IoT devices than the people in that room. All of those devices are connected to the Internet, and are communicating with data servers across the world. The …

Low-Power Hardware-Based Real-Time Cervical Spine Localization Via Image Processing, Patricia Angela R. Abu, Chao-Shin Liu, Sung-Hsin Tsai, Po Lin Huang, Hong-Kai Wang, Shih Wei Chung, Chiung-An Chen, Shih-Lun Chen, Sze-Teng Liong, Tsung-Yi Chen

Department of Information Systems & Computer Science Faculty Publications

With the growing prevalence of cervical spine degeneration in the aging population, there is an urgent need for accurate and real-time cervical image analysis to assist in preliminary evaluations during neurosurgical outpatient visits. This study suggests a hard-ware-based real-time cervical spine localization system that uses image preprocessing algorithms to address this need. The system can quickly finish image enhancement and greatly speed up the localization process by turning preprocessing steps like median filtering and binarization into hardware modules. With a power consumption as low as 4.859 mW, the proposed hardware-based median filter demonstrates over 60% reduction in power and 35% …

Development Of A Wearable Biosensor For Cortisol Detection In Human Sweat Utilizing Pani/Peo Polymer Blend And Nitrogen-Doped Graphene Quantum Dots, Cesar Sanchez

Theses and Dissertations

Since the development of the first biosensor in 1962, the evolution of commercially available wearable biosensors has been driven by an increasing consumer interest in real-time health tracking. However, challenges related to sensor sensitivity and cost have hindered progress. Deploying a novel approach, the biosensor integrates a blend of Polyaniline (PANi) and Polyethylene Oxide (PEO) along with Nitrogen-doped Graphene Quantum Dots (N-GQDs) to enhance sensitivity and electroactivity, crucial for cortisol detection. To optimize performance, three distinct synthesis methods for N-GQDs; hydrothermal, microwave, and hot plate synthesis were compared employing a bottom-up approach utilizing citric acid (CA) as the primary reactant …

Low-Dimensional Learning For Remaining Useful Life Prediction Of Batteries Operating Under Various Environments, Rodrigo Benavides

Theses and Dissertations

In reliability, we typically define the standard operating conditions under which a component operates. However, the differences in battery operating conditions cause variability in the degradation patterns of identically manufactured batteries, rendering remaining useful life prediction a major challenge. To aid this task, several sensors are utilized to monitor battery state-of-health. However, traditional prognostics algorithms do not scale well to the volume of data generated. Furthermore, several authors do not explicitly consider operating environments in their prediction models. Therefore, we present a high-dimensional data analytics framework that integrates operating environment information for battery prognostics. This framework combines Multilinear Principal Component …

Interdigitated Gear-Shaped Screen-Printed Electrode Using G-Pani Ink For Sensitive Electrochemical Detection Of Stress Related Hormones Dopamine And Cortisol, Pritu Parna Sarkar

Theses and Dissertations

This research introduces a novel interdigitated gear-shaped graphene-based electrochemical biosensor for the simultaneous detection of dopamine (DA) and cortisol. Modified with graphene–polyaniline (G–PANI) conductive ink, the sensor increased active surface area—94.52% and 57% higher than Metrohm DropSens 110 and circular printed sensors, respectively. Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) Spectroscopy and X-ray diffraction (XRD) were employed for physicochemical characterization. The sensor detects dopamine and cortisol over a linear range of 0.1–100 µM, with limits of detection of 0.043 µM (R² = 0.98) and 0.0577 µg/mL (R² = 0.976), respectively, in phosphate-buffered saline (PBS) using redox probe. Electrochemical performance …

Impact Of Cysteine And Tyrosine Dipeptides On Cho Cell Performance In A Perfusion Mimic, Corrin L. Pruitt

All Theses

Perfusion cell cultures typically achieve higher cell densities and generate higher volumetric productivities than fed-batch cultures due to continuous nutrient supply and spent media removal. Despite these advantages, perfusion cell cultures remain underutilized for licensed product manufacturing, primarily due to the lack of small-scale perfusion models for high-throughput process development and the complexities involved in media formulation capable of supporting high cell densities during long-term continuous operation. To avoid nutrient limitation at high cell densities, current perfusion processes rely on using higher perfusion rates, which results in significant media wastage and downstream product dilution. Therefore, there has been an effort …

Wires, Roads, And Real-World Challenges: An Interdisciplinary Case Study Bridging Roadway And Electric Utility Design, Juliann A. Lloyd

All Theses

Electric utilities are a foundational component of modern society and depend heavily on civil engineers for planning, design, construction, and maintenance. However, educational content related to this industry is often underrepresented in civil engineering programs. To bridge this gap, a case study activity was implemented in two transportation engineering courses at Clemson University. The case study introduced students to the integration between electric utility infrastructure and roadway design by simulating a realistic and common conflict scenario faced by Departments of Transportation (DOTs) nationwide.

Students were placed in interdisciplinary teams, with each member assigned a specialized role such as Land Agent, …

Biological Hydrogen Process Improvements By High Temperature Simultaneous Saccharification And Fermentation, Frank W. Jeffries V

All Theses

The hyperthermophilic bacterium Thermotoga neapolitana is established as a versatile organism for fermentative hydrogen (H₂) production. Batch experiments were carried out to investigate the cell yield, product yield, and kinetic parameter values for individual media containing five carbohydrates. The highest H₂ yield of 15.56±0.31 mmol-H₂/g-carbohydrate was reported for glucose medium. H₂ yield was measured to be 14.51±0.38, 14.44±1.15, 11.88±0.84, and 11.53±0.73 mmol/g for media containing xylose, cellobiose, arabinose and xylan respectively. Acetic acid yield followed a similar trend, where the obtained values were 0.470±0.01, 0.462±0.04, 0.431±0.01, 0.409±0.03, and 0.406±0.01 g-acid/g-carbohydrate for glucose, cellobiose, xylose, …

Dealuminated Metakaolin In Supplementary Cementitious Material And Alkali-Activated Systems: A Review, Amany G. Micheal Prof., Mostafa Adel Elsebaei Eng., Maria Mavroulidou Prof., Maria Centeno Assoc. Prof., Rabee Shamass Senior Lec., Ottavia Rispolio Mrs.

Architectural Engineering

This paper presents a comprehensive review of dealuminated metakaolin (DK), a hazardous industrial by-product generated by the aluminium sulphate (alum) industry and evaluates its potential as a component in cementitious systems for the partial or full replacement of Portland cement (PC). Positioned within the context of waste valorisation in concrete, the review aims to establish a critical understanding of DK formation, properties, and reactivity, particularly its pozzolanic potential, to assess its suitability for use as a supplementary cementitious material (SCM), or as a precursor in alkali-activated cement (AAC) systems for concrete. A systematic methodology is used to extract and synthesise …

Complex System Governance And Cyber Operations, Willie Gernard Mccallister

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation examines the potential integration of Complex System Governance (CSG) within cybersecurity, emphasizing the development of a reference model for Cybersecurity Infrastructures. Traditional strategies for securing digital environments have struggled to address the intricate and dynamic layers inherent in modern cybersecurity systems. The purpose of this research is to explore the applicability of CSG as a framework to assess cybersecurity infrastructure using a case study research design. The research addresses two key questions: (1) How can the CSG reference model be adapted to explore cybersecurity infrastructure? (2) What results from CSG based exploration of cybersecurity infrastructure through a case …

Computational Modeling For Automatic Superconducting Cavity Fault Prediction And Classification Using Time Series Signals, Md Monibor Rahman

Electrical & Computer Engineering Theses & Dissertations

Processing multivariate time series signals collected from sensor networks is challenging because of complex temporal dependencies and non-stationarity. With the advent of artificial intelligence (AI) like machine learning and deep learning, it has become possible to process sensor-driven time series data more effectively than traditional statistical methods.

This dissertation aims to develop machine learning and deep learning models to address machine fault diagnosis using multivariate time series signals collected from the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The first goal of the proposed work is to develop deep learning–based classification models and an unsupervised fault clustering approach …

Systems Statistical Engineering – Hierarchical Fuzzy Constraint Propagation, Hengameh Fakhravar

Engineering Management & Systems Engineering Theses & Dissertations

Driven by the growing need in the 21st century for integrating rigorous statistical analysis into engineering research, there is a movement to develop an integrated statistical engineering science within statistics and quality communities (Hoerl & Snee, 2010; Anderson-Cook et al., 2012). Systems Statistical Engineering research seeks to integrate the Causal Bayesian hierarchical modeling (Pearl, 2009) and cybernetic control theory within Beer’s Viable System Model (1972, 1979, 1985) and the Complex Systems Governance framework (Keating, 2014; Keating & Katina, 2015, 2016) to produce multivariate systemic models for robust dynamic systems mission performance. Cotter & Quigley (2018) set forth the Bayesian systemic …

Challenges And Artificial Intelligence Solutions For Clinically Optimal Hepatic Venous Vessel Segmentation, Håvard Bjørke Jenssen, Varatharajan Nainamalai, Egidijus Pelanis, Rahul P. Kumar, Andreas Abildgaard, Finn Kristian Kolrud, Bjørn Edwin, Jingfeng Jiang, Joseph Vettukattil, Ole Jakob Elle, Smund Avdem Fretland

Michigan Tech Publications

Background:: Liver vessel identification is crucial for clinical disease assessment and treatment planning, especially concerning local treatment of liver tumors. As artificial intelligence (AI) develops in radiology, opportunities arise to craft models adept at hepatic venous vessel segmentation, opening possibilities for creating patient-specific models of the liver anatomy quickly, despite the diverse features of CT images encountered in clinical settings. Objective: This research evaluates the performance of AI models combined with various pre-processing filters for liver vessel segmentation, emphasizing clinically relevant results. A novel evaluation method was introduced to offer more anatomically accurate assessments, moving beyond traditional metrics like the …

Development Of A Machine Learning Framework For An Irrigation Decision Support System, Eric Wilkening, Derek M. Heeren, Yeyin Shi, Laila A. Puntel, Guillermo R. Balboa, Abia Katimbo, Kuan Zhang, Precious Nneka Amori, Bruno Lena

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Currently used irrigation scheduling techniques often require significant human intervention and are time consuming, particularly for variable rate irrigation. This research aimed to develop a conceptual framework that incorporates disparate data sources leveraging both mechanistic and machine learning (ML) approaches. The overarching objective is to utilize the growing availability of data and technology to manage irrigation more precisely, which will minimize negative impacts of irrigation on our water resources. An initial irrigation machine learning model was proposed and tested in this study as a key component of an edge-cloud computing and federated learning decision-making framework. The specific objectives were (1) …

Studies On The Effects Of Operator Fatigue On Performance, Trust, And Workload Demand In Human-In-The-Loop Ai-Enabled Drone Systems, Snowil Lopes

All Dissertations

Civil infrastructure must be regularly inspected to ensure its safety and reliability. Traditionally, risk engineers performed these inspections manually and in person. However, with the introduction of drones equipped with artificial intelligence (AI), inspections of civil infrastructure can now be conducted remotely. These AI-enabled drones capture and analyze images, helping engineers monitor large and complex structures from a distance. However, working with integrated systems consisting of multiple drones, especially those with varying levels of reliability, can be challenging. Operators must divide their attention, determine how much to trust each drone, and manage mental workload, which can affect their performance. Another …

Impact Of Humidity From Shrink (Wrap) Tunnels On Refrigeration Systems: Comparing Economic And Environmental Impact Of Natural Gas And Electric, Segun Samuel Oladipo

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

This thesis examines the economic and environmental effects of electric and steam shrink-wrapping tunnels used in beef packaging processes, paying particular attention to the indirect refrigeration loads caused by the heat and humidity that each system releases. Traditional sustainability evaluations frequently ignore these indirect impacts, which are especially important in meat processing facilities where 45–55% of electricity use is attributed to refrigeration. Life cycle assessment (LCA), field measurements, and thermodynamic modeling are all used in this work to offer a thorough analysis of both tunnel types.

The case study facility in Nebraska operates both steam and electric shrink tunnels to …

Development And Evaluation Of Supported Ionic Liquid Membrane And Porphyrin Frameworks For Carbon Capture Separation, Sarang Ismail

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

The global urgency to mitigate anthropogenic CO₂ emissions has intensified the pursuit of energy-efficient separation technologies. Supported Ionic Liquid Membranes (SILMs) have emerged as promising candidates for CO₂ capture due to their tunable solubility-selectivity and low energy requirements. However, challenges such as mechanical instability, limited scalability, and trade-offs in transport performance have impeded their widespread adoption.

This thesis explores a systematic approach to designing and optimizing SILMs for enhanced CO₂ separation by tailoring polymer–ionic liquid interactions, processing conditions, and material architectures. A comprehensive set of studies were conducted using poly(vinylidene fluoride) (PVDF) with varying molecular weights, different grades of PEBAX®, …

Replacement Optimization For Offshore Wind Turbine Farms, Morteza Soltani

All Dissertations

This dissertation is concerned with devising optimal replacement policies for offshore wind turbines with a focus on minimizing the costs associated with major component replacements and production losses due to downtime. Like their onshore counterparts, offshore wind turbines are subject to progressive degradation due to normal operations, as well as the influence of dynamic environmental conditions that influence their rate of degradation. Due to their proximity, wind farm turbines share common environmental conditions, as well as specialized maintenance resources. Their common exposure to the environment and need to share resources introduce both stochastic and economic dependence between the wind turbines. …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Structural Design Using Conditional-Gan Fused With Property Text Information: A Case For Masonry Structures, Arash Teymori Gharah Tapeh

All Dissertations

Structural design, by nature, is a complex process that requires a considerable amount of time, expertise, and knowledge. In such a process, the structural designer must navigate various codal provisions to crystallize a proper and adequate design. As the role of automation continues to shape the domain of structural engineering over the past few decades, a new front leverages artificial intelligence (AI). Currently, AI acts as a "copilot," collaborating to advance workflow speed and accelerate the design process. Among all the different collaborations between humans and AI, GANs (Generative Adversarial Networks) are seen to complement human creativity by automating specific …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Constructing A State: Canals And The Transformation Of The Economy, Politics, And Finance In Nineteenth-Century New York, Youwei Xing

All Dissertations

This dissertation consists of three essays in economic history, unified by a focus on one of America's earliest transportation infrastructures, the canal system, in nineteenth-century New York. Each chapter explores a different aspect of the state's transformation: its economy, politics, and finance, each of which helped construct New York as the Empire State.

The first chapter studies the economic impact of canals on economic modernization from three aspects: sectoral transition, urbanization, and banking development. Contrary to much of the modern literature finds transportation infrastructure leads to decentralization, I find the opposite-evidence of centralization. Specially: (1) canal towns experienced a transition …

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 …