A High-Precision Electron Emission Model: Computational Methods For Nanoscale Structures, Alister J. Tencate

Graduate Research Theses & Dissertations

The high-intensity, high-brightness and precision frontiers for charged particle beams are an increasingly important focus for study. Electron microscopy has demonstrated high quality beams from a single nanotip emitter, and cathodes of structured nanoscale arrays show promise as ultracold electron sources. Optimization of the cathode design for precision applications necessitates a detailed treatment of the interplay between the structure geometry, quantum mechanical emission mechanism, and electromagnetic interactions between the emitted electrons and the boundary interface. This dissertation details the numerical tools developed to simulate these processes efficiently with enough fidelity to be accurate even in the ultracold regime.

Conventional simulation …

Simulations Of Implementation Of Advanced Communication Technologies, Ivy Yousuf Moutushi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Wireless communication systems have seen significant advancements with the introduction of 3G, 4G, and 5G mobile standards. Since the simulation of entire systems is complex and may not allow evaluation of the impact of individual techniques, this thesis presents techniques and results for simulating the performance of advanced signaling techniques used in 3G, 4G, and 5G systems, including Code division multiple access (CDMA), Multiple Input Multiple Output (MIMO) systems, and Low-Density Parity Check (LDPC) codes. One implementation issue that is explored is the use of quantized Analog to Digital Converter (ADC) outputs and their impact on system performance.

Code division …

Component Optimization Of A Parallel P4 Hybrid Electric Vehicle Utilizing An Equivalent Consumption Minimization Strategy, Holden Ryan Fraser

Graduate Theses, Dissertations, and Problem Reports (ETD)

Advancements in battery and electric motor technology have driven the development of hybrid electric vehicles to improve fuel economy. Hybrid electric vehicles can utilize an internal combustion engine and an electric motor in many configurations, requiring the development of advanced energy management strategies for a range of component configurations. The Equivalent Consumption Minimization Strategy (ECMS) is an advanced energy management strategy that can be calculated in-vehicle in real-time operation. This energy management strategy uses an equivalence factor to equate electrical to mechanical power when performing the torque split determination between the internal combustion engine and electric motor. This equivalence factor …

System Analysis Of An Internal Combustion Engine (Ice) – Solid Oxide Fuel Cell (Sofc) Hybrid Cycle, Jose Javier Colon Rodriguez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Due to the intermittent nature of renewable energy and the rigid operation of existing coal plants, the need for flexible power generation technology is eminent. Hybrid energy systems have shown potential for flexible, grid following dynamics while maintaining higher efficiencies. The work below focuses on the performance analysis of a proposed 100 kW pressurized Internal Combustion Engine (ICE) and Solid Oxide Fuel Cell (SOFC) hybrid system. The un-utilized fuel from the SOFC stack provided the chemical energy to operate the engine. A turbocharger was used to deliver the necessary air flow for both the stack and engine. An external reformer …

Analysis Of Localization Algorithms For Wireless Sensor Networks Using Binary Data, Alexander Joseph Hart

Graduate Research Theses & Dissertations

The detection, localization, and tracking of environmental and physical conditions can be accomplished using wireless sensor networks (WSNs). Recent advancements in sensors, processors, and wireless communications have improved the quality and acquisition speed of data in WSNs. However, the data gathered by a WSN is inherently random due to component and environmental variations. Thus, statistical signal processing algorithms are needed to analyze the random data in a robust way. Though many algorithms for the analysis of random data are established and available, they are problem-specific and must be adapted to the application. This thesis provides an analysis of established localization …

Ocean Vector Wind Measurement Potential From The Global Precipitation Measurement Mission Using A Combined Active And Passive Algorithm, Alamgir Hossan

Electronic Theses and Dissertations, 2020-2023

Ocean surface vector wind (OVW) is an essential parameter for understanding the physics and dynamics of the ocean-atmosphere system, thereby improving weather forecasting and climate studies. Satellite scatterometers, synthetic aperture radars, and polarimetric microwave radiometers have provided almost global coverage of ocean surface vector wind for the last four decades. Nonetheless, a consistent and uninterrupted long-time data record with the capability of resolving sub-diurnal variability has remained a critical challenge over the years. The Global Precipitation Measurement Mission (GPM) is a satellite mission designed to provide space-based precipitation information on a global scale with complete diurnal sampling. This dissertation presents …

Automatic Data-Driven Partitioned Modeling Of Power System Dynamics With Smart Power Electronic Inverters, Sunil Subedi

Electronic Theses and Dissertations

The primary aim of this dissertation is to provide an efficient statistical modeling and simulation technique for extracting the dynamics of converter-dominated power systems (CDPS) with the device level details using the least amount of computation time while maintaining a reasonable level of accuracy. These test cases are intended for use by power system researchers that need to develop test cases that can perform accurate dynamic analysis on a high integration of inverter-based resources (IBRs) for stability analysis while speeding up simulation time and reducing computational complexity. Additionally, utilities/grid operators must properly plan, operate, and dispatch. Case studies that can …

Probing Signal-Based Data-Driven Modeling Of Power Electronics Smart Converter Dynamics Using Power Hardware-In-The-Loop, Nischal Guruwacharya

Electronic Theses and Dissertations

The main objective of this dissertation is to develop a generalized simulation and modeling framework for extracting dynamics of power electronic converters (PECs) with grid support functions (GSFs) and validate model accuracy through experimental comparison with physical measurements. The dynamic models obtained from this modeling framework aim to facilitate accurate dynamic analysis of a highly integrated power system comprising inverter-based resources (IBRs), specifically for stability assessment. These dynamic models helped in reducing simulation time and computational complexity, thereby enhancing efficiency. Moreover, it provides valuable insights for utilities and grid operators involved in effective system planning, operation, and dispatch. The dynamics …

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …

Energy-Efficient Hmac For Wireless Communications, Cesar Enrique Castellon Escobar

UNF Graduate Theses and Dissertations

This thesis introduces the Farming Lightweight Protocol (FLP) optimized for energy-restricted environments that depend upon secure communication, such as multi-robot information gathering systems within the vision of ``smart'' agriculture. FLP uses a hash-based message authentication code (HMAC) to achieve data integrity. HMAC implementations, resting upon repeated use of the SHA256 hashing operator, impose additional resource requirements and thus also impact system availability. We address this particular integrity/availability trade-off by proposing an energy-saving algorithmic engineering method on the internal SHA256 hashing operator. The energy-efficient hash is designed to maintain the original security benefits yet reduce the negative effects on system availability. …

Analyzing Physiological Signals During The Menstrual Cycle: Introducing An Application Of Circular Statistics, Krystal D. Sides

UNF Graduate Theses and Dissertations

Physiological signals are used in engineering and the sciences to determine the state of functionality of certain physiological systems such as the human endometrium. Many women use the basal body temperature method to track ovulation, or their fertile window. However, temperature tracking alone is subject to environmental factors. Non-invasive wearable devices can be tools in recording cycle-related physiological features relevant to women’s health research. This research uses the Empatica E4 wristband to track changes in the physiological features during sleep across the menstrual cycle of ovulating and non-ovulating females. Due to the cyclic nature of menstrual cycles, analytic solutions to …

Technical And Economic Feasibility Of A Microgrid For A Fire Station In Humboldt County, California., Nishaant Kumar Sinha

Cal Poly Humboldt theses and projects

Microgrids are emerging as a promising solution to unreliable grid energy. Today, California is not only witnessing grid resiliency challenges from natural disasters such as wildfires, earthquakes, floods and heatwaves, but it is also seeking to green the grid and bring more renewables online. For example, Humboldt County, where this project is focused, has recently experienced an earthquake of 6.4M (on December 22nd, 2022), which shut down the regional grid for ~20 hours.

Microgrid adoption enables critical facilities to operate seamlessly. The Humboldt Bay Fire Station (HBFS) No.1 is one such example, where first responders work to protect citizens against …

Fiber Optic Sensors For Liquid Identifications, Wassana Naku

Doctoral Dissertations

"The fiber optic Fabry-Perot interferometer (FPI) is a widely utilized sensing configuration, offering numerous advantages over conventional electronic sensors, including high accuracy, distributed sensing capabilities, immunity to electromagnetic interference, and compact size. In this study, we propose a remarkably simple fiber optic-tip sensor system combined with machine learning techniques for the identification of pure and volatile organic liquids (VOLs).

A liquid droplet forms an extrinsic FPI (EFPI), with its effective reflectance being a function of the droplet's length. As the droplet evaporates, its length decreases. We conducted immersion tests using optical fiber tip sensors and monitored the time-transient responses of …

Design, Modeling And Analysis Of An Ac-Ac Dual Active Bridge Converter, Kartikeya Jayadurga Prasad Veeramraju

Doctoral Dissertations

"The Solid-State Transformer (SST) is gaining attention as an alternative to conventional iron-core transformers in the power electronic community. The power industry's increasing demands for smaller size, higher efficiency, and greater energy density have made the SST an attractive option. Among various power electronic converter topologies, the Dual Active Bridge (DAB) has become popular for its bidirectional power flow capability and galvanic isolation, primarily in the DC application space. Advancements in semiconductor technologies have introduced new bidirectional switches, opening avenues for novel SST topologies. This research investigates the application of the DAB as a single-stage SST and focuses on advancements …

Introduction Of A Variable Inductance Transformer For The Design Of Resonant Power Converters, Angshuman Sharma

Doctoral Dissertations

"Magnetic integration is a hot topic in power electronics that concerns the use of a transformer's leakage and magnetizing inductances purposefully in isolated power electronic converters, thereby giving the opportunity to save the cost and footprint of any additional inductor. This is of prime interest, especially in CLLLC resonant converters which require up to three inductors. For a complete integration of these inductances, the concept of a variable inductance transformer (VIT) is introduced in this thesis. A VIT is an adaptive magnetic structure that facilitates an easy adjustment of both magnetizing and leakage inductances to meet their desired values. However, …

Generative Adversarial Network And Its Application In Aerial Vehicle Detection And Biometric Identification System, Moktari Mostofa

Graduate Theses, Dissertations, and Problem Reports (ETD)

In recent years, generative adversarial networks (GANs) have shown great potential in advancing the state-of-the-art in many areas of computer vision, most notably in image synthesis and manipulation tasks. GAN is a generative model which simultaneously trains a generator and a discriminator in an adversarial manner to produce real-looking synthetic data by capturing the underlying data distribution. Due to its powerful ability to generate high-quality and visually pleasing
results, we apply it to super-resolution and image-to-image translation techniques to address vehicle detection in low-resolution aerial images and cross-spectral cross-resolution iris recognition. First, we develop a Multi-scale GAN (MsGAN) with multiple …

Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick

Graduate Theses, Dissertations, and Problem Reports (ETD)

With the introduction of a larger portion of renewable sources of power coming onto the U.S. power grid in recent decades, the operational strategy of coal-fired power plants has changed significantly to focus more on flexibility in response to the changing energy market. This has naturally led to different operational challenges. Many of these challenges are focused on the boilers within these plants, as they are producing more emissions and experiencing increased damage during load-following, which in turn leads to increased costs from penalties for not achieving emission standards or maintenance costs as boilers accumulate damage from the cycling behavior. …

Computational Mechanisms Of Face Perception, Jinge Wang

Graduate Theses, Dissertations, and Problem Reports (ETD)

The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for …

Investigating The Impact Of Demographic Factors On Contactless Fingerprint Interoperability, Aeddon David Berti

Graduate Theses, Dissertations, and Problem Reports (ETD)

Improvements in contactless fingerprinting have resulted in contactless fingerprints becoming a faster and more convenient alternative to contact fingerprints. The interoperability between contactless fingerprints and contact fingerprints and how demographic factors can change interoperability has been challenging since COVID-19; the need for hygienic alternatives has only grown because of the sudden focus during the pandemic. Past work has shown issues with the interoperability of contactless prints from kiosk devices and phone fingerprint collection apps. Demographic bias in photography for facial recognition could affect photographed fingerprints. The paper focuses on evaluating match performance between contact and contactless fingerprints and evaluating match …

Framework For Data Acquisition And Fusion Of Camera And Radar For Autonomous Vehicle Systems, Clay Edward Vincent

Graduate Theses, Dissertations, and Problem Reports (ETD)

The primary contribution is the development of the data collection testing methodology for autonomous driving systems of a hybrid electric passenger vehicle. As automotive manufacturers begin to develop adaptive cruise control technology in vehicles, progress is being made toward the development of fully-autonomous vehicles. Adaptive cruise control capability is classified into five levels defined by the Society of Automotive Engineering. Some vehicles under development have attained higher levels of autonomy, but the focus of most commercial development is Level 2 autonomy. As the level of autonomy increases, the sensor technology becomes more advanced with a sensor suite which includes radar, …

Machine Learning For Biosensors, Gayathri Anapanani

Graduate Theses, Dissertations, and Problem Reports (ETD)

Biosensors have become increasingly popular as diagnostic tools due to their ability to detect and quantify biological analytes in a wide range of applications. With the growing demand for faster and more reliable biosensing devices, machine learning has become a valuable tool in enhancing biosensor performance. In this report, we review recent progress in the application of machine learning to biosensors. We discuss the potential benefits of using machine learning in biosensors, including improved sensitivity, selectivity, and accuracy. We also discuss the various machine learning techniques that have been applied to biosensors, including data preprocessing, feature extraction, and classification and …

Moment-Based Reinforcement Learning For Ensemble Control, Yao-Chi Yu, Vignesh Narayanan, Jr-Shin Li

Publications

Problems involving controlling the collective behavior of a population of structurally similar dynamical systems, the so-called ensemble control, arise in diverse emerging applications and pose a grand challenge in systems science and control engineering. Owing to the severely under-actuated nature and the difficulty of placing large-scale sensor networks, ensemble systems are limited to being actuated and monitored at the population level. Moreover, mathematical models describing the dynamics of ensemble systems are often elusive. Therefore, it is essential to design broadcast controls that excite the entire population in such a way that the heterogeneity in system dynamics are robustly compensated. In …

Implications Of Physical Fault Injections On Single Chip Motes, Sara Faour, Mališa Vučinić, Filip Maksimovic, David Burnett, Paul Muhlethaler, Thomas Watteyne, Kristofer Pister

Electrical and Computer Engineering Faculty Publications and Presentations

Single-chip motes are wireless sensor nodes that integrate computation, communication, power and sensing on a single chip. We consider the security threats these novel devices are subject to when employed in safety-critical applications. Fault injection attacks are a prominent form of physical attacks that pose a threat to the normal and secure functioning of targeted devices, potentially compromising their intended behavior. These attacks have been studied mainly on commercial off-the-shelf devices which rely on external components such as crystal oscillators and passives. Such external components are absent from single-chip motes, resulting in a uniquely different attack surface compared to commercial …

Battery Energy Storage Systems Applications And Deployment In Dense Urban Areas, Mohamed K. Kamaludeen

Dissertations and Theses

Energy Storage has emerged as an important focus of the U.S. federal government, which has established the goal of developing global leadership in energy storage and has a near-term focus on strengthening the supply chain, manufacturing, and funding streams available to achieve the overarching objectives. At the state level, similar efforts are underway in which policy objectives have set aggressive targets around energy storage deployment. New York State, through its landmark climate act “CLCPA” and subsequent Energy Storage roadmap 2.0, has set one of the most aggressive goals in the Country targeting 6,000MW of energy storage by 2030. While much …

Nonlinear And Time-Modulated Metamaterials: Applications At Microwave Frequencies, Hady Mohammed Saied Sayed Moussa

Dissertations and Theses

Metamaterials (the Greek prefix meta, means beyond) are artificially structured materials that interact with the incoming waves in extraordinary ways, beyond the properties of natural materials, yielding unusual and exotic electromagnetics phenomena. By careful engineering of the material properties, invoking nonlinear elements and/or time-modulating some of the material parameters, linearity and/or time-invariance can be broken in metamaterials, enabling extraordinary wave phenomena that open opportunities for the microwave engineering community, including the creation of nonreciprocal devices, frequency conversion, and more. In this dissertation, we explore, investigate, design, and fabricate metamaterials that open new applications for nonlinearity-based and time-varying devices, particularly in …

Impact Of Atmospheric Correction On Classification And Quantification Of Seagrass Density From Worldview-2 Imagery, Victoria J. Hill, Richard C. Zimmerman, Paul Bissett, David Kohler, Blake Schaeffer, Megan Coffer, Jiang Li, Kazi Aminul Islam

OES Faculty Publications

Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors’ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGC_seagrass) estimates. This study assessed atmospheric correction’s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (L_w), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line …

Tutorial - Shodhguru Labs: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin

Articles

The increasing power consumption of Data Center Networks (DCN) is becoming a major concern for network operators. The object of this paper is to provide a survey of state-of-the-art methods for reducing energy consumption via (1) enhanced scheduling and (2) enhanced aggregation of traffic flows using Software-Defined Networks (SDN), focusing on the advantages and disadvantages of these approaches. We tackle a gap in the literature for a review of SDN-based energy saving techniques and discuss the limitations of multi-controller solutions in terms of constraints on their performance. The main finding of this survey paper is that the two classes of …

Suitability Of Quantized Devs-Lim Methods For Simulation Of Power Systems, Navid Gholizadeh

Theses and Dissertations

This research presents an investigation of behavioral intricacies of the Quantized DEVS Latency Insertion Method (QDL) method and proposes resolutions to the previously unsolved and unexplained discrepancies between the reference solution and the QDL method. QDL method is a combination of two other methods namely the Latency Insertion Method (LIM) and Linear Implicit Quantized State (LIQSS)method. This technique is rigorously evaluated across a diverse array of systems and scenarios, with the aim of unearthing nuanced insights into its respective functionalities.

The research seeks to discern novel attributes of this method while gauging its comparative efficacy against conventional discrete-time methodologies, both …

Boosting Snr Of Cascaded Fbgs In A Sapphire Fiber Through A Rapid Heat Treatment, Farhan Mumtaz, Hanok Tekle, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Rex Gerald, Jie Huang

PSMRC Faculty Research

This Letter reports the performance of femtosecond (fs) laser-written distributed fiber Bragg gratings (FBGs) under high-temperature conditions up to 1600°C and explores the impact of rapid heat treatment on signal-to-noise ratio (SNR) enhancement. FBGs are essential for reliable optical sensing in extreme temperature environments. Comprehensive tests demonstrate the remarkable performance and resilience of FBGs at temperatures up to 1600°C, confirming their suitability for deployment in such conditions. The study also reveals significant fringe visibility improvements of up to ∼10 dB on a 1-m-long sapphire optical fiber through rapid heat treatment, representing a first-time achievement to the best of our knowledge. …