Engineering Commons^™

Carrier Dynamics In Green Iii-Nitride Leds Using Small-Signal Electroluminescence, Xuefeng Li

Optical Science and Engineering ETDs

Solid-state lighting has achieved significant success over the past two decades, but the low quantum efficiency of green LEDs (i.e., the “green gap”) remains a barrier to full red-green-blue (RGB) displays in numerous applications. Combating efficiency reduction in longer-wavelength LEDs requires understanding the relative roles of intrinsic effects (e.g., wave-function overlap, carrier-current density relationship, phase-space filling (PSF)) vs. extrinsic effects (e.g., material degradation due to increased defect density, compositional inhomogeneities, etc.). A systematic study of the carrier dynamics in InGaN/GaN LEDs is very important for understanding the origin of the green gap and for providing solutions to improve the efficiency …

Study Of Si-Gan Photoconductive Switches Operating Modes Using Near-Ir Radiation, Nicolas Eduardo Gonzalez Padilla

Electrical and Computer Engineering ETDs

One of the most promising solid-state devices for fast switching and radio frequency generation applications is the photoconductive switch (PCSS). These devices have been thoroughly explored since the late 1980s and exhibit remarkable switching properties in gallium arsenide (GaAs). With recent advances in wide bandgap (WBG) semiconductor manufacturing processes, there has been an increasing interest in using WBG semiconductors to implement PCSS. WBG semiconductors could exhibit the same switching characteristics as GaAs while overcoming their poor power management and short lifetime under pulsed power conditions, making PCSS a reliable option in high-power applications. Gallium Nitride (GaN) has emerged as one …

Mobile Intelligent Agents: Interplay Of Communications, Privacy, And Decision Making, Saeede Enayati

Doctoral Dissertations

The development of processors and sensor technologies and the advent of artificial intelligence (AI) have led to the growth of more capable and affordable mobile intelligent agents like unmanned aerial vehicles (UAVs) which have numerous applications in areas such as construction, search and rescue operations, oil and gas, agriculture, etc. The use of AI and machine learning (ML) algorithms in UAVs has enabled real-time data-driven decision-making frameworks but poses numerous challenges including high-impact decision-making, security, energy management, communication, and automation, to name a few. In this dissertation, we propose solutions to some of these problems. First, we give our attention …

Analog Cancellation Of A Known Remote Interference: Hardware Realization And Analysis, James M. Doty

Masters Theses

The onset of quantum computing threatens commonly used schemes for information secrecy across wireless communication channels, particularly key-based data-level encryption. This calls for secrecy schemes that can provide everlasting secrecy resistant to increased computational power of an adversary. One novel physical layer scheme proposes that an intended receiver capable of performing analog cancellation of a known key-based interference would hold a significant advantage in recovering small underlying messages versus an eavesdropper performing cancellation after analog-to-digital conversion. This advantage holds even in the event that an eavesdropper can recover and use the original key in their digital cancellation. Inspired by this …

Refinement And Performance Analysis Of The Stepped Frequency Microwave Radiometer In Extra Tropical Cyclone Conditions, Jezabel Vilardell Sanchez

Doctoral Dissertations

The Stepped Frequency Microwave Radiometer (SFMR) is a key instrument for estimation of ocean surface wind speed and rain rate in tropical and extra-tropical cyclones research. Through the observed brightness temperature (TB) over a range of six C-band frequencies, the SFMR derives these key parameters used by hurricane specialists to issue watches and warnings. The information gathered with this instru- ment is also pivotal for post-storm studies and satellite calibrations. Currently, the SFMR requires an average time of 5-10 seconds of averaging to cycle through the six di↵erent frequency channels, so in regions with strong wind/rain gradients such as the …

Design, Optimization, And Hardware Deployment Of A Deep Learning Model For Gps Spoofing Detection Using Gnss Satellite Receiver Protocol Data, Clarizza Morales Chacon

Electrical and Computer Engineering ETDs

The contemporary GPS infrastructure plays a vital role in advancing Position, Navigation, and Timing (PNT) applications across various sectors, including transportation, commerce, finance, and aviation. To provide a robust and authenticated infrastructure for users, it is important to develop a methodology for verifying the authenticity of satellite navigation signals, especially in civilian applications using the C/A code. This thesis explores Machine Learning (ML) techniques, focusing on the analysis of Global Navigation Satellite System (GNSS) protocol messages like UBX and NMEA to detect anomalies in receiver and satellite behavior, indicative of potential spoofing. The research demonstrates the deployment of Machine Learning …

The Automated Wheelchair, Jonathan Doksa Kamba Ngoyi

Honors College Theses

Automation refers to the use of technology to execute tasks through programmed instructions and automated control mechanisms to ensure accurate execution. This minimizes human involvement and encompasses various fields, including business process automation. A notable form of automation is assistive technology, which refers to any device or software that enhances individuals' learning, communication, or overall functionality. This can range from advanced tools like computers to simpler aids like walking sticks. Assistive technology aims to promote inclusivity and participation, particularly among individuals with disabilities, the elderly, and those with non-communicable diseases.

The Automated Airport Wheelchair is a culmination of prior projects …

Characterization Analysis And Design Of Mid-Wave Infrared Iii- V-Based Type-Ii Superlattice Nbn Photodetectors For Space Applications, Alexander Timothy Newell

Electrical and Computer Engineering ETDs

The performance of the mid-wave infrared InGaAs/InAsSb nBn photodetector is investigated and its viability for space applications is assessed. Three structures are grown with unique absorber layer doping profiles via molecular beam epitaxy. Material and device characterizations are performed and analyzed to determine the effects of doping on fundamental material parameters and detector performance. Noise-equivalent irradiance is calculated to be a factor of 4x that of an ideal detector exhibiting Rule 07 dark current and 100% quantum efficiency, demonstrating high sensitivity. The structures are then irradiated with 63 MeV protons to evaluate the extent of performance degradation over the course …

Skin Cancer Detection By Deep Learning Algorithms, Faezeh Mohammadi Aydoghmishi

Electronic Theses and Dissertations

Skin cancer, characterized by the abnormal growth of skin cells, is a globally prevalent and serious condition. Despite advancements in digital diagnosis techniques, many existing skin cancer detection methods often fail to achieve satisfactory accuracy levels. In our first study, we propose a novel superpixel-based segmentation method that significantly surpasses the traditional k-means clustering in performance. After segmentation, we utilize Convolutional Neural Networks such as VGG16, ResNet50, DenseNet, Xception, Inception, and Mobilenet for feature extraction and classification. We also conducted a comparative analysis with other existing techniques. Our results suggest that our superpixel-based segmentation method notably enhances the accuracy of …

Novel Systems Engineering Framework Analysis Of Photovoltaic Models And Equations, Peter R. Michael

USF Tampa Graduate Theses and Dissertations

This dissertation analyzes Photovoltaic PV equations and models for silicon based systems from a Systems Engineering framework. Background information includes an introduction, a summary of the state of PV use, a brief history of photovoltaics, and the detailed derivation of equations that enable the finding of the PV parameters contained in the PV models.The novel inquiry, leveraging systems engineering frameworks, includes three areas useful in analyzing PV equations and models. The first is a statistical verification of common simplifications of PV equations at the primary conditions of short circuit, open circuit, and maximum power. Additional analysis shows other simplifications that …

Molecular Dynamics Study Of Characterization In Metal-Free Friction Materials, Yizhan Zhang

Electronic Theses and Dissertations

Metallic friction materials currently used in industry may adversely impact the environment. Substitutions for metals in friction materials, on the other hand, can introduce operational safety issues and other unforeseeable issues such as thermal-mechanical instabilities and insufficient strength. In view of it, this dissertation focuses on developing different kinds of materials from simple structure to complex structure and evaluating the material properties with the assistance of molecular dynamics (MD) tools at the nano scale.

First, the concept of the contacted surfaces in friction at the atomic scale was introduced in order to get accurate understanding of the friction process compared …

Electrophertic Deposition And Characterization Of Molybdenum Disulfide On Silicon Substrates, Alex J. Young

LSU Doctoral Dissertations

The electrical characteristics of 2D materials such as high electron mobility and current density are of great interest to various fields from optoelectronics to renewable energy. Researchers have focused their efforts on transition metal dichalcogenides (TMDCs) due to their direct energy band gap. One such TMDC that has garnered much attention is molybdenum disulfide (MoS2). MoS2 has electrical properties comparable to graphene and is a TMDC with characteristics amenable to applications such as solar cells and sensors. Commonly deposited through time-consuming and complex deposition methods such as chemical vapor deposition (CVD), the viability of MoS2 as an electronic material will …

Dynamic Spectrum Management In 3d Networks Inspired By Biological Systems, Jordan Anthony Patrizi

Electrical and Computer Engineering ETDs

In this thesis, the challenge of dynamic spectrum management is treated following an economic-based perspective. In particular, a novel bioinspired spectrum allocation from the Network Service Providers (NSPs) to the users is introduced, exploiting the theory of symbiosis under the free competition. The overall objective is to determine the NSPs optimal bandwidth prices to maximize their profit, while satisfying the users bandwidth needs. The aforementioned spectrum management framework is analyzed while exploiting a novel 3D network architecture consisting of High Altitude Platforms (HAPs), Unmanned Aerial Vehicles (UAVs), and ground gNBs NSPs, each one of them presenting different operational characteristics and …

Analysis Of The Pros And Cons Of The Acquisition Of Training Ships By Metis, Jeremiah Yaw Frimpong

World Maritime University Dissertations

No abstract provided.

Cyber-Physical Multi-Robot Systems In A Smart Factory: A Networked Ai Agents Approach, Zixiang Nie

USF Tampa Graduate Theses and Dissertations

This dissertation focuses on addressing the technical challenges of non-stationarity in smart factories through the use of cyber-physical AI agents. Industry 4.0 and smart manufacturing with smart factories as a central role, have a growing demand for Just-in-Time (JIT) and on-demand production, as well as mass customization—all while maintaining high productivity, resource efficiency and resilience. This research positions Multi-Robot Systems (MRS)-driven smart factories. The heterogeneous production and transportation robots in an MRS collaborate to form multiple real-time adjusted production flows achieving the flexibility to accommodate such on-demand, mass customization.

However, the implementation of MRS introduces new sets of challenges, including …

Enhancing Breast Cancer Detection Through Combination Of Contrastive Learning And Adversarial Domain Adaptation, Mahnoosh Torabi

Electronic Theses and Dissertations

The most common cancer diagnosed worldwide is breast cancer and early detection is essential for reducing mortality. The best standard for early detection of breast cancer is digital mammography, which can aid physicians in treating the illness when it is still curable. However, inaccurate mammography diagnoses are frequent and can cause patients to undergo unnecessary examinations and therapies. This study aims to explore deep-learning techniques that can be utilized to implement and train a model to identify breast cancer cases in mammograms. Current deep learning-based diagnostic techniques are hindered by two fundamental issues: the expensive and time-consuming task of data …

Enabling Intelligent Network Management Through Multi-Agent Systems: An Implementation Of Autonomous Network System, Petro Mushidi Tshakwanda

Electrical and Computer Engineering ETDs

This Ph.D. dissertation presents a pioneering Multi-Agent System (MAS) approach for intelligent network management, particularly suited for next-generation networks like 5G and 6G. The thesis is segmented into four critical parts. Firstly, it contrasts the benefits of agent-based design over traditional micro-service architectures. Secondly, it elaborates on the implementation of network service agents in Python Agent Development Environment (PADE), employing machine learning and deep learning algorithms for performance evaluation. Thirdly, a new scalable approach, Scalable and Efficient DevOps (SE-DO), is introduced to optimize agent performance in resource-constrained settings. Fourthly, the dissertation delves into Quality of Service (QoS) and Radio Resource …

Modeling And Compensating Of Noise In Time-Of-Flight Sensors, Bryan Rodriguez

Electrical Engineering Theses and Dissertations

Three-dimensional (3D) sensors provide the ability to perform contactless measurements of objects and distances that are within their field of view. Unlike traditional two-dimensional (2D) cameras, which only provide RGB data about objects within a scene, 3D sensors are able to directly provide depth information for objects within a scene. Of these 3D sensing technologies, Time-of-Flight (ToF) sensors are becoming more compact which allows them to be more easily integrated with other devices and to find use in more applications. ToF sensors also provide several benefits over other 3D sensing technologies that increase the types of applications where ToF sensors …

Probabilistic Cable Aging Diagnosis And Prognosis With Reflectometry And Capacitance Methods, Xuan Wang

Theses and Dissertations

Safe and reliable operation of power plants and power transmission are critical to economy and society. Cables in power generation and transmission are subject to various thermal, chemical, and mechanical stresses, which generally lead to aging and degradation of cable insulation. It is reported that some cables with a projected lifetime of 40 years need to be replaced in 10-15 years. Poorly maintained aged cables can adversely affect power delivery and lead to catastrophic events, such as blackout, fires, and loss of lives. The current research on cable is mainly focused on the detection and localization of hard faults, which …

Circularly-Shifted Chirps For Triple Functionality: Communications, Radar, And Computation, Safi Shams Muhtasimul Hoque

Theses and Dissertations

This dissertation presents circularly-shifted chirps (CSCs), synthesized within orthogonal frequency domain multiplexing (OFDM) framework, as a novel solution for integrating radar, communication, and computation functionalities to a wireless network. Firstly, {index modulation (IM)} with circularly-shifted chirps (CSCs) (CSC-IM) for dual-function radar and communication (DFRC) system is discussed. The proposed scheme encodes the information bits with the CSC indices and the phase-shift keying (PSK) symbols. It allows the receiver to exploit the frequency selectivity naturally in fading channels by combining IM and wideband CSCs. It also leverages the fact that a CSC is a constant-envelope signal to achieve a controllable peak-to-mean …

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …

Simulation-Based Optimization Of A Dc Microgrid: With Machine-Learning-Based Models And Hybrid Meta-Heuristic Algorithms, Tyler Van Deese

Theses and Dissertations

The field of economic dispatch (ED) focuses on optimizing power flow in a power system to minimize costs. It has the potential to significantly enhance system effectiveness, and efficiency, and reduce operating costs. Various techniques have been employed to tackle this problem, each with its own strengths and weaknesses. One promising approach is simulation-based optimization (SBO), which allows for accurate modeling of system interactions and improved representation of expected results. However, SBO requires running numerous simulations to identify an optimal solution, and there is a possibility of not achieving the global optimum. This work aims to address these challenges using …

Robust Deep Learning Models For Multi-Label Image Classification In Limited And Free Annotation Scenarios, Rabab Ezzeldin Rabie Abdelfattah

Theses and Dissertations

This proposal introduces various methods for tackling the challenge of multi-label image classification in different scenarios, including partial labels and free-annotation settings. Multi-label image classification is typically formulated as a partial-label learning problem because it can be expensive to annotate all labels in every training image. Existing partial-label learning approaches typically focus on annotating each training image with only a subset of its labels, including a special case of annotating only one positive label per image. To further alleviate the annotation burden and improve classifier performance, this proposal introduces a new partial-label setting where only a subset of training images …

Novel Approach To In-Situ Mocvd Oxide/Dielectric Deposition For Iii-Nitride-Based Heterojunction Field Effect Transistors, Samiul Hasan

Theses and Dissertations

III-Nitride-based compound semiconductors have unique properties such as high bandgap and high breakdown field, which make them attractive for a variety of applications, including high-power and high-frequency electronics and optoelectronics. The most common types of III-Nitride-based field effect transistors (FETs) are aluminum gallium nitride (AlGaN)/gallium nitride (GaN) based, which suffer from some inherent problems such as virtual gate effect, current collapse, gate leakage, etc. The solution to this problem can be the inclusion of a dielectric passivation layer under the gate. However, the addition of the dielectric layer impacts one of the most critical device-controlling parameters, “threshold voltage”, which suffers …

Design And Fabrication Of High-Resolution Epitaxial 4h-Sic Metal Insulator Semiconductor Detectors, Omerfaruk Karadavut

Theses and Dissertations

In the last two decades, significant strides have been made in the epitaxial film growth of 4H-silicon carbide (4H-SiC), establishing it as a premier wide bandgap material for radiation detection application under harsh environments. This is primarily attributed to its unique combination of physical properties such as high thermal conductivity, wide bandgap, robust breakdown field, and radiation hardness. Metal/4H-SiC epitaxial layer Schottky barrier diodes (SBDs) have emerged as reliable radiation detectors for harsh environments. However, the utilization of thicker epitaxial layer devices encounters challenges due to the minimum achievable doping concentration in 4H-SiC epitaxial layers, necessitating higher bias voltages for …

Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris

Electrical & Computer Engineering Theses & Dissertations

Every year in the United States many people are killed or injured when maritime vessels collide with other vessels or fixed objects. According to the United States Coast Guard, the top contributing factors to these collisions are operator inattention, operator inexperience and an improper lookout. Larger commercial vessels are required to have RADAR systems which support Automatic RADAR Plotting Aid (ARPA) which can automatically detect collisions and alert an operator to change course. These systems can be very expensive which put them out of reach of the average recreational boater. It is however possible to implement a low cost ARPA …

Fabrication Of Smooth Sac305 Thin Films Via Magnetron Sputtering And Evaluations Of Microstructure, Creep, And Electrical Resistivity, Manish Ojha

Mechanical & Aerospace Engineering Theses & Dissertations

SAC305 (96.5%Sn-3%Ag-0.5%Cu) is the leading alternative to the traditional Sn-Pb solder eutectic alloy owing to its low melting temperature, better compatibility with other components, and excellent mechanical/structural properties. In the realm of modern electronics, where devices are increasingly miniaturized, the design and characterization of thin solder joints become paramount. The orientation and size of the grains within the solder can influence its ability to withstand mechanical stresses. However, research on SAC thin films remains sparse, and these films present unique challenges and characteristics compared to their bulk counterparts, influenced by factors like interfaces, stresses, thickness, microstructure, and the nature of …

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara

Physics Theses & Dissertations

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …

Design And Characterization Of 2.4ghz Antennas For Wireless Sensor Applications, Luis Zogby Brennan

Dissertations and Theses

Wireless sensor networks benefit greatly from advances in circuit integration and miniaturization. However, antennas are bound to specific geometries both in terms of fundamental limits and their response to immediate surroundings. As such, various successful techniques for antenna miniaturization must still be carefully tested and characterized as part of the design process of a sensor system. The work presented here fully characterizes a number of miniaturized 2.4GHz antennas and successfully integrates designs into a sensor system using the highly integrated Single Chip Micro Mote (SCµM), which uses a crystal-less radio design resulting in the requirement of only a …

Digital Realization Of Spiking Neural Network, Mahsasadat Seyedbarhagh

Electronic Theses and Dissertations

Spiking Neural Network which is known as the third generation of artificial neural networks can imitate the same biological patterns of human brain. Neuromorphic Computing is a multidisciplinary research topic which employs digital and analog platforms to implement bio-inspired systems and is able to operate parallelly with low-power consumption. This research study presents the digital design for several bio-inspired systems such as biophysical spiking neuron, calcium signaling astrocyte, and a neuron-astrocyte interaction models using various approximation methodologies. Astrocytes have an essential impact within the neural network and their role is to maintain support for neuron, control the ion hemostasis and …