Engineering Commons^™

Shape Memory Alloy Capsule Micropump For Drug Delivery Applications, Youssef Mohamed Kotb

Theses and Dissertations

Implantable drug delivery devices have many benefits over traditional drug administration techniques and have attracted a lot of attention in recent years. By delivering the medication directly to the tissue, they enable the use of larger localized concentrations, enhancing the efficacy of the treatment. Passive-release drug delivery systems, one of the various ways to provide medication, are great inventions. However, they cannot dispense the medication on demand since they are nonprogrammable. Therefore, active actuators are more advantageous in delivery applications. Smart material actuators, however, have greatly increased in popularity for manufacturing wearable and implantable micropumps due to their high energy …

Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish

Theses and Dissertations

Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …

Development Of An Electromagnetic System For Wireless Magnetic Manipulation Of Soft Capsule Endoscope For Drug Delivery Applications, Nada Ashraf Hussein Mahmoud

Theses and Dissertations

Wireless capsule endoscopy (WCE) is a remarkable diagnostic device that examines the gastrointestinal (GI) tract. The WCE is a small capsule integrated with a camera that is used to visualize the inner mucosa of the GI tract. WCE has been proven to be the most effective method to diagnose GI diseases and GI cancers. The procedure reduces the discomfort and risk compared to conventional endoscopy methods. However, current WCEs lack the ability to take a biopsy or deliver a drug to a specific location. Those therapeutic functions can be introduced by wirelessly controlled WCEs. This thesis introduces an electromagnetic system …

Nano-Patterned Si Structures For Optical Filters And Electro-Mechanical Relays: Fabrication, Characterization, Prospects, And Limitations, Md Ataul Mamun

Theses and Dissertations

Nanofabrication technology, especially nanopatterning, is a rapidly advancing field that has already resulted in creating novel devices and holds promise for producing even more with unmatched performance. These techniques also allow us to gain insight into physical phenomena at the micro- and nanoscale. The ultimate performance of nanofabricated devices and their compatibility with existing Si-based CMOS technology hinge upon the careful selection of materials and precise design, coordinated with meticulous pattern transfer. In this work, we applied nanopatterning techniques on silicon to create optical filters for the shortwave infrared (SWIR) region and nanoelectromechanical system (NEMS) relay-based logic gates. Additionally, these …

Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov

Theses and Dissertations

This study explores the potential of beryllium (Be) as an alternative dopant to magnesium (Mg) for achieving higher hole concentrations in gallium nitride (GaN). Despite Mg prominence as an acceptor in optoelectronic and high-power devices, its deep acceptor level at 0.22 eV above the valence band limits its effectiveness. By examining Be, this research aims to pave the way to overcoming these limitations and extend the findings to aluminum nitride and aluminum gallium nitride (AlGaN) alloy. Key contributions of this work include. i)Identification of three Be-related luminescence bands in GaN through photoluminescence spectroscopy, improving the understanding needed for further material …

Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber

Theses and Dissertations

As cyber-physical systems (CPS) become more integrated into everyday life, the security of these systems must also be considered during their development due to their ever-increasing importance. With the growth of physical components in the system, more autonomous control requirements, and increased dependence on proper functionality, verifying system safety and correct operation becomes increasingly difficult. CPS have become more complex through the combination of additional hardware and the resulting interconnected software in many layers, each requiring unique security solutions. One example of such a safety-critical CPS embedded system is the Flight Control System (FCS) of an Unmanned Aerial System (UAS). …

Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis

Theses and Dissertations

This dissertation explores how to better manage resources in mobile networks, especially for enhancing the performance of Unmanned Aerial Vehicles (UAV)-supported IoT networks. We explored ways to set up a flexible communication architecture that can handle large IoT deployments by making good use of mobile core network resources like bearers and data paths. We developed strategies that meet the needs of IoT networks and enhance network performance. We also developed and tested a system that combines traffic from several mobile devices that use the same user identity and network resources within the core mobile network. We used everyday smartphones, SIM …

Modeling And Mitigating Power Grid Vulnerabilities: A Comprehensive Analysis Of Renewable Energy Integration, Cascading Failures, And Microgrid Resilience, Saikat Das

Theses and Dissertations

In modern power systems, rapid integration of renewable energy and the emergence of microgrid technology emphasize the necessity for a comprehensive understanding of vulnerabilities and robust defense mechanisms. The research begins with an exploration of power grid vulnerabilities to cascading failure amidst the increasing integration of renewable energy sources. A novel power balance technique is employed for cascading failure analysis and power grid vulnerability measurement. Simulation results indicate that the growing penetration of renewable energy has a proportionally higher impact on grid vulnerability to cascading failures. After a certain level of renewable energy penetration, some systems may deteriorate rapidly, necessitating …

Traffic Light Detection And V2i Communications Of An Autonomous Vehicle With The Traffic Light For An Effective Intersection Navigation Using Mavs Simulation, Mahfuzur Rahman

Theses and Dissertations

Intersection Navigation plays a significant role in autonomous vehicle operation. This paper focuses on enhancing autonomous vehicle intersection navigation through advanced computer vision and Vehicle-to-Infrastructure (V2I) communication systems. The research unfolds in two phases. In the first phase, an approach utilizing YOLOv8s is proposed for precise traffic light detection and recognition, trained on the Small-Scale Traffic Light Dataset (S2TLD). The second phase establishes seamless connectivity between autonomous vehicles and traffic lights in a simulated Mississippi State University Autonomous Vehicle Simulation (MAVS) environment resembling a small city with multiple intersections. This V2I system enables the transmission of Signal Phase and Timing …

Neural Networks For Improved Signal Source Enumeration And Localization With Unsteered Antenna Arrays, John T. Rogers Ii

Theses and Dissertations

Direction of Arrival estimation using unsteered antenna arrays, unlike mechanically scanned or phased arrays, requires complex algorithms which perform poorly with small aperture arrays or without a large number of observations, or snapshots. In general, these algorithms compute a sample covriance matrix to obtain the direction of arrival and some require a prior estimate of the number of signal sources. Herein, artificial neural network architectures are proposed which demonstrate improved estimation of the number of signal sources, the true signal covariance matrix, and the direction of arrival. The proposed number of source estimation network demonstrates robust performance in the case …

Improved Methodology For Conducted Emi Assessment Of Power Electronics And Line Impedance Measurement, Mark Anthony Didat

Theses and Dissertations

Electromagnetic Interference (EMI), primarily common mode (CM), is problematic in a wide range of electronic circuits due to its propensity to radiate, particularly in high power applications. It is routine for much effort and resources to be dedicated to its characterization and reduction as EMI compliance is a requirement for most electronic systems and devices, including power electronics. Many well-known factors contribute to a system’s EMI performance including intentional coupling from system components as well as unintentional coupling from parasitics. Sources of intentional coupling may include Y-capacitors intended to mitigate EMI as part of a filter. Unintentional coupling is more …

Use Of Digital Twins To Mitigate Communication Failures In Microgrids, Andrew Eggebeen

Theses and Dissertations

This work investigates digital twin (DT) applications for electric power system (EPS) resilience. A novel DT architecture is proposed consisting of a physical twin, a virtual twin, an intelligent agent, and data communications. Requirements for the virtual twin are identified. Guidelines are provided for generating, capturing, and storing data to train the intelligent agent. The relationship between the DT development process and an existing controller hardware-in-the-loop (CHIL) process is discussed. To demonstrate the proposed DT architecture and development process, a DT for a battery energy storage system (BESS) is created based on the simulation of an industrial nanogrid. The creation …

A Design Strategy To Improve Machine Learning Resiliency Of Physically Unclonable Functions Using Modulus Process, Yuqiu Jiang

Theses and Dissertations

Physically unclonable functions (PUFs) are hardware security primitives that utilize non-reproducible manufacturing variations to provide device-specific challenge-response pairs (CRPs). Such primitives are desirable for applications such as communication and intellectual property protection. PUFs have been gaining considerable interest from both the academic and industrial communities because of their simplicity and stability. However, many recent studies have exposed PUFs to machine-learning (ML) modeling attacks. To improve the resilience of a system to general ML attacks instead of a specific ML technique, a common solution is to improve the complexity of the system. Structures, such as XOR-PUFs, can significantly increase the nonlinearity …

Project Thetis: A Low-Cost, Low-Profile Inertial Data Logger, Braidan Duffy

Theses and Dissertations

This thesis details the design, testing, calibration, and verification of a nine degree of freedom inertial measurement data logger for use with floating bodies. The instrument was conceived to address limitations of equipment used in classes within the Ocean Engineering department at Florida Institute of Technology. By meeting with several stakeholders and end users, a series of stakeholder requirements, capabilities, and component-level requirements were de- veloped that informed the design constraints. There were several hardware iterations of the board, culminating in Revision F5 which was extensively tested and proven. The design was inspected after testing concluded to determine which capabilities …

Gpu Based Monte Carlo Estimation Of Eddy Current Losses In Electromagnetic Coil-Core System, Adwaith Ravichandran

Theses and Dissertations

A novel parallelizable probabilistic approach to model eddy currents in AC electromagnets is presented in this research. Consequently, power loss associated with the formation of these eddy currents is estimated and validated using experimental data. Furthermore, predicting the effect of ferromagnetic alternating field enhancement on power loss in the source excitation winding has been an active area of research. Unlike a stationary field, an alternating sinusoidal field diffuses partially into the ferromagnetic material leading to a predictably sub-optimal field enhancement. To model these physics, finite element techniques employ nonlinear iterative solvers which are time consuming. A novel method is developed …

Metasurface Beam-Steering Antenna At X-Band Frequencies With Cloaking Applications, Erik Jermaine Kosh

Theses and Dissertations

I intend to use metasurface materials to adjust antenna field properties while applying a cloaking application to the antenna. Cloaking applications have been used to shield the neighboring antenna waveforms so that they do not affect it’s antenna patterns and reduce the mutual coupling between the two antennas [15], [16]. In this application, I propose a metasurface beam-steering antenna at X-band frequencies using mantle-cloaking techniques to adjust and direct the beam-steering while ignoring other adjacent antenna patterns.

The first part of this application provides a method for cloaking antennas that are close to each other in distance (less than a …

Qasm-To-Hls: A Framework For Accelerating Quantum Circuit Emulation On High-Performance Reconfigurable Computers, Anshul Maurya

Theses and Dissertations

High-performance reconfigurable computers (HPRCs) make use of Field-Programmable Gate Arrays (FPGAs) for efficient emulation of quantum algorithms. Generally, algorithm-specific architectures are implemented on the FPGAs and there is very little flexibility. Moreover, mapping a quantum algorithm onto its equivalent FPGA emulation architecture is challenging. In this work, we present an automation framework for converting quantum circuits to their equivalent FPGA emulation architectures. The framework processes quantum circuits represented in Quantum Assembly Language (QASM) and derives high-level descriptions of the hardware emulation architectures for High-Level Synthesis (HLS) on HPRCs. The framework generates the code for a heterogeneous architecture consisting of a …

Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad

Theses and Dissertations

Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …

Characterization Of Human Mobility From Cellular Data, Zaid Matloub

Theses and Dissertations

This dissertation investigates human mobility patterns using crowd-sourced cellular network data from different Metropolitan Statistical Areas (MSAs) in the United States, spanning the Houston, New York-Newark, NJ City, and 13 other significant MSAs. By focusing on prominent spatial mobility parameters highlighted in existing literature, the study unveils consistent findings regarding the predictability of human mobility across diverse time scales and geographic regions. The research underscores the significance of selecting appropriate sampling thresholds based on the mobility parameters being examined, the size of the dataset, and available computational resources. Through a meticulous analysis, it emerges that while values such as mean …

Robust And Uncertainty-Aware Image Classification Using Bayesian Vision Transformer Model, Fazlur Rahman Bin Karim

Theses and Dissertations

Transformer Neural Networks have emerged as the predominant architecture for addressing a wide range of Natural Language Processing (NLP) applications such as machine translation, speech recognition, sentiment analysis, text anomaly detection, etc. This noteworthy achievement of Transformer Neural Networks in the NLP field has sparked a growing interest in integrating and utilizing Transformer models in computer vision tasks. The Vision Transformer (ViT) model efficiently captures long-range dependencies by employing a self-attention mechanism to transform different image data into meaningful, significant representations. Recently, the Vision Transformer (ViT) has exhibited incredible performance in solving image classification problems by utilizing ViT models, thereby …

Electromagnetic Field Analysis, Materials Characterization, And Advanced Modeling Of Modern Guitar Pickups, Luis Alonso Villarreal

Theses and Dissertations

This Thesis establishes the foundations of modern guitar pickup theory, enhancing current pickup design by an increase in voltage output, reduction of DC resistance, and a reduction of production costs. This research investigates factors that have received insufficient attention, such as the performance of different magnetic materials, magnet geometry, bobbin geometry, metal effects, etc. An equation to calculate the output of guitar pickups is developed. Additionally, this work constructs a modern pickup using the techniques developed in this thesis incorporating theory and advanced modeling techniques to simulate changes in performance and interactions with different magnetic materials and geometries. The new …

Robust Uncertainty Estimation Framework In Deep Reinforcement Learning For Active Slam, Bryan Joseph Pedraza

Theses and Dissertations

Autonomous mobile robots are essential in various domains such as industry, manufacturing and healthcare. Navigating autonomously and avoiding obstacles are crucial tasks that involve localizing the robot to explore and map unknown environments without prior knowledge. Simultaneous localization and mapping (SLAM) present significant challenges. In this study, we introduce a new approach to address robust navigation and mapping of robot actions using Bayesian Actor-Critic (A2C) reinforcement learning. The A2C framework combines policy-based and value-based learning by dividing the model into two components: (1) the policy model (Actor) determines the actions based on the state, and (2) the value model (Critic) …

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 …

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 …

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 …

Better Models For High-Stakes Tasks, Jacob Ryan Epifano

Theses and Dissertations

The intersection of machine learning and healthcare has the potential to transform medical diagnosis, treatment, and research. Machine learning models can analyze vast amounts of medical data and identify patterns that may be too complex for human analysis. However, one of the major challenges in this field is building trust between users and the model. Due to things like high false alarm rate and the black box nature of machine learning models, patients and medical professionals need to understand how the model arrives at its recommendations. In this work, we present several methods that aim to improve machine learning models …

Resource Optimization Of Edge Servers Dealing With Priority-Based Workloads By Utilizing Service Level Objective-Aware Virtual Rebalancing, Amna Shahid

Theses and Dissertations

IoT enables profitable communication between sensor/actuator devices and the cloud. Slow network causing Edge data to lack Cloud analytics hinders real-time analytics adoption. VRebalance solves priority-based workload performance for stream processing at the Edge. BO is used in VRebalance to prioritize workloads and find optimal resource configurations for efficient resource management. Apache Storm platform was used with RIoTBench IoT benchmark tool for real-time stream processing. Tools were used to evaluate VRebalance. Study shows VRebalance is more effective than traditional methods, meeting SLO targets despite system changes. VRebalance decreased SLO violation rates by almost 30% for static priority-based workloads and 52.2% …