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 …

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 …

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 …

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 …

Exploring Bistatic Scattering Modeling For Land Surface Applications Using Radio Spectrum Recycling In The Signal Of Opportunity Coherent Bistatic Simulator, Dylan R. Boyd

Theses and Dissertations

The potential for high spatio-temporal resolution microwave measurements has urged the adoption of the signals of opportunity (SoOp) passive radar technique for use in remote sensing. Recent trends in particular target highly complex remote sensing problems such as root-zone soil moisture and snow water equivalent. This dissertation explores the continued open-sourcing of the SoOp coherent bistatic scattering model (SCoBi) and its use in soil moisture sensing applications. Starting from ground-based applications, the feasibility of root-zone soil moisture remote sensing is assessed using available SoOp resources below L-band. A modularized, spaceborne model is then developed to simulate land-surface scattering and delay-Doppler …

Eddy Current Defect Response Analysis Using Sum Of Gaussian Methods, James William Earnest

Theses and Dissertations

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics.

An Epileptic Seizure Detection Method From Eeg Signals Based On A Classifier-Driven Feature Reduction Technique, Raymond N. Kamel

Theses and Dissertations

Epileptic seizure detection can improve the quality of life of epileptic patients, allow for more accurate medication, and minimize the risk of sudden unexpected death in epilepsy (SUDEP). This thesis work aims to develop a robust and stable algorithm for epileptic seizure detection through the classification of EEG signals. To achieve this aim, a methodology is proposed to develop a classifier that can differentiate between the healthy (normal), interictal, and ictal states of EEG signals, while maximizing the classification accuracy and minimizing the computational redundancy. The main pillar upon which this methodology is designed is using a problem-specific classifier-driven feature …

Wifi Sensing At The Edge Towards Scalable On-Device Wireless Sensing Systems, Steven M. Hernandez

Theses and Dissertations

WiFi sensing offers a powerful method for tracking physical activities using the radio-frequency signals already found throughout our homes and offices. This novel sensing modality offers continuous and non-intrusive activity tracking since sensing can be performed (i) without requiring wearable sensors, (ii) outside the line-of-sight, and even (iii) through the wall. Furthermore, WiFi has become a ubiquitous technology in our computers, our smartphones, and even in low-cost Internet of Things devices. In this work, we consider how the ubiquity of these low-cost WiFi devices offer an unparalleled opportunity for improving the scalability of wireless sensing systems. Thus far, WiFi sensing …

Full Pattern Analysis And Comparison Of The Center Fed And Offset Fed Cassegrain Antennas With Large Focal Length To Diameter Ratios For High Power Microwave Transmission, Derek W. Mantzke

Theses and Dissertations

High power microwaves (HPM) have been a topic of research since the Cold War era. This paper will present a comparison between two Cassegrain-type antennas: the axially, or center fed, and the offset fed. Specifically, the 10 GHz operating frequency will be investigated with large focal length to diameter () ratios. Beam patterns which encompass the entire radiation pattern will be included for data validation and optimization. The simulations will follow a design of experiments factorial model to ensure all possible combinations of prescribed parameters are included, including an analysis of variance (ANOVA) study to find parameter influence on the …

Theory And Design Of A Highly Compressed Dropped-Channel Polarimetric Synthetic Aperture Radar, John T. Becker

Theses and Dissertations

Compressed sensing (CS) is a recent mathematical technique that leverages the sparsity in certain sets of data to solve an underdetermined system and recover a full set of data from a sub-Nyquist set of measurements of the data. Given the size and sparsity of the data, radar has been a natural choice to apply compressed sensing to, typically in the fast-time and slow-time domains. Polarimetric synthetic aperture radar (PolSAR) generates a particularly large amount of data for a given scene; however, the data tends to be sparse. Recently a technique was developed to recover a dropped PolSAR channel by leveraging …

Effects Of Motion Measurement Errors On Radar Target Detection, Darnell D. Parker

Theses and Dissertations

This thesis investigates the relationships present between signal-to-clutter ratios, motion measurement errors, image quality metrics, and the task of target detection, in order to discover what factor merit greater focus in order to attain the highest probability of target detection success. This investigation is accomplished by running a high number of Monte Carlo trials through a coherent target detector and analyzing the results. The aforementioned relationships are demonstrated via sample synthetic aperture radar imagery, histograms, receiver operating characteristics curves, and error bar plots.

Methods For Focal Plane Array Resolution Estimation Using Random Laser Speckle In Non-Paraxial Geometries, Phillip J. Plummer

Theses and Dissertations

The infrared (IR) imaging community has a need for direct IR detector evaluation due to the continued demand for small pixel pitch detectors, the emergence of strained-layer-super-lattice devices, and the associated lateral carrier diffusion issues. Conventional laser speckle-based modulation transfer function (MTF) estimation is dependent on Fresnel propagation and a wide-sense-stationary input random process, limiting the use of this approach for lambda (wavelength)-scale IR devices. This dissertation develops two alternative methodologies for speckle-based resolution evaluation of IR focal plane arrays (FPAs). Both techniques are formulated using Rayleigh-Sommerfield electric field propagation, making them valid in the non-paraxial geometries dictated for resolution …

Polarization-Based Image Segmentation And Height Estimation For Interferometric Sar, Augusta J. Vande Hey

Theses and Dissertations

To find scatterers in a synthetic aperture radar (SAR) image, a modification is proposed to improve peak region segmentation (PRS) with region merging. The modification considers the polarization of each pixel before it is added to a segment to ensure the segment only contains pixels of the same polarization. Prior to region merging, the polarization of the segments is compared, so that only segments with the same polarization are merged into a single region. The segmented regions are used to find the height of each scatterer through interferometric SAR (IFSAR) processing. Multiple methods of IFSAR are examined to find the …

Spatial-Spectral Analysis In Dimensionality Reduction For Hyperspectral Image Classification, Chiranjibi Shah

Theses and Dissertations

This dissertation develops new algorithms with different techniques in utilizing spatial and spectral information for hyperspectral image classification. It is necessary to perform spatial and spectral analysis and conduct dimensionality reduction (DR) for effective feature extraction, because hyperspectral imagery consists of a large number of spatial pixels along with hundreds of spectral dimensions.

In the first proposed method, it employs spatial-aware collaboration-competition preserving graph embedding by imposing a spatial regularization term along with Tikhonov regularization in the objective function for DR of hyperspectral imagery. Moreover, Collaboration representation (CR) is an efficient classifier but without using spatial information. Thus, structure-aware collaborative …

A Harmonic Radar System For Honey Bee Tracking To Better Understand Colony Collapse Disorder, William B. Woo

Theses and Dissertations

Honey bees are some of the most important pollinators for agriculture in the world and are pivotal to the health of worldwide ecosystems. Like all insects, bees struggle with exposure to parasites, diseases, and other environmental factors that can negatively affect the overall health of the colony. Recently, a new unexplainable phenomenon called Colony Collapse Disorder (CCD) has been wreaking havoc on bee populations worldwide. As a result, a system capable of tracking bees is required to understand the different contributions of chemicals, parasites, etc. to CCD. This research seeks to show data supporting the development of systems for an …

Challenges And Signal Processing Of High Strain Rate Mechanical Testing, Barae Lamdini

Theses and Dissertations

Dynamic testing provides valuable insight into the behavior of materials undergoing fast deformation. During Split-Hopkinson Pressure Bar testing, stress waves are measured using strain gauges as voltage variations that are usually very small. Therefore, an amplifier is required to amplify the data and analyze it. One of the few available amplifiers designed for this purpose is provided by Vishay Micro-Measurements which limits the user’s options when it comes to research or industry. Among the challenges of implementing the Hopkinson technology in the industry are the size and cost of the amplifier. In this work, we propose a novel design of …

Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy

Theses and Dissertations

The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in the EcoCAR Mobility …

Recognizing Traffic Signaling Gestures Through Automotive Sensors., Benjamin James Bartlett

Theses and Dissertations

As technology advances with each new day, so do the applications and uses of the different modalities of technology, including transportation, particularly in ADAS vehicles. These systems allow the vehicle to avoid collisions, change lanes, adjust the vehicle’s speed, and more without the need of driver input. However, each sensor type has a weakness, and most advanced driver- assisted system (ADAS) vehicles rely heavily on sensors, such as RGB cameras, radars, and LiDAR sensors. These visual-based sensors may collect very noisy data in cloudy, raining, foggy, or other obscuring phenomena. Radar, on the other hand, does not rely on visual …

Performance Enhancement Of Wide-Range Perception Issues For Autonomous Vehicles, Suvash Sharma

Theses and Dissertations

Due to the mission-critical nature of the autonomous driving application, underlying algorithms for scene understanding should be given special care during their development. Mostly, they should be designed with precise consideration of accuracy and run-time. Accuracy should be considered strictly which if compromised leads to faulty interpretation of the environment that may ultimately result in accidental scenarios. On the other hand, run-time holds an important position as the delayed understanding of the scene would hamper the real-time response of the vehicle which again leads to unforeseen accidental cases. These factors come as the functions of several factors such as the …

Analysis And Implementation Of Low Fidelity Radar-Based Remote Sensing For Unmanned Aircraft Systems, Matthew Duck

Theses and Dissertations

Radar-based remote sensing is consistently growing, and new technologies and subsequent techniques for characterization are changing the feasibility of understanding the environment. The emergence of easily accessible unmanned aircraft system (UAS) has broadened the scope of possibilities for efficiently surveying the world. The continued development of low-cost sensing systems has greatly increased the accessibility to characterize physical phenomena. In this thesis, we explore the viability and implementation of using UAS as a means of radar-based remote sensing for ground penetrating radar (GPR) and polarimetric scatterometry. Additionally, in this thesis, we investigate the capabilities and implementations of low-cost microwave technologies for …

Electromechanical Fatigue Properties Of Dielectric Elastomer Stretch Sensors Under Orthopaedic Loading Conditions, Andrea Karen Persons

Theses and Dissertations

Fatigue testing of stretch sensors often focuses on high amplitude, low-cycle fatigue (LCF) behavior; however, when used for orthopaedic, athletic, or ergonomic assessments, stretch sensors are subjected to low amplitude, high-cycle fatigue (HCF) conditions. As an added layer of complexity, the fatigue testing of stretch sensors is not only focused on the life of the material comprising the sensor, but also on the reliability of the signal produced during the extension and relaxation of the sensor. Research into the development of a smart sock that can be used to measure the range of motion (ROM) of the ankle joint during …

Uav Positioning Data Determined Via Aruco Tags For Aircraft Surface Inspection, Caleb B. Schmidt

Theses and Dissertations

Aircraft are frequently inspected to ensure that military and civilian safety standards are adhered to. These inspections are performed pre- and post-flight and are currently performed by trained maintenance personnel. This work furthers the automation of aircraft surface inspection by using ArUco tags to determine the position of the UAV during aerial inspections. The ArUco tag based position data was then compared to a highly accurate infrared motion capture system to determine the viability of this for accurate positioning of the vehicle. This work includes flight experiments with two different UAVs to perform a system viability comparison.

Detection And Identification Of Cellphone Emitted Light Detection And Ranging Light In Security Camera Video Footage, Tristan V. Creek

Theses and Dissertations

The prevalence of Light Detection and Ranging (LiDAR) sensors in consumer cellphones has ushered in an era of access to technologies previously inaccessible to the average person. Although LiDAR sensors emit light in the infrared spectrum invisible to the naked eye, many security cameras possess the ability to capture infrared light reflected off surfaces to detect LiDAR light in an environment. Once detected and recorded to video footage, current classification methods fail to identify the LiDAR light. Therefore, this research develops a methodology to detect LiDAR light in security camera video footage and identify it as cellphone LiDAR. A proposed …

Relative Magnetic Position And Rotation Sensor Assisted Dual-Foot Pedestrian Dead Reckoning, Jenario Y. Johnson

Theses and Dissertations

The use of wearable foot-based inertial measurement units (IMUs) incorporated in a navigation system can address the problem of single-person location tracking in situations and environments where GPS signals may be unavailable or inconsistent. This Pedestrian Dead Reckoning (PDR) approach enables standalone personal tracking. A notable solution involves using inertial measurement units (IMUs) in a filter to apply zero-velocity updates to a Kalman filter to get a position solution. This paper continues on the path of the former method by investigating the feasibility of PDR using a pair of low cost IMUs along with a pair of relative position and …

Evaluation Of The Armas-Som Framework With Real Data, Brandon M. Blakely

Theses and Dissertations

The ARMAS framework was created with the goal of developing a framework for all-source sensors which is able to combine detection, identification, calibration, model selection, and independent evaluation into a single system. Stable Observability Monitoring (SOM), augments the original ARMAS framework by enabling ARMAS to detect whether or not its Fault Detection and Exclusion (FDE) capabilities can be trusted and when additional sensor information is required to maintain resiliency. While previously tested with simulated sensor data, SOM has yet to be tested with real-life sensor data. Furthermore, ARMAS has only been tested with real-life GNSS data. This work expands on …

Global Sporadic-E Climatological Analysis Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos

Theses and Dissertations

A climatology of sporadic-E (Es) derived from a combined data set of GPS radio occultation (GPS-RO) and ground-based ionosonde soundings is presented for the period from September 2006 to February 2019. The ionosonde soundings were measured using the Lowell Digisonde International (LDI) Global Ionosphere Radio Observatory (GIRO) network consisting of 65 sites and 13,141,060 total soundings. The GPS-RO observations were taken aboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites and processed using two binary Es detection algorithms, totaling 9,072,922 occultations. The first algorithm is an S4 amplitude threshold calibrated to the occurrence of any blanketing Es …

Testbed Creation To Study Noise Radar Network Weighting Models And Data Fusion With Radio Tomographic Imaging, Ryan M. Jans

Theses and Dissertations

Significant research has been conducted on RTI weighting models; however, very little comparative research has been conducted for NRN weighting methods. In order to create comparative weighting methods for NRN, it is necessary to create a testbed which allows for RTI and NRN research to be conducted simultaneously and allow for data fusion methods to also be researched. After creating the testbed and analyzing results, the newly proposed weighting method provides an up to 33% performance increase in target localization accuracy when compared to the previous weighting model used for NRN. The attenuation image resolution improvements resulted in a 79% …

Monocular Camera Localization Using A Bag Of Visual Words From Virtual World Data, Joshua A. Rinaldi

Theses and Dissertations

The Visual Localization problem is the question of how to use visual information to determine the location of the camera that captured that data. The wide availability and low price of RGB cameras has made this useful in many fields such as SLAM, SAM and AR. This research seeks to determine if a BOVW can adequately overcome repetitious features in indoor environments and be effectively incorporated into a VL pipeline.

Deep Learning Techniques To Estimate 3d Position In Stereoscopic Imagery, Jonathan I. Nicholson

Theses and Dissertations

Current AAR efforts utilize machine vision algorithms to estimate the pose of a receiver aircraft. However, these algorithms are dependent on several conditions such as the availability of precise 3D aircraft models; the accuracy of the pipeline significantly degrades in the absence of high-quality information given beforehand. We propose a deep learning architecture that estimates the 3D position of an object based on stereoscopic imagery. We investigate the use of both machine learning techniques and neural networks to directly regress the 3D position of the receiver aircraft. We present a new position estimation framework that is based on the differences …

Design Study For An Antenna Radar Cross Section Measurement Test Fixture, Wayne C. Kreimeyer

Theses and Dissertations

Military technology requires equipment to be undetected by adversaries. Stealth aircraft are designed to be undetected through electromagnetic means by minimizing a return signature called the RCS. Therefore, it is essential to understand how antennas, which are necessary for communication, affect the overall RCS of the aircraft. The antenna is measured in a compact RADAR range. The antenna needs a structure to support it, also referred to as a test fixture, that does not interfere with the measuring process of the antenna’s RCS. This thesis set out to get the lowest RCS possible of a test fixture by evaluating different …