Physical Sciences and Mathematics Commons^™

The Tidal Prism, Viable Eelgrass Habitat, And The Effects Of Sea Level Rise In Morro Bay, Kaden A. Caliendo

Master's Theses

The tidal prism, or the volume of water exchanged from the sea to an estuary from mean low to mean high tide, influences system hydrodynamics and ecological functioning. Since 1884, the tidal prism in Morro Bay, California has been estimated to be decreasing over time due to sedimentation from upstream practices. What is the current tidal prism in Morro Bay and how will that change with sea level rise? How will eelgrass respond to rising sea levels?

For this study, inexpensive tidal gauges were deployed at four locations in Morro Bay from March to August 2023 to measure spatially varying …

Smartphone Based Object Detection For Shark Spotting, Darrick W. Oliver

Master's Theses

Given concern over shark attacks in coastal regions, the recent use of unmanned aerial vehicles (UAVs), or drones, has increased to ensure the safety of beachgoers. However, much of city officials' process remains manual, with drone operation and review of footage still playing a significant role. In pursuit of a more automated solution, researchers have turned to the usage of neural networks to perform detection of sharks and other marine life. For on-device solutions, this has historically required assembling individual hardware components to form an embedded system to utilize the machine learning model. This means that the camera, neural processing …

Understanding The Flow Dynamics Of The Pearl River, Ms, Through Hydrodynamic Modeling, Nahruma Mehzabeen Pieu

Master's Theses

The Pearl River brings fresh water and nutrients into Lake Borgne regulating conditions for oyster growth in estuarine waters. However, there are no flow measurement stations installed on East Pearl or West Pearl either at the river outlets or after the upstream bifurcation of the Pearl. This study aims to model the Lower Pearl River to understand the flow dynamics in the major branches, and to determine the final outflow distribution into the Mississippi Sound, aiming to improve river forcing for ocean models studying estuarine dynamics of the Mississippi Sound.

Synthetic meandering bathymetry with updated banks is developed and applied …

Distributed Control Of Servicing Satellite Fleet Using Horizon Simulation Framework, Scott Plantenga

Master's Theses

On-orbit satellite servicing is critical to maximizing space utilization and sustainability and is of growing interest for commercial, civil, and defense applications. Reliance on astronauts or anchored robotic arms for the servicing of next-generation large, complex space structures operating beyond Low Earth Orbit is impractical. Substantial literature has investigated the mission design and analysis of robotic servicing missions that utilize a single servicing satellite to approach and service a single target satellite. This motivates the present research to investigate a fleet of servicing satellites performing several operations for a large, central space structure.

This research leverages a distributed control approach, …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis

Master's Theses

This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.

The third part involved applying the Diamond Dye solution by spraying it onto …

Wildfire Spread Prediction Using Attention Mechanisms In U-Net, Kamen Haresh Shah, Kamen Haresh Shah

Master's Theses

An investigation into using attention mechanisms for better feature extraction in wildfire spread prediction models. This research examines the U-net architecture to achieve image segmentation, a process that partitions images by classifying pixels into one of two classes. The deep learning models explored in this research integrate modern deep learning architectures, and techniques used to optimize them. The models are trained on 12 distinct observational variables derived from the Google Earth Engine catalog. Evaluation is conducted with accuracy, Dice coefficient score, ROC-AUC, and F1-score. This research concludes that when augmenting U-net with attention mechanisms, the attention component improves feature suppression …

Effects Of Experimental Scale On The Adsorption Of Two Pharmaceutical Drugs Detected In Municipal Wastewater Effluent, Michael Moore

Master's Theses

Pharmaceutical drugs are being produced and consumed in increasing quantities every year and are poorly treated by conventional wastewater treatment processes, leading to increasing detection of such compounds in surface water, groundwater, and municipal drinking water. Soil aquifer treatment (SAT) is a promising method for treating these emerging compounds through combined adsorption and degradation of target compounds in soil. This thesis examines the consistency of results from typical studies like adsorption isotherms and soil columns utilized in analysis of SAT performance, across varying experimental scales. The adsorption behavior of two pharmaceuticals was investigated as a function of experimental scale and …

On The Mobility Of Small Aperture Telescopes For Initial Orbit Determination And Apparent Magnitude Derivation Of Low Earth Satellites, Jonathan Ian Hernandez

Master's Theses

Maintaining Space Domain Awareness (SDA) of satellites in low Earth orbit (LEO) requires effective methods of tracking and characterization. Optical measurements of these objects are generally sparse due to limited access intervals and high angular rates. Light pollution and geographic obstructions may also preclude consistent observations. However, a mobile small aperture telescope grants the ability to minimize such environmental effects, thereby increasing capture likelihoods for objects within this regime. By enhancing LEO satellite visibility in this way, extensive orbital and visual data are obtainable.

An 8-inch Meade LX200GPS telescope equipped with a Lumenera SKYnyx2-0M CCD camera comprises the system that …

Chitosan Graphene Composite Fabrication And Characterization For Treatment Of Harmful Algal Blooms And Toxins, Sarah Zetterholm

Master's Theses

Chitosan graphene composites were fabricated and characterized as a management strategy for harmful algal blooms (HABs) caused by various species of cyanobacteria. These chitosan graphene materials were compared to previously studied chitosan graphene-oxide composites in both material properties and HAB treatment. In previous studies, adsorption of the cyanobacteria onto the surface of the composite materials has been observed. Investigations of the pure materials for these composites are also included in this study to determine whether removal is a result of charge interactions with the composite, or as an inherent property of the graphene or graphene oxide. Initial results suggest that …

A Study Of Implementation Methodologies For Distributed Real Time Collaboration, Lauren A. Craft

Master's Theses

Collaboration drives our world and is almost unavoidable in the programming industry. From higher education to the top technological companies, people are working together to drive discovery and innovation. Software engineers must work with their peers to accomplish goals daily in their workplace. When working with others there are a variety of tools to choose from such as Google Docs, Google Colab and Overleaf. Each of the aforementioned collaborative tools utilizes the Operational Transform (OT) technique in order to implement their real time collaboration functionality. Operational transform is the technique seen amongst most if not all major collaborative tools in …

Modeling And Solving The Outsourcing Risk Management Problem In Multi-Echelon Supply Chains, Arian A. Nahangi

Master's Theses

Worldwide globalization has made supply chains more vulnerable to risk factors, increasing the associated costs of outsourcing goods. Outsourcing is highly beneficial for any company that values building upon its core competencies, but the emergence of the COVID-19 pandemic and other crises have exposed significant vulnerabilities within supply chains. These disruptions forced a shift in the production of goods from outsourcing to domestic methods.

This paper considers a multi-echelon supply chain model with global and domestic raw material suppliers, manufacturing plants, warehouses, and markets. All levels within the supply chain network are evaluated from a holistic perspective, calculating a total …

Soarnet, Deep Learning Thermal Detection For Free Flight, Jake T. Tallman

Master's Theses

Thermals are regions of rising hot air formed on the ground through the warming of the surface by the sun. Thermals are commonly used by birds and glider pilots to extend flight duration, increase cross-country distance, and conserve energy. This kind of powerless flight using natural sources of lift is called soaring. Once a thermal is encountered, the pilot flies in circles to keep within the thermal, so gaining altitude before flying off to the next thermal and towards the destination. A single thermal can net a pilot thousands of feet of elevation gain, however estimating thermal locations is not …

Design And Characterization Of Standard Cell Library Using Finfets, Phanindra Datta Sadhu

Master's Theses

The processors and digital circuits designed today contain billions of transistors on a small piece of silicon. As devices are becoming smaller, slimmer, faster, and more efficient, the transistors also have to keep up with the demands and needs of the daily user. Unfortunately, the CMOS technology has reached its limit and cannot be used to scale down due to the transistor's breakdown caused by short channel effects. An alternative solution to this is the FinFET transistor technology, where the gate of the transistor is a three dimensional fin that surrounds the transistor and prevents the breakdown caused by scaling …

Multi-Scale Computational Modeling Of Metal/Ceramic Interfaces, Abu Shama Mohammad Miraz

Master's Theses

Multi-scale atomistic calculations were carried out to understand the interfacial features that dictate the mechanical integrity of the metal/ceramic nanolaminates. As such, first principles density functional theory (DFT) calculations were performed to understand the electronic and atomistic factors governing adhesion and resistance to shear for simple metal/ceramic interfaces, whereas molecular dynamics (MD) simulations were performed to observe the impact of interfacial structures, such as misfit dislocation network geometries and orientation relationships, on interfacial mechanical properties.

For the DFT investigation, we choose metals with different crystal structures, namely - Cu (fcc), Cr (bcc) and Ti (hcp) along with a variety of …

A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships, Ojonoka Erika Atawodi

Master's Theses

An important feature of an Autonomous Surface Vehicles (ASV) is its capability of automatic object detection to avoid collisions, obstacles and navigate on their own.

Deep learning has made some significant headway in solving fundamental challenges associated with object detection and computer vision. With tremendous demand and advancement in the technologies associated with ASVs, a growing interest in applying deep learning techniques in handling challenges pertaining to autonomous ship driving has substantially increased over the years.

In this thesis, we study, design, and implement an object recognition framework that detects and recognizes objects found in the sea. We first curated …

Comparing Radiation Shielding Potential Of Liquid Propellants To Water For Application In Space, John Czaplewski

Master's Theses

The radiation environment in space is a threat that engineers and astronauts need to mitigate as exploration into the solar system expands. Passive shielding involves placing as much material between critical components and the radiation environment as possible. However, with mass and size budgets, it is important to select efficient materials to provide shielding. Currently, NASA and other space agencies plan on using water as a shield against radiation since it is already necessary for human missions. Water has been tested thoroughly and has been proven to be effective. Liquid propellants are needed for every mission and also share similar …

Investigation On The Use Of Small Aperture Telescopes For Leo Satellite Orbit Determination, Luis R. Curiel Iii

Master's Theses

The following thesis regards the use of small aperture telescopes for space domain awareness efforts. The rapidly populating space domain was motivation for the development of a new operation scheme to conduct space domain awareness feasibility studies using small telescopes. Two 14-inch Schmidt-Cassegrain Telescopes at the California Polytechnic State University and the Air Force Research Lab in Kirtland AFB, NM, in conjunction with a dedicated CCD camera and a commercial DSLR camera, were utilized to conduct optical observations on satellites in Earth orbit.

Satellites were imaged during August 2019, and from January 2020 to March 2020, resulting in the collection …

Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman

Master's Theses

Several regions of the Western United States utilize statistical binary classification models to predict and manage debris flow initiation probability after wildfires. As the occurrence of wildfires and large intensity rainfall events increase, so has the frequency in which development occurs in the steep and mountainous terrain where these events arise. This resulting intersection brings with it an increasing need to derive improved results from existing models, or develop new models, to reduce the economic and human impacts that debris flows may bring. Any development or change to these models could also theoretically increase the ease of collection, processing, and …

Telescope Parallel Actuator Mount: Control And Testing, Samuel S. Artho-Bentz

Master's Theses

This thesis approaches the task of designing a control system for the Parallel Actuator Mount developed by Dr. John Ridgely and Mr. Garrett Gudgel. It aims to create a base framework that directly controls the telescope and can be expanded to accept external command. It incorporates lower priced components and develops more easily approachable software with great functionality. An open-loop method for velocity control is established. Developing repeatable tests is a major focus. Testing finds the control methods developed result in velocity error of less than 5% and position error of less than 1.5% despite several mechanical issues and inaccuracies. …

An Adaptive Approach To Gibbs’ Phenomenon, Jannatul Ferdous Chhoa

Master's Theses

Gibbs’ Phenomenon, an unusual behavior of functions with sharp jumps, is encountered while applying the Fourier Transform on them. The resulting reconstructions have high frequency oscillations near the jumps making the reconstructions far from being accurate. To get rid of the unwanted oscillations, we used the Lanczos sigma factor to adjust the Fourier series and we came across three cases. Out of the three, two of them failed to give us the right reconstructions because either it was removing the oscillations partially but not entirely or it was completely removing them but smoothing out the jumps a little too much. …

Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen

Master's Theses

Current methods of production forecasting such as decline curve analysis (DCA) or numerical simulation require years of historical production data, and their accuracy is limited by the choice of model parameters. Unconventional resources have proven challenging to apply traditional methods of production forecasting because they lack long production histories and have extremely variable model parameters. This research proposes a data-driven alternative to reservoir simulation and production forecasting techniques. We create a proxy-well model for predicting cumulative oil production by selecting statistically significant well completion parameters and reservoir information as independent predictor variables in regression-based models. Then, principal component analysis (PCA) …

Conceptual Design Of A South Pole Carrier Pigeon Uav, Kendrick M. Dlima

Master's Theses

Currently, the South Pole has a large data problem. It is estimated that 1.2 TB of data is being produced every day, but less than 500 GB of that data is being uploaded via aging satellites to researchers in other parts of the world. This requires those at the South Pole to analyze the data and carefully select the parts to send, possibly missing out on vital scientific information. The South Pole Carrier Pigeon will look to bridge this data gap.

The Carrier Pigeon will be a small unmanned aerial vehicle that will carry a 30 TB solid-state hard drive …

A Study Of The Design Of Adaptive Camber Winglets, Justin J. Rosescu

Master's Theses

A numerical study was conducted to determine the effect of changing the camber of a winglet on the efficiency of a wing in two distinct flight conditions. Camber was altered via a simple plain flap deflection in the winglet, which produced a constant camber change over the winglet span. Hinge points were located at 20%, 50% and 80% of the chord and the trailing edge was deflected between -5° and +5°. Analysis was performed using a combination of three-dimensional vortex lattice method and two-dimensional panel method to obtain aerodynamic forces for the entire wing, based on different winglet camber configurations. …

Design Of A 5 Degree Of Freedom Kinematic Stage For The Dual Crystal Backlighter Imager Diagnostic, Nicholas Nguyen

Master's Theses

The National Ignition Facility (NIF) is home to the world’s most energetic laser. The facility is one of the leading centers in inertial confinement fusion (ICF) experiments to research and understand sustainable fusion energy. To fully document and understand the physics occurring during experiments, precise diagnostics are used for a wide range of purposes. One diagnostic, the crystal backlighter imager (CBI), allows for X-ray imaging of the target at late stages of its implosion.

The aim of this project was to increase the current capabilities of the CBI diagnostic with the addition of a second crystal. This thesis focuses on …

Investigation On The Morphology Of Charge-Transfer Complexes In Low Density Polyethylene, Wade Korf

Master's Theses

Fillers are used ubiquitously throughout the fields of polymer and material science to overcome many inherent limitations to polymeric materials (i.e. poor stiffness or strength) and to expand their potential applications. There is a need to develop controllable particle architectures to better understand fundamental structure-property relationships in particle reinforced polymer composites. Charge-transfer complexes (CTCs) can assemble in situ into various needle and dendritic shapes via simple fabrication processes and at low loading levels. In this study, the effect of tetrathiafulvalene (TTF) and 7,7,8,8-tetracyanoquinodimethane (TCNQ) CTC crystallites of various shapes and sizes on composite mechanical properties was investigated in an LDPE …

Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge

Master's Theses

Convolutional Neural Networks (CNNs) are a widely accepted means of solving complex classification and detection problems in imaging and speech. However, problem complexity often leads to considerable increases in computation and parameter storage costs. Many successful attempts have been made in effectively reducing these overheads by pruning and compressing large CNNs with only a slight decline in model accuracy. In this study, two pruning methods are implemented and compared on the CIFAR-10 database and an ECG arrhythmia classification task. Each pruning method employs a pruning phase interleaved with a finetuning phase. It is shown that when performing the scale-factor pruning …

A Rotating Aperture Mask For Small Telescopes, Edward L. Foley

Master's Theses

Observing the dynamic interaction between stars and their close stellar neighbors is key to establishing the stars’ orbits, masses, and other properties. Our ability to visually discriminate nearby stars is limited by the power of our telescopes, posing a challenge to astronomers at small observatories that contribute to binary star surveys. Masks placed at the telescope aperture promise to augment the resolving power of telescopes of all sizes, but many of these masks must be manually and repetitively reoriented about the optical axis to achieve their full benefits. This paper introduces a design concept for a mask rotation mechanism that …

Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm

Master's Theses

Machine learning has been gaining popularity over the past few decades as computers have become more advanced. On a fundamental level, machine learning consists of the use of computerized statistical methods to analyze data and discover trends that may not have been obvious or otherwise observable previously. These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new material discovery has been of high interest …

The Performance Cost Of Security, Lucy R. Bowen

Master's Theses

Historically, performance has been the most important feature when optimizing computer hardware. Modern processors are so highly optimized that every cycle of computation time matters. However, this practice of optimizing for performance at all costs has been called into question by new microarchitectural attacks, e.g. Meltdown and Spectre. Microarchitectural attacks exploit the effects of microarchitectural components or optimizations in order to leak data to an attacker. These attacks have caused processor manufacturers to introduce performance impacting mitigations in both software and silicon.

To investigate the performance impact of the various mitigations, a test suite of forty-seven different tests was created. …