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Articles 211 - 240 of 3078

Full-Text Articles in Physical Sciences and Mathematics

Optimization Of Bluetooth Auracast Broadcast Audio Transmissions Via Signal Modeling, Lauren J. Puseman Mar 2024

Optimization Of Bluetooth Auracast Broadcast Audio Transmissions Via Signal Modeling, Lauren J. Puseman

Theses and Dissertations

Since 1994, Bluetooth has been used as a Personal Area Network (PAN) to transfer data between devices within a short range. After thirty years of progressive improvement in functionality, security, range, and power efficiency, the Bluetooth Special Interest Group has released a new feature called Auracast, which allows users to tune into nearby public audio streams and receive the feed directly to their wireless headphones or hearing aids. Soon, venues such as convention centers, museums, public forums, and sporting arenas can implement Auracast to better suit their needs. In addition to these public benefits, the Department of Defense can take …

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Global Empirical Model Of Sporadic-E Occurrence Rates, Eli V. Parsch Mar 2024

Global Empirical Model Of Sporadic-E Occurrence Rates, Eli V. Parsch

Theses and Dissertations

Encompassing the Earth, the ionosphere presents unique challenges to modern communication, navigation, and surveillance technologies. Intense ionization enhancements known as sporadic-E (Es), can degrade and disrupt signals in unpredictable ways. Much work has been done to understand this phenomenon and more recent efforts have attempted to model its behavior and impacts. However, there have been limited efforts at modeling global Es occurrence rates (OR) at high time resolutions. This study develops a global empirical model of blanketing sporadic-E (fbEs) occurrence rates using a Karhunen-Lo´eve Expansion (KLE) of global fbEs OR climatologies built with Global Positioning System radio occultations (GPS-RO) and …

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Investigation Of High-Latitude Gnss Radio Occulation Sporadic-E And Auroral-E Measurements, Kyle D. Roberts Mar 2024

Investigation Of High-Latitude Gnss Radio Occulation Sporadic-E And Auroral-E Measurements, Kyle D. Roberts

Theses and Dissertations

Abnormal sporadic-E (Es) occurrences were found in the high latitude regions during a recent climatology study by (Hodos, 2022), that calculated sporadic-E occurrence rates derived from a data set of GPS radio occultation (GPS-RO) and ionosondes. In this study, sporadic-E GNSS-RO techniques are shown to falsely attribute sporadic-E events to auroral-E (Ea) events. A comparative study is conducted on GPS-RO measurement techniques to find false occurrence rates for various RO techniques using a single ionosonde site in Gakona, Alaska. Phase-based RO techniques were found to be more likely to falsely attribute sporadic-E as auroral-E, while amplitude …

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Modeling Lightning Flashes In Dissimilar Non-Homogeneous Clouds, Scott R. Wolff Mar 2024

Modeling Lightning Flashes In Dissimilar Non-Homogeneous Clouds, Scott R. Wolff

Theses and Dissertations

A new methodology for near-infrared lightning radiative transfer through clouds is presented. High-resolution weather modeling is used to generate realistic three-dimensional non-homogeneous clouds, which are then used as environments for a Monte Carlo simulation of photon multiple scattering from approximations of lightning flashes. Resultant emissions from the cloud tops are in line with previous studies and satellite observations.

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Group Convolutional Decoders For Toric Codes, Jim Wang Mar 2024

Group Convolutional Decoders For Toric Codes, Jim Wang

Theses and Dissertations

Quantum Error Correction (QEC) enables both industrial and defense applications of quantum computing. Toric codes and other quantum Low-Density Parity-Check (LDPC) codes are promising and well-researched methods of QEC. However, their decoding cost increases exponentially with a computer’s qubit count. Neural Network (NN) decoders have been shown to decode a code’s error syndrome both accurately and fast enough for a real-time error correcting scheme. Recent key developments introduced Convolutional Neural Network (CNN) to implement a translationally equivariant decoder for a toric code. These CNN decoders both outperform NN decoders and require less training data. This research applies a Group Convolutional …

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Quantum Circuit Reduction Using Three Layer Transposition, Christian L. Grauberger Mar 2024

Quantum Circuit Reduction Using Three Layer Transposition, Christian L. Grauberger

Theses and Dissertations

The potential of quantum computing to revolutionize critical military applications has led the US Department of Defense to recognize it as a keen interest. However, the practical implementation of these theoretical applications on physical quantum devices is currently limited by inherent reliability and accuracy issues in quantum hardware. To mitigate errors stemming from these limitations, the incorporation of software-based solutions is imperative. Quantum circuit optimization stands out as a primary method of increasing the accuracy of quantum computations. One of the key components of this approach is circuit reduction, whereby circuits are condensed to realize the same computation using fewer …

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Neutron Spectrum Unfolding From Activation Foils Irradiated In Gamble Ii Using Deuterated Polyethylene Anodes, Christopher J. Smith Mar 2024

Neutron Spectrum Unfolding From Activation Foils Irradiated In Gamble Ii Using Deuterated Polyethylene Anodes, Christopher J. Smith

Theses and Dissertations

Neutrons can cause irreparable harm to electronics, and experiments are needed to understand their effects fully. This work explores using pulsed power, which is low-cost compared to other sources, to create a useful neutron-rich environment. Deuterated polyethylene was used as anode and catcher material to generate the neutrons from the Deuterium-Deuterium (DD) fusion reaction. A simple, effective, and repeatable method was employed to directly cast deuterated polyethylene onto polyethylene sheets to fabricate the anode and catcher. The DD reactions were made by an ion beam-driven pulsed power generator, Gamble II, with the catcher located in the cathode. Zinc, copper, aluminum, …

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Modeling & Engineering Of Usmepcom Business Intelligence Data, Merrick A. Bedford Mar 2024

Modeling & Engineering Of Usmepcom Business Intelligence Data, Merrick A. Bedford

Theses and Dissertations

This thesis investigates the USMEPCOM’s issue of modeling and engineering Business Intelligence data centralized around the MEPS of Excellence (MOE) program. MEPS around the US conduct military personnel in-processing and in doing so have a vested interest in the standardization and application of the data associated with such processes. There are currently 65 MEPS stations and one RPS that handle military personnel onboarding paperwork and make determinations for military eligibility. This topic is important due to the MEPS cloud data processing system modernization efforts requiring data processing adaptation to ensure relevant and meaningful usage of current data.

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Examining The Effect Of Contractor Logistics Support On The Reliability Of Military Aircraft, Rodrigo S. Campos De Moura Mar 2024

Examining The Effect Of Contractor Logistics Support On The Reliability Of Military Aircraft, Rodrigo S. Campos De Moura

Theses and Dissertations

This study utilizes survival analysis for examining the effect of Contractor Logistics Support (CLS) on the reliability of military aircraft before and after implementing CLS. The provider of CLS in this study is the original equipment manufacturer that designed and produced the target aircraft of this study, the Embraer A-29 Super Tucano.

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On Intrinsic Dimensionality Of Data Sets And Neural Networks, Ori Chachmo Mar 2024

On Intrinsic Dimensionality Of Data Sets And Neural Networks, Ori Chachmo

Theses and Dissertations

The concept of Intrinsic Dimensionality (ID) is of special interest in the field of Neural Networks (NNs) since it promotes both (a) a deeper understanding of the underlying mechanisms, and (b) embraces parsimonious modeling (that is, building the right-sized model for the task) with associated benefits to processing speed and storage requirements. This thesis explores the concept of ID via two separate, but related, questions. First, we study the potential of NN ID prediction by exploiting easily obtained quantities measured on the data. We then explore NN ID as an independent concept by comparing the results of different methods for …

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Reinforcement Learning For Team Based Air Combat Maneuvering Decisions With Directed Energy Weaponry, Joshua D. Combs Mar 2024

Reinforcement Learning For Team Based Air Combat Maneuvering Decisions With Directed Energy Weaponry, Joshua D. Combs

Theses and Dissertations

Leveraging the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) we investigate the use of reinforcement learning (RL) techniques for imbuing AUCAV agents with high-quality behaviors for the within-visual-range air combat maneuvering problem (ACMP). We formulate the 2v2 WVR ACMP as a Markov decision process wherein friendly AUCAVs are equipped with DEW capabilities and operate with 6 degrees of freedom. We utilize the Double Deep Q-Network RL algorithm, which centrally trains two friendly AUCAVs and employ a phased learning approach, initially exposing the AUCAVs to a dense reward environment for early training, followed by a sparse reward environment to encourage …

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An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models, Layton C. Hedge Mar 2024

An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models, Layton C. Hedge

Theses and Dissertations

This research examines China and derives insights specific to it and the First Island Chain and the Second Island Chain. In doing so, this research demonstrates a methodology to examine other competitors and their geostrategic interests. In the first phase of analysis, it develops a value hierarchy to depict objectives within subregions of the area of interest and considers four alternative weightings of the value hierarchy. In the second phase of analysis, it applies four location-covering models to assess how the competitor would emplace a range of limited resources to deter and/or control points of interest. Results indicate that land-based …

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Simulating Human-Autonomous Aircraft Teams In An Anti-Access Area Denial (A2ad) Environment, Michael Kaminski Mar 2024

Simulating Human-Autonomous Aircraft Teams In An Anti-Access Area Denial (A2ad) Environment, Michael Kaminski

Theses and Dissertations

The role of autonomy has evolved recently, demanding tighter integration between human and autonomous systems, particularly in highly contested A2AD environments. Near-peer adversaries have modernized their integrated air defense systems (IADS), diminishing the current advantages of the United States Air Force. To regain air dominance, efforts like the Collaborative Combat Aircraft (CCA) program are underway, aiming to deploy unmanned autonomous alongside manned next-generation fighter aircraft. This research assesses various operational concepts, focusing on autonomous tactics post-manned fighter loss, strike timing of independent teams, and weapon configuration observability. Using the Advanced Framework for Simulation, Integration and Modeling (AFSIM), an agent-based model …

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U.S. Army Cadet Command Branch Prediction Model, Daniel M. Krizan Mar 2024

U.S. Army Cadet Command Branch Prediction Model, Daniel M. Krizan

Theses and Dissertations

The current system for providing US Army ROTC cadets their branches leaves significant uncertainty until the final pronouncement of branch assigned. This uncertainty can be alleviated by providing a prediction model for cadets to input personal data and desired branch to identify likelihood of receiving the request. This thesis produces a machine learning model capable of producing branch prediction for cadets.

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Automated Image Registration For Titanium Aircraft Components Via Resolution-Robust Parallel Neural Networks, Paige T. Luebbering Mar 2024

Automated Image Registration For Titanium Aircraft Components Via Resolution-Robust Parallel Neural Networks, Paige T. Luebbering

Theses and Dissertations

Titanium alloys are vital to the structural integrity of military and commercial aircraft, comprising numerous critical components. These components are composed of microtexture regions (MTRs) that, at a specific size and orientation, can lead to aircraft failure. Existing MTR testing methods, such as Electron Backscatter Diffraction, often fall short in effectively detecting these MTRs without causing damage to the component. Addressing this gap, this thesis develops a Parallel Convolutional Neural Network (CNN) model tailored for multi-resolution image registration of Polarized Light Microscopy (PLM) images to enhance MTR identification in a non-invasive manner. The findings reveal a significant enhancement in the …

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Federated Analysis Of Wearables Data For United States Air Force Mental And Physical Readiness, Sung Yong O Mar 2024

Federated Analysis Of Wearables Data For United States Air Force Mental And Physical Readiness, Sung Yong O

Theses and Dissertations

This thesis investigates the use of machine learning and deep learning models within a federated learning framework to predict physical and mental readiness in military personnel, using wearable technology data. The collaboration with the 711th Human Performance Wing’s STRONG Lab highlights the importance of readiness as emphasized by the National Defense and Security Strategies. The study evaluates various predictive models, incorporating federated learning to ensure data privacy and security in healthcare systems. By analyzing a comprehensive dataset, the research aims to contribute to military readiness enhancement through technological advancements, supporting health and wellness initiatives to bolster the effectiveness of military …

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A Reinforcement Learning Approach To The 2v2 Beyond Visual Range Air Combat Maneuvering Problem, Jacob J. Pike Mar 2024

A Reinforcement Learning Approach To The 2v2 Beyond Visual Range Air Combat Maneuvering Problem, Jacob J. Pike

Theses and Dissertations

This research examines a 2v2 air combat maneuvering problem (ACMP) in a Beyond Visual Range (BVR) environment. A discrete-time, infinite-horizon Markov Decision Process (MDP) model represents the BVR-ACMP, seeking to determine high-quality policies for a pair of autonomous aircraft to execute tactical maneuvers and firing decisions. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) characterizes the complex six-degree of freedom (6-DOF) aircraft operations, encompassing kinematics, sensors, and weapons. Given the high dimensionality and continuous nature of the state and decision variables, a deep reinforcement learning (RL) solution approach is adopted wherein the value function is approximated via a Neural …

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A Random Forest-Based Q-Learning Algorithm: Toward Interpretable Artificial Intelligence, Victor R. Rae Mar 2024

A Random Forest-Based Q-Learning Algorithm: Toward Interpretable Artificial Intelligence, Victor R. Rae

Theses and Dissertations

A growing demand exists for interpretable artificial intelligence models, leading to extensive research efforts to enhance the explainability and transparency of policies generated by reinforcement learning (RL) methods. This research develops random forest-based RL algorithms as a logical progression in this academic pursuit. The algorithms are evaluated using three standard benchmark environments from OpenAI gym — CartPole, MountainCar, and LunarLander — and compared to implementations of the Deep Q-learning Network (DQN) and Double DQN (DDQN) algorithms for various metrics, including performance, robustness, efficiency, and interpretability. The random forest-based algorithms exhibit superior performance to both neural network-based algorithms in two out …

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A Staged Framework For Llm-Powered Information Extraction In Government Contracts, Jung H. Yae Mar 2024

A Staged Framework For Llm-Powered Information Extraction In Government Contracts, Jung H. Yae

Theses and Dissertations

The manual extraction of meaningful insights and conversion of content into structured forms to enhance document processing require substantial resources and are susceptible to errors. Despite numerous applications of various Natural Language Processing (NLP) models to streamline the manual process, challenges persist due to domain-specific data constraints and the deficiency of annotated data. This study attempts to address these challenges by leveraging a Large Language Model (LLM) to analyze government contracts. Through rigorous evaluation, we demonstrate the LLM’s effectiveness in information extraction and mitigating hallucinations, achieving a 87.86% accuracy in metadata extraction.

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Artificial Intelligence And Perception: An Empirical Study, Anthony J. Neil Mar 2024

Artificial Intelligence And Perception: An Empirical Study, Anthony J. Neil

Theses and Dissertations

This thesis investigates the impact of adjusting artificial intelligence explainability levels’ outputs on user perception. The overarching study extends within the Explainable Artificial Intelligence (XAI) domain. It examines a spectrum of variables, including performance, cognizance, familiarity, transparency, system bias, and the overall impact of AI, to understand their collective and individual effects that enable effective professional use in an organization. The study aims to illuminate the relationship between the degree of explainability provided by large language models such as ChatGPT, Bard, and Bing AI and the performance of these models when tasked with XAI adjustments.

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A Model-Based And System-Theoretic Approach To Design Advanced Autonomy For Air Dominance Missions: A Loyal Wingman Case Study, Elizabeth S. Pennington Mar 2024

A Model-Based And System-Theoretic Approach To Design Advanced Autonomy For Air Dominance Missions: A Loyal Wingman Case Study, Elizabeth S. Pennington

Theses and Dissertations

In contested air environments, safe coordination between decision-makers is paramount. Although the Department of Defense (DoD) prioritizes the development of Artificially Intelligent (AI) wingmen for air combat, a lack of methodology exists to design safe, holistic coordination between human and autonomous wingmen in the same environment. This thesis delivers a framework using Systems Theoretic Process Analysis Extended for Coordination (STPA-Coord) to analyze and design holistic coordination for the Loyal Wingman concept in an Air Dominance mission. STPA-Coord is a safety and hazard analysis process that uses Systems Theory to analyze and design coordination between decisionmakers in a system-of-systems architecture. Using …

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Analyzing The Effects Of Atmospheric Turbulence On Polarization-Entangled Photon Pairs Using Quantum State Tomography, Noah S. Everett Mar 2024

Analyzing The Effects Of Atmospheric Turbulence On Polarization-Entangled Photon Pairs Using Quantum State Tomography, Noah S. Everett

Theses and Dissertations

To help in building a quantum-based communication link, we experimentally designed a system to simulate atmospheric turbulence and characterize its effects on a polarization-entangled photon-pair source. The simulated turbulence is constructed using two afocal optical systems with a phase plate inserted in each to mimic both weak and strong atmospheric turbulence respectively. After propagation, quantum state tomography (QST) is performed on each pair to reconstruct the density matrix of the pair’s overall polarization state. In characterization of the simulated turbulence, we were able to reach strengths up to a D/r0 of 18.2, which begins to approach the strong turbulent regime. …

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Center Fixing Tropical Depressions And Tropical Storms Using Machine Learning-Nighttime Visible Imagery, Nathan K. Stanford Mar 2024

Center Fixing Tropical Depressions And Tropical Storms Using Machine Learning-Nighttime Visible Imagery, Nathan K. Stanford

Theses and Dissertations

The first step in most TC-retrieval algorithms is determining the storm’s central position. In mature TCs, the center is highlighted by a distinct eye and curved band pattern; however, in intensifying and decaying storms, the center is often obscured by thick clouds or overlying cirrus. This study assesses the benefits of incorporating machine learning-derived nighttime visual imagery to improve analysis of center fix in intensifying and decaying TD- and TS-strength TCs during periods of darkness and when polar orbiting satellites are unavailable. The study is divided into two parts: the first, an objective analysis using the ARCHER-2 algorithm, and the …

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Proving The Existence Of Equichordal Tight Fusion Frames Using The Newton–Kantorovich Theorem, Staci R. Davis Mar 2024

Proving The Existence Of Equichordal Tight Fusion Frames Using The Newton–Kantorovich Theorem, Staci R. Davis

Theses and Dissertations

An equichordal tight fusion frame (ECTFF) is an example of an optimal packing of subspaces. In particular, an ECTFF is an optimal packing of points in the Grassmannian with respect to chordal distance. Equivalently, every ECTFF is an arrangement of subspaces that meet certain criteria; tightness and equichordality. The existence of an ECTFF can be rephrased as, a certain polynomial mapping as a root. Hence, one can prove the existence of an ECTFF by applying Newton–Kantorovich theorem to this polynomial mapping, given a close enough approximation of one. Newton–Kantorovich requires checking an inequality within a neighborhood of the approximate root, …

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Feasibility Of A Zero-Length Spring Gravimeter For Use In Portal Monitoring, Matthew C. Stone Mar 2024

Feasibility Of A Zero-Length Spring Gravimeter For Use In Portal Monitoring, Matthew C. Stone

Theses and Dissertations

In recent years, gravimeters have become sensitive enough to theoretically measure masses of interest at distances relevant for portal monitoring. Characterizing the re[1]sponse of the gravimeter to close range masses across a large solid angle is necessary before attempting to demonstrate a portal-monitoring-like measurement due to this mission being outside the scope of typical gravimeter operations. The characterization of the gravimeter focused on three primary topics. For the position-dependent bias, it is found that the models used overestimate the expected observed gravity when the test mass is closest to the gravimeter in four out of seventeen experiments and under[1]estimate the …

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Standardization Of Risk Classifications For Unmanned Space Vehicle Missions, Collin A. Gwaltney Mar 2024

Standardization Of Risk Classifications For Unmanned Space Vehicle Missions, Collin A. Gwaltney

Theses and Dissertations

This paper seeks to model risk classification levels (A-D) for 122 Space Vehicle programs. Models include multinomial logistic regression as well as random forest, a machine learning technique based on decision trees. We use independent variables (IVs) which are theoretically correlated to risk class for the regression and one random forest model. We then include all IVs and allow the random forest technique to use those which provide the most information on risk class before paring down the number of IVs to only 7. We show that the accuracy of predictions increases from 62% to 87% by using random forest …

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Advanced Oxidation Of Methyl Tert Butyl Ether With Ultraviolet Light Emitting Diodes, Aaron R. Neal Mar 2024

Advanced Oxidation Of Methyl Tert Butyl Ether With Ultraviolet Light Emitting Diodes, Aaron R. Neal

Theses and Dissertations

Methyl Tert-Butyl Ether (MTBE) is a volatile, soluble, organic compound introduced to gasoline within the United States as a fuel oxygenator in 1979. MTBE is a common groundwater pollutant due to its high water solubility and resistance to bio-degradation; it commonly infiltrates groundwater sources via leaking underground storage tanks or fuel spills. This research employed ultraviolet light emitting diodes (UV-LEDs) and hydrogen peroxide (H2O2) induced advanced oxidation process (AOP) to treat MTBE contaminated water at the bench scale. Using four H2O2:MTBE molar peroxide ratios (100:1, 200:1, 400:1, 500:1), MTBE degradation was induced …

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Signal-To-Image Method For Counterfeit Detection In Layered Security Paradigm, Jordan Williamson Mar 2024

Signal-To-Image Method For Counterfeit Detection In Layered Security Paradigm, Jordan Williamson

Theses and Dissertations

National level attention, resources, and priority regarding critical infrastructure have increased in recent years. This has led to adversaries and defenders exchanging positions between fortification and exploitation. One area that continues to be vulnerable is supply chain attacks like counterfeit insertion. This work investigates the application of converting collected signals into images from devices that may be considered for these critical networks. There are several aspects regarding the conversion of signals into images - specifically Red, Green, Blue (RGB) images. The methodology proposed here is potentially ideal fit for an initial security layer by achieving comparable classification results as more …

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Spectroscopic Characterization Of Trivalent Holmium In Liyf4 And Bay2F8 Crystals, Vivian R. Hedberg Mar 2024

Spectroscopic Characterization Of Trivalent Holmium In Liyf4 And Bay2F8 Crystals, Vivian R. Hedberg

Theses and Dissertations

Yttrium-fluoride crystals doped with trivalent holmium are promising laser gain media for mid-infrared laser systems. To accurately model laser systems, a complete optical characterization of the laser gain medium is required. The key modeling parameters were obtained by a spectroscopic investigation of Ho3+ in LiYF4 and BaY2F8 crystal hosts. Several important mid-infrared laser transitions were characterized at nominal Ho3+ ion concentrations of 10-30 at.%. Polarized emission cross-sections were determined from the fluorescence spectra using the Füchtbauer-Ladenburg method. Polarized absorption cross-sections were obtained using the Integral Reciprocity method. The upper-state lifetimes were measured at room …

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Single Particle Analysis Of Operation Roller Coaster Environmental Samples, Caleb J. Sapp Mar 2024

Single Particle Analysis Of Operation Roller Coaster Environmental Samples, Caleb J. Sapp

Theses and Dissertations

The release of plutonium and other actinides into the environment following a nuclear detonation or accident, poses a health risk to biological systems. The spread, or transportation of that plutonium and its daughter products through environmental and meteorological means increases the potential affect and inherent danger within the surrounding area. In the 1960’s, a study was conducted in a joint effort by the US and Great Britain to collect information regarding the spread of plutonium released into the environment through a sub-critical detonation. Soil samples from these tests were collected by the USAF in 2015, approximately 50 years after these …

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