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Pulsed Power Neutron Production With Deuterated Polymer Accelerator Targets, Anthony O. Hagey Mar 2023

Pulsed Power Neutron Production With Deuterated Polymer Accelerator Targets, Anthony O. Hagey

Theses and Dissertations

This document presents an investigation of the effect of deuterated polyethylene accelerator targets on the neutron fluence from a local mass injection dense plasma focus driven by the United States Naval Research Laboratory’s Hawk pulsed-power generator. After successful production of thin targets, the acquisition of thicker targets, and testing inside Hawk, it was found that the presence of a deuterated polyethylene target increased the neutron fluence. Results suggested that fluence can significantly increase with the presence of a deuterated target vs a nondeuterated target. Additive manufacturing printing was used as a production method in order to determine if deuterated accelerator …


Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill Mar 2023

Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill

Theses and Dissertations

Federated learning (FL) is a budding machine learning (ML) technique that seeks to keep sensitive data private, while overcoming the difficulties of Big Data. Specifically, FL trains machine learning models over a distributed network of devices, while keeping the data local to each device. We apply FL to a Parkinson’s Disease (PD) telemonitoring dataset where physiological data is gathered from various modalities to determine the PD severity level in patients. We seek to optimally combine the information across multiple modalities to assess the accuracy of our FL approach, and compare to traditional ”centralized” statistical and deep learning models.


Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid Mar 2023

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …


Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore Mar 2023

Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore

Theses and Dissertations

As the threat of near-peer adversaries has increased, the DoD has increased its emphasis on Joint All-Domain Operations (JADO). This emphasis on JADO highlights the need for hands-on training that can engage military members at all levels. The serious game Battlespace Next (BSN) was designed to teach high-level JADO concepts by modeling real-world military assets in the context of a strategic card game. To keep pace with the evolving landscape of warfare as well as fit the needs of a variety of Department of Defense (DoD) communities, this research introduces the Battlespace Next Education Framework (BSNEF). The BSNEF allows JADO …


Temporal And Spatial Variability Of Specific Energy Consumption For Atmospheric Water Generators, Anthony T. Brenes Mar 2023

Temporal And Spatial Variability Of Specific Energy Consumption For Atmospheric Water Generators, Anthony T. Brenes

Theses and Dissertations

Atmospheric Water Generators (AWG) produce potable water from the moisture in the air, providing a potentially viable water source in austere locations or emergency response scenarios. In this study, the operating constraints of three existing commercially available AWG devices are investigated, compared to historical weather data from across the continental United States. Utilizing linear regression modeling and weather station data for the years of 1985-2019, the monthly and spatial trends of energy demand to produce water from these devices are evaluated. Energy and water production efficiencies for the devices are highly dependent on environmental conditions with relative humidity and temperature …


A Comparative Analysis Of Viral Aerosol Biological Sampling Efficiency Of A Small Unmanned Aircraft System (Suas)-Mounted Aerosol Sampler And A Reference Static Biosampler®, Jonathan D. Moroz Mar 2023

A Comparative Analysis Of Viral Aerosol Biological Sampling Efficiency Of A Small Unmanned Aircraft System (Suas)-Mounted Aerosol Sampler And A Reference Static Biosampler®, Jonathan D. Moroz

Theses and Dissertations

Bioaerosol sampling using small unmanned aerial systems (sUAS) is a rapidly developing field that may result in a paradigm shift in emergency response and industrial hygiene sampling conventions. These technologies offer decreased sample acquisition times, larger sampling area coverage, and reduced health and safety risks to traditional human sampling teams. This potential requires a comprehensive investigation of sUAS capabilities and limitations. This study is a continuation of the characterization of an AFIT-developed sUAS-mounted aerosol sampler, proven capable of collecting viable vegetative and spore-forming bacteria through previous AFIT research. Within this study, viral biological sampling efficiency (BSE) of the sUAS-mounted aerosol …


Regular Simplices Within Doubly Transitive Equiangular Tight Frames, Evan C. Lake Mar 2023

Regular Simplices Within Doubly Transitive Equiangular Tight Frames, Evan C. Lake

Theses and Dissertations

An equiangular tight frame (ETF) yields an optimal way to pack a given number of lines into a given space of lesser dimension. Every ETF has minimal coherence, and this makes it potentially useful for compressed sensing. But, its usefulness also depends on its spark: the size of the smallest linearly dependent subsequence of the ETF. When formed into a sensing matrix, a larger spark means a lower chance that information is lost when sensing a sparse vector. Spark is difficult to compute in general, but if an ETF contains a regular simplex, then every such simplex is a linearly …


Intel Total Memory Encryption: Functional Verification And Performance Analysis, Tallas Tian Sheng Goo Mar 2023

Intel Total Memory Encryption: Functional Verification And Performance Analysis, Tallas Tian Sheng Goo

Theses and Dissertations

While more attention is generally focused on software security, computer hardware security remains an important effort. Should an attacker gain direct physical access, computers with little to no hardware security can quickly be compromised via a manner of methods. One such attacker method is to steal information directly from the active memory of a locked, powered-on computer. To counter this attack, a hardware security method was developed called memory encryption. Memory encryption, as the name suggests, protects against adversary methods like cold boot attacks by encrypting all of memory. This research evaluates the efficacy and performance specifically of Intel TME. …


The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold Mar 2023

The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold

Theses and Dissertations

The quiet zone of a radar range is the region over which a transmitted EM field approximates a uniform plane wave to within some finite error tolerance. Any target to be measured must physically fit within this quiet zone to prevent excess measurement error. Compact radar ranges offer significant operational advantages for performing RCS measurements but their quiet zone sizes are constrained by space limitations. In this work, a scientific computing approach is used to investigate whether equivalent-current transmitters can be designed that generate larger quiet zones than a conventional version at short range. A time-domain near-field solver, JefimenkoModels, was …


Fast And Accurate 3d Object Reconstruction For Cargo Load Planning, Adam R. Nasi Mar 2023

Fast And Accurate 3d Object Reconstruction For Cargo Load Planning, Adam R. Nasi

Theses and Dissertations

Cargo load planning involves efficiently packing objects into aircraft subject to constraints such as space and weight distribution. Currently, this is performed manually by loadmasters. The United States Air Force is investigating ways to automate this process in order to improve airlift operational readiness while saving money. The first step in such a process would be generating 3D reconstructions of cargo objects to be used by a load planning algorithm. To that end, this thesis presents a novel method for fast, scaled, and accurate 3D reconstruction of cargo objects. This method can scan a 2.5m×3m×2m object in less than 10 …


Ensemble Aggregation In A Multi-Perspective Environment, Jonathan P. Nash Mar 2023

Ensemble Aggregation In A Multi-Perspective Environment, Jonathan P. Nash

Theses and Dissertations

Research towards improving the performance of artificial intelligence networks has found that larger and more complex networks tends to yield better results, and continuous hardware upgrades enables the development of larger, more complicated, and better performing neural networks. However, many devices that are widely available and more practical to everyday use, such as drones or smartphones, are unable to use the state-of-the-art neural networks because they simply do not have the processing capabilities to run them in addition to their normal function. It is possible to overcome this lower performance by using a variety of these smaller neural networks as …


Effectiveness Of A Timing Side Channel For Deriving Neural Network Depth, Matthew P. Weeks Mar 2023

Effectiveness Of A Timing Side Channel For Deriving Neural Network Depth, Matthew P. Weeks

Theses and Dissertations

From facial recognition on cell phones to vehicle traffic modeling for city planning, integrating ML models can be an expensive investment in resources. Protecting that investment is difficult, as information about the model and how it was built can be leaked through multiple channels, such as timing and memory access. In this thesis, one method of extracting data through a timing side-channel is examined across multiple hardware and software configurations to determine its reliability for general use. While attempting to determine the layer count of a target model solely from its inference time, the research determined that it is not …


Temporal Convolutional Neural Networks For Device Discrimination, Ryan T. Zacher Mar 2023

Temporal Convolutional Neural Networks For Device Discrimination, Ryan T. Zacher

Theses and Dissertations

This research uses TCN modifications to CNN classifiers, specifically dilation, causal padding, and residual blocks, to focus on temporal features and improve existing DNA analysis processes. Dilation significantly improves classification accuracy, even detecting features where no other models were able to. The smallest improvement shown is a 3-6dB reduction in SNR to reach a 90% classification accuracy. The maximum improvement is shown in the data-delivery region of the Cisco dataset, with the dilated model being the only model to exceed 90% classification accuracy. The other TCN modifications are shown to have no beneficial effect on the models.


Induced Correlation And Its Effects In The Performance Of Fused Classification Systems, Mary K. Collins Mar 2023

Induced Correlation And Its Effects In The Performance Of Fused Classification Systems, Mary K. Collins

Theses and Dissertations

Classification systems are abundant in modern-day life. The United States Air Force uses classification systems across many applications such as radar, satellite, and infrared sensing just to name a few. Combining classification systems allows an opportunity to get more accurate results. Using the known information from already built and tested systems that can be mathematically combined can give insight into the performance of the fused system without having to build a combined system. Leveraging this can save time, resources, and money. This work examines the correlation effects of fusing two classifier systems, each with only two labels, using the Boolean …


Student Performance In Traditional In-Person Vs. Online Sections Of An Introductory Graduate Mathematics Course, Lauran E. Kittle Mar 2023

Student Performance In Traditional In-Person Vs. Online Sections Of An Introductory Graduate Mathematics Course, Lauran E. Kittle

Theses and Dissertations

The growth of technology impacts nearly every aspect of everyday life, to include education and learning. The availability of distance learning (online) classes has increased drastically in the last few decades, expanding access to education for millions of people. However, it is imperative to consider exactly how the growth of technology impacts education – whether it is a positive, negative, or neutral impact. Previous research comparing distance learning and in-residence (traditional) classes have widely mixed, disparate conclusions. This type of research, two-stage analysis, and modeling has yet to be conducted on a graduate school level. For this reason, a detailed …


Modeling Radiation Exposure On Flight Missions To Analyze Aircrew Risk, Camila V. Quintero Hilsaca Mar 2023

Modeling Radiation Exposure On Flight Missions To Analyze Aircrew Risk, Camila V. Quintero Hilsaca

Theses and Dissertations

GCR and SPE comprise the majority of the ionizing radiation experienced in the upper atmosphere within flight-altitude environments. Although previous studies have analyzed radiation doses from single sources on civilian flight operations, there is a lack of research focused on dose received by military personnel during flight from both sources simultaneously. In-flight radiation environments are modeled through the MCNP6 for two separate aircraft, an Air Force A-10 and a Boeing 737. Particle fluence values for galactic cosmic rays and solar particle events for four separate flight paths are determined using the CARI-7A software and the SIRE2 toolkit, respectively. MCNP6 code …


Air Force Digital Badges, Jacob Chan Mar 2023

Air Force Digital Badges, Jacob Chan

Theses and Dissertations

The Air Force talent management and force development systems are antiquated. Airmen records are often stored on different Air Force information systems. Existing records sometimes lack granularity and context to recognize Airmen skills. Digital badges are a newer technology utilized by academia and industry to recognize member skills. However, military badging research is sparse and existing studies do not provide sufficient evidence on the value of digital badging to the Air Force. The studies: (1) lack background research on badging; (2) do not provide quantitative data on the effects of badging; and (3) issued badges through commercial entities which may …


Cellphone-Acoustics Based Suas Detection And Tracking, Ryan D. Clendening Mar 2023

Cellphone-Acoustics Based Suas Detection And Tracking, Ryan D. Clendening

Theses and Dissertations

Small Unmanned Aerial Systems (sUAS) are an easily accessible technology that has become an increasingly large threat to US critical systems. This threatening technology demands using fault-tolerant, low-cost, replaceable, and accurate sensing resources, which counter the ubiquitous nature of sUAS [1]. Therefore, the methods developed in this thesis detect and track sUAS using easily accessible sensing resources, such as cellphones. First, we develop an acoustics sensor network-based sUAS detection methodology. In the latter effort, a deep learning model is trained using the acoustics data from the data collection to predict sUAS range from a cellphone. Combined, these two efforts demonstrate …


Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens Mar 2023

Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens

Theses and Dissertations

This thesis introduces two methods to generate Courses of Action (COA) in distributed warfare scenarios: the Wargaming Commodity Course of Action Automated Method Under Uncertainty (WCCAAM-U2) and Dynamic Transshipment Problem (DTP)-generated COAs. Previous work by Deberry et al. used a Multi-Commodity Flow Problem (MCFP) to generate COAs for single-period wargame scenarios with known enemy force amounts. In WCCAAM-U2, we adapt an MCFP to work in situations where only intelligence estimates of enemy forces are known. Compared to two other COA-generation methods, the WCCAAAM-U2 COA outperforms the next highest-performing COA by 307% when compared by a ratio of objective success rate …


Monocular Vision And Machine Learning For Pose Estimation, Quang Ngoc Tran Mar 2023

Monocular Vision And Machine Learning For Pose Estimation, Quang Ngoc Tran

Theses and Dissertations

This thesis introduces a monocular vision-based approach for 6 DoF pose estimation on a known object. The proposed solution is to use a CNN to find known features of an object in an image. These known features, together with their known locations, are used by a PnP algorithm to estimate the pose of the target object with respect to the camera. The primary difficulty with CNN-based methods is needing to generate a large amount of training data to effectively create the CNN. To overcome this difficulty, a 3D model of the real-world object is created and used in a visualization …


Detection Algorithms And Clutter Metrics Comparison For Long Wave Infrared Point-Source Targets, Rudolf N. Vonniederhausern Mar 2023

Detection Algorithms And Clutter Metrics Comparison For Long Wave Infrared Point-Source Targets, Rudolf N. Vonniederhausern

Theses and Dissertations

In Infrared Search and Track (IRST) systems, clutter in the image hinders target detection especially in point-source target scenarios. Currently there is not a standardized metric for quantifying background clutter. Many clutter metrics have been proposed, but none have demonstrated effectiveness or compatibility for point-source targets. Factors such as environment conditions, detection algorithm, and correlation coefficient to probability of detection (PD) and false alarm (PFA) are the main considerations in determining the effectiveness of clutter metrics. Determining the most successful metric will increase Air Force Test and Evaluation (T&E) units’ capability by providing additional information on test conditions and environments …


Safe And Reliable Software And The Formal Verification Of Prim's Algorithm In Spark, Brian S. Wheelhouse Mar 2023

Safe And Reliable Software And The Formal Verification Of Prim's Algorithm In Spark, Brian S. Wheelhouse

Theses and Dissertations

Despite evidence that formal verification helps produce highly reliable and secure code, formal methods, i.e., mathematically based tools and approaches for software and hardware verification, are not commonly used in software and hardware development. The limited emphasis on formal verification in software education and training suggests that many developers have never considered the benefits of formal verification. Despite the challenging nature of their mathematical roots, software verification tools have improved; making it easier than ever to verify software. SPARK, a programming language and a formal verification toolset, is of particular interest for the AFRL, and will be a primary focus …


Entering Hyperspace: Conditional Hyperspectral Reflectance Image Generation Using Convolutional Neural Networks, Bret M. Wagner Mar 2023

Entering Hyperspace: Conditional Hyperspectral Reflectance Image Generation Using Convolutional Neural Networks, Bret M. Wagner

Theses and Dissertations

The field of remote sensing continues to expand in both commercial and defense domains. Development of advanced space based EOIR sensors has driven corresponding demand for sensor data for algorithm development. The AFIT Sensor and Scene Emulation Tool (ASSET) produces realistic synthetic electro-optical and infrared (EO/IR) data with absolute truth for the purpose of clutter suppression, target detection, and tracking algorithm development. This thesis presents a novel model which transforms panchromatic images into realistic hyperspectral reflectance images. The direct application of this model is to allows users to generate hyperspectral background images as inputs to ASSET allowing users to benefit …


Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson Mar 2023

Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson

Theses and Dissertations

The goal of automated aerial refueling (AAR) is to extend the range of unmanned aircraft. Control latency prevents a human from remotely controlling the receiving aircraft as it approaches a tanker. To conform with the size, weight, and power constraints of a small unmanned aircraft, an AAR system must execute in real-time on an embedded platform. This thesis explores the timing and computational performance of a NVIDIA Jetson AGX Orin to a state-of-the-art general-purpose computer using existing AAR algorithms. It also constructs an augmented reality framework as an intermediate step for testing vision-based AAR algorithms between virtual testing and expensive …


Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler Mar 2023

Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler

Theses and Dissertations

Simulation and physical testing of a sensor that measures relative position of the Sun and polarization of light in the atmosphere as a navigational aid in a Kalman filter.


Net Zero Water Air Force Installations, Kenneth R. Mcknight Mar 2023

Net Zero Water Air Force Installations, Kenneth R. Mcknight

Theses and Dissertations

The United States continues to face problems of a reduction in quality and quantity of groundwater sources because water extraction exceeds natural source recharge. The Air Force has recognized the importance of these groundwater sources but has put minimal effort into determining their contribution to the depletion of these sources. The purpose of this study is to determine this contribution by determining whether Air Force installations are net zero water. This is done using a geospatial information system to determine the volume of water recharging groundwater sources associated with an Air Force installation. This volume is then compared to the …


Fragility Of The Florida Panhandle's Electrical Transmission Grid To Hurricanes, Zachary D. Schumann Mar 2023

Fragility Of The Florida Panhandle's Electrical Transmission Grid To Hurricanes, Zachary D. Schumann

Theses and Dissertations

The increased frequency and intensity of extreme weather events from climate change necessitates understanding impacts on critical infrastructure, particularly electrical transmission grids. One of the foundational concepts of a grid’s resilience is its robustness to extreme weather events, such as hurricanes. Resilience of the electric grid to high wind speeds is predicated upon the location and physical characteristics of the system components. Previous modeling assessments of electric grid failure were done at the systems level with assumptions on location and type of specific components. To facilitate more explicit adaptation metrics, accurate component-level information is needed. In this study, we build …


Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian Mar 2023

Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian

Theses and Dissertations

Neural networks have become increasingly popular in real time object detection algorithms. A major concern with these algorithms is their ability to quantify their own uncertainty, leading to many high profile failures. This research proposes three novel real time detection algorithms. The first of leveraging Bayesian convolutional neural layers producing a predictive distribution, the second leveraging predictions from previous frames, and the third model combining these two techniques together. These augmentations seek to mitigate the calibration problem of modern detection algorithms. These three models are compared to the state of the art YOLO architecture; with the strongest contending model achieving …


Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald Mar 2023

Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald

Theses and Dissertations

This research examines the Cadet to Air Force Specialty Code (AFSC) Matching Problem (CAMP). Currently, the matching problem occurs annually at the Air Force Personnel Center (AFPC) using an integer program and value focused thinking approach. This paper presents a novel method to match cadets with AFSCs using a generalized structure of the Hospitals Residents problem with special emphasis on lower quotas. This paper also examines the United States Army Matching problem and compares it to the techniques and constraints applied to solve the CAMP. The research culminates in the presentation of three algorithms created to solve the CAMP and …


Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller Mar 2023

Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller

Theses and Dissertations

The purposes of this study are to confirm the applicability of survival analysis for predicting recurrent failures of a component of a military aircraft and to provide practical insights to maintenance managers and mission planners. The results of this study also can help the United States Department of Defense improve the CBM+ program. This study was able to predict recurrent failures of the component using Nelson-Aalen cumulative estimates. In addition, this study used a Cox proportional hazards regression model with shared frailty for measuring the effect of covariates on recurrent failures and unidentified heterogeneity in the model, which warranted future …