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Air Force Institute of Technology

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Articles 61 - 90 of 2678

Full-Text Articles in Physical Sciences and Mathematics

A Comparison Of Quaternion Neural Network Backpropagation Algorithms, Jeremiah Bill, Bruce A. Cox, Lance Champaign Jun 2023

A Comparison Of Quaternion Neural Network Backpropagation Algorithms, Jeremiah Bill, Bruce A. Cox, Lance Champaign

Faculty Publications

This research paper focuses on quaternion neural networks (QNNs) - a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. Previous studies have shown that QNNs outperform real-valued neural networks in basic tasks and have potential in high-dimensional problem spaces. However, research on QNNs has been fragmented, with contributions from different mathematical and engineering domains leading to unintentional overlap in QNN literature. This work aims to unify existing research by evaluating four distinct QNN backpropagation algorithms, including the novel GHR-calculus backpropagation algorithm, and providing concise, scalable implementations of each algorithm using a …

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Failure Distributions For Parallel Dependent Identical Weibull Components, Gina S. Sigler Jun 2023

Failure Distributions For Parallel Dependent Identical Weibull Components, Gina S. Sigler

Theses and Dissertations

For a parallel system, when one component fails, the failure distribution of the remaining components will have an increased failure rate. This dissertation takes a novel approach to finding the associated failure distribution of the full system using ordinal statistic distributions for correlated Weibull components, allowing for unknown correlations between the dependent components. A Taylor series approximation is presented for the two component; system failure time distributions are also derived for two failures in a two component system, two failures in an n component system, three failures in a three component system, and k failures in an n component system. …

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Quantitative Modeling Of Text-Based Intelligence Source Uncertainty, Adam D. Nesmith Jun 2023

Quantitative Modeling Of Text-Based Intelligence Source Uncertainty, Adam D. Nesmith

Theses and Dissertations

An all-source intelligence analyst’s primary job is delivering timely, well-sourced assessments on relevant targets based on uncertain and incomplete information. Each assessment includes a likelihood that the assessment is true, and a confidence level based on the uncertainty of the sources used. Quantitative all-source intelligence analysis is not widely implemented despite the acknowledged limitations of qualitative intelligence assessments and the existence of proposed quantitative methods. This is due to the challenge of quantitatively representing uncertainty in text-based intelligence reporting (i.e., HUMINT, OSINT, SIGINT), which limits the effectiveness and usability of previously suggested methods. This research creates a novel framework for …

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Non-Degenerate Two-Photon Absorption And Excited State Line Shapes In Alkali Vapors, Timothy M. True Jun 2023

Non-Degenerate Two-Photon Absorption And Excited State Line Shapes In Alkali Vapors, Timothy M. True

Theses and Dissertations

The rubidium 5S-5D two-photon transitions were probed between 758-798 nm, where a six order of magnitude change in the cross section was observed and the polarization dependence was seen explicitly. Collisional rates are measured in cesium on the 6P-9S and 5D-10F transitions, with broadening rates as large as 710 MHz/Torr and shifting rates as large as 273 MHz/Torr. We observe Stark broadening on the cesium 5D-10F line shape, with Lorentzian width increasing from 200 MHz to 40 GHz. The influence of electron impact is discussed under these conditions and with 0-20 Torr of helium. Cascade amplified spontaneous emission is seen …

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Fate And Transport Of Per- And Polyfluoroalkyl Substances (Pfas) At Aqueous Film Forming Foam (Afff) Discharge Sites: A Review, Jeffery T. Mcgarr, Eric G. Mbonimpa, Drew C. Mcavoy, Mohamad R. Soltanian May 2023

Fate And Transport Of Per- And Polyfluoroalkyl Substances (Pfas) At Aqueous Film Forming Foam (Afff) Discharge Sites: A Review, Jeffery T. Mcgarr, Eric G. Mbonimpa, Drew C. Mcavoy, Mohamad R. Soltanian

Faculty Publications

Per- and polyfluorinated alkyl substances (PFAS) are an environmentally persistent group of chemicals that can pose an imminent threat to human health through groundwater and surface water contamination. In this review, we evaluate the subsurface behavior of a variety of PFAS chemicals with a focus on aqueous film forming foam (AFFF) discharge sites. AFFF is the primary PFAS contamination risk at sites such as airports and military bases due to use as a fire extinguisher. Understanding the fate and transport of PFAS in the subsurface environment is a multifaceted issue. This review focuses on the role of adsorbent, adsorbate, and …

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Method Of Evanescently Coupling Whispering Gallery Mode Optical Resonators Using Liquids, Hengky Chandrahalim, Kyle T. Bodily May 2023

Method Of Evanescently Coupling Whispering Gallery Mode Optical Resonators Using Liquids, Hengky Chandrahalim, Kyle T. Bodily

AFIT Patents

The present invention relates to evanescently coupling whispering gallery mode optical resonators having a liquid coupling as well as methods of making and using same. The aforementioned evanescently coupling whispering gallery mode optical resonators having a liquid couplings provide increased tunability and sensing selectivity over current same. The aforementioned. Applicants’ method of making evanescent-wave coupled optical resonators can be achieved while having coupling gap dimensions that can be fabricated using standard photolithography. Thus economic, rapid, and mass production of coupled WGM resonators-based lasers, sensors, and signal processors for a broad range of applications can be realized.

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Optical Fiber Tip Micro Anemometer, Jeremiah C. Williams, Hengky Chandrahalim Apr 2023

Optical Fiber Tip Micro Anemometer, Jeremiah C. Williams, Hengky Chandrahalim

AFIT Patents

A passive microscopic flow sensor includes a three-dimensional microscopic optical structure formed on a cleaved tip of an optical fiber. The three-dimensional microscopic optical structure includes a post attached off-center to and extending longitudinally from the cleaved tip of the optical fiber. A rotor of the three-dimensional microscopic optical structure is received for rotation on the post. The rotor has more than one blade. Each blade has a reflective undersurface that reflects a light signal back through the optical fiber when center aligned with the optical fiber, the blades of the rotor shaped to rotate at a rate related to …

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Filter-Based Air Sampler Capable Of Integration Into Small Unmanned Aerial Vehicles, Robert M. Eninger, Stepanie A. Ohms, Jeremy M. Slagley Apr 2023

Filter-Based Air Sampler Capable Of Integration Into Small Unmanned Aerial Vehicles, Robert M. Eninger, Stepanie A. Ohms, Jeremy M. Slagley

AFIT Patents

A filter-based air sampler, more specifically a filter-based air sampler capable of integration into small unmanned aerial systems is disclosed. The filter-based air sampler may include a filter assembly which has as its component parts: an open faced air intake component, a filter, and a filter support that has a central supporting grid. The filter assembly may joined to the housing of a fan, such as a centrifugal fan, with the supporting grid of the filter support being disposed over the air inlet of the fan.

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Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins Apr 2023

Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins

Faculty Publications

Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …

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Toward A Simulation Model Complexity Measure, J. Scott Thompson, Douglas D. Hodson, Michael R. Grimaila, Nicholas Hanlon, Richard Dill Mar 2023

Toward A Simulation Model Complexity Measure, J. Scott Thompson, Douglas D. Hodson, Michael R. Grimaila, Nicholas Hanlon, Richard Dill

Faculty Publications

Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity. This article offers an overview of the complexity from a variety of perspectives and provides a body of knowledge with respect to the complexity of simulation models. The key terms model detail, resolution, and scope are defined. An important concept from algorithmic information theory, Kolmogorov complexity, and an application of this concept, normalized compression distance, are used to indicate the possibility of measuring changes …

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Numerical Simulation Of Steady-State Thermal Blooming With Natural Convection, Jeremiah S. Lane, Justin Cook, Martin Richardson, Benjamin F. Akers Mar 2023

Numerical Simulation Of Steady-State Thermal Blooming With Natural Convection, Jeremiah S. Lane, Justin Cook, Martin Richardson, Benjamin F. Akers

Faculty Publications

This work investigates steady-state thermal blooming of a high-energy laser in the presence of laser-driven convection. While thermal blooming has historically been simulated with prescribed fluid velocities, the model introduced here solves for the fluid dynamics along the propagation path using a Boussinesq approximation to the incompressible Navier–Stokes equations. The resultant temperature fluctuations were coupled to refractive index fluctuations, and the beam propagation was modeled using the paraxial wave equation. Fixed-point methods were used to solve the fluid equations as well as to couple the beam propagation to the steady-state flow. The simulated results are discussed relative to recent experimental …

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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 …

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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 …

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Automated Additive Layering Of Vat Polymerized Plastic Organic Scintillators, Chandler J. Moore Mar 2023

Automated Additive Layering Of Vat Polymerized Plastic Organic Scintillators, Chandler J. Moore

Theses and Dissertations

The current technology for fast neutron detection imaging is limited in achieving the required high spatial resolution, strong neutron discrimination, and practical time of manufacturing. Traditional fabrication methods require days of thermal polymerization and hundreds of man-hours to produce average resolution pixelated scintillator arrays. The present work helps to eliminate this limitation by developing an additive manufacturing technique to construct such detectors for use in in dual particle imaging applications. In this work, fast-, light-curing resins are used in a prototype automated assembly machine, capable of layering of individual light-cured resin layers and optical segmentation with a self-bonded specular reflector, …

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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 …

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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 …

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Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim Mar 2023

Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim

Theses and Dissertations

A post-traumatic headache (PTH), resulting from a mild traumatic brain injury (mTBI), potentially develops into persistent post-traumatic headache (PPTH). Although no known cure for PPTH exists, research has shown that receiving treatment at earlier stages of PTH lowers the risk of patients developing PPTH. Previous studies have shown machine learning (ML) models capable of predicting a patient’s PTH progression, but none have considered the issue of protecting patient privacy. Due to patient privacy, ML models only have access to data within the institution. Federated learning (FL) harnesses data from separate institutions without sacrificing patient privacy as institutions can run ML …

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Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King Mar 2023

Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King

Theses and Dissertations

The United States Air Force (USAF) has struggled with a sustained pilot shortage over the past several years; senior military and government leaders have been working towards a solution to the problem, with no noticeable improvements. Both attrition of more experienced pilots as well as wash out rates within pilot training contribute to this issue. This research focuses on pilot training attrition. Improving the process for selecting pilot candidates can reduce the number of candidates who fail. This research uses historical specialized undergraduate pilot training (SUPT) data and leverages select machine learning techniques to determine which factors are associated with …

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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 …

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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.

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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 …

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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.

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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 …

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Improving Accessibility And Efficiency Of Analytic Provenance Tools For Reverse Engineering, Caleb W. Richardson Mar 2023

Improving Accessibility And Efficiency Of Analytic Provenance Tools For Reverse Engineering, Caleb W. Richardson

Theses and Dissertations

Reverse engineering is a vital technique for identifying and mitigating cyber threats. Yet, despite its importance, reverse engineering is a time-consuming process. Provenance tools help to improve the workflow of reverse engineers by providing an accessible method of viewing their flow through a binary. The current state-of-theart provenance tool for reverse engineering software called SensorRE, leverages an external server, web browser, and a large array of javascript libraries. This thesis presents Provenance Ninja, a software reverse engineering tool developed in Python that runs directly within Binary Ninja. Provenance Ninja captures reverse engineers’ provenance data and provides an interactive graph within …

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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 …

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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 …

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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 …

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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 …

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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 …

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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 …

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