Physical Sciences and Mathematics Commons^™

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw

Faculty Publications

Generative Adversarial Networks (GANs) have received immense attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. This manuscript focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to empirically determine the effects of 10 fundamental image degradation modes, applied to the training image dataset, on the Fréchet inception distance …

An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, Jeffrey Choate, Derek Worth, Scott Nykl, Clark N. Taylor, Brett J. Borghetti, Christine M. Schubert Kabban

Faculty Publications

Achieving precise 6 degrees of freedom (6D) pose estimation of rigid objects from color images is a critical challenge with wide-ranging applications in robotics and close-contact aircraft operations. This study investigates key techniques in the application of YOLOv5 object detection convolutional neural network (CNN) for 6D pose localization of aircraft using only color imagery. Traditional object detection labeling methods suffer from inaccuracies due to perspective geometry and being limited to visible key points. This research demonstrates that with precise labeling, a CNN can predict object features with near-pixel accuracy, effectively learning the distinct appearance of the object due to perspective …

Lithium Tetraborate As A Neutron Scintillation Detector: A Review, Elena Echeverria, John W. Mcclory, Lauren Samson, Katherine Shene, Juan A. Colon Santana, Yaroslav V. Burak, Volodymyr T. Adamiv, Ihor M. Teslyuk, Lu Wang, Wai-Ning Mei, Kyle A. Nelson, Douglas S. Mcgregor, Peter A. Dowben, Carolina C. Ilie, James C. Petrosky, Archit Dhingra

Faculty Publications

The electronic structure and translucent nature of lithium tetraborate (Li₂B₄O₇) render it promising as a scintillator medium for neutron detection applications. The inherently large neutron capture cross-section due to ¹⁰B and ⁶Li isotopes and the ease with which Li₂B₄O₇ can be enriched with these isotopes, combined with the facile inclusion of rare earth dopants (occupying the Li⁺ sites), are expected to improve the luminescent properties, as well as the neutron detection efficiency, of Li₂B₄O₇. The electronic structure of both doped …

Passive Physical Layer Distinct Native Attribute Cyber Security Monitor, Christopher M. Rondeau, Michael A. Temple, Juan L. Lopez Jr., J. Addison Betances

AFIT Patents

A method for cyber security monitor includes monitoring a network interface that is input-only configured to surreptitiously and covertly receive bit-level, physical layer communication between networked control and sensor field devices. During a training mode, a baseline distinct native attribute (DNA) fingerprint is generated for each networked field device. During a protection mode, a current DNA fingerprint is generated for each networked field device. The current DNA fingerprint is compared to the baseline DNA fingerprint for each networked field device. In response to detect at least one of RAA and PAA based on a change in the current DNA fingerprint …

Shock-Wave Tolerant Phase Reconstruction Algorithm For Shack–Hartmann Wavefront Sensor Data, Thomas E. Defoor, Matthew Kalensky, Matthew R. Kemnetz, Timothy J. Bukowski, Mark F. Spencer

Faculty Publications

We develop a phase reconstruction algorithm for the Shack–Hartmann wavefront sensor (SHWFS) that is tolerant to phase discontinuities, such as the ones imposed by shock waves. In practice, this algorithm identifies SHWFS locations where the resultant tilt information is affected by the shock and improves the tilt information in these locations using the local SHWFS observation-plane irradiance patterns. The algorithm was shown to work well over the range of conditions tested with both simulated and experimental data. In turn, the reconstruction algorithm will enable robust wavefront sensing in transonic, supersonic, and hypersonic environments.

Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminate Surrogate Particle From A Military Uniform Fabric, George Cooksey, Jeremy M. Slagley, Casey W. Cooper, Douglas Lewis, Alisha Helm

Faculty Publications

In a mass casualty medical evacuation after a bioaerosol (BA) dispersal event, a decontamination (DC) method is needed that can both decontaminate and prevent biological particle (BP) re-aerosolization (RA) of contaminated clothes. However, neither the efficacy of current DC methods nor the risk of BP RA is greatly explored in the existing literature. The goals of this study were to develop a repeatable method to quantify the RA of a biological contaminant off military uniform fabric swatches and to test the efficacy of one DC protocol (high-volume, low-pressure water) using 1 µm polystyrene latex (PSL) spheres as a surrogate. A …

A Hybrid Cognitive Model For Machine Agents In Project And Action Teams, Joshua A. Lapso

Theses and Dissertations

High performing human teams transcend complex domain uncertainty by achieving an emergent state of shared cognition, in which knowledge is organized, represented, and distributed to team members for rapid execution. However, this requires that individuals emit perceivable qualities upon which other members can make inferences about intent. In pursuit of future human and machine team studies, this research presents a hybrid cognitive model for machine agents in fully cooperative and semi-cooperative action and project teams. The hybrid cognitive model unifies the characteristics of the shared mental model and transactive memory system. The resultant model facilitates anytime selection over the two …

Federated Active Learning For Network Intrusion Detection, Matthew D. R. Sauer

Theses and Dissertations

This thesis addresses challenges with detecting attacks on computer networks within a Federated Learning (FL) framework, when labeled instances are few. We explore the integration of active learning (AL) and semi-supervised learning (SSL). AL efficiently uses data that would otherwise be wasted or require substantial time for labeling. SSL provides capacity to train models that have a limited amount of labeled data, by utilizing additional unlabeled data that is available. We show how FL combined with AL or SSL can realize a detection system that adapts and trains quickly to new networks, reducing the total amount of data labeling needed. …

Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding

Theses and Dissertations

Multi-agent systems and swarms in spacecraft formation flying are of ever-increasing importance in a contested space environment—use of multiple spacecraft to contribute to a cooperative mission potentially increases positive outcomes on orbit, while autonomy becomes an ever more important requirement to reduce reaction time in dynamic situations and lower the burden on space operators. This research explores difficult swarm Guidance Navigation and Control (GNC) scenarios using Deep Reinforcement Learning (DRL). DRL polices are trained to provide guidance inputs to agents in multi-agent swarm environments for completing complex, teamwork focused objectives in geosynchronous orbit. An example scenario is explored for a …

Analysis And Requirement Generation For Defense Intelligence Search: Addressing Data Overload Through Human–Ai Agent System Design For Ambient Awareness, Mark C. Duncan, Michael E. Miller, Brett J. Borghetti

Faculty Publications

This research addresses the data overload faced by intelligence searchers in government and defense agencies. The study leverages methods from the Cognitive Systems Engineering (CSE) literature to generate insights into the intelligence search work domain. These insights are applied to a supporting concept and requirements for designing and evaluating a human-AI agent team specifically for intelligence search tasks. Domain analysis reveals the dynamic nature of the ‘value structure’, a term that describes the evolving set of criteria governing the intelligence search process. Additionally, domain insight provides details for search aggregation and conceptual spaces from which the value structure could be …

Detailed Characterization Of A Khz-Rate Laser-Driven Fusion At A Thin Liquid Sheet With A Neutron Detection Suite, Benjamin M. Knight, Connor M. Gautam, Colton R. Stoner, Bryan V. Egner, Joseph R. Smith, Christopher M. Orban, Juan J. Manfredi, Kyle Frische, Michael L. Dexter, Enam A. Chowdury, Anil K. Patnaik

Faculty Publications

We present detailed characterization of laser driven fusion and neutron production (∼10⁵/second) employing 8 mJ, 40fs laser pulses on a thin (< 1 µm) D₂O liquid sheet employing a measurement suite. At relativistic intensity (∼5×10¹⁸W/cm²) and high repetition-rate (1 kHz), the system produces consistent D-D fusion, allowing for consistent neutron generation. Evidence of D-D fusion neutron production is verified b y a measurement suite with three independent detection systems: an EJ-309 organic scintillator with pulse-shape discrimination, a ³He proportional counter, and a set of 36 bubble detectors. Time-of-flight analysis of the scintillator data shows …

Legendre Pairs Of Lengths ℓ ≡ 0 (Mod 5), Ilias S. Kotsireas, Christopher Koutschan, Dursun A. Bulutoglu, David M. Arquette, Jonathan S. Turner, Kenneth J. Ryan

Faculty Publications

By assuming a type of balance for length ℓ = 87 and nontrivial subgroups of multiplier groups of Legendre pairs (LPs) for length ℓ = 85 , we find LPs of these lengths. We then study the power spectral density (PSD) values of m compressions of LPs of length 5 m . We also formulate a conjecture for LPs of lengths ℓ ≡ 0 (mod 5) and demonstrate how it can be used to decrease the search space and storage requirements for finding such LPs. The newly found LPs decrease the number of integers in the range ≤ 200 for …

A Computational Approach For Mapping Electrochemical Activity Of Multi-Principal Element Alloys, Jodie A. Yuwono, Xinyu Li, Tyler D. Dolezal, Adib J. Samin, Javen Qinfeng Shi, Zhipeng Li, Nick Birbilis

Faculty Publications

Multi principal element alloys (MPEAs) comprise an atypical class of metal alloys. MPEAs have been demonstrated to possess several exceptional properties, including, as most relevant to the present study a high corrosion resistance. In the context of MPEA design, the vast number of potential alloying elements and the staggering number of elemental combinations favours a computational alloy design approach. In order to computationally assess the prospective corrosion performance of MPEA, an approach was developed in this study. A density functional theory (DFT) – based Monte Carlo method was used for the development of MPEA ‘structure’; with the AlCrTiV alloy used …

System-Level Noise Performance Of Coherent Imaging Systems, Derek J. Burrell, Joshua H. Follansbee, Mark F. Spencer, Ronald G. Driggers

Faculty Publications

We provide an in-depth analysis of noise considerations in coherent imaging, accounting for speckle and scintillation in addition to “conventional” image noise. Specifically, we formulate closed-form expressions for total effective noise in the presence of speckle only, scintillation only, and speckle combined with scintillation. We find analytically that photon shot noise is uncorrelated with both speckle and weak-to-moderate scintillation, despite their shared dependence on the mean signal. Furthermore, unmitigated speckle and scintillation noise tends to dominate coherent-imaging performance due to a squared mean-signal dependence. Strong coupling occurs between speckle and scintillation when both are present, and we characterize this behavior …

Impact Of Silicon Ion Irradiation On Aluminum Nitride-Transduced Microelectromechanical Resonators, David D. Lynes, Joshua Young, Eric Lang, Hengky Chandrahalim

Faculty Publications

Microelectromechanical systems (MEMS) resonators use is widespread, from electronic filters and oscillators to physical sensors such as accelerometers and gyroscopes. These devices' ubiquity, small size, and low power consumption make them ideal for use in systems such as CubeSats, micro aerial vehicles, autonomous underwater vehicles, and micro-robots operating in radiation environments. Radiation's interaction with materials manifests as atomic displacement and ionization, resulting in mechanical and electronic property changes, photocurrents, and charge buildup. This study examines silicon (Si) ion irradiation's interaction with piezoelectrically transduced MEMS resonators. Furthermore, the effect of adding a dielectric silicon oxide (SiO₂) thin film is …

Strong Evidence For 9N And The Limits Of Existence Of Atomic Nuclei, R. J. Charity, J. Wylie, S. M. Wang, T. B. Webb, K. W. Brown, G. Cerizza, Z. Chajecki, J. M. Elson, J. Estee, D. E. M. Hoff, S. A. Kuvin, W. G. Lynch, Juan J. Manfredi, N. Michel, D. G. Mcneel, P. Morfouace, W. Nazarewicz, C. D. Pruitt, C. Santamaria, S. Sweany, J. Smith, L. G. Sobotka, M. B. Tsang, A. H. Wuosmaa

Faculty Publications

The boundaries of the chart of nuclides contain exotic isotopes that possess extreme proton-to-neutron asymmetries. Here we report on strong evidence of ⁹N, one of the most exotic proton-rich isotopes where more than one half of its constitute nucleons are unbound. With seven protons and two neutrons, this extremely proton-rich system would represent the first-known example of a ground-state five-proton emitter. The invariant-mass spectrum of its decay products can be fit with two peaks whose energies are consistent with the theoretical predictions of an open-quantum-system approach; however, we cannot rule out the possibility that only a single resonancelike peak …

Active-Illumination Extension To The Priest And Meier Pbrdf, Mark F. Spencer, Milo W. Hyde Iv, Santasri R. Bose-Pillai, Michael A. Marciniak

Faculty Publications

This paper develops a 3D vector solution for the scattering of partially coherent laser-beam illumination from statistically rough surfaces. Such a solution enables a rigorous comparison to the well-known Priest and Meier polarimetric bidirectional reflectance distribution function (pBRDF) [Opt Eng 41(5),988 (2002).]. Overall, the comparison shows excellent agreement for the normalized spectral density and the degree of polarization. Based on this agreement, the 3D vector solution also enables an extension to the Priest and Meier pBRDF that accounts for the effects of active illumination. In particular, the 3D vector solution enables the development of a closed-form expression for the spectral …

Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patnaik

Faculty Publications

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1–26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.

Deconstructing The Software Factory: A Practical Application Of Interorganizational Network Analysis, Zachary O. Ryan, Mark Reith, Clay Koschnick

Faculty Publications

Over the past 5 years, the number of DoD software organizations that employ nontraditional organizational structures has increased. These organizations, commonly referred to as software factories, often employ the network-based organizational structures found within high-technology industries. This article details ways in which network analysis techniques can be used to create a big picture view of these nontraditional organizations. Drawing on methodologies employed by network researchers, the authors develop and present an interorganizational analysis process that highlights a program's social and economic structures. Following the case history approach, they demonstrate the applicability of this approach by analyzing an emergent DoD software …

Lightning Forecast From Chaotic And Incomplete Time Series Using Wavelet De-Noising And Spatiotemporal Kriging, Jared K. Nystrom, Raymond Hill, Andrew J. Geyer, Joseph J. Pignatiello Jr., Eric Chicken

Faculty Publications

Purpose: Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Design/Methodology/Approach: Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lighting prediction.

Findings: The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

Abstract © Emerald Publishing …

Comparison Of A Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Densities With Ionosondes And Firi, Dylan J. Shaver, Dong L. Wu, Nimalan Swarnalingam, Anthony L. Franz, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

High-frequency skywave propagation can be heavily impacted by D- and E-region dynamics requiring accurate global measurements to optimize performance. A standard measurement technique is to use ionosondes, but they are unable to measure below 1 MHz and are only available at a limited number of land-locked sites around the globe. In contrast, the Global Navigation Satellite System radio occultation (GNSS-RO) bottom-up method is a new approach specifically designed to generate electron density profiles in the D- and E- region ionosphere. It takes advantage of satellite constellations that currently provide over 20,000 daily measurements and global coverage. In this paper, GNSS-RO …

Ironnetinjector: Weaponizing .Net Dynamic Language Runtime Engines, Anthony J. Rose, Scott R. Graham, Jacob Krasnov

Faculty Publications

As adversaries evolve their Tactics, Techniques, and Procedures (TTPs) to stay ahead of defenders, Microsoft’s .NET Framework emerges as a common component found in the tradecraft of many contemporary Advanced Persistent Threats (APTs), whether through PowerShell or C#. Because of .NET’s ease of use and availability on every recent Windows system, it is at the forefront of modern TTPs and is a primary means of exploitation. This article considers the .NET Dynamic Language Runtime as an attack vector, and how APTs have utilized it for offensive purposes. The technique under scrutiny is Bring Your Own Interpreter (BYOI), which is the …

Improving And Evaluating Performance Of The Proton Prediction System Through An Expanded Solar Proton Event Catalog, Samantha R. Howard

Theses and Dissertations

Solar energetic particles (SEPs) are especially high energy protons (≥ 5 or 10MeV kinetic energies) originating from the Sun that are known to have significant effects on space-based military operations. The Air Force’s current forecast model, the Proton Prediction System (PPS), forecasts less than half of SEP events that are observed, motivating the need for an update to the operational model. To develop the updated PPS model, PPS2.0, an expanded SEP catalog was produced, which includes 103 previously unidentified events and specification of the proton flux response above background levels or prior events. Event detection and source association were initially …

Quantifying Atmospheric Turbulence Effects On Image Quality Using A Deconvolution Algorithm, Ahmad M. Almalki

Theses and Dissertations

Imaging through turbulence is affected by several factors including imaging system specifications, imaging system setup and more importantly the atmospheric turbulence as it is uncontrollable. One important parameter which is used to quantify the atmospheric turbulence severity is the atmospheric coherence diameter (𝑟₀ ), known as Fried's parameter. This thesis explores ways to characterize the atmospheric turbulence effects on image quality using simulated and laboratory generated turbulence where 𝑟₀ is estimated using a maximum a posteriori (MAP) estimator and frequency domain analysis algorithms. Furthermore, image quality metrics such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) …

Methods Of Evaluating Quantum Phase Estimation Circuit Output, Charles A. Woodrum

Theses and Dissertations

The quantum phase estimation (QPE) algorithm is one of the most important quantum computing algorithms that has been developed. The QPE algorithm estimates the phase or phases of the eigenvalue or eigenvalues of a unitary operator. It is a critical step for applications like Shor’s algorithm for factoring and the HHL algorithm for solving linear systems of equations, but it remains difficult to implement on current quantum computers due to small numbers of logical qubits and high error rates. This investigation derives a more accurate estimation of the phase of a unitary operator than would otherwise be attained with the …

Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv

Theses and Dissertations

This dissertation explores the application of machine learning to the control of autonomous unmanned combat aerial vehicles (AUCAVs). In particular, this research applies deep reinforcement learning methodologies to a defensive air combat scenario wherein a fleet of AUCAVs protects a military high-value asset (HVA). A collection of air battle management scenarios along with an original simulation environment and a set of designed computational experiments support the approximation of high-quality decision policies by employing Markov decision processes, approximate dynamic programming algorithms, and deep neural networks for value function approximation.

Brdf Measurements And Physical Optics Modeling Applied To Anisotropic Satellite Solar Cells, Madilynn E. Compean

Theses and Dissertations

Light curve analysis is often used to discern information about satellites in geosynchronous orbits, and since solar panels comprise relatively large surface areas, their reflected energy can contribute greatly to observed light curves. Data was collected using a space qualified solar cell interrogated by a green HeNe laser. The data validated certain aspects from previous work, but also identified multi-slit behavior, showed that the specular term was a second diffraction pattern, and diagnosed the out-of-plane diffraction curvature as the conical diffraction phenomenon. Two physical-optics-based models were developed to incorporate these new features and better predict solar cell BRDF solely from …

Atmospheric Propagation Of Qubits: Laboratory Experiments To Field Demonstrations, Keith A. Wyman

Theses and Dissertations

Free-space quantum networks can enable global-scale quantum communication via satellite-based nodes and quantum ground transceivers. To enable building of robust global quantum networks, it is critical to learn how the state of the qubit is transformed while propagating through the atmosphere. With such an overarching goal, we built a laboratory based atmospheric turbulence simulator (ATS) to characterize the effects of atmospheric turbulence on an entangled pair of photons as a function of statistical quantities such as the Fried parameter or scintillation index for long-distance communication. Specifically, the changes in the statistical properties associated with a quantum source was investigated using …

Pattern-Of-Life Modeling With Automatic Dependent Surveillance-Broadcast (Ads-B), Sarah J. Bolton

Theses and Dissertations

This dissertation and research were sponsored by the Air Force Research Laboratory Layered Sensing Exploitation Branch (AFRL/RYA) to investigate the utility of using the data found within aircraft secondary radar to make predictions about aircraft characteristics and intent. The research focuses on making predictions on aircraft characteristics using only the kinetic data within one type of secondary radar, Automatic Dependent Surveillance-Broadcast (ADS-B), as a surrogate for primary radar. The results from this research provide a means to reduce the reliance on a type of aircraft tracking that is vulnerable to cyber attack and other integrity concerns.

Leveraging Galois Theory And Computational Results In The Search For Legendre Pairs, David M. Arquette

Theses and Dissertations

With applications spanning myriad disciplines, Hadamard matrices have tremendous utility. Infinitely many have been discovered, but there is no general proof of their existence. Proving the Hadamard conjecture would provide a significant technological edge. Hadamard matrices are difficult to construct in general; however, they can be created directly from Legendre pairs (LPs). While LPs are not trivial to find, a breakthrough in this area would be pivotal in the quest to prove the Hadamard conjecture. Most recent efforts rely upon refined search algorithms, and we seek to either develop a better such algorithm or discover an altogether new theoretical construction. …