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Full-Text Articles in Physical Sciences and Mathematics

Malware Classification Through Abstract Syntax Trees And L-Moments, Anthony J. Rose [*], Christine M. Schubert Kabban, Scott R. Graham, Wayne C. Henry, Christopher M. Rondeau Sep 2024

Malware Classification Through Abstract Syntax Trees And L-Moments, Anthony J. Rose [*], Christine M. Schubert Kabban, Scott R. Graham, Wayne C. Henry, Christopher M. Rondeau

Faculty Publications

The ongoing evolution of malware presents a formidable challenge to cybersecurity: identifying unknown threats. Traditional detection methods, such as signatures and various forms of static analysis, inherently lag behind these evolving threats. This research introduces a novel approach to malware detection by leveraging the robust statistical capabilities of L-moments and the structural insights provided by Abstract Syntax Trees (ASTs) and applying them to PowerShell. L-moments, recognized for their resilience to outliers and adaptability to diverse distributional shapes, are extracted from network analysis measures like degree centrality, betweenness centrality, and closeness centrality of ASTs. These measures provide a detailed structural representation …


Coarse-Gridded Simulation Of The Nonlinear Schrödinger Equation With Machine Learning, Benjamin F. Akers, Kristina O. F. Williams Sep 2024

Coarse-Gridded Simulation Of The Nonlinear Schrödinger Equation With Machine Learning, Benjamin F. Akers, Kristina O. F. Williams

Faculty Publications

A numerical method for evolving the nonlinear Schrödinger equation on a coarse spatial grid is developed. This trains a neural network to generate the optimal stencil weights to discretize the second derivative of solutions to the nonlinear Schrödinger equation. The neural network is embedded in a symmetric matrix to control the scheme’s eigenvalues, ensuring stability. The machine-learned method can outperform both its parent finite difference method and a Fourier spectral method. The trained scheme has the same asymptotic operation cost as its parent finite difference method after training. Unlike traditional methods, the performance depends on how close the initial data …


Twisted Spatiotemporal Optical Vortex Beams In Dispersive Media, Milo W. Hyde Iv Sep 2024

Twisted Spatiotemporal Optical Vortex Beams In Dispersive Media, Milo W. Hyde Iv

Faculty Publications

We derive a closed-form expression for the mutual coherence function (MCF) of a twisted spatiotemporal optical vortex (STOV) beam after propagating a distance in a linear dispersive medium. A twisted STOV beam is a partially coherent optical field that possesses a coherent STOV and a stochastic twist coupling its space and time dimensions. These beams belong to a special class of space–time-coupled light fields that carry transverse (to the direction of propagation) orbital angular momentum, making them potentially useful in numerous applications including quantum optics, optical manipulation, and optical communications. After presenting the derivation, we validate our new general MCF …


Open-Loop Wavefront Sensing In The Presence Of Speckle And Weak Scintillation, Derek J. Burrell, Mark F. Spencer, Ronald G. Driggers Aug 2024

Open-Loop Wavefront Sensing In The Presence Of Speckle And Weak Scintillation, Derek J. Burrell, Mark F. Spencer, Ronald G. Driggers

Faculty Publications

In this paper, we show that speckle averaging helps to reduce the measurement error associated with a Shack–Hartmann wavefront sensor (SHWFS); however, this reduction is rendered ineffective with increasing beacon anisoplanatism. We do so operating in a weak-scintillation regime, where the SHWFS offers robust performance, and using in-plane translation of the illuminated rough surface to accomplish frame-to-frame speckle diversity. Understanding these trade-space limitations is critical when performing wavefront sensing with noncooperative, extended-source beacons.


Numerically Efficient Coherent Mode Representations For Partially Coherent Beams With Separable Phases, Milo W. Hyde, Carolina Rickenstorff Aug 2024

Numerically Efficient Coherent Mode Representations For Partially Coherent Beams With Separable Phases, Milo W. Hyde, Carolina Rickenstorff

Faculty Publications

We present a method to numerically compute the coherent mode representations (CMRs) for partially coherent beams with separable phases. This special class of random light field has the ability to self-focus and is resistant to turbulence-induced degradation, making it potentially useful in applications such as optical communications. We validate our method by generating (in simulation) two such sources from the literature using their computed CMRs. Lastly, we conclude with a summary of our approach and a discussion of potential applications.


On Large Language Models In National Security Applications, William N. Caballero, Philip R. Jenkins Jul 2024

On Large Language Models In National Security Applications, William N. Caballero, Philip R. Jenkins

Faculty Publications

The overwhelming success of GPT-4 in early 2023 highlighted the transformative potential of large language models (LLMs) across various sectors, including national security. This article explores the implications of LLM integration within national security contexts, analyzing their potential to revolutionize information processing, decision-making, and operational efficiency. Whereas LLMs offer substantial benefits, such as automating tasks and enhancing data analysis, they also pose significant risks, including hallucinations, data privacy concerns, and vulnerability to adversarial attacks. Through their coupling with decision-theoretic principles and Bayesian reasoning, LLMs can significantly improve decision-making processes within national security organizations. Namely, LLMs can facilitate the transition from …


An Integrated Space Test Lexicon: A Taxonomy For The Integrated Test And Evaluation Of Space Systems, Stephen Tullino, Andrew Keys, Robert A. Bettinger, Amy M. Cox, David R. Jacques Jul 2024

An Integrated Space Test Lexicon: A Taxonomy For The Integrated Test And Evaluation Of Space Systems, Stephen Tullino, Andrew Keys, Robert A. Bettinger, Amy M. Cox, David R. Jacques

Faculty Publications

The proposed Integrated Space Test Lexicon is intended to amalgamate the numerous definitions of integrated (IT or IT&E), development test (DT or DT&E), and operational test (OT or OT&E) into unified, service-wide definitions, aligned with the Space Test Enterprise Vision. Refining such definitions will help distill the core characteristics of these fundamental test types to first identify space system activities composing what is traditionally known as DT and OT, then to provide a means of how these activities fit into the IT paradigm and support space system development. In forging a common understanding of how DT and OT support space …


Phase Error Scaling Law In Two-Wavelength Adaptive Optics, Milo W. Hyde Iv, Matthew Kalensky, Michael J. Spencer Jun 2024

Phase Error Scaling Law In Two-Wavelength Adaptive Optics, Milo W. Hyde Iv, Matthew Kalensky, Michael J. Spencer

Faculty Publications

We derive a simple, physical, closed-form expression for the optical-path difference (OPD) of a two-wavelength adaptive-optics (AO) system. Starting from Hogge and Butts’ classic OPD variance integral expression, we apply Mellin transform techniques to obtain series and asymptotic solutions to the integral. For realistic two-wavelength AO systems, the former converges slowly and has limited utility. The latter, on the other hand, is a simple formula in terms of the separation between the AO sensing (i.e., the beacon) and compensation (or observation) wavelengths. We validate this formula by comparing it to the OPD variances obtained from the aforementioned series and direct …


Improving 2–5 Qubit Quantum Phase Estimation Circuits Using Machine Learning, Charles Woodrum [*], Torrey J. Wagner, David E. Weeks May 2024

Improving 2–5 Qubit Quantum Phase Estimation Circuits Using Machine Learning, Charles Woodrum [*], Torrey J. Wagner, David E. Weeks

Faculty Publications

Quantum computing has the potential to solve problems that are currently intractable to classical computers with algorithms like Quantum Phase Estimation (QPE); however, noise significantly hinders the performance of today’s quantum computers. Machine learning has the potential to improve the performance of QPE algorithms, especially in the presence of noise. In this work, QPE circuits were simulated with varying levels of depolarizing noise to generate datasets of QPE output. In each case, the phase being estimated was generated with a phase gate, and each circuit modeled was defined by a randomly selected phase. The model accuracy, prediction speed, overfitting level …


Analysis Of Modeled 3d Solar Magnetic Field During 30 X/M-Class Solar Flares, Seth H. Garland, Vasyl B. Yurchyshyn, Robert D. Loper, Benjamin F. Akers May 2024

Analysis Of Modeled 3d Solar Magnetic Field During 30 X/M-Class Solar Flares, Seth H. Garland, Vasyl B. Yurchyshyn, Robert D. Loper, Benjamin F. Akers

Faculty Publications

Using non-linear force free field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-min cadence Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of 1 hour before through 1 hour after the start of 18 X-class and 12 M-class solar flares. Several magnetic field parameters were calculated from the modeled fields directly, as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis, for two different regions: areas with photospheric |Bz|≥ 300 G (active region—AR) and areas above the photosphere with the …


Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila May 2024

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …


Deep Selenium Donors In Zngep2 Crystals: An Electron Paramagnetic Resonance Study Of A Nonlinear Optical Material, Timothy D. Gustafson, Larry E. Halliburton, Nancy C. Giles, Peter G. Schunemann, Kevin T. Zawilski, J. Jesenovec, Kent L. Averett, Jonathan E. Slagle [*] Apr 2024

Deep Selenium Donors In Zngep2 Crystals: An Electron Paramagnetic Resonance Study Of A Nonlinear Optical Material, Timothy D. Gustafson, Larry E. Halliburton, Nancy C. Giles, Peter G. Schunemann, Kevin T. Zawilski, J. Jesenovec, Kent L. Averett, Jonathan E. Slagle [*]

Faculty Publications

Zinc germanium diphosphide (ZnGeP2) is a ternary semiconductor best known for its nonlinear optical properties. A primary application is optical parametric oscillators operating in the mid-infrared region. Controlled donor doping provides a method to minimize the acceptor-related absorption bands that limit the output power of these devices. In the present study, a ZnGeP2 crystal is doped with selenium during growth. Selenium substitutes for phosphorus and serves as a deep donor. Significant concentrations of native defects (zinc vacancies, germanium-on-zinc antisites, and phosphorous vacancies) are also present in the crystal. Electron paramagnetic resonance (EPR) is used to establish the …


Exploring Quaternion Neural Network Loss Surfaces, Jeremiah Bill, Bruce A. Cox Apr 2024

Exploring Quaternion Neural Network Loss Surfaces, Jeremiah Bill, Bruce A. Cox

Faculty Publications

This paper explores the superior performance of quaternion multi-layer perceptron (QMLP) neural networks over real-valued multi-layer perceptron (MLP) neural networks, a phenomenon that has been empirically observed but not thoroughly investigated. The study utilizes loss surface visualization and projection techniques to examine quaternion-based optimization loss surfaces for the first time. The primary contribution of this research is the statistical evidence that QMLP models yield smoother loss surfaces than real-valued neural networks, which are measured and compared using a robust quantitative measure of loss surface “goodness” based on estimates of surface curvature. Extensive computational testing validates the effectiveness of these surface …


Effect Of Fabrication Parameters On The Ferroelectricity Of Hafnium Zirconium Oxide Films: A Statistical Study, Guillermo A. Salcedo, Ahmad E. Islam, Elizabeth Reichley, Michael Dietz, Christine M. Schubert Kabban, Kevin D. Leedy, Tyson C. Back, Weison Wang, Andrew Green, Timothy S. Wolfe, James M. Sattler Mar 2024

Effect Of Fabrication Parameters On The Ferroelectricity Of Hafnium Zirconium Oxide Films: A Statistical Study, Guillermo A. Salcedo, Ahmad E. Islam, Elizabeth Reichley, Michael Dietz, Christine M. Schubert Kabban, Kevin D. Leedy, Tyson C. Back, Weison Wang, Andrew Green, Timothy S. Wolfe, James M. Sattler

Faculty Publications

Ferroelectricity in hafnium zirconium oxide (Hf1−xZrxO2) and the factors that impact it have been a popular research topic since its discovery in 2011. Although the general trends are known, the interactions between fabrication parameters and their effect on the ferroelectricity of Hf1−xZrxO2 require further investigation. In this paper, we present a statistical study and a model that relates Zr concentration (x), film thickness (tf), and annealing temperature (Ta) with the remanent polarization (Pr) in tungsten (W)-capped Hf1−xZrxO2. …


Scriptblock Smuggling: Uncovering Stealthy Evasion Techniques In Powershell And .Net Environments, Anthony J. Rose Mar 2024

Scriptblock Smuggling: Uncovering Stealthy Evasion Techniques In Powershell And .Net Environments, Anthony J. Rose

Faculty Publications

The Antimalware Scan Interface (AMSI) plays a crucial role in detecting malware within Windows operating systems. This paper presents ScriptBlock Smuggling, a novel evasion and log spoofing technique exploiting PowerShell and .NET environments to circumvent the AMSI. By focusing on the manipulation of ScriptBlocks within the Abstract Syntax Tree (AST), this method creates dual AST representations, one for compiler execution and another for antivirus and log analysis, enabling the evasion of AMSI detection and challenging traditional memory patching bypass methods. This research provides a detailed analysis of PowerShell’s ScriptBlock creation and its inherent security features and pinpoints critical limitations in …


Data Supporting Research On Personalized Learning Paths, Sean Mochocki, Mark Reith Mar 2024

Data Supporting Research On Personalized Learning Paths, Sean Mochocki, Mark Reith

Faculty Publications

Personalized Learning Paths (PLPs) are a key application of Artificial Intelligence in E-Learning. In contrast to regular Learning Paths, they return a unique sequence of learning materials identified as meeting the individual needs of the students. In the literature, PLPs are often created from knowledge graphs, which assist with ordering topics and their associated learning materials. Knowledge graphs are typically directed and acyclic, to capture prerequisite relationships between topics, though they can also have bidirectional edges when these prerequisite relationships are not necessary. This data package provides a primarily un-directed knowledge graph, with associated repository of open-source learning materials that …


The Impact Of Data Preparation And Model Complexity On The Natural Language Classification Of Chinese News Headlines, Torrey J. Wagner, Dennis Guhl, Brent T. Langhals Mar 2024

The Impact Of Data Preparation And Model Complexity On The Natural Language Classification Of Chinese News Headlines, Torrey J. Wagner, Dennis Guhl, Brent T. Langhals

Faculty Publications

Given the emergence of China as a political and economic power in the 21st century, there is increased interest in analyzing Chinese news articles to better understand developing trends in China. Because of the volume of the material, automating the categorization of Chinese-language news articles by headline text or titles can be an effective way to sort the articles into categories for efficient review. A 383,000-headline dataset labeled with 15 categories from the Toutiao website was evaluated via natural language processing to predict topic categories. The influence of six data preparation variations on the predictive accuracy of four algorithms was …


Laboratory Exercise For The Radiometry Student, Michael A. Marciniak Mar 2024

Laboratory Exercise For The Radiometry Student, Michael A. Marciniak

Faculty Publications

The U.S. Air and Space Forces require optical expertise among their personnel. The Air Force Institute of Technology offers a graduate optics curriculum, which includes a three-course sequence to educate students in the optical concepts of radiometry and radiometric instrumentation. We find radiometry is often a deceptively difficult concept for students to master. To address this, we have developed an experiment in our optics-laboratory coursework to help them gain this mastery. A Fourier-transform infrared spectrometer (FTS) is used to collect spectral data from an unknown sample. FTS calibration and data collection are discussed here, as are the two specific samples …


Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor Mar 2024

Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor

Faculty Publications

Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …


Seasonal Variability And Predictability Of Monsoon Precipitation In Southern Africa, Matthew F. Horan, Fred Kucharski, Moetasim Ashfaq Mar 2024

Seasonal Variability And Predictability Of Monsoon Precipitation In Southern Africa, Matthew F. Horan, Fred Kucharski, Moetasim Ashfaq

Faculty Publications

Rainfed agriculture is the mainstay of economies across Southern Africa (SA), where most precipitation is received during the austral summer monsoon. This study aims to further our understanding of monsoon precipitation predictability over SA. We use three natural climate forcings, El Niño–Southern Oscillation, Indian Ocean Dipole (IOD), and the Indian Ocean Precipitation Dipole (IOPD)—the dominant precipitation variability mode—to construct an empirical model that exhibits significant skill over SA during monsoon in explaining precipitation variability and in forecasting it with a five-month lead. While most explained precipitation variance (50%–75%) comes from contemporaneous IOD and IOPD, preconditioning all three forcings is key …


The Behavior Of ½⟨111⟩ Screw Dislocations In W–Mo Alloys Analyzed Through Atomistic Simulations, Lucas A. Heaton, Kevin Chu, Adib J. Samin Feb 2024

The Behavior Of ½⟨111⟩ Screw Dislocations In W–Mo Alloys Analyzed Through Atomistic Simulations, Lucas A. Heaton, Kevin Chu, Adib J. Samin

Faculty Publications

Analyzing plastic flow in refractory alloys is relevant to many different commercial and technological applications. In this study, screw dislocation statics and dynamics were studied for various compositions of the body-centered cubic binary alloy tungsten–molybdenum (W–Mo). The core structure did not appear to change for different alloy compositions, consistent with the literature. The pure tungsten and pure molybdenum samples had the lowest plastic flow, while the highest dislocation velocities were observed for equiatomic, W0.5Mo0.5 alloys. In general, dislocation velocities were found to largely align with a well-established dislocation mobility phenomenological model supporting two discrete dislocation mobility regimes, …


Residual Optical Absorption From Native Defects In Cdsip2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Elizabeth M. Scherrer, Kevin T. Zawilski, Peter G. Schunemann, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton Feb 2024

Residual Optical Absorption From Native Defects In Cdsip2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Elizabeth M. Scherrer, Kevin T. Zawilski, Peter G. Schunemann, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton

Faculty Publications

CdSiP2 crystals are used in optical parametric oscillators to produce tunable output in the mid-infrared. As expected, the performance of the OPOs is adversely affected by residual optical absorption from native defects that are unintentionally present in the crystals. Electron paramagnetic resonance (EPR) identifies these native defects. Singly ionized silicon vacancies (V-Si) are responsible for broad optical absorption bands peaking near 800, 1033, and 1907 nm. A fourth absorption band, peaking near 630 nm, does not involve silicon vacancies. Exposure to 1064 nm light when the temperature of the CdSiP2 crystal is near 80K converts …


Editorial: Observations And Simulations Of Layering Phenomena In The Middle/Upper Atmosphere And Ionosphere, Bingkun Yu, Xuguang Cai, Daniel J. Emmons Ii, Chong Wang And Jianfei Wu Jan 2024

Editorial: Observations And Simulations Of Layering Phenomena In The Middle/Upper Atmosphere And Ionosphere, Bingkun Yu, Xuguang Cai, Daniel J. Emmons Ii, Chong Wang And Jianfei Wu

Faculty Publications

The middle/upper atmosphere and ionosphere are the transition between neutral and ionized components of the Earth’s atmosphere, including stratosphere, mesosphere, thermosphere, ionospheric E region and ionospheric F region (Laštovička et al., 2006; Xu, et al., 2007; Smith, 2012). The atmospheric thermal structure and composition are significantly affected by dynamical processes through coupling. The layering phenomena such as mesospheric metal layers, sporadic E layers, and noctilucent clouds are important tracers to study mechanisms of the vertical coupling from the lower to the upper atmosphere (Dou et al., 2010; Plane, 2012; Xue et al., 2013).


Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw Jan 2024

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 …


Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won Jan 2024

Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won

Faculty Publications

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …


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 Jan 2024

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 …


Complete Solution Of The Lady In The Lake Scenario, Alexander Von Moll, Meir Pachter Jan 2024

Complete Solution Of The Lady In The Lake Scenario, Alexander Von Moll, Meir Pachter

Faculty Publications

In the Lady in the Lake scenario, a mobile agent, L, is pitted against an agent, M, who is constrained to move along the perimeter of a circle. L is assumed to begin inside the circle and wishes to escape to the perimeter with some finite angular separation from M at the perimeter. This scenario has, in the past, been formulated as a zero-sum differential game wherein L seeks to maximize terminal separation and M seeks to minimize it. Its solution is well-known. However, there is a large portion of the state space for which the canonical solution does not …


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 Dec 2023

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 Lopez Jr, J. Addison Betances Dec 2023

Passive Physical Layer Distinct Native Attribute Cyber Security Monitor, Christopher M. Rondeau, Michael A. Temple, Juan 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 …


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 Dec 2023

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 …