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Engaging Empirical Dynamic Modeling To Detect Intrusions In Cyber-Physical Systems, David R. Crow, Scott R. Graham, Brett J. Borghetti, Patrick J. Sweeney
Engaging Empirical Dynamic Modeling To Detect Intrusions In Cyber-Physical Systems, David R. Crow, Scott R. Graham, Brett J. Borghetti, Patrick J. Sweeney
Faculty Publications
Modern cyber-physical systems require effective intrusion detection systems to ensure adequate critical infrastructure protection. Developing an intrusion detection capability requires an understanding of the behavior of a cyber-physical system and causality of its components. Such an understanding enables the characterization of normal behavior and the identification and reporting of anomalous behavior. This chapter explores a relatively new time series analysis technique, empirical dynamic modeling, that can contribute to system understanding. Specifically, it examines if the technique can adequately describe causality in cyber-physical systems and provides insights into it serving as a foundation for intrusion detection.
2 × 2 Anisotropic Transfer Matrix Approach For Optical Propagation In Uniaxial Transmission Filter Structures, Hammid Al-Ghezi, Rudra Gnawali, Partha P. Banerjee, Lirong Sun, Jonathan E. Slagle, Dean Evans
2 × 2 Anisotropic Transfer Matrix Approach For Optical Propagation In Uniaxial Transmission Filter Structures, Hammid Al-Ghezi, Rudra Gnawali, Partha P. Banerjee, Lirong Sun, Jonathan E. Slagle, Dean Evans
Student Publications
Multi-layered metamaterial structures show promise in a wide variety of optical applications such as superlenses, electromagnetic cloaking, tunable filters, sensors, and spatial light modulators. Optical transmission analysis of multilayer metallo-dielectric stacks with overall thickness less than the wavelength of light can be modeled using effective medium theory and the Berreman matrix method. For multilayer anisotropic stacks of arbitrary thickness, a rigorous 4 × 4 transfer matrix embodiment is typically used. In this work, a 2 × 2 anisotropic transfer matrix method is developed to analyze optical propagation through multilayer uniaxial stacks of arbitrary thicknesses. Optical transmission of a multilayer silver–zinc …
Establishing The Foundations To Measure Organizational Agility For Military Organizations, Jeremy R. Geiger, John J. Elshaw, David R. Jacques
Establishing The Foundations To Measure Organizational Agility For Military Organizations, Jeremy R. Geiger, John J. Elshaw, David R. Jacques
Faculty Publications
There is an ongoing demand for organizations to become more agile in order to prosper amongst their competitors. Many military organizations have declared a renewed focus towards organizational agility. The goal of this research is to isolate the variables needed to measure organizational agility (OA) in military organizations, allowing for the future development of a suitable method to measure OA without the need to interact with outside organizations. This article begins by providing a suitable and formal definition of organizational agility by exploring and analyzing relevant scholarly literature on the subject. Related terms, such as organizational resiliency, flexibility, robustness, versatility, …
Legendre G-Array Pairs And The Theoretical Unification Of Several G-Array Families, K. T. Arasu, Dursun A. Bulutoglu, J. R. Hollon
Legendre G-Array Pairs And The Theoretical Unification Of Several G-Array Families, K. T. Arasu, Dursun A. Bulutoglu, J. R. Hollon
Faculty Publications
We investigate how Legendre G-array pairs are related to several different perfect binary G-array families. In particular we study the relations between Legendre G-array pairs, Sidelnikov-Lempel-Cohn-Eastman ℤq−1-arrays, Yamada-Pott G-array pairs, Ding-Helleseth-Martinsen ℤ2×ℤmp-arrays, Yamada ℤ(q−1)/2-arrays, Szekeres ℤmp-array pairs, Paley ℤmp-array pairs, and Baumert ℤm1p1×ℤm2p2-array pairs. Our work also solves one of the two open problems posed in Ding~[J. Combin. Des. 16 (2008), 164-171]. Moreover, we provide several computer search based existence and non-existence results regarding Legendre ℤn-array pairs. …
Generation Of Vector Partially Coherent Optical Sources Using Phase-Only Spatial Light Modulators, Milo W. Hyde Iv, Santasri R. Bose-Pillai
Generation Of Vector Partially Coherent Optical Sources Using Phase-Only Spatial Light Modulators, Milo W. Hyde Iv, Santasri R. Bose-Pillai
AFIT Patents
A vector partially coherent source (VPCS) generator includes a laser that emits coherent light; an interferometer consisting of polarizing beam splitters (PBSs) to split the laser light into its vertical and horizontal polarization components;] first and second spatial light modulators (SLMs) that respectively control the vertical and horizontal polarization components; and a control system communicatively coupled to the first and second SLMs to adjust beam shape and coherence without physically moving or removing optical elements in the interferometer.
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Faculty Publications
Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …
Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael V. Pak, Dmitri S. Golubev, Alexey Bezryadin
Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael V. Pak, Dmitri S. Golubev, Alexey Bezryadin
Faculty Publications
We study one-dimensional chains of superconducting islands with a particular emphasis on the regime in which every second island is switched into its normal state, thus forming a superconductor-insulator-normal metal (S-I-N) repetition pattern. As is known since Giaever tunneling experiments, tunneling charge transport between a superconductor and a normal metal becomes exponentially suppressed, and zero-bias resistance diverges, as the temperature is reduced and the energy gap of the superconductor grows larger than the thermal energy. Here we demonstrate that this physical phenomenon strongly impacts transport properties of inhomogeneous superconductors made of weakly coupled islands with fluctuating values of the critical …
Graduate School Of Engineering And Management Fall 2020 Fact Book, Graduate School Of Engineering And Management, Air Force Institute Of Technology
Graduate School Of Engineering And Management Fall 2020 Fact Book, Graduate School Of Engineering And Management, Air Force Institute Of Technology
AFIT Documents
No abstract provided.
Impacts Of Laboratory Vibrations And Laser Flicker Noise On Digital Holography, Douglas E. Thornton, Mark F. Spencer, Christopher A. Rice, Glen P. Perram
Impacts Of Laboratory Vibrations And Laser Flicker Noise On Digital Holography, Douglas E. Thornton, Mark F. Spencer, Christopher A. Rice, Glen P. Perram
Faculty Publications
In this paper, we experimentally demonstrate the impacts of laboratory vibrations and laser flicker noise on digital holography (DH). Specifically, we measure both the vibration efficiency and the coherence efficiency of our DH system at various focal-plane array integration times and path-length differences between the signal and reference. These efficiencies, in practice, contribute to the overall mixing efficiency, which is a measure for how well the detected signal and reference interfere. The results show that when the integration time is ≤1ms, the laboratory vibrations are negligible with a vibration efficiency of 100%; however, when the integration time equals 100 ms, …
A Fully Quantum Calculation Of Broadening And Shifting Coefficients Of The D1 And D2 Spectral Lines Of Alkali-Metal Atoms Colliding With Noble-Gas Atoms, Robert D. Loper, David E. Weeks
A Fully Quantum Calculation Of Broadening And Shifting Coefficients Of The D1 And D2 Spectral Lines Of Alkali-Metal Atoms Colliding With Noble-Gas Atoms, Robert D. Loper, David E. Weeks
Faculty Publications
We use the Baranger model to compute collisional broadening and shift rates for the D1 and D2 spectral lines of M + Ng, where M = K, Rb, Cs and Ng = He, Ne, Ar. Scattering matrix elements are calculated using the channel packet method, and non-adiabatic wavepacket dynamics are determined using the split-operator method together with a unitary transformation between adiabatic and diabatic representations. Scattering phase shift differences are weighted thermally and are integrated over temperatures ranging from 100 K to 800 K. We find that predicted broadening rates compare well with experiment, but shift rates are …
Multimodal Representation Learning And Set Attention For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Christine M. Schubert Kabban, Jacob Martin, Joseph Meola
Multimodal Representation Learning And Set Attention For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Christine M. Schubert Kabban, Jacob Martin, Joseph Meola
Faculty Publications
A multimodal generative modeling approach combined with permutation-invariant set attention is investigated in this paper to support long-wave infrared (LWIR) in-scene atmospheric compensation. The generative model can produce realistic atmospheric state vectors (T;H2O;O3) and their corresponding transmittance, upwelling radiance, and downwelling radiance (TUD) vectors by sampling a low-dimensional space. Variational loss, LWIR radiative transfer loss and atmospheric state loss constrain the low-dimensional space, resulting in lower reconstruction error compared to standard mean-squared error approaches. A permutation-invariant network predicts the generative model low-dimensional components from in-scene data, allowing for simultaneous estimates of the atmospheric state and TUD …
End-To-End Direct Digital Synthesis Simulation And Mathematical Model To Minimize Quantization Effects Of Digital Signal Generation, Pranav R. Patel, Richard K. Martin
End-To-End Direct Digital Synthesis Simulation And Mathematical Model To Minimize Quantization Effects Of Digital Signal Generation, Pranav R. Patel, Richard K. Martin
Faculty Publications
Direct digital synthesis (DDS) architectures are becoming more prevalent as modern digital-to-analog converter (DAC) and programmable logic devices evolve to support higher bandwidths. The DDS architecture provides the benefit of digital control but at a cost of generating spurious content in the spectrum. The generated spurious content may cause intermodulation distortion preventing proper demodulation of the received signal. The distortion may also interfere with the neighboring frequency bands. This article presents the various DDS architectures and explores the DDS architecture which provides the most digital reconfigurability with the lowest spurious content. End-to-end analytical equations, numerical and mathematical models are developed …
Analytic Provenance For Software Reverse Engineers, Wayne C. Henry
Analytic Provenance For Software Reverse Engineers, Wayne C. Henry
Theses and Dissertations
Reverse engineering is a time-consuming process essential to software-security tasks such as malware analysis and vulnerability discovery. During the process, an engineer will follow multiple leads to determine how the software functions. The combination of time and possible explanations makes it difficult for the engineers to maintain a context of their findings within the overall task. Analytic provenance tools have demonstrated value in similarly complex fields that require open-ended exploration and hypothesis vetting. However, they have not been explored in the reverse engineering domain. This dissertation presents SensorRE, the first analytic provenance tool designed to support software reverse engineers. A …
Artificial Intelligence In Pursuit-Evasion Games, Specifically In The Scotland Yard Game, Arif M. Alamri
Artificial Intelligence In Pursuit-Evasion Games, Specifically In The Scotland Yard Game, Arif M. Alamri
Theses and Dissertations
This research provides a heuristic algorithm for the detectives, who try to collectively capture a criminal known as Mr. X, in the Scotland Yard pursuer-evasion game. In Scotland Yard, a team of detectives attempts to converge on and capture a criminal known as Mr. X. The heuristic algorithm developed in this thesis is designed to emulate human strategies when playing the game. The algorithm uses the current state of the board at each time step, including the current positions of the detectives as well as the last known position of Mr. X. The heuristic algorithm then analyses all of the …
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Theses and Dissertations
Hyperspectral target detection promises new operational advantages, with increasing instrument spectral resolution and robust material discrimination. Resolving surface materials requires a fast and accurate accounting of atmospheric effects to increase detection accuracy while minimizing false alarms. This dissertation investigates deep learning methods constrained by the processes governing radiative transfer to efficiently perform atmospheric compensation on data collected by long-wave infrared (LWIR) hyperspectral sensors. These compensation methods depend on generative modeling techniques and permutation invariant neural network architectures to predict LWIR spectral radiometric quantities. The compensation algorithms developed in this work were examined from the perspective of target detection performance using …
Chronos Spacecraft With Chiron Probe: Exploration Of The Hydrosphere, Principle Satellites, Atmosphere, And Rings Of Uranus, Payton E. Pearson
Chronos Spacecraft With Chiron Probe: Exploration Of The Hydrosphere, Principle Satellites, Atmosphere, And Rings Of Uranus, Payton E. Pearson
Theses and Dissertations
A design reference mission using more modern technological innovations has been developed for exploration of the outer reaches of our Solar System, specifically Uranus and its system of satellites. This mission will utilize theoretical technologies mostly without regard to their current technological readiness level (TRL), though most systems have a TRL of at least 5. The primary innovations explored in this thesis are the new launch systems that provide far greater payload capacity potentially sent to anywhere in the Solar System, new Stirling-engine radioisotope thermoelectric generators (SRTGs), vastly improved data storage technologies, optimized satellite antenna relay of data using much …
Joint 1d And 2d Neural Networks For Automatic Modulation Recognition, Luis M. Rosario Morel
Joint 1d And 2d Neural Networks For Automatic Modulation Recognition, Luis M. Rosario Morel
Theses and Dissertations
The digital communication and radar community has recently manifested more interest in using data-driven approaches for tasks such as modulation recognition, channel estimation and distortion correction. In this research we seek to apply an object detector for parameter estimation to perform waveform separation in the time and frequency domain prior to classification. This enables the full automation of detecting and classifying simultaneously occurring waveforms. We leverage a lD ResNet implemented by O'Shea et al. in [1] and the YOLO v3 object detector designed by Redmon et al. in [2]. We conducted an in depth study of the performance of these …
Low-Information Radiation Imaging Using Rotating Scatter Mask Systems And Neural Network Algorithms, Robert J. Olesen
Low-Information Radiation Imaging Using Rotating Scatter Mask Systems And Neural Network Algorithms, Robert J. Olesen
Theses and Dissertations
While recent studies have demonstrated the directional capabilities of the single-detector rotating scatter mask (RSM) system for discrete, dual-particle environments, there has been little progress towards adapting it as a true imaging device. In this research, two algorithms were developed and tested using an RSM mask design previously optimized for directional detection and simulated 137Cs signals from a variety of source distributions. The first, maximum-likelihood expectation-maximization (ML-EM), was shown to generate noisy images, with relatively low accuracy (145% average relative error) and signal-to-noise ratio (0.27) for most source distributions simulated. The second, a novel regenerative neural network (ReGeNN), performed exceptionally …
Aligning Performance Management Systems For Lasting Outcomes In Humanitarian Operations, Kalyn M. Howard
Aligning Performance Management Systems For Lasting Outcomes In Humanitarian Operations, Kalyn M. Howard
Theses and Dissertations
Logistics is dynamic, expansive, and critical to organizational success. While it is generally believed that effective logistics management is associated with positive performance outcomes, the links between organizational practice and performance are understudied. This dissertation leverages resource-based theory and organizational learning theory to examine organizational practice and performance in non-traditional logistics settings, with particular focus on military organizations and humanitarian operational settings. First, a meta-analytical study establishes generalizable associations between various operations management practices and performance outcomes. Then, this is applied to dynamic humanitarian logistics settings, exploring how practitioners perceive practice and performance, and how this is reported and documented …
A Methodology To Identify Alternative Suitable Nosql Data Models Via Observation Of Relational Database Interactions, Paul M. Beach
A Methodology To Identify Alternative Suitable Nosql Data Models Via Observation Of Relational Database Interactions, Paul M. Beach
Theses and Dissertations
The effectiveness and performance of data-intensive applications are influenced by the suitability of the data models upon which they are built. The relational data model has been the de facto data model underlying most database systems since the 1970’s. However, the recent emergence of NoSQL data models have provided users with alternative ways of storing and manipulating data. Previous research has demonstrated the potential value in applying NoSQL data models in non-distributed environments. However, knowing when to apply these data models has generally required inputs from system subject matter experts to make this determination. This research, sponsored by the Air …
Agility Measurement For Large Organizations, Jeremy R. Geiger
Agility Measurement For Large Organizations, Jeremy R. Geiger
Theses and Dissertations
There is an ongoing demand for organizations to become more agile in order to prosper amongst their competitors. Many organizations, including the United States Department of Defense (DoD), have declared a renewed focus towards organizational agility. This research begins by providing a suitable and formal definition of organizational agility (OA) by exploring and analyzing relevant scholarly literature on the subject. Existing methods to measure OA are examined and summarized, and their current limitations are highlighted. Previous studies to find characteristics associated with organizational agility are examined and the Q-sort method was employed to discover, analyze and eliminate redundant items from …
Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung
Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung
Theses and Dissertations
This dissertation focuses on improving the ability to detect dim stellar objects that are in close proximity to a bright one, through statistical image processing using short exposure images. The goal is to improve the space domain awareness capabilities with the existing infrastructure. Two new algorithms are developed. The first one is through the Neighborhood System Blind Deconvolution where the data functions are separated into the bright object, the neighborhood system, and the background functions. The second one is through the Dimension Reduction Blind Deconvolution, where the object function is represented by the product of two matrices. Both are designed …
Investigation Of Factors Impacting A Helicopter Height-Velocity Diagram, Timothy A. Brown
Investigation Of Factors Impacting A Helicopter Height-Velocity Diagram, Timothy A. Brown
Theses and Dissertations
A dynamic helicopter model was incorporated into an optimal control problem to determine minimal landing velocities. The solutions were determined using pseudospectral collocation methods as implemented by the GPOPS-II software. These solutions were then compiled to develop a HV diagram. An HV diagram displays regions of flight based on a helicopter's airspeed and height above the ground in which a safe landing would not be possible following engine failure. The applied methodology for constructing the HV diagram reduced issues involving solution convergence that was encountered in previous research. The influence of ground effect on the dynamic model was also investigated. …
Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel
Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel
Theses and Dissertations
In legacy Global Positioning System (GPS) Satellite Navigation (SatNav) payloads, the architecture does not provide the flexibility to adapt to changing circumstances and environments. GPS SatNav payloads have largely remained unchanged since the system became fully operational in April 1995. Since then, the use of GPS has become ubiquitous in our day-to-day lives. GPS availability is now a basic assumption for distributed infrastructure; it has become inextricably tied to our national power grids, cellular networks, and global financial systems. Emerging advancements of easy to use radio technologies, such as software-defined radios (SDRs), have greatly lowered the difficulty of discovery and …
Artificial Neural Network Discovery Of A Switchable Metasurface Reflector, J. R. Thompson, J. A. Burrow, P. J. Shah, Jonathan E. Slagle, E. S. Harper, A. Van Rynbach, I. Agha, M. S. Mills
Artificial Neural Network Discovery Of A Switchable Metasurface Reflector, J. R. Thompson, J. A. Burrow, P. J. Shah, Jonathan E. Slagle, E. S. Harper, A. Van Rynbach, I. Agha, M. S. Mills
Student Publications
Optical materials engineered to dynamically and selectively manipulate electromagnetic waves are essential to the future of modern optical systems. In this paper, we simulate various metasurface configurations consisting of periodic 1D bars or 2D pillars made of the ternary phase change material Ge2Sb2Te5 (GST). Dynamic switching behavior in reflectance is exploited due to a drastic refractive index change between the crystalline and amorphous states of GST. Selectivity in the reflection and transmission spectra is manipulated by tailoring the geometrical parameters of the metasurface. Due to the immense number of possible metasurface configurations, we train deep neural networks capable of exploring …
Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew Terzuoli
Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew Terzuoli
Faculty Publications
The spectral method is typically applied as a simple and efficient method to solve the parabolic wave equation in phase screen scintillation models. The critical factors that can greatly affect the spectral method accuracy is the uniformity and smoothness of the input function. This paper observes these effects on the accuracy of the finite difference and the spectral methods applied to a wideband SATCOM signal propagation model simulated in the ultra-high frequency (UHF) band. The finite difference method uses local pointwise approximations to calculate a derivative. The spectral method uses global trigonometric interpolants that achieve remarkable accuracy for continuously differentiable …
Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew J. Terzuoli Jr.
Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew J. Terzuoli Jr.
Faculty Publications
The spectral method is typically applied as a simple and efficient method to solve the parabolic wave equation in phase screen scintillation models. The critical factors that can greatly affect the spectral method accuracy is the uniformity and smoothness of the input function. This paper observes these effects on the accuracy of the finite difference and the spectral methods applied to a wideband SATCOM signal propagation model simulated in the ultra-high frequency (UHF) band. The finite difference method uses local pointwise approximations to calculate a derivative. The spectral method uses global trigonometric interpolants that achieve remarkable accuracy for continuously differentiable …
Through-The-Wall Radar Detection Using Machine Learning, Aihua W. Wood, Ryan Wood, Matthew Charnley
Through-The-Wall Radar Detection Using Machine Learning, Aihua W. Wood, Ryan Wood, Matthew Charnley
Faculty Publications
This paper explores the through-the-wall inverse scattering problem via machine learning. The reconstruction method seeks to discover the shape, location, and type of hidden objects behind walls, as well as identifying certain material properties of the targets. We simulate RF sources and receivers placed outside the room to generate observation data with objects randomly placed inside the room. We experiment with two types of neural networks and use an 80-20 train-test split for reconstruction and classification.
Residual-Based Multi-Filter Methodology For All-Source Fault Detection, Exclusion, And Performance Monitoring, Juan Jurado, John F. Raquet, Christine M. Schubert Kabban Air Force Institute Of Technology, Jonathon S. Gipson
Residual-Based Multi-Filter Methodology For All-Source Fault Detection, Exclusion, And Performance Monitoring, Juan Jurado, John F. Raquet, Christine M. Schubert Kabban Air Force Institute Of Technology, Jonathon S. Gipson
Faculty Publications
All-source navigation has become increasingly relevant over the past decade with the development of viable alternative sensor technologies. However, as the number and type of sensors informing a system increases, so does the probability of corrupting the system with sensor modeling errors, signal interference, and undetected faults. Though the latter of these has been extensively researched, the majority of existing approaches have constrained faults to biases and designed algorithms centered around the assumption of simultaneously redundant, synchronous sensors with valid measurement models, none of which are guaranteed for all-source systems. As part of an overall all-source assured or resilient navigation …
Simulated Experince Evaluation In Developing Multi-Agent Coordination Graphs, Andrew J. Watson
Simulated Experince Evaluation In Developing Multi-Agent Coordination Graphs, Andrew J. Watson
Theses and Dissertations
Cognitive science has proposed that a way people learn is through self-critiquing by generating 'what-if' strategies for events (simulation). It is theorized that people use this method to learn something new as well as to learn more quickly. This research adds this concept to a graph-based genetic program. Memories are recorded during fitness assessment and retained in a global memory bank based on the magnitude of change in the agent’s energy and age of the memory. Between generations, candidate agents perform in simulations of the stored memories. Candidates that perform similarly to good memories and differently from bad memories are …