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Air Force Institute of Technology

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Articles 421 - 450 of 2678

Full-Text Articles in Physical Sciences and Mathematics

Generation Of Vector Partially Coherent Optical Sources Using Phase-Only Spatial Light Modulators, Milo W. Hyde Iv, Santasri R. Bose-Pillai Oct 2020

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.

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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 Oct 2020

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 …

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Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael Pak, Dmitri S. Golubev, Alexey Bezryadin Oct 2020

Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael 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 …

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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 Oct 2020

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 …

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Detection Of Reconnection Signatures In Solar Flares, Taylor R. Whitney Aegerter, Daniel J. Emmons Ii, Robert D. Loper Oct 2020

Detection Of Reconnection Signatures In Solar Flares, Taylor R. Whitney Aegerter, Daniel J. Emmons Ii, Robert D. Loper

Faculty Publications

Solar flare forecasting is limited by the current understanding of mechanisms that govern magnetic reconnection, the main physical phenomenon associated with these events. As a result, forecasting relies mainly on climatological correlations to historical events rather than the underlying physics principles. Solar physics models place the neutral point of the reconnection event in the solar corona. Correspondingly, studies of photospheric magnetic fields indicate changes during solar flares—particularly in relation to the field helicity—on the solar surface as a result of the associated magnetic reconnection. This study utilizes data from the Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI) and …

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Analytic Provenance For Software Reverse Engineers, Wayne C. Henry Sep 2020

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 …

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Low-Information Radiation Imaging Using Rotating Scatter Mask Systems And Neural Network Algorithms, Robert J. Olesen Sep 2020

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 …

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Artificial Intelligence In Pursuit-Evasion Games, Specifically In The Scotland Yard Game, Arif M. Alamri Sep 2020

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 …

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Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing Sep 2020

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 …

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Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel Sep 2020

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 …

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A Methodology To Identify Alternative Suitable Nosql Data Models Via Observation Of Relational Database Interactions, Paul M. Beach Sep 2020

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 …

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Chronos Spacecraft With Chiron Probe: Exploration Of The Hydrosphere, Principle Satellites, Atmosphere, And Rings Of Uranus, Payton E. Pearson Sep 2020

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 …

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Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung Sep 2020

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 …

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Joint 1d And 2d Neural Networks For Automatic Modulation Recognition, Luis M. Rosario Morel Sep 2020

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 …

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Through-The-Wall Radar Detection Using Machine Learning, Aihua W. Wood, Ryan Wood, Matthew Charnley Aug 2020

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.

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Measurements Of Optical Turbulence Over 149-Km Path, Jack E. Mccrae, Santasri Bose-Pillai, Steven T. Fiorino, Aaron J. Archibald, Joel Meoak, Brannon Elmore, Thomas Kesler, Christopher A. Rice Jul 2020

Measurements Of Optical Turbulence Over 149-Km Path, Jack E. Mccrae, Santasri Bose-Pillai, Steven T. Fiorino, Aaron J. Archibald, Joel Meoak, Brannon Elmore, Thomas Kesler, Christopher A. Rice

Faculty Publications

An experiment was conducted to study turbulence along a 149-km path between the Mauna Loa and Haleakala mountain tops using digital cameras and light-emitting diode (LED) beacons. Much of the path is over the ocean, and a large portion of the path is 3 km above sea level. On the Mauna Loa side, six LED beacons were placed in a roughly linear array with pair spacings from 7 to 62 m. From the Haleakala side, a pair of cameras separated by 83.8 cm observed these beacons. Turbulence along the path induces tilts on the wavefronts, which results in displacements of …

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Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: Ii. Using Time-Dependent Simulations, Mark F. Spencer Jul 2020

Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: Ii. Using Time-Dependent Simulations, Mark F. Spencer

Faculty Publications

Part II of this two-part paper uses wave-optics simulations to look at the Monte Carlo averages associated with turbulence and time-dependent thermal blooming (TDTB). The goal is to investigate turbulence thermal blooming interaction (TTBI). At wavelengths near 1 μm, TTBI increases the amount of constructive and destructive interference (i.e., scintillation) that results from high-power laser beam propagation through distributed-volume atmospheric aberrations. As a result, we use the spherical-wave Rytov number, the number of wind-clearing periods, and the distortion number to gauge the strength of the simulated turbulence and TDTB. These parameters simply greatly given propagation paths with constant atmospheric conditions. …

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Implications Of Four-Dimensional Weather Cubes For Improved Cloud-Free Line-Of-Sight Assessments Of Free-Space Optical Communications Link Performance, Steven T. Fiorino, Santasri Bose-Pillai, Jaclyn Schmidt, Brannon Elmore, Kevin J. Keefer Jul 2020

Implications Of Four-Dimensional Weather Cubes For Improved Cloud-Free Line-Of-Sight Assessments Of Free-Space Optical Communications Link Performance, Steven T. Fiorino, Santasri Bose-Pillai, Jaclyn Schmidt, Brannon Elmore, Kevin J. Keefer

Faculty Publications

We advance the benefits of previously reported four-dimensional (4-D) weather cubes toward the creation of high-fidelity cloud-free line-of-sight (CFLOS) beam propagation for realistic assessment of autotracked/dynamically routed free-space optical (FSO) communication datalink concepts. The weather cubes accrue parameterization of optical effects and custom atmospheric resolution through implementation of numerical weather prediction data in the Laser Environmental Effects Definition and Reference atmospheric characterization and radiative transfer code. 4-D weather cube analyses have recently been expanded to accurately assess system performance (probabilistic climatologies and performance forecasts) at any wavelength/frequency or spectral band in the absence of field tests and employment data. The …

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Simulated Experince Evaluation In Developing Multi-Agent Coordination Graphs, Andrew J. Watson Jul 2020

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 …

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Turbulence Profiling Using Pupil Plane Wavefront Data Derived Fried Parameter Values For A Dynamically Ranged Rayleigh Beacon, Steven M. Zuraski, Elizabeth Beecher, Jack E. Mccrae, Steven T. Fiorino Jul 2020

Turbulence Profiling Using Pupil Plane Wavefront Data Derived Fried Parameter Values For A Dynamically Ranged Rayleigh Beacon, Steven M. Zuraski, Elizabeth Beecher, Jack E. Mccrae, Steven T. Fiorino

Faculty Publications

Long-range optical imaging applications are typically hindered by atmospheric turbulence. The effect of turbulence on an imaging system can manifest itself as an image blur effect usually quantified by the phase distortions present in the system. The blurring effect can be understood on the basis of the measured strength of atmospheric optical turbulence along the propagation path and its impacts on phase perturbation statistics within the imaging system. One method for obtaining these measurements is by the use of a dynamically ranged Rayleigh beacon system that exploits strategically varied beacon ranges along the propagation path, effectively obtaining estimates of the …

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Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: I. Using Steady-State Simulations, Mark F. Spencer Jul 2020

Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: I. Using Steady-State Simulations, Mark F. Spencer

Faculty Publications

Part I of this two-part paper uses wave-optics simulations to look at the Monte Carlo averages associated with turbulence and steady-state thermal blooming (SSTB). The goal is to investigate turbulence thermal blooming interaction (TTBI). At wavelengths near 1 μm, TTBI increases the amount of constructive and destructive interference (i.e., scintillation) that results from high-power laser beam propagation through distributed-volume atmospheric aberrations. As a result, we use the spherical-wave Rytov number and the distortion number to gauge the strength of the simulated turbulence and SSTB. These parameters simplify greatly given propagation paths with constant atmospheric conditions. In addition, we use the …

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Applications Of Portable Libs For Actinide Analysis, Ashwin P. Rao, John D. Auxier Ii, Dung Vu, Michael B. Shattan Jul 2020

Applications Of Portable Libs For Actinide Analysis, Ashwin P. Rao, John D. Auxier Ii, Dung Vu, Michael B. Shattan

Faculty Publications

A portable LIBS device was used for rapid elemental impurity analysis of plutonium alloys. This device demonstrates the potential for fast, accurate in-situ chemical analysis and could significantly reduce the fabrication time of plutonium alloys.

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Cyberspace Odyssey: A Competitive Team-Oriented Serious Game In Computer Networking, Kendra Graham [I], James Anderson [I], Conrad Rife [I], Bryce Heitmeyer [I], Pranav R. Patel [*], Scott L. Nykl, Alan C. Lin, Laurence D. Merkle Jul 2020

Cyberspace Odyssey: A Competitive Team-Oriented Serious Game In Computer Networking, Kendra Graham [I], James Anderson [I], Conrad Rife [I], Bryce Heitmeyer [I], Pranav R. Patel [*], Scott L. Nykl, Alan C. Lin, Laurence D. Merkle

Faculty Publications

Cyber Space Odyssey (CSO) is a novel serious game supporting computer networking education by engaging students in a race to successfully perform various cybersecurity tasks in order to collect clues and solve a puzzle in virtual near-Earth 3D space. Each team interacts with the game server through a dedicated client presenting a multimodal interface, using a game controller for navigation and various desktop computer networking tools of the trade for cybersecurity tasks on the game's physical network. Specifically, teams connect to wireless access points, use packet monitors to intercept network traffic, decrypt and reverse engineer that traffic, craft well-formed and …

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Effects Of Temperature And Antioxidants On The Oxidation Of Biodiesel Derived From Waste Vegetable Oil, Randy L. Maglinao, Torrey J. Wagner, Keegan Duff Jun 2020

Effects Of Temperature And Antioxidants On The Oxidation Of Biodiesel Derived From Waste Vegetable Oil, Randy L. Maglinao, Torrey J. Wagner, Keegan Duff

Faculty Publications

Biodiesel offers several environmental benefits and improvements to some fuel performance properties, but its poor oxidative stability has been a major concern. Currently, the accepted practice to improve biodiesel oxidative stability is the addition of antioxidants; numerous antioxidants have been studied but their effectiveness in inhibiting biodiesel oxidation is difficult to predict due to variation with resonance stability, solubility, reactivity, and volatility. To improve prediction efforts, this study explored the Rapid Small-Scale Oxidation Test (RSSOT) as a means to investigate how biodiesel oxidation is affected by antioxidant concentration and temperature, and compared its results with the oxidative stability index test. …

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Fourier Propagation Tool For Aberration Analysis And A Point Spread Function Calculation Of Systems With Curved Focal Planes, Stephen C. Cain Jun 2020

Fourier Propagation Tool For Aberration Analysis And A Point Spread Function Calculation Of Systems With Curved Focal Planes, Stephen C. Cain

Faculty Publications

This paper describes a new Fourier propagator for computing the impulse response of an optical system with a curved focal plane array, while including terms ignored in Fresnel and Fraunhofer calculations. The propagator includes a Rayleigh-Sommerfeld diffraction formula calculation from a distant point through the optical system to its image point predicted by geometric optics on a spherical surface. The propagator then approximates the neighboring field points via the traditional binomial approximation of the Taylor series expansion around that field point. This technique results in a propagator that combines the speed of a Fourier transform operation with the accuracy of …

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Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky Jun 2020

Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky

AFIT Patents

An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.

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Statistical Photo-Calibration Of Photo-Detectors For Radiometry Without Calibrated Light Sources Comprising An Arithmetic Unit To Determine A Gain And A Bias From Mean Values And Variance Values, Adrian M. Catarius, Nicholas Yielding, Stephen C. Cain, Michael D. Seal Jun 2020

Statistical Photo-Calibration Of Photo-Detectors For Radiometry Without Calibrated Light Sources Comprising An Arithmetic Unit To Determine A Gain And A Bias From Mean Values And Variance Values, Adrian M. Catarius, Nicholas Yielding, Stephen C. Cain, Michael D. Seal

AFIT Patents

Calibration of a radiometry system uses a readout circuit of a photo-detector to provide first and second measurements collected over first and second integration times, respectively, where the first and second measurements are related to a photonic input to the photo-detector by a gain and a bias. First mean and variance values are computed for a plurality of first measurements. Second mean and variance values are computed for a plurality of second measurements. The gain and bias are determined from the first and second mean values and the first and second variance values without the use of a calibrated source. …

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Battlespace Next™: Developing A Serious Game To Explore Multi-Domain Operations, Nathaniel Flack, Alan C. Lin, Gilbert L. Peterson, Mark G. Reith Jun 2020

Battlespace Next™: Developing A Serious Game To Explore Multi-Domain Operations, Nathaniel Flack, Alan C. Lin, Gilbert L. Peterson, Mark G. Reith

Faculty Publications

Changes in the geopolitical landscape and increasing technological complexity have prompted the U.S. Military to coin the terms Multi-Domain Operations (MDO) and Joint All-Domain Command and Control (JADC2) as over-arching strategy to frame the complexity of warfare across both traditional and emerging warfighting domains. Teaching new concepts associated with these terms requires both innovation as well as distinct education and training tools in order to realize the cultural change advocated by senior military leaders. Battlespace Next™ (BSN) is a serious game designed to teach concepts integral to MDO and initiate discussion on military strategy while conserving time, money, and manpower. …

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Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei Jun 2020

Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei

Theses and Dissertations

Operation of Unmanned Aerial Vehicles (UAV) support many critical missions in the United State Air Force (USAF). Monitoring abnormal behavior is one of many responsibilities of the operator during a mission. Some behaviors are hard to be detect by an operator, especially when flying one or more autonomous vehicles; as such, detections require a high level of attention and focus to flight parameters. In this research, a monitoring system and its algorithm are designed and tested for a target fixed-wing UAV. The Autonomy Monitoring Service (AMS) compares the real vehicle or simulated Vehicle with a similar simulated vehicle using Software …

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Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery Jun 2020

Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery

Theses and Dissertations

This thesis takes the Scotland Yard board game and modifies its rules to mimic important aspects of space in order to facilitate the creation of artificial intelligence for space asset pursuit/evasion scenarios. Space has become a physical warfighting domain. To combat threats, an understanding of the tactics, techniques, and procedures must be captured and studied. Games and simulations are effective tools to capture data lacking historical context. Artificial intelligence and machine learning models can use simulations to develop proper defensive and offensive tactics, techniques, and procedures capable of protecting systems against potential threats. Monte Carlo Tree Search is a bandit-based …

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