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Air Force Institute of Technology

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Full-Text Articles in Physical Sciences and Mathematics

Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco, Torrey J. Wagner, Brent T. Langhals Jun 2021

Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco, Torrey J. Wagner, Brent T. Langhals

Faculty Publications

Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wavelength bands available in Landsat 8 imagery. The methods classify each pixel into 4 different classes: clear, cloud shadow, light cloud, or cloud. The first method is based on a fully connected neural network with ten input neurons, two hidden layers of 8 and 10 neurons respectively, and a single-neuron output for each class. This type of model is considered with and without L2 regularization applied to the kernel weighting. The final model type is a random forest classifier created from an ensemble of …

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Year-Independent Prediction Of Food Insecurity Using Classical & Neural Network Machine Learning Methods, Caleb Christiansen, Torrey J. Wagner, Brent Langhals May 2021

Year-Independent Prediction Of Food Insecurity Using Classical & Neural Network Machine Learning Methods, Caleb Christiansen, Torrey J. Wagner, Brent Langhals

Faculty Publications

Current food crisis predictions are developed by the Famine Early Warning System Network, but they fail to classify the majority of food crisis outbreaks with model metrics of recall (0.23), precision (0.42), and f1 (0.30). In this work, using a World Bank dataset, classical and neural network (NN) machine learning algorithms were developed to predict food crises in 21 countries. The best classical logistic regression algorithm achieved a high level of significance (p < 0.001) and precision (0.75) but was deficient in recall (0.20) and f1 (0.32). Of particular interest, the classical algorithm indicated that the vegetation index and the food price index were both positively correlated with food crises. A novel method for performing an iterative multidimensional hyperparameter search is presented, which resulted in significantly improved performance when applied to this dataset. Four iterations were conducted, which resulted in excellent 0.96 for metrics of precision, recall, and f1. Due to this strong performance, the food crisis year was removed from the dataset to prevent immediate extrapolation when used on future data, and the modeling process was repeated. The best “no year” model metrics remained strong, achieving ≥0.92 for recall, precision, and f1 while meeting a 10% f1 overfitting threshold on the test (0.84) and holdout (0.83) datasets. The year-agnostic neural network model represents a novel approach to classify food crises and outperforms current food crisis prediction efforts.

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Model For Quantifying The Quality Of Secure Service, Paul M. Simon, Scott R. Graham, Christopher Talbot, Micah J. Hayden May 2021

Model For Quantifying The Quality Of Secure Service, Paul M. Simon, Scott R. Graham, Christopher Talbot, Micah J. Hayden

Faculty Publications

Although not common today, communications networks could adjust security postures based on changing mission security requirements, environmental conditions, or adversarial capability, through the coordinated use of multiple channels. This will require the ability to measure the security of communications networks in a meaningful way. To address this need, in this paper, we introduce the Quality of Secure Service (QoSS) model, a methodology to evaluate how well a system meets its security requirements. This construct enables a repeatable and quantifiable measure of security in a single- or multi-channel network under static configurations. In this approach, the quantification of security is based …

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The Effects Of Individual Differences, Non‐Stationarity, And The Importance Of Data Partitioning Decisions For Training And Testing Of Eeg Cross‐Participant Models, Alexander J. Kamrud, Brett J. Borghetti, Christine M. Schubert Kabban May 2021

The Effects Of Individual Differences, Non‐Stationarity, And The Importance Of Data Partitioning Decisions For Training And Testing Of Eeg Cross‐Participant Models, Alexander J. Kamrud, Brett J. Borghetti, Christine M. Schubert Kabban

Faculty Publications

EEG-based deep learning models have trended toward models that are designed to perform classification on any individual (cross-participant models). However, because EEG varies across participants due to non-stationarity and individual differences, certain guidelines must be followed for partitioning data into training, validation, and testing sets, in order for cross-participant models to avoid overestimation of model accuracy. Despite this necessity, the majority of EEG-based cross-participant models have not adopted such guidelines. Furthermore, some data repositories may unwittingly contribute to the problem by providing partitioned test and non-test datasets for reasons such as competition support. In this study, we demonstrate how improper …

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Single-Shot Positron Annihilation Lifetime Spectroscopy Using A Liquid Scintillator, Joshua R. Machacek, Shawn Mctaggart, Larry W. Burggraf May 2021

Single-Shot Positron Annihilation Lifetime Spectroscopy Using A Liquid Scintillator, Joshua R. Machacek, Shawn Mctaggart, Larry W. Burggraf

Faculty Publications

Liquid scintillators provide a fast, single component response. However, they traditionally have a low flashpoint and high vapor pressure. We demonstrate the use of an EJ-309 scintillator (high flashpoint and low vapor pressure variant) to acquire single-shot positron annihilation lifetime spectroscopy spectra using a trap-based positron beam.

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Defect Detection In Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning, Philip Cho, Aihua W. Wood, Krishnamurthy Mahalingam, Kurt Eyink May 2021

Defect Detection In Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning, Philip Cho, Aihua W. Wood, Krishnamurthy Mahalingam, Kurt Eyink

Faculty Publications

Point defects play a fundamental role in the discovery of new materials due to their strong influence on material properties and behavior. At present, imaging techniques based on transmission electron microscopy (TEM) are widely employed for characterizing point defects in materials. However, current methods for defect detection predominantly involve visual inspection of TEM images, which is laborious and poses difficulties in materials where defect related contrast is weak or ambiguous. Recent efforts to develop machine learning methods for the detection of point defects in TEM images have focused on supervised methods that require labeled training data that is generated via …

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Meta-Heuristic Optimization Methods For Quaternion-Valued Neural Networks, Jeremiah Bill, Lance E. Champagne, Bruce Cox, Trevor J. Bihl Apr 2021

Meta-Heuristic Optimization Methods For Quaternion-Valued Neural Networks, Jeremiah Bill, Lance E. Champagne, Bruce Cox, Trevor J. Bihl

Faculty Publications

In recent years, real-valued neural networks have demonstrated promising, and often striking, results across a broad range of domains. This has driven a surge of applications utilizing high-dimensional datasets. While many techniques exist to alleviate issues of high-dimensionality, they all induce a cost in terms of network size or computational runtime. This work examines the use of quaternions, a form of hypercomplex numbers, in neural networks. The constructed networks demonstrate the ability of quaternions to encode high-dimensional data in an efficient neural network structure, showing that hypercomplex neural networks reduce the number of total trainable parameters compared to their real-valued …

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Characterization Of A Boron-Loaded Deuterated Liquid Scintillator For Fast And Thermal Neutron Detection, Bryan V. Egner, Michael Febbraro, James E. Bevins Apr 2021

Characterization Of A Boron-Loaded Deuterated Liquid Scintillator For Fast And Thermal Neutron Detection, Bryan V. Egner, Michael Febbraro, James E. Bevins

Faculty Publications

The preparation and characterization of novel boron-loaded deuterated liquid scintillators (BLDLS) are presented for the first time to investigate the performance of a detector sensitive to both fast and thermal neutrons intended for future neutron spectroscopy measurements. Three deuterated toluene-based scintillation cocktails were produced, one without boron, one loaded with ortho-carborane (natural boron isotopic abundance), and one with 96 wt% 10B enriched ortho-carborane. General optical and material properties were analyzed to include the composition, density, index of refraction, photoluminescence emission spectra, and absorbance spectra in addition to the relative light yield, resolution, relative efficiency, and pulse-shape-discrimination performance for all three …

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Impact Of Hurricane Michael (2018) On Local Vertical Total Electron Content, Joanna E.S. Williams, Robert C. Tournay, H. Rose Tseng, Daniel J. Emmons Ii, Omar A. Nava Apr 2021

Impact Of Hurricane Michael (2018) On Local Vertical Total Electron Content, Joanna E.S. Williams, Robert C. Tournay, H. Rose Tseng, Daniel J. Emmons Ii, Omar A. Nava

Faculty Publications

An analysis of vertical total electron content (TEC) estimates from the MIT Madrigal database is performed for the regions surrounding the eye of Hurricane Michael (2018). Absolute and detrended TEC values show a noticeable increase during the tropical cyclone (TC) relative to fluctuations at the same locations prior to the storm. Direct comparisons of TEC perturbation magnitudes to the number of lightning flashes in latitude-longitude boxes surrounding the eye of Hurricane Michael for each 5 min period of 10 October 2018 showed no visible trends. A similar comparison of the vertical TEC fluctuations with respect to the rainfall rates showed …

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Twisted Spatiotemporal Optical Vortex Random Fields, Milo W. Hyde Iv Apr 2021

Twisted Spatiotemporal Optical Vortex Random Fields, Milo W. Hyde Iv

Faculty Publications

We present twisted spatiotemporal optical vortex (STOV) beams, which are partially coherent light sources that possess a coherent optical vortex and a random twist coupling their space and time dimensions. These beams have controllable partial coherence and transverse orbital angular momentum (OAM), which distinguishes them from the more common spatial vortex and twisted beams (known to carry longitudinal OAM) in the literature and should ultimately make them useful in applications such as optical communications and optical tweezing. We present the mathematical analysis of twisted STOV beams, deriving the mutual coherence function and linear and angular momentum densities. We simulate the …

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Zn Acceptors In Β-Ga2O3 Crystals, Timothy D. Gustafson, J. Jesenovec, Christopher A. Lenyk, Nancy C. Giles, J. S. Mccloy, M. Mccluskey, Larry E. Halliburton Apr 2021

Zn Acceptors In Β-Ga2O3 Crystals, Timothy D. Gustafson, J. Jesenovec, Christopher A. Lenyk, Nancy C. Giles, J. S. Mccloy, M. Mccluskey, Larry E. Halliburton

Faculty Publications

Electron paramagnetic resonance (EPR) is used to identify and characterize neutral zinc acceptors in Zn-doped β-Ga2O3 crystals. Two EPR spectra are observed at low temperatures, one from Zn ions at tetrahedral Ga(1) sites (the Zn0Ga1 acceptor) and one from Zn ions at octahedral Ga(2) sites (the Zn0Ga2 acceptor). These Zn acceptors are small polarons, with the unpaired spin localized in each case on a threefold coordinated oxygen O(I) ion adjacent to the Zn ion. Resolved hyperfine interactions with neighboring 69Ga and 71Ga nuclei allow the EPR spectra from the two acceptors …

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Achieving The Shot-Noise Limit Using Experimental Multi-Shot Digital Holography Data, Douglas E. Thornton, Cameron J. Radosevich, Samuel Horst, Mark F. Spencer Mar 2021

Achieving The Shot-Noise Limit Using Experimental Multi-Shot Digital Holography Data, Douglas E. Thornton, Cameron J. Radosevich, Samuel Horst, Mark F. Spencer

Faculty Publications

In this paper, we achieve the shot-noise limit using straightforward image-post-processing techniques with experimental multi-shot digital holography data (i.e., off-axis data composed of multiple noise and speckle realizations). First, we quantify the effects of frame subtraction (of the mean reference-only frame and the mean signal-only frame from the digital-hologram frames), which boosts the signal-to-noise ratio (SNR) of the baseline dataset with a gain of 2.4 dB. Next, we quantify the effects of frame averaging, both with and without the frame subtraction. We show that even though the frame averaging boosts the SNR by itself, the frame subtraction and the stability …

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Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Hengky Chandrahalim, Jonathan W. Smith Mar 2021

Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Hengky Chandrahalim, Jonathan W. Smith

AFIT Patents

A passive microscopic Fabry-Pérot Interferometer (FPI) sensor an optical fiber a three-dimensional microscopic optical structure formed on a cleaved tip of an optical fighter that reflects a light signal back through the optical fiber. The reflected light is altered by refractive index changes in the three-dimensional structure that is subject to at least one of: (i) thermal radiation; and (ii) volatile organic compounds.

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An Examination Of Civilian Retention In The United States Air Force, William F. Wilson Mar 2021

An Examination Of Civilian Retention In The United States Air Force, William F. Wilson

Theses and Dissertations

The backbone of the United States Air Force is undoubtedly the large civilian workforce that supplements the great work that is accomplished. Many research studies have been conducted on officer and enlisted personnel to ensure that the career fields are properly developed and managed to meet the ever growing demands of the military's varied missions, but no recent studies have focused on the civilian workforce. Striking a balance between new and experienced employees is paramount to success given the ever-changing economic and political landscapes where we find ourselves. The first part of the research uses logistic regression to determine the …

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Analysis Of Functional Responses In Experimental Design, Matthew E. Scherer Mar 2021

Analysis Of Functional Responses In Experimental Design, Matthew E. Scherer

Theses and Dissertations

The growth of sensor streamed data in recent years increases the demand for an analytical technique to properly address data measured continuously. The design and analysis of experiments (DOE) of U.S. Air Force assets are based off of sensor streamed data. Functional data analysis (FDA) is an approach of analyzing data existing over a continuum. This research aids in filling the intersection of FDA and DOE by examining a case study of an experimental design with a functional response in addition to insight on software capabilities in FDA. The case study considers a functional linear model of a whole-plot from …

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Water Security At United States Air Force Installations, John D. Pollock Mar 2021

Water Security At United States Air Force Installations, John D. Pollock

Theses and Dissertations

Global water security is a growing concern that poses unique challenges that stem from geopolitical arrangement, regional location, and local climate conditions. United States national defense relies on an uninterrupted water supply to sustain operations to carry out its readiness mission. Accurate water security assessments are necessary for adapting to climate factors and to provide essential information to meet the changing needs of human water demand. This research presents how different water metrics are applied at various United States Air Force locations to measure water scarcity. Geographical Information Systems (GIS) software is used to conduct spatial correlation across the United …

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Operational Carbon Footprint Of The U.S. Water Sector’S Energy Consumption, Louis J. Zib Iii Mar 2021

Operational Carbon Footprint Of The U.S. Water Sector’S Energy Consumption, Louis J. Zib Iii

Theses and Dissertations

Accounting of energy-related GHG emissions in the water sector have largely been conducted at single utilities or cities and rarely at a regional or country scale. In this study, we assess the carbon footprints of operational energy use for 76 wastewater utilities and 64 water utilities across the United States. Additionally, we investigate water-related GHG emissions at a sub-annual scale through three case cities to understand how GHG emissions change at the monthly scale. We estimate the total drinking water and wastewater GHG emissions associated with electricity, biogas, natural gas, and fuel oil consumption across the United States to be …

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Remote Monitoring Of Memory Data Structures For Malware Detection In A Talos Ii Architecture, Robert A. Willburn Mar 2021

Remote Monitoring Of Memory Data Structures For Malware Detection In A Talos Ii Architecture, Robert A. Willburn

Theses and Dissertations

New forms of malware, namely xC;leless malware and rootkits, pose a threat to traditional anti-malware. In particular, Rootkits have the capacity to obscure the present state of memory from the user space of a target machine. If thishappens, anti-malware running in the user space of an axB;ected machine cannot be trusted to operate properly. To combat this threat, this research proposes the remote monitoring of memory from a second, secure processor runningOpenBMC, serving as a baseboard management controller for a POWER9 processor, which is assumed vulnerable to exploitation. The baseboard management controller includes an application called pdbg, used for debugging …

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Cyclic Pursuit, Daniel E. Oke Mar 2021

Cyclic Pursuit, Daniel E. Oke

Theses and Dissertations

This thesis analyzes cyclic pursuit with the intent of developing swarm attack strategies for autonomous agents. Research was focused on finding the effects of pursuers capture range, evader speed and size of formation on the probability of escape. The temporal evolution of several polygonal formations was analyzed. The polygons could be regular or arbitrary polygons. The thesis demonstrated that an increased capture range, formation size, reduced evader speed aided capture probability. Irregular n-gon formations reduced to n-1 gon repeatedly, pursuer clusters formed until two clusters remained which eventually came together, so all the n pursuers coalesced until convergence. Regular n-gon …

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Error Detection In Quantum Algorithms, Simeon R. Hanks Mar 2021

Error Detection In Quantum Algorithms, Simeon R. Hanks

Theses and Dissertations

Quantum computers need to be able to control highly entangled quantum states in the presence of environmental perturbations that lead to errors in calculations. Progress in superconducting qubits has enabled the development of computers capable of running small quantum circuits. The current era of Noise Intermediate Scale Quantum computing has a high error rate. To alleviate this error rate we apply an encoding scheme that allows us to remove results with known errors improving the quality of our results. The encoding uses multiple qubits as a single logical qubit and balances the natural tendency of state-of-the-art quantum computers to decohere …

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Examination Of A Lenseless Setup For Reflective Inverse Diffusion Of Light, John Nguyen Mar 2021

Examination Of A Lenseless Setup For Reflective Inverse Diffusion Of Light, John Nguyen

Theses and Dissertations

Reflective inverse diffusion uses spatial light modulators to shape an incident wavefront so that when the wavefront interacts with some diffuse scattering sample, the reflected light will constructively interfere at a single focus. This thesisexamines the efficacy of using a lensless setup against a focal plane setup in achieving reflective inverse diffusion while simultaneously beamsteering. The lensless setup outperformed its counterpart by being able to focus more energy in a region, but failed to achieve the same beamsteering capabilities as the focal plane system. Understanding the flaws behind the lensless setup will be instrumental in creating a setup that can …

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Dynamic Holography In Resonant Nonlinear Media: Theory And Application, Jonathan E. Slagle Mar 2021

Dynamic Holography In Resonant Nonlinear Media: Theory And Application, Jonathan E. Slagle

Theses and Dissertations

Two beam coupling (TBC) is a coherent interaction in which energy is transferred from one laser beam to another and has promising applications in real-time holography and coherent beam combing. We have recently shown efficient degenerate frequency TBC for counter-propagation geometries in isotropic two-photon absorbing media pumped with a nanosecond pulsed laser. When an interference pattern is generated in this media, single and two photon absorption initiates a population redistribution resulting in a holographic grating with the same modulation period and phase initially. However, due to temporal convolution of self- and cross-phase modulation, the grating will begin to shift in …

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Fluid Dynamics Modeling For Per- And Polyfluoroalkyl Substances Removal In Legacy Fire Suppression Systems, Jacob G. Spaulding Mar 2021

Fluid Dynamics Modeling For Per- And Polyfluoroalkyl Substances Removal In Legacy Fire Suppression Systems, Jacob G. Spaulding

Theses and Dissertations

Legacy per- and polyfluoroalkyl substances (PFASs) exist in the form of aqueous film-forming foams within hangar fire suppression systems throughout the country, posing a threat to both surrounding environments as well as local populations. The United States (US) Department of Defense (DoD), in conjunction with the US Environmental Protection Agency (EPA), is investigating best practices to flush out existing contaminants prior to disposal and replacement with a less environmentally harmful replacement. While current procedures dictate a triple rinse of the entire system to yield contaminant levels acceptable to the DoD, the practice has never truly been tested. Designed as a …

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Lithium Compound Characterization Via Laser Induced Breakdown Spectroscopy And Raman Spectroscopy, James T. Stofel Mar 2021

Lithium Compound Characterization Via Laser Induced Breakdown Spectroscopy And Raman Spectroscopy, James T. Stofel

Theses and Dissertations

Industries such as lithium-ion battery producers and the nuclear industry community seek to produce and store lithium in pure chemical forms. However, these lithium compounds are reactive with the atmosphere and quickly degrade into less desirable forms. Therefore, industry desires a fast and effective quality control approach to quantify the ingrowth of these secondary lithium chemical forms. This research presents a novel approach using Laser-Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy in tandem to enhance lithium compound characterization beyond what is achieved by either technique alone. The resulting spectral data are aggregated using data fusion and analyzed using chemometrics for …

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Data Driven Investigation Into The Off-Axis Brdf To Develop An Algorithm To Classify Anisotropicity, Anne W. Werkley Mar 2021

Data Driven Investigation Into The Off-Axis Brdf To Develop An Algorithm To Classify Anisotropicity, Anne W. Werkley

Theses and Dissertations

The Bi-directional Reflectance Distribution Function (BRDF) is used to describe reflectances of materials by calculating the ratio of the reflected radiance to the incident irradiance. While it was found that isotropic BRDF microfacet models maintained symmetry about ɸs = π, such symmetry was not maintained about the θs = θi axis, except for close to the specular peak. This led to development of a novel data-driven metric for how isotropic a BRDF measurement is. Research efforts centered around developing an algorithm that could determine material anisotropy without having to fit to models. The algorithm developed here successfully …

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Display Design To Avoid And Mitigate Limit Cycle Oscillations (Lco) On The F-16c, David J. Feibus Mar 2021

Display Design To Avoid And Mitigate Limit Cycle Oscillations (Lco) On The F-16c, David J. Feibus

Theses and Dissertations

The U.S. Air Force F-16 Fighting Falcons flying characteristics and flight envelope are dynamic and defined by its external weapon stores configuration. The employment of its munitions at certain speeds can put the F-16 into a flutter-like state in which Limit Cycle Oscillations (LCO) are induced. In LCO, a pilots fine motor control might be hindered, and the aircraft may lose combat effectiveness until flight conditions are reduced. The current research attempted to provide pilots with a predictive feedback display to avoid an LCO-susceptible configuration by increasing their situation awareness about the consequences of employing certain munitions to their flight …

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Correction Of Back Trajectories Utilizing Machine Learning, Britta F. Gjermo Morrison Mar 2021

Correction Of Back Trajectories Utilizing Machine Learning, Britta F. Gjermo Morrison

Theses and Dissertations

The goal of this work was to analyze 24-hour back trajectory performance from a global, low-resolution weather model compared to a high-resolution limited area weather model in particular meteorological regimes, or flow patterns using K-means clustering, an unsupervised machine learning technique. The duration of this study was from 2015-2019 for the contiguous United States (CONUS). Three different machine learning algorithms were tested to study the utility of these methods improving the performance of the CFS relative to the performance of the RAP. The aforementioned machine learning techniques are linear regression, Bayesian ridge regression, and random forest regression. These results mean …

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Long Distance Bluetooth Low Energy Exploitation On A Wireless Attack Platform, Stephanie L. Long Mar 2021

Long Distance Bluetooth Low Energy Exploitation On A Wireless Attack Platform, Stephanie L. Long

Theses and Dissertations

In the past decade, embedded technology, known as the Internet of Things, has expanded for many uses. The smart home infrastructure has drastically grown to include networked refrigerators, lighting systems, speakers, watches, and more. This increase in the use of wireless protocols provides a larger attack surface for cyber actors than ever before. Wireless loT traffic is susceptible for sniffing by an attacker. The attack platform skypie is upgraded to incorporate Bluetooth Low Energy (BLE) beacon collection for pattern-of-life data, as well as device characteristic enumeration and potential characteristic modification. This platform allows an attacker to mount the skypie to …

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The Wargaming Commodity Course Of Action Automated Analysis Method, William T. Deberry Mar 2021

The Wargaming Commodity Course Of Action Automated Analysis Method, William T. Deberry

Theses and Dissertations

This research presents the Wargaming Commodity Course of Action Automated Analysis Method (WCCAAM), a novel approach to assist wargame commanders in developing and analyzing courses of action (COAs) through semi-automation of the Military Decision Making Process (MDMP). MDMP is a seven-step iterative method that commanders and mission partners follow to build an operational course of action to achieve strategic objectives. MDMP requires time, resources, and coordination – all competing items the commander weighs to make the optimal decision. WCCAAM receives the MDMP's Mission Analysis phase as input, converts the wargame into a directed graph, processes a multi-commodity flow algorithm on …

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Improving Airfield Pavement Degradation Prediction Skill With Local Climate And Traffic, Evan M. Fortney Mar 2021

Improving Airfield Pavement Degradation Prediction Skill With Local Climate And Traffic, Evan M. Fortney

Theses and Dissertations

Airfield pavements are a critical component of the global transportation network that provide a platform for national defense. Preventative and corrective maintenance activities are founded upon accurate expectations of degradation. The leading pavement management software creates degradation predictions from pavement groups using age as the IV and current state conditions as the DV. For this work, a framework is created and implemented that utilizes a PCR model to build upon accepted practices for degradation modeling to enhance and possibly augment future prediction capabilities. The model was applied to pairs of location and pavement family and reveals several findings: the selected …

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