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Air Force Institute of Technology

Theses and Dissertations

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Articles 61 - 90 of 2019

Full-Text Articles in Physical Sciences and Mathematics

Analytic Case Study Using Unsupervised Event Detection In Multivariate Time Series Data, Jeremy M. Wightman Sep 2022

Analytic Case Study Using Unsupervised Event Detection In Multivariate Time Series Data, Jeremy M. Wightman

Theses and Dissertations

Analysis of cyber-physical systems (CPS) has emerged as a critical domain for providing US Air Force and Space Force leadership decision advantage in air, space, and cyberspace. Legacy methods have been outpaced by evolving battlespaces and global peer-level challengers. Automation provides one way to decrease the time that analysis currently takes. This thesis presents an event detection automation system (EDAS) which utilizes deep learning models, distance metrics, and static thresholding to detect events. The EDAS automation is evaluated with case study of CPS domain experts in two parts. Part 1 uses the current methods for CPS analysis with a qualitative …

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Innovative Heuristics To Improve The Latent Dirichlet Allocation Methodology For Textual Analysis And A New Modernized Topic Modeling Approach, Jamie T. Zimmerman Jun 2022

Innovative Heuristics To Improve The Latent Dirichlet Allocation Methodology For Textual Analysis And A New Modernized Topic Modeling Approach, Jamie T. Zimmerman

Theses and Dissertations

Natural Language Processing is a complex method of data mining the vast trove of documents created and made available every day. Topic modeling seeks to identify the topics within textual corpora with limited human input into the process to speed analysis. Current topic modeling techniques used in Natural Language Processing have limitations in the pre-processing steps. This dissertation studies topic modeling techniques, those limitations in the pre-processing, and introduces new algorithms to gain improvements from existing topic modeling techniques while being competitive with computational complexity. This research introduces four contributions to the field of Natural Language Processing and topic modeling. …

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Methods For Focal Plane Array Resolution Estimation Using Random Laser Speckle In Non-Paraxial Geometries, Phillip J. Plummer Jun 2022

Methods For Focal Plane Array Resolution Estimation Using Random Laser Speckle In Non-Paraxial Geometries, Phillip J. Plummer

Theses and Dissertations

The infrared (IR) imaging community has a need for direct IR detector evaluation due to the continued demand for small pixel pitch detectors, the emergence of strained-layer-super-lattice devices, and the associated lateral carrier diffusion issues. Conventional laser speckle-based modulation transfer function (MTF) estimation is dependent on Fresnel propagation and a wide-sense-stationary input random process, limiting the use of this approach for lambda (wavelength)-scale IR devices. This dissertation develops two alternative methodologies for speckle-based resolution evaluation of IR focal plane arrays (FPAs). Both techniques are formulated using Rayleigh-Sommerfield electric field propagation, making them valid in the non-paraxial geometries dictated for resolution …

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Full Pattern Analysis And Comparison Of The Center Fed And Offset Fed Cassegrain Antennas With Large Focal Length To Diameter Ratios For High Power Microwave Transmission, Derek W. Mantzke Jun 2022

Full Pattern Analysis And Comparison Of The Center Fed And Offset Fed Cassegrain Antennas With Large Focal Length To Diameter Ratios For High Power Microwave Transmission, Derek W. Mantzke

Theses and Dissertations

High power microwaves (HPM) have been a topic of research since the Cold War era. This paper will present a comparison between two Cassegrain-type antennas: the axially, or center fed, and the offset fed. Specifically, the 10 GHz operating frequency will be investigated with large focal length to diameter () ratios. Beam patterns which encompass the entire radiation pattern will be included for data validation and optimization. The simulations will follow a design of experiments factorial model to ensure all possible combinations of prescribed parameters are included, including an analysis of variance (ANOVA) study to find parameter influence on the …

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Scheduling For Space Tracking And Heterogeneous Sensor Environments, Gabriel H. Greve Jun 2022

Scheduling For Space Tracking And Heterogeneous Sensor Environments, Gabriel H. Greve

Theses and Dissertations

This dissertation draws on the fields of heuristic and meta-heuristic algorithm development, resource allocation problems, and scheduling to address key Air Force problems. The world runs on many schedules. People depend upon them and expect these schedules to be accurate. A process is needed where schedules can be dynamically adjusted to allow tasks to be completed efficiently. For example, the Space Surveillance Network relies on a schedule to track objects in space. The schedule must use sensor resources to track as many high-priority satellites as possible to obtain orbit paths and to warn of collision paths. Any collisions that occurred …

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Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low Jun 2022

Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low

Theses and Dissertations

The Air Force Inspection System is a proponent of utilizing a risk-based sampling strategy (RBSS) for conducting inspections from major command levels down to the unit level. The strategy identifies areas deemed most important or risky by commanders and prioritizes them accordingly for an independent assessment by the Inspector General. While Air Force regulation specifies the need to use a RBSS for inspection, the implementation process is delegated to individual commands and, subsequently, wings. The 23rd Wing, the sponsor for this research, directed us to analyze a RBSS tool highlighted as an example from which to adopt for those units …

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Efficiency Mapping And Determination Of Reliability, Resiliency And Vulnerability Of Atmospheric Water Generators In The United States, Erica F. Sadowski Mar 2022

Efficiency Mapping And Determination Of Reliability, Resiliency And Vulnerability Of Atmospheric Water Generators In The United States, Erica F. Sadowski

Theses and Dissertations

Atmospheric Water Generators (AWG) extract water from the air using one of three available technologies: refrigeration, sorption, and fog harvesting. A refrigeration device works like a dehumidifier and works best in conditions above 60% relative humidity. A sorption device utilizes a desiccant to extract the water vapor from the air and works in very low humidity levels. A fog harvesting device utilizes a mesh to capture the water vapor from the air and requires 100% relative humidity. In this research, I analyze two refrigeration-based devices and one sorption-based device and their efficacy in providing supplemental water supply. Due to climatological …

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The Impacts Of Climate Uncertainty On Streamflow In Andes, Antioquia, Colombia, Kristen R. Roberts Mar 2022

The Impacts Of Climate Uncertainty On Streamflow In Andes, Antioquia, Colombia, Kristen R. Roberts

Theses and Dissertations

Natural hazards, such as hurricanes, wildfires, floods, and droughts impact human systems that rely on predictable patterns in the natural elements with which they interact. Skillful prediction of the impacts of climate change on linked, human-natural systems, like surface water resources, can help ensure physical risks within vulnerable communities are mitigated, resource sustainability is maximized, and intersectoral markets continue to contribute to socioeconomic stability. Due to water resources being a primary conduit through which climate uncertainty impacts people, economies, and ecosystems, its study is worthy of investigation; particularly, where those resources are uncertain and demanded by a variety of competitive …

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Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli Mar 2022

Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli

Theses and Dissertations

Users often sacrifice personal data for more relevant search results, presenting a problem to communities that desire both search anonymity and relevant results. To balance these priorities, this research examines the impact of using Siamese networks to extend word embeddings into document embeddings and detect similarities between documents. The predicted similarity can locally re-rank search results provided from various sources. This technique is leveraged to limit the amount of information collected from a user by a search engine. A prototype is produced by applying the methodology in a real-world search environment. The prototype yielded an additional function of finding new …

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Incorporating Armed Escorts To The Military Medical Evacuation Dispatching Problem Via Stochastic Optimization And Reinforcement Learning, Andrew G. Gelbard Mar 2022

Incorporating Armed Escorts To The Military Medical Evacuation Dispatching Problem Via Stochastic Optimization And Reinforcement Learning, Andrew G. Gelbard

Theses and Dissertations

The military medical evacuation (MEDEVAC) dispatching problem seeks to determine high-quality dispatching policies to maximize the survivability of casualties within contingency operations. This research leverages applied operations research and machine learning techniques to solve the MEDEVAC dispatching problem and evaluate system performance. More specifically, we develop an infinite-horizon, continuous-time Markov decision process (MDP) model and approximate dynamic programming (ADP) solution approach to generate high-quality policies. The ADP solution approach utilizes an approximate value iteration algorithm strategy incorporating gradient descent Q-learning to approximate the value function. A notional, synthetically-generated scenario in Africa based around the capital city of Niger, Niamey is …

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Automated Aircraft Visual Inspection With Artificial Data Generation Enabled Deep Learning, Nathan J. Gaul Mar 2022

Automated Aircraft Visual Inspection With Artificial Data Generation Enabled Deep Learning, Nathan J. Gaul

Theses and Dissertations

Aircraft visual inspection, which is essential to daily maintenance of an aircraft, is expensive and time-consuming to perform. Augmenting trained maintenance technicians with automated UAVs to collect and analyze images for aircraft inspection is an active research topic and a potential application of CNNs. Training datasets for niche research topics such as aircraft visual inspection are small and challenging to produce, and the manual process of labeling these datasets often produces subjective annotations. Recently, researchers have produced several successful applications of artificially generated datasets with domain randomization for training CNNs for real-world computer vision problems. The research outlined herein builds …

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A Critical Review Of Climate Change On Coastal Infrastructure Systems, Gregory J. Howland Jr. Mar 2022

A Critical Review Of Climate Change On Coastal Infrastructure Systems, Gregory J. Howland Jr.

Theses and Dissertations

This thesis is a response to climate threats identified by DoD report on Climate Change in 2019. A critical review of climate change literature related to coastal infrastructure was conducted to synthesize past research and to inform future research. This review intends to inform how climate change may impact infrastructure systems, how those impacts are evaluated, can the investigation be improved, and what can stakeholders learn from the outcomes. The end goal is to find climate change mitigation strategies and adaptation measures, or identify the easiest path to get to that end. The compiled information will inform civilian and military …

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The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold Mar 2022

The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold

Theses and Dissertations

Traditional control mechanisms restrict human input on the displays in 5th generation aircraft. This research explored methods for enhancing pilot interaction with large, information dense cockpit displays; specifically, the effects of visual feedback and control button configuration when augmenting cursor control with head tracking technology. Previous studies demonstrated that head tracking can be combined with traditional cursor control to decrease selection times but can increase pilot mental and physical workload. A human subject experiment was performed to evaluate two control button configurations and three visual feedback conditions. A Fitts Law analysis was performed to create predictive models of selection time …

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Evaluating Semantic Matching Techniques For Technical Documents, Rain F. Dartt Mar 2022

Evaluating Semantic Matching Techniques For Technical Documents, Rain F. Dartt

Theses and Dissertations

Machine learning models that employ NLP techniques have become more widely accessible, making them an attractive solution for text and document classification tasks traditionally accomplished by humans. Two such use cases are matching the specialized experience required for a job to statements in applicant resumes, and finding and labelling clauses in legal contracts The AFMC has an immediate need for solutions to civilian hiring. However, there is currently no truth data to validate against. A similar task is contract understanding for which there is the CUAD, a recently published repository of 510 contracts manually labelled by legal experts. The presented …

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Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith Mar 2022

Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith

Theses and Dissertations

The growing surge of misinformation among COVID-19 communication can pose great hindrance to truth, magnify distrust in policy makers and/or degrade authorities’ credibility, and it can even harm public health. Classification of textual context on social media data relating to COVID-19 is an effective tool to combat misinformation on social media platforms. In this research, Twitter data was leveraged to 1) develop classification methods to detect misinformation and identify Tweet sentiment with respect to COVID-19 and 2) develop a human-in-the-loop interactive framework to enable identification of keywords associated with social context, here, being misinformation regarding COVID-19. 1) Six fusion-based classification …

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Telemetry Data Mining For Unmanned Aircraft Systems, Li Yu Mar 2022

Telemetry Data Mining For Unmanned Aircraft Systems, Li Yu

Theses and Dissertations

With ever more data becoming available to the US Air Force, it is vital to develop effective methods to leverage this strategic asset. Machine learning (ML) techniques present a means of meeting this challenge, as these tools have demonstrated successful use in commercial applications. For this research, three ML methods were applied to a unmanned aircraft system (UAS) telemetry dataset with the aim of extracting useful insight related to phases of flight. It was shown that ML provides an advantage in exploratory data analysis and as well as classification of phases. Neural network models demonstrated the best performance with over …

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Global Sporadic-E Climatological Analysis Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos Mar 2022

Global Sporadic-E Climatological Analysis Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos

Theses and Dissertations

A climatology of sporadic-E (Es) derived from a combined data set of GPS radio occultation (GPS-RO) and ground-based ionosonde soundings is presented for the period from September 2006 to February 2019. The ionosonde soundings were measured using the Lowell Digisonde International (LDI) Global Ionosphere Radio Observatory (GIRO) network consisting of 65 sites and 13,141,060 total soundings. The GPS-RO observations were taken aboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites and processed using two binary Es detection algorithms, totaling 9,072,922 occultations. The first algorithm is an S4 amplitude threshold calibrated to the occurrence of any blanketing Es …

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Exploring Learning Classifier System Behaviors In Multi-Action, Turn-Based Wargames, Garth J.S. Terlizzi Iii Mar 2022

Exploring Learning Classifier System Behaviors In Multi-Action, Turn-Based Wargames, Garth J.S. Terlizzi Iii

Theses and Dissertations

State of the art game-playing Artificial Intelligence research focuses heavily on non-symbolic learning methods. These methods offer little explainable insight into their decision-making processes. Learning Classifier Systems (LCSs) provide an alternative. LCSs use rule-based learning, guided by a Genetic Algorithm (GA), to produce a human-readable rule-set. This thesis explores LCS usefulness in game-playing agents for multi-agent wargames. Several Multi-Agent Learning Classifier System (MALCS) variants are implemented in the wargame Stratagem MIST: a Zeroeth-Level Classifier System (ZCS), an extended Classifier System (XCS), and an Adaptive Pittsburgh Classifier System (APCS). These algorithms were tested against baseline agents as well as the Online …

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Exploiting The Iot Through Network-Based Covert Channels, Kyle S. Harris Mar 2022

Exploiting The Iot Through Network-Based Covert Channels, Kyle S. Harris

Theses and Dissertations

Information leaks are a top concern to industry and government leaders. The IoT is a technology capable of sensing real-world events. A method for exfiltrating data from these devices is by covert channel. This research designs a novel IoT CTC without the need for inter-packet delays to encode data. Instead, it encodes data within preexisting network information, namely ports or addresses. Additionally, the CTC can be implemented in two different modes: Stealth and Bandwidth. Performance is measured using throughput and detectability. The Stealth methods mimic legitimate traffic captures while the Bandwidth methods forgo this approach for maximum throughput. Detection results …

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Application Of Machine Learning Models With Numerical Simulations Of An Experimental Microwave Induced Plasma Gasification Reactor, Owen D. Sedej Mar 2022

Application Of Machine Learning Models With Numerical Simulations Of An Experimental Microwave Induced Plasma Gasification Reactor, Owen D. Sedej

Theses and Dissertations

This thesis aims to contribute to the future development of this technology by providing an in-depth literature review of how this technology physically operates and can be numerically modeled. Additionally, this thesis reviews literature of machine learning models that have been applied to gasification to make accurate predictions regarding the system. Finally, this thesis provides a framework of how to numerically model an experimental plasma gasification reactor in order to inform a variety of machine learning models.

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Intercomparison Of Four Microphysics Schemes In Simulating Persistent Arctic Mixed-Phase Stratocumulus Clouds, Zachary A. Cleveland Mar 2022

Intercomparison Of Four Microphysics Schemes In Simulating Persistent Arctic Mixed-Phase Stratocumulus Clouds, Zachary A. Cleveland

Theses and Dissertations

Persistent Arctic mixed-phase stratocumulus clouds (AMPS) are important to the surface radiation budget of the Arctic. Their presence produces warming within the boundary layer and at the surface and inaccurately forecasting AMPS can lead to large, erroneous temperature forecasts. A Large Eddy Simulation of a case study of a persistent AMPS cloud was conducted using the Advanced Research Weather Research and Forecasting (WRF-ARW) model. The case examined occurred near Oliktok Point, AK between 26 and 27 April, 2017. The produced cloud pattern and properties of four different microphysics schemes -- P3, Thompson, Morrison, and WSM6 -- are compared to observations. …

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Persistence And Mitigation Of Pfas Within Concrete Stormwater Drainage Infrastructure, Jason R. Mcdonald Mar 2022

Persistence And Mitigation Of Pfas Within Concrete Stormwater Drainage Infrastructure, Jason R. Mcdonald

Theses and Dissertations

The persistence, fate, and transport of per- and poly-fluoroalkyl substances, which have been shown to have adverse effects on human health, have been previously studied in environmental media such as soils and groundwater. This study investigates concrete, a medium that is rarely studied but frequently present in instances where PFAS originating from AFFF releases and spills have occurred. Used heavily throughout aviation firefighting, AFFF poses environmental hazards due to the length of PFAS degradation and toxicological implications, thus its classification as a forever chemical. From the very limited reports to date, studies have suggested very slow release from concrete, potentially …

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Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry Mar 2022

Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry

Theses and Dissertations

The software verification in this thesis concentrates on verifying a particle filter for use in tracking and estimation, a key application area for the Air Force. The development and verification process described in this thesis is a demonstration of the power, limitation, and compromises involved in applying automated software verification tools to critical embedded software applications.

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A Framework For Assessing Facility-Level Vulnerability And Risk To Extreme Weather Events, Blake A. Gawlik Mar 2022

A Framework For Assessing Facility-Level Vulnerability And Risk To Extreme Weather Events, Blake A. Gawlik

Theses and Dissertations

Intensifying extreme weather events, tied to the rise in the global average temperature, put global built infrastructure at risk. This presents a daunting challenge for organizational leaders who are tasked to determine how best to adapt current infrastructure to uncertain future events. To develop adaptation plans and policies, vulnerability and risk must be downscaled to an actionable scale, such that planners, designers, and engineers can make adaptation recommendations. However, previous research has largely assessed risk at coarser scales, e.g., regional, national, or global. These assessments are informative, but do not help those tasked to lead adaptation to make detailed, actionable …

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Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park Mar 2022

Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park

Theses and Dissertations

The military deploys many IoT in battlefield operations to provide information on terrain and enemy combatants. It also deploys automated robots or UAVs where securing and trusting collected data is essential. Choosing the middleware that handles this message transfer is crucial for real-time operations. Networks with multiple entities, including IoT devices, UAVs, and small computers, require robust middleware facilitating message sending in real-time. Ideally, the middleware would provide QoS to handle lost packets and retransmissions in lossy environments, especially between low-power machines. DDS is a middleware that implements real-time and QoS capabilities by sending messages, not based on endpoints but …

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Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey Mar 2022

Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey

Theses and Dissertations

A challenging task in computer vision is finding techniques to improve the object detection and classification capabilities of ML models used for processing images acquired by moving aerial platforms. This research explores if GAN augmented UAV training sets can increase the generalizability of a detection model trained on said data. To answer this question, the YOLOv4-Tiny Object Detection Model was trained with aerial image training sets depicting rural environments. The salient objects within the frames were recreated using various GAN architectures, placed back into the original frames, and the augmented frames appended to the original training sets. GAN augmentation on …

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Carbon Estimation And Decision Making In Usaf Acquisition, Robert F. Gray Mar 2022

Carbon Estimation And Decision Making In Usaf Acquisition, Robert F. Gray

Theses and Dissertations

Recent executive orders and international agreements require the United States to significantly reduce its carbon and greenhouse gas emissions. The DoD is a significant contributor to the carbon emissions of the USA and will be required to reduce the emissions. Therefore, in order to make appropriate programmatic decisions the DoD needs to develop an appropriate method for estimating carbon and making programmatic decisions; trading-off carbon emissions with the traditional cost-schedule-performance metrics. This thesis examines the possibility of developing a model that can be used to estimate the carbon footprint of producing a system before detailed engineering designed have been complete.

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Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price Mar 2022

Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price

Theses and Dissertations

Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …

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Real Time Evaluation Of Boom And Drogue Occlusion With Aar, Xiaoyang Wu Mar 2022

Real Time Evaluation Of Boom And Drogue Occlusion With Aar, Xiaoyang Wu

Theses and Dissertations

In recent years, Unmanned Aerial Vehicles (UAV) have seen a rise in popularity. Various navigational algorithms have been developed as a solution to estimate a UAV’s pose relative to the refueler aircraft. The result can be used to safely automate aerial refueling (AAR) to improve UAVs’ time-on-station and ensure the success of military operations. This research aims to reach real-time performance using a GPU accelerated approach. It also conducts various experiments to quantify the effects of refueling boom/drogue occlusion and image exposure on the pose estimation pipeline in a lab setting.

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Coupled Orbit-Attitude Dynamics And Control Of A Cubesat Equipped With A Robotic Manipulator, Charles M. Carr Mar 2022

Coupled Orbit-Attitude Dynamics And Control Of A Cubesat Equipped With A Robotic Manipulator, Charles M. Carr

Theses and Dissertations

This research investigates the utility and expected performance of a robotic servicing CubeSat. The coupled orbit-attitude dynamics of a 6U CubeSat equipped with a four-link serial manipulator are derived. A proportional-integral-derivative controller is implemented to guide the robot through a series of orbital scenarios, including rendezvous and docking following ejection from a chief spacecraft, repositioning the end effector to a desired location, and tracing a desired path with the end effector. Various techniques involving path planning and inverse differential kinematics are leveraged. Simulation results are presented and performance metrics such as settling time, state errors, control use, and system robustness …

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