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Air Force Institute of Technology

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Articles 181 - 210 of 2678

Full-Text Articles in Physical Sciences and Mathematics

Automated Computer Network Exploitation With Bayesian Decision Networks, Graeme Roberts, Gilbert L. Peterson May 2022

Automated Computer Network Exploitation With Bayesian Decision Networks, Graeme Roberts, Gilbert L. Peterson

Faculty Publications

Penetration Testing (pentesting) is the process of using tactics and techniques to penetrate computer systems and networks to expose any issues in their cybersecurity \cite{rsa}. It is currently a manual process requiring significant experience and time that are in limited supply. One way to supplement the shortage is through automation. This paper presents the Automated Network Discovery and Exploitation System (ANDES) which demonstrates that it is feasible to automate the pentesting process. The uniqueness of ANDES is the use of Bayesian decision networks to represent the pentesting domain and subject matter expert knowledge. ANDES conducts multiple execution cycles, which build …

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Evolution Of Combined Arms Tactics In Heterogeneous Multi-Agent Teams, Robert J. Wilson, David W. King, Gilbert L. Peterson May 2022

Evolution Of Combined Arms Tactics In Heterogeneous Multi-Agent Teams, Robert J. Wilson, David W. King, Gilbert L. Peterson

Faculty Publications

Multi-agent systems research is concerned with the emergence of system-level behaviors from relatively simple agent interactions. Multi-agent systems research to date is primarily concerned with systems of homogeneous agents, with member agents both physically and behaviorally identical. Systems of heterogeneous agents with differing physical or behavioral characteristics may be able to accomplish tasks more efficiently than homogeneous teams, via cooperation between mutually complementary agent types. In this article, we compare the performance of homogeneous and heterogeneous teams in combined arms situations. Combined arms theory proposes that the application of heterogeneous forces, en masse, can generate effects far greater than outcomes …

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Hinged Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim May 2022

Hinged Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim

AFIT Patents

A passive microscopic Fabry-Pérot Interferometer (FPI) sensor includes a three-dimensional microscopic optical structure formed on a cleaved tip of the optical fighter using a two-photon polymerization process on a photosensitive polymer by a three-dimensional micromachining device. The three-dimensional microscopic optical structure having a hinged optical layer pivotally connected to a distal portion of a suspended structure. A reflective layer is deposited on a mirror surface of the hinged optical layer while in an open position. The hinged optical layer is subsequently positioned in the closed position to align the mirror surface to at least partially reflect a light signal back …

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Particle-In-Cell Simulations Of Ion Dynamics In A Pinched-Beam Diode, Jesse C. Foster, John W. Mcclory, S. B. B. Swanekamp, D. D. Hinshelwood, A. S. Richardson, Paul E. Adamson, J. W. Schumer, R. W. James, P. F. Ottinger, D. Mosher May 2022

Particle-In-Cell Simulations Of Ion Dynamics In A Pinched-Beam Diode, Jesse C. Foster, John W. Mcclory, S. B. B. Swanekamp, D. D. Hinshelwood, A. S. Richardson, Paul E. Adamson, J. W. Schumer, R. W. James, P. F. Ottinger, D. Mosher

Faculty Publications

article-in-cell simulations of a 1.6 MV, 800 kA, and 50 ns pinched-beam diode have been completed with emphasis placed on the quality of the ion beams produced. Simulations show the formation of multiple regions in the electron beam flow characterized by locally high charge and current density (“hot spots”). As ions flow through the electron-space-charge cloud, these hot spots electrostatically attract ions to produce a non-uniform ion current distribution. The length of the cavity extending beyond the anode-to-cathode gap (i.e., behind the cathode tip) influences both the number and amplitude of hot spots. A longer cavity length increases the number …

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Aerial Radiation Detection Identification And Measurement System Detector Material Comparison Study, Benjamin C. Troxell, Kacey D. Mcgee, Christina L. Dugan Apr 2022

Aerial Radiation Detection Identification And Measurement System Detector Material Comparison Study, Benjamin C. Troxell, Kacey D. Mcgee, Christina L. Dugan

Faculty Publications

The 20th Chemical Biological Radiological Nuclear and Explosives Command (CBRNE) currently utilizes an airborne sodium iodide gamma and beta detection system to map radiation fields over large areas of interest. The 20th CBRNE explored emergent detector technologies utilizing two detection materials; thallium-activated cesium iodide and high purity germanium (HPGe). These detectors were simulated at various altitudes and compared to background measurements. The sodium iodide detector failed to provide isotopic discrimination at distance. The thallium-activated cesium iodide CsI(Tl) detector provided sufficient absolute efficiency and energy resolution to identify isotopics at distance. The HPGe detector provided the best energy resolution. However, current …

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Application Of Machine Learning To Predict The Performance Of An Emipg Reactor Using Data From Numerical Simulations, Owen Sedej, Eric G. Mbonimpa, Trevor Sleight, Jeremy Slagley Mar 2022

Application Of Machine Learning To Predict The Performance Of An Emipg Reactor Using Data From Numerical Simulations, Owen Sedej, Eric G. Mbonimpa, Trevor Sleight, Jeremy Slagley

Faculty Publications

Microwave-driven plasma gasification technology has the potential to produce clean energy from municipal and industrial solid wastes. It can generate temperatures above 2000 K (as high as 30,000 K) in a reactor, leading to complete combustion and reduction of toxic byproducts. Characterizing complex processes inside such a system is however challenging. In previous studies, simulations using computational fluid dynamics (CFD) produced reproducible results, but the simulations are tedious and involve assumptions. In this study, we propose machine-learning models that can be used in tandem with CFD, to accelerate high-fidelity fluid simulation, improve turbulence modeling, and enhance reduced-order models. A two-dimensional …

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Method Of Making Hinged Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim Mar 2022

Method Of Making Hinged Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim

AFIT Patents

A method is provided for fabricating a passive optical sensor on a tip of an optical fiber. The method includes perpendicularly cleaving a tip of an optical fiber and mounting the tip of the optical fiber in a specimen holder of a photosensitive polymer three-dimensional micromachining machine. The method includes forming a three-dimensional microscopic optical structure within the photosensitive polymer that comprises a two cavity Fabry-Perot Interferometer (FPI) having a hinged optical layer that is pivotally coupled to a suspended structure. The method includes removing an uncured portion of the photosensitive polymer using a solvent. The method includes depositing a …

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Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam Mar 2022

Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam

Faculty Publications

Lack of instrument sensitivity to low electron density (Ne) concentration makes it difficult to measure sharp Ne vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region Ne from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the …

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Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple Mar 2022

Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple

Faculty Publications

Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from …

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Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell Mar 2022

Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell

Theses and Dissertations

The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …

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An Entity-Component System Based, Ieee Dis Interoperability Interface, Noah W. Scott Mar 2022

An Entity-Component System Based, Ieee Dis Interoperability Interface, Noah W. Scott

Theses and Dissertations

In practice, there are several different methods of organizing data within a given software to fulfil its function. The method known as the Entity-Component System (ECS) is a software architecture where data components define entities. These components are stored as organized lists which are operated upon by systems to inject the system's desired behavior. Data is sent across the networks to communicate between simulation nodes as Protocol Data Units (PDUs). When sending PDUs across a network protocol, each simulation represents a common understanding of the world at the desired level of detail. DIS-compliant simulations are commonly written using an Object-Oriented …

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Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice Mar 2022

Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice

Theses and Dissertations

We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …

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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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Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis Mar 2022

Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis

Theses and Dissertations

In 2007, the Office of the Assistant Secretary of Defense for Sustainment pushed for the need to transition to a Condition Based Maintenance Plus (CBM ) initiative for weapon systems in the U.S. Department of Defense. The CBM initiative can help increase aircraft availability (AA) for the United States Air Force. There are many reasons where AA can be affected but one such issue is engine availability primarily due to oil issues. Within the CBM perspective, this study examines the risk of a jet engine failure due to an oil issue and attempts to predict an engines time until next …

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Hydrologic Profiles And Geospatial Trend Analysis Evaluating Recurrent Flooding At Coastal U.S. Air Force Installations, Dylan D. Bechen Mar 2022

Hydrologic Profiles And Geospatial Trend Analysis Evaluating Recurrent Flooding At Coastal U.S. Air Force Installations, Dylan D. Bechen

Theses and Dissertations

Military installations are exposed to numerous threats, including a changing climate and the risk of recurrent flooding. The four components of recurrent flooding are sea-level rise, tidal fluctuations, storm surges, and precipitation. This research analyzed 40 years of historical precipitation and tidal data at 17 coastal U.S. Air Force installations using indicators of both peak and threshold exceedances to identify long-term temporal trends in the hydrologic components that make up recurrent flood risk, establishing an installation’s “hydrologic profile” which can be used to better inform decision makers when evaluating portfolio-wide adaptation strategies and prioritization of long-term infrastructure investments.

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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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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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Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich Mar 2022

Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich

Theses and Dissertations

In the pursuit of digital transformation, the Air Force creates digital airmen. Digital airmen are robotic process automations designed to eliminate the repetitive high-volume low-cognitive tasks that absorb so much of our Airmen's time. The automation product results in more time to focus on tasks that machines cannot sufficiently perform data analytics and improving the Air Force's informed decision-making. This research investigates the assessment of potential automation cases to ensure that we choose viable tasks for automation and applies multivariate analysis to determine which factors indicate successful projects. The data is insufficient to provide significant insights.

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Determination Of Vortex Locations In A 2x2 Array Of Josephson Junctions For Topological Quantum Computation, Casey L. Kowalski Mar 2022

Determination Of Vortex Locations In A 2x2 Array Of Josephson Junctions For Topological Quantum Computation, Casey L. Kowalski

Theses and Dissertations

A large barrier to practical quantum computation exists in the form of qubit decoherence, which leads to high noise and error when implementing quantum algorithms. A potential solution to this problem is the use of topologically-protected Majorana-based qubits, as their nonlocal nature and unique non-abelian exchange statistics render them virtually immune to decoherence while still allowing the state to be easily manipulated. For such a qubit to be constructed, it is essential to know the locations of the Majorana-hosting vortices in the system. This work presents a solution for the formation locations of vortices in a 2x2 superconducting island array, …

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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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Experimental Design On High-Speed Sliding Wear, Irene D. Liew Mar 2022

Experimental Design On High-Speed Sliding Wear, Irene D. Liew

Theses and Dissertations

The purpose of this research is to develop, conduct, and analyze an experimental design that characterizes wear rates of various materials sliding at high speeds along AISI 4340 steel. This work is in support of Holloman Air Force Base, which is invested in engineering a more wear-resistant rocket slipper for its high-speed test track. This research uses a design of experiments approach to systematically identify and evaluate potential slipper attributes that mitigate wear according to a heat transfer model. Final findings include recommendations of slipper materials that theoretically perform similar to or better than the baseline Vascomax®C300 maraging steel material. …

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An Investigation Of Data Storage In Entity-Component Systems, Bailey V. Compton Mar 2022

An Investigation Of Data Storage In Entity-Component Systems, Bailey V. Compton

Theses and Dissertations

Entity-Component Systems (ECS) have grown vastly in application since their introduction more than 20 years ago. Providing the ability to efficiently manage data and optimize program execution, ECSs, as well as the wider field of data-oriented design, have attained popularity in the realms of modeling, simulation, and gaming. This manuscript aims to elucidate and document the storage frameworks commonly found in ECSs, as well as suggesting conceptual connections between ECSs and relational databases. This formal documentation of the in-memory storage formats of entity-component systems affords the United States Air Force, the Department of Defense, and the software engineering community a …

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A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia Mar 2022

A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia

Theses and Dissertations

The purpose of this research is to explore the utility and current state of touchless technologies. Five categories of technologies are identified as a result of collecting and reviewing literature: facial/biometric recognition, gesture recognition, touchless sensing, personal devices, and voice recognition. A thematic analysis was conducted to evaluate the advantages and disadvantages of the five categories. A reference analysis was also conducted to determine the similarities between articles in each category. Touchless sensing showed to have the most advantages and least similar references. Gesture recognition was the opposite. Comparing analyses shows more reliable technology types are more beneficial and diverse.

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A Post-Disaster Construction Portfolio Optimization Framework For Tyndall Afb Rebuild Post Hurricane Michael, Andre J. May Mar 2022

A Post-Disaster Construction Portfolio Optimization Framework For Tyndall Afb Rebuild Post Hurricane Michael, Andre J. May

Theses and Dissertations

Natural disasters such as hurricanes, earthquakes, tsunamis, and extreme flooding cause severe social and economic disruptions. Restoration of social and revenue-generating services often requires extensive reconstruction, from the facility to the campus scale. For multi-facility portfolios, decision-makers must prioritize post-disaster reconstruction activities appropriately to ensure facilities and infrastructure are restored. In addition, any expansion or new construction initiatives are ideally completed in order of decision-maker and community preference. Most post-disaster optimization and decision framework research consider a single stakeholder as guiding decisions related to a project portfolio. However, these portfolio prioritization frameworks ignore the effect of multiple stakeholders and competing …

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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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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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Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner Mar 2022

Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner

Theses and Dissertations

Artificial Intelligence is the next competitive domain; the first nation to develop human level artificial intelligence will have an impact similar to the development of the atomic bomb. To maintain the security of the United States and her people, the Department of Defense has funded research into the development of artificial intelligence and its applications. This research uses reinforcement learning and deep reinforcement learning methods as proxies for current and future artificial intelligence agents and to assess potential issues in development. Agent performance were compared across two games and one excursion: Cargo Loading, Tower of Hanoi, and Knapsack Problem, respectively. …

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Double Cone Flow Field Reconstruction Between Mach 4 And 12 Using Machine Learning Techniques, Trevor A. Toros Mar 2022

Double Cone Flow Field Reconstruction Between Mach 4 And 12 Using Machine Learning Techniques, Trevor A. Toros

Theses and Dissertations

No abstract provided.

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Leveraging Machine Learning For Large Scale Analysis Of Publicly-Available Data For Gnss Interference Events, David K. Stamper Mar 2022

Leveraging Machine Learning For Large Scale Analysis Of Publicly-Available Data For Gnss Interference Events, David K. Stamper

Theses and Dissertations

This research documents architecture and implementation of an enhanced interference detection and classification analysis system, using both a database and storage solution utilizing machine learning algorithms to detect changes in Carrier-to-Noise strength over multiple GNSS sites. The system uses publicly-available government supported receivers to detect interference, and built using FOSS packaged as a programming library through Python. Two algorithms are discussed in terms of enhancing interference detection using both non-machine learning and machine learning approaches. Two algorithms are also discussed which are used for classification of events. In addition, an approach to Large Scale data analytics is demonstrated via a …

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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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