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An Analysis Of A Modular Open System Approach On Program Management Metrics For Cost And Schedule, Kayla I. Vogler Mar 2023

An Analysis Of A Modular Open System Approach On Program Management Metrics For Cost And Schedule, Kayla I. Vogler

Theses and Dissertations

A modular open system approach (MOSA) and its inclusion of open architecture are among the prevailing acquisition strategies for cost and schedule management. This approach involves the incorporation of reusable, modular packages that can be incrementally added and upgraded throughout programs’ lifecycles. Many practitioners throughout the acquisitions community find that MOSA enables better opportunities for affordability, rapid acquisition, flexibility, enhanced competition, and innovation. A literature review reveals that few studies examine the interaction between MOSA and the extent to which it influences cost and schedule performance. However, no studies to date examine open architecture’s impact via programmatic evaluation of Earned …

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Integrating Ace And Mca Requirements Into The Civil Engineer Officer Occupational Competency Framework, Stone D. Williford Mar 2023

Integrating Ace And Mca Requirements Into The Civil Engineer Officer Occupational Competency Framework, Stone D. Williford

Theses and Dissertations

The Air Force Civil Engineer officer career field has made dedicated efforts to the professional development of its company grade officers. In response to the 2015 Air Force Strategic Master plan, the Civil Engineer officer career field adopted a competency-based education approach. In 2020, the Civil Engineer Officer Career Field Education and Training Plan was published, officially integrating the career field’s operational requirements into a competency framework. However, since 2020, the Air Force has adopted an updated force generation strategy, and with it, changes to the way the Air Force assets are employed in contingency environments. This new scheme of …

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Validation Of Digital System Models, James R. Winton Mar 2023

Validation Of Digital System Models, James R. Winton

Theses and Dissertations

The Department of Defense is undergoing a Digital Transformation driven by Digital Engineering and Model-Based Systems Engineering. Document-based processes are being replaced by digital artifacts, pedigreed data, and an Authoritative Source of Truth for a system across its life cycle. As traditional Design-Build-Test transitions to a Model-Analyze-Build methodology, digital models will proliferate throughout the enterprise and require novel validation processes earlier in the development timeline. A new definition for digital system model validation is proposed to address the identified shortcomings in existing guidance. The proposed validation framework leverages the Systems Modeling Language, use cases, requirements, test cases, and a custom …

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Arctic Construction Under Climatological Constraints: A Decision Support System For Expeditionary Construction Site Selection In The Arctic Environment, Zachary S. Wontrop Mar 2023

Arctic Construction Under Climatological Constraints: A Decision Support System For Expeditionary Construction Site Selection In The Arctic Environment, Zachary S. Wontrop

Theses and Dissertations

The natural physical barriers present in the Arctic are being eroded by climate change, increasing near peer adversaries' abilities to exploit this region for strategic and economic gain. To maintain the Arctic as a region of strategic and economic international cooperation, increased infrastructure investment by the United States and its allies are required. No methodology currently exists to quantify construction-limiting climatological factors over time and space. Decision support systems can provide actionable information to guide decision makers during site selection. This research employs geographic, and time-coded historical climatology applied to a project case study, to develop a site selection decision …

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Prediction Of Persistent Post-Traumatic Headache With Long Short-Term Memory Networks, Todd C. Campo Mar 2023

Prediction Of Persistent Post-Traumatic Headache With Long Short-Term Memory Networks, Todd C. Campo

Theses and Dissertations

Military members in combat situations are at a high risk for experiencing a Traumatic Brain Injury (TBI), often leaving them with Post-Traumatic Headache (PTH). There is currently a poor understanding of what factors predict if a patient will endure acute (short-term) PTH or Persistent PTH (PPTH). The Concussion Assessment, Research, and Education (CARE) Consortium dataset contains a variety of pre-and-post-injury concussion assessments taken by NCAA athletes and service academy cadets between 2014 and 2018. Participants in this study (n = 1769) suffered a TBI. Using this longitudinal data, three models were constructed: an LSTM model using the raw assessment scores, …

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Information System Availability Status And Its Impact On Customer Wait Times, Joshua A. Cramer Mar 2023

Information System Availability Status And Its Impact On Customer Wait Times, Joshua A. Cramer

Theses and Dissertations

The Military Personnel Flight relies on Air Force Information Systems, specifically the Defense Enrollment Eligibility and Reporting System (DEERS), to manage the personnel records. When DEERS experiences a failure, then the operational ability of the Military Personnel Flight is affected. This study aims at identifying the impact Air Force information system’s availability status has on customer wait times using linear regression.

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Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino Mar 2023

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino

Theses and Dissertations

Generative Adversarial Networks (GANs) have received increasing attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. While this research has yielded GAN variants robust to training set shrinkage and corruption, our research focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to determine empirically the effects of 10 fundamental …

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The Aerial Refueling Asset Basing And Assignment Problem, Camryn E. Deames Mar 2023

The Aerial Refueling Asset Basing And Assignment Problem, Camryn E. Deames

Theses and Dissertations

With growing tensions in the European theatre and Indo-Pacific theatre, the constraints of aerial refueling impede the missions of Air Mobility Command and USTRANSCOM in their execution of both the National Security Strategy and National Defense Strategy. Introducing and integrating semi-autonomous aerial refueling aircraft is a logical next step due to advantages in endurance, survivability, runway requirements, and fuel offloading capacity. This research frames the Aerial Refueling Asset Basing and Assignment Problem with two model approaches: a baseline model and a fuel shuttle concept model. Whereas the former model considers instances with only manned refuelers or only semi-autonomous refuelers, the …

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A Comparison Of Wireless Sensor Networks Under Stochastic Deployment Methods To Ideal Network Structures, Andrew J. Grove Mar 2023

A Comparison Of Wireless Sensor Networks Under Stochastic Deployment Methods To Ideal Network Structures, Andrew J. Grove

Theses and Dissertations

This research addresses the ideal structure of a deployed network of sensors over a geographical area based on metrics such as coverage and connectivity. Using a genetic algorithm, the ideal structure for a range of target network sizes is determined. Then, a series of realistic methods of sensor distribution simulating the scattering of sensors such as a single linear pass, perpendicular passes, and parallel passes are compared to determine the ability of each method to achieve the ideal structure for each target network size. From the results, it is determined that the ideal structure for smaller networks contains a highly …

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An Analysis Of Aircraft Maintenance Leading Indicator Metrics To Unit-Level Aircraft Availability Rates, William C. Hardy Mar 2023

An Analysis Of Aircraft Maintenance Leading Indicator Metrics To Unit-Level Aircraft Availability Rates, William C. Hardy

Theses and Dissertations

The purpose of this research is to improve the usefulness of data that is already collected within aircraft maintenance organizations to better identify trends, and outliers, and possibly better explain relationships between leading and lagging indicator metrics. Specifically, this graduate research paper sought to answer two research questions addressing what aircraft maintenance metrics significantly impact aircraft availability, and how to measure those to understand which metrics impact aircraft availability most. The research questions were answered through a comprehensive literature review, and the use of multiple linear regression analysis on data from two specific aircraft maintenance organizations from the same location. …

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Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill Mar 2023

Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill

Theses and Dissertations

Federated learning (FL) is a budding machine learning (ML) technique that seeks to keep sensitive data private, while overcoming the difficulties of Big Data. Specifically, FL trains machine learning models over a distributed network of devices, while keeping the data local to each device. We apply FL to a Parkinson’s Disease (PD) telemonitoring dataset where physiological data is gathered from various modalities to determine the PD severity level in patients. We seek to optimally combine the information across multiple modalities to assess the accuracy of our FL approach, and compare to traditional ”centralized” statistical and deep learning models.

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Lunar Search And Rescue: The Next Step For Human Spaceflight Recovery, Benjamin J. Johnis Mar 2023

Lunar Search And Rescue: The Next Step For Human Spaceflight Recovery, Benjamin J. Johnis

Theses and Dissertations

Humans return to the Moon in 2024 under the NASA Artemis mission. Commercial space explorations are rapidly expanding. The sudden increase of human spaceflight calls for increased emphasis on space rescue. These revelations drove an AFRL/AFIT capability gap assessment to provide specific proposals for a modern space rescue program guided by Transaction Cost Economics Theory. The mission analysis arms USSPACECOM and NASA to coordinate an interagency approach to Lunar Search and Rescue, positioning America to compete in the new space race. The strategic consequences of failing to act could fundamentally jeopardize American leadership in space.

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Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston Mar 2023

Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston

Theses and Dissertations

Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …

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Pattern Of Life Modeling On Maritime Vessels With Bayesian Inferencing, Miles A. Kelly Mar 2023

Pattern Of Life Modeling On Maritime Vessels With Bayesian Inferencing, Miles A. Kelly

Theses and Dissertations

Despite decades of research, maritime traffic models’ limited predictive power continues to constrain their operational utility. We build on previous pattern of life modeling algorithms and contribute a Bayesian inferencing model for anomaly detection. Our probabilistic approach provides decision makers the capability to tailor the belief threshold for identifying anomalies and to enact a measured response based on the degree of abnormality. We perform a case study to evaluate the results, verifying that our Bayesian inferencing method accurately refines its probability when given the location and time of a ship of interest, and serving as a proof of concept for …

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Designing A Counter-Iads Drone Swarm: Using Evolution To Evaluate Combat Assumptions Underpinning Drone Swarm Target Assignment, Olin H. Kennedy Mar 2023

Designing A Counter-Iads Drone Swarm: Using Evolution To Evaluate Combat Assumptions Underpinning Drone Swarm Target Assignment, Olin H. Kennedy

Theses and Dissertations

The original research goal was to combine the best techniques in the drone swarm literature and model a functional combat drone swarm that conducts a Suppression of Enemy Air Defense (SEAD) mission. However, the body of literature regarding Drone Swarm Target Assignment (DSTA) does not model enemy counteraction and assumes that the drones’ targets are compliant against destruction. Therefore, a model of enemy counteraction against drone swarms is developed, and Novel DSTA (NDSTA) is proposed to respond to the weaknesses of the current DSTA. Both methods of target assignment are combined with a tunable trajectory generation model, and the performance …

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Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim Mar 2023

Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim

Theses and Dissertations

A post-traumatic headache (PTH), resulting from a mild traumatic brain injury (mTBI), potentially develops into persistent post-traumatic headache (PPTH). Although no known cure for PPTH exists, research has shown that receiving treatment at earlier stages of PTH lowers the risk of patients developing PPTH. Previous studies have shown machine learning (ML) models capable of predicting a patient’s PTH progression, but none have considered the issue of protecting patient privacy. Due to patient privacy, ML models only have access to data within the institution. Federated learning (FL) harnesses data from separate institutions without sacrificing patient privacy as institutions can run ML …

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Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian Mar 2023

Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian

Theses and Dissertations

Neural networks have become increasingly popular in real time object detection algorithms. A major concern with these algorithms is their ability to quantify their own uncertainty, leading to many high profile failures. This research proposes three novel real time detection algorithms. The first of leveraging Bayesian convolutional neural layers producing a predictive distribution, the second leveraging predictions from previous frames, and the third model combining these two techniques together. These augmentations seek to mitigate the calibration problem of modern detection algorithms. These three models are compared to the state of the art YOLO architecture; with the strongest contending model achieving …

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Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King Mar 2023

Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King

Theses and Dissertations

The United States Air Force (USAF) has struggled with a sustained pilot shortage over the past several years; senior military and government leaders have been working towards a solution to the problem, with no noticeable improvements. Both attrition of more experienced pilots as well as wash out rates within pilot training contribute to this issue. This research focuses on pilot training attrition. Improving the process for selecting pilot candidates can reduce the number of candidates who fail. This research uses historical specialized undergraduate pilot training (SUPT) data and leverages select machine learning techniques to determine which factors are associated with …

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Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald Mar 2023

Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald

Theses and Dissertations

This research examines the Cadet to Air Force Specialty Code (AFSC) Matching Problem (CAMP). Currently, the matching problem occurs annually at the Air Force Personnel Center (AFPC) using an integer program and value focused thinking approach. This paper presents a novel method to match cadets with AFSCs using a generalized structure of the Hospitals Residents problem with special emphasis on lower quotas. This paper also examines the United States Army Matching problem and compares it to the techniques and constraints applied to solve the CAMP. The research culminates in the presentation of three algorithms created to solve the CAMP and …

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Advancing Autonomous Swarm Behavior In A Simulated Anti-Access Area Denial (A2ad) Environment, Chad P. Macwilkinson Mar 2023

Advancing Autonomous Swarm Behavior In A Simulated Anti-Access Area Denial (A2ad) Environment, Chad P. Macwilkinson

Theses and Dissertations

Advancements in modern IADS have bolstered A2AD environments and subsequently degraded the advantages that the Air Force once held, prompting a call to reform the nature of warfare in order to challenge these threats. A solution is weapon swarming technology, which has the ability to overwhelm IADS by engagement of a large numbers of low-cost, but lethal air assets that have autonomous functionalities. This research proposes the application of a four dimensional framework for autonomy to a swarm of cruise missiles. A virtual A2AD environment of two opposing forces is constructed using the AFSIM, wherein a manned bomber seeks to …

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Simulating Autonomous Drone Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Alexander L. Martinez Mar 2023

Simulating Autonomous Drone Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Alexander L. Martinez

Theses and Dissertations

Army senior military leaders are invested in acquiring modernized aerial platforms and equipment to augment the U.S. Army’s ability to overcome A2AD threats imposed by modern IADS. A prominent element of this modernization effort is the employment of autonomous drones to defeat IADS threats while minimizing risk to Army Soldiers. This research utilizes a framework for classifying the levels of autonomous capability along three dimensions: the ability to act alone, the ability to cooperate, and the ability to adapt. A virtual combat model, created using the AFSIM, simulates the engagement between an enemy IADS and a friendly formation comprised of …

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Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia Mar 2023

Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia

Theses and Dissertations

Recent events show that fuel supply is a large contributor to the success or failure of a military operation in response to a contingency. Any future near-peer conflict will stress the supply chain and require fully operational vehicles to be ready for the primary mission sets they support. In the United States Air Force (USAF), the readiness of fuel distribution trucks is crucial to meeting those mission sets in global operations. Utilizing non-parametric and semi-parametric survival models, which do not assume specific probability distributions, this study analyzes maintenance data for R-11 trucks that refuel aircraft.

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Inducing Sparsity Within High-Dimensional Remote Sensing Modalities For Lightning Prediction, Grace E. Metzgar Mar 2023

Inducing Sparsity Within High-Dimensional Remote Sensing Modalities For Lightning Prediction, Grace E. Metzgar

Theses and Dissertations

The uncertainty of lightning constantly threatens many weather-sensitive fields where the slightest presence of lightning can endanger valuable personnel and assets. The consequences of delaying operations have incited the research of methods that can accurately predict the location of future lightning strikes from the current weather conditions. High-dimensional remote sensing modalities contain information capable of detecting significant patterns and intensities within storms that could indicate the presence of lightning. This thesis induces sparsity into convolutional neural networks (CNNs) and remote sensing modalities through a combination of regularization and tensor decomposition techniques to call attention to sparse features that are most …

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Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller Mar 2023

Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller

Theses and Dissertations

The purposes of this study are to confirm the applicability of survival analysis for predicting recurrent failures of a component of a military aircraft and to provide practical insights to maintenance managers and mission planners. The results of this study also can help the United States Department of Defense improve the CBM+ program. This study was able to predict recurrent failures of the component using Nelson-Aalen cumulative estimates. In addition, this study used a Cox proportional hazards regression model with shared frailty for measuring the effect of covariates on recurrent failures and unidentified heterogeneity in the model, which warranted future …

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An Approximate Dynamic Programming Approach For Solving An Air Combat Maneuvering Problem With Directed Energy Weapons, Elisha A. Palm Mar 2023

An Approximate Dynamic Programming Approach For Solving An Air Combat Maneuvering Problem With Directed Energy Weapons, Elisha A. Palm

Theses and Dissertations

Performing within visual range (WVR) air combat involves the execution of complex air maneuvers and rapid sequential decision making. The complexity of these decisions can increase even further when including additional weapon capabilities. The advancement of unmanned autonomous vehicle technology and weapon capabilities can help combat the hindrance that comes with human limitations. Autonomous unmanned combat aerial vehicles (AUCAVs) and the implementation of advanced weapon capabilities such as Directed Energy Weapons (DEWs) can prove to be vital in a WVR air combat context. This derives the question – Can AUCAV’s possess the proper artificial intelligence and weapon capabilities to attain …

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The U.S. Army Officer-To-Unit Assignment Problem, Andrea L. Phillips Mar 2023

The U.S. Army Officer-To-Unit Assignment Problem, Andrea L. Phillips

Theses and Dissertations

Every two to three years, U.S. Army officers must change duty stations, which entails a selection process based on preferences. Currently, officers are assigned to units using a stable-marriage algorithm. Two impracticalities occur within this process. First, officers are required to submit strictly ranked preferences, not allowing indifference among units. Second, the stable-marriage algorithm does not give flexibility to alternative priorities. This research focuses on two modifications to the current model. First, a mixed integer program is created that allows the user, U.S. Army Human Resources Command, to consider other priorities: unit preferences and maximum officer disappointment. Second, generated data …

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Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid Mar 2023

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …

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A Transformer Based Architecture For Indonesian Sentiment Analysis - Exploring Indobert Variations, Training Size, And Self-Supervised Model Training, Connor F. Shaw Mar 2023

A Transformer Based Architecture For Indonesian Sentiment Analysis - Exploring Indobert Variations, Training Size, And Self-Supervised Model Training, Connor F. Shaw

Theses and Dissertations

There is strong motivation in both civilian and military circles to understand the attitudes, motivations, feelings, and emotions of a population of interest. Social media is a rich source of self-disclosed information by individuals from all walks of life about virtually every domain of the human experience, but the vast quantity of data is impossible to effectively analyze without advanced natural language processing algorithms. This research creates a transfer learning based emotion classification model for Indonesian language Twitter data. Transfer learning consists of two steps: pre-training and fine tuning. Three variations of Indonesian Bidirectional Encoder Representations from Transformers (IndoBERT) are …

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Analysis And Optimization Of Contract Data Schema, Franklin Sun Mar 2023

Analysis And Optimization Of Contract Data Schema, Franklin Sun

Theses and Dissertations

agement, development, and growth of U.S Air Force assets demand extensive organizational communication and structuring. These interactions yield substantial amounts of contracting and administrative information. Over 4 million such contracts as a means towards obtaining valuable insights on Department of Defense resource usage. This set of contracting data is largely not optimized for backend service in an analytics environment. To this end, the following research evaluates the efficiency and performance of various data structuring methods. Evaluated designs include a baseline unstructured schema, a Data Mart schema, and a snowflake schema. Overall design success metrics include ease of use by end …

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Probability Of Agreement As A Simulation Validation Methodology, Matthew C. Ledwith Mar 2023

Probability Of Agreement As A Simulation Validation Methodology, Matthew C. Ledwith

Theses and Dissertations

Determining whether a simulation model is operationally valid requires the rigorous assessment of agreement between observed functional responses of the simulation model and the corresponding real world system or process of interest. This research seeks to extend and formulate the probability of agreement approach to the operational validation of simulation models. The first paper provides a methodological approach and an initial demonstration which leverages bootstrapping to overcome situations where one’s ability to collect real-world data is limited. The second paper extends the probability of agreement approach to account for second-order heteroscedastic variability structures and establishes a weighted probability of agreement …

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