Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Operations Research, Systems Engineering and Industrial Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 2191 - 2220 of 13822

Full-Text Articles in Engineering

Rate Effects In Aircraft Learning Curves, Caleb J. Ahern Mar 2023

Rate Effects In Aircraft Learning Curves, Caleb J. Ahern

Theses and Dissertations

Across the Department of Defense (DoD), a wide variety of analytical tools are employed by cost analysts to estimate weapon system costs. One of the techniques widely employed by practitioners is the learning curve (LC). Although learning curves have been widely studied, using rate-adjustments or production rate effects (PRE), their usage have only intermittently been evaluated in place of using the traditional learning curve. Previous studies analyzing production rate found mixed results. This research aims to examine aircraft production data to determine if production rate model is preferrable in United States Air Force programs. Additionally, this PRE research seeks to …

Go to article

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick Mar 2023

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick

Theses and Dissertations

This research trains, tests, and analyzes bot and troll classification models using publicly available, open source datasets. Specifically, it applies decision tree, random forest, feed forward neural networks, and long-short term memory neural networks with hyperparameters tuned via designed experiment to five labeled bot datasets created between 2011 and 2020 and one dataset labeling state-sponsored disinformation accounts or trolls. The first three models utilize account profile features, while the last model applies natural language processing techniques, specifically GloVe embedding, to analyze a user’s Tweet history. Results indicate that the random forest model outperforms the other three models with an average …

Go to article

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. …

Go to article

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.

Go to article

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 …

Go to article

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 …

Go to article

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.

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

Critical Infrastructure System Resiliency Modeling Using Multi-Layer Network Optimization, Spencer R. Figge Mar 2023

Critical Infrastructure System Resiliency Modeling Using Multi-Layer Network Optimization, Spencer R. Figge

Theses and Dissertations

ccurately modeling the interdependent operation of critical infrastructure systems is an effective and efficient way of proactively evaluating system vulnerabilities and resiliency. Infrastructure systems are designed to transport essential commodities from where they are produced to where they are consumed and network flow-based models are one of the most effective ways to simulate and quantify infrastructure performance. The literature is populated with proposed models that must balance accuracy of interdependent operations, capability to include real-world considerations, and computational cost. This research proposes an alternative network-flow based model called the Critical Infrastructure System Resiliency Model (CISRM) that focuses on modeling a …

Go to article

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 …

Go to article

A Reinforcement Learning Approach To A Beyond Visual Range Air Combat Maneuvering Problem, Caleb A. Taylor Mar 2023

A Reinforcement Learning Approach To A Beyond Visual Range Air Combat Maneuvering Problem, Caleb A. Taylor

Theses and Dissertations

A one-versus-one air combat maneuvering problem is considered wherein a friendly autonomous aircraft must engage and defeat an adversary autonomous aircraft in a beyond visual range environment. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) is leveraged to model the complex and interdependent operations of aircraft, sensors, and weapons utilized in beyond visual range air combat. We formulate a Markov decision process to obtain high-quality decision policies wherein our autonomous aircraft makes maneuvering and missile firing decisions. We utilize a reinforcement learning solution procedure that implements a linear value function approximation to represent state-decision pairs due to the high …

Go to article

A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang Mar 2023

A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

An efficient manufacturing system is key to maintaining a healthy economy today. With the rapid development of science and technology and the progress of human society, the modern manufacturing system is becoming increasingly complex, posing new challenges to both academia and industry. Ever since the beginning of industrialisation, leaps in manufacturing technology have always accompanied technological breakthroughs from other fields, for example, mechanics, physics, and computational science. Recently, machine learning (ML) technology, one of the crucial subjects of artificial intelligence, has made remarkable progress in many areas. This study thoroughly reviews how ML, specifically deep (reinforcement) learning, motivates new ideas …

Go to article

Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar Mar 2023

Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar

Research Collection School Of Computing and Information Systems

Rapid developments in city infrastructure and technol-ogies are creating numerous opportunities and inspiring innovative and emerging urban services. Among these innovations, complex systems of urban transportation and logistics have embraced advances and have been reshaped significantly. They enable innovative new urban services, which are now booming and changing everyday life for urban residents.This special issue of Service Science explores perspectives on innovation in transportation-enabled urban services. We hope that the special issue will enhance the understanding of the planning, operation, and management of such services. Contributions are expected to demonstrate rigorous model development, economic/ econometric analysis, and decision-making tools based …

Go to article

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.

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

Optimal Control Of Precision Airdrop Trajectories Using Direct Collocation And Analytical Methods, Edward J. Maxwell Mar 2023

Optimal Control Of Precision Airdrop Trajectories Using Direct Collocation And Analytical Methods, Edward J. Maxwell

Theses and Dissertations

The work herein investigates the preliminary designs of an optimal navigation controller for a scalable cylindrical airdrop system controlled with grid fins in planar motion. Precision airdrop capabilities are desired for a range of military and humanitarian missions. Fielded airdrop systems have not met desired performance objectives, particularly regarding accuracy. Direct collocation and analytical methods were utilized to solve the optimal control problem for the grid fin controlled precision airdrop system examined in this work. The optimal control problem was comprised of two phases: controlled descent and parachute descent. Minimum and maximum ranges for the system under varying wind fields …

Go to article

Long-Term Asset Prioritization To Support District Planning, Melissa R. Sallberg Mar 2023

Long-Term Asset Prioritization To Support District Planning, Melissa R. Sallberg

Theses and Dissertations

The United States Air Force (USAF) relies on its installations to project military power across the globe. However, due to the deferred infrastructure maintenance and recapitalization backlog of $33 billion as of 2019 (Wilson & Goldfein, 2019), it is more critical than ever for base-level community planners to focus their attention to the projects that will achieve each installation’s long-term goals. The recent incorporation of asset management principles into the USAF District Planning Process allows a unique opportunity to improve the existing scoring model for a holistic look at what matters to enterprise leaders and community planners making the plans …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

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 …

Go to article

First Prev Next Last