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Articles 451 - 480 of 664
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Reinforcement Learning For Team Based Air Combat Maneuvering Decisions With Directed Energy Weaponry, Joshua D. Combs
Reinforcement Learning For Team Based Air Combat Maneuvering Decisions With Directed Energy Weaponry, Joshua D. Combs
Theses and Dissertations
Leveraging the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) we investigate the use of reinforcement learning (RL) techniques for imbuing AUCAV agents with high-quality behaviors for the within-visual-range air combat maneuvering problem (ACMP). We formulate the 2v2 WVR ACMP as a Markov decision process wherein friendly AUCAVs are equipped with DEW capabilities and operate with 6 degrees of freedom. We utilize the Double Deep Q-Network RL algorithm, which centrally trains two friendly AUCAVs and employ a phased learning approach, initially exposing the AUCAVs to a dense reward environment for early training, followed by a sparse reward environment to encourage …
Hybrid Features Extraction For The Online Mineral Grades Determination In The Flotation Froth Using Deep Learning, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Abderrahmane Benhayoun, Oumkeltoum Amar, François Bourzeix, Karim Baïna, Mouhamed Cherkaoui, Oussama Hasidi
Hybrid Features Extraction For The Online Mineral Grades Determination In The Flotation Froth Using Deep Learning, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Abderrahmane Benhayoun, Oumkeltoum Amar, François Bourzeix, Karim Baïna, Mouhamed Cherkaoui, Oussama Hasidi
Manufacturing & Industrial Engineering Faculty Publications
The control of the froth flotation process in the mineral industry is a challenging task due to its multiple impacting parameters. Accurate and convenient examination of the concentrate grade is a crucial step in realizing effective and real-time control of the flotation process. The goal of this study is to employ image processing techniques and CNN-based features extraction combined with machine learning and deep learning to predict the elemental composition of minerals in the flotation froth. A real world dataset has been collected and preprocessed from a differential flotation circuit at the industrial flotation site based in Guemassa, Morocco. …
The Use Of Deep Learning And Transfer Learning In Complex Problems, Jacob S. Lang
The Use Of Deep Learning And Transfer Learning In Complex Problems, Jacob S. Lang
Theses and Dissertations
Deep neural networks and transfer learning show potential in addressing complex problems such as the Tower of Hanoi and knapsack problems. The primary aim is to examine how the use of deep neural networks and transfer learning can enhance the ability of artificial learning systems to generalize. Transfer learning plays a crucial role in machine learning, particularly in the domain of artificial neural networks, as it helps overcome the challenges associated with limited data, computational efficiency, and generalization. The methodology used in this research involves the creation of data sets for the Tower of Hanoi and knapsack problems. To predict …
Electric Vehicle Support Equipment Deployment At Military Installations: A Mixed-Integer Linear Programming Approach, Katelyn M. Barton
Electric Vehicle Support Equipment Deployment At Military Installations: A Mixed-Integer Linear Programming Approach, Katelyn M. Barton
Theses and Dissertations
This research provides insights into a mixed integer linear programming model that finds the ideal number and type of Electric Vehicle Support Equipment (EVSE) required to meet U.S. military installations’ electric energy demands. Executive Order No. 14057 (2021) requires federal agencies to transition to electric non-tactical vehicles by 2035. This research determines minimum cost solutions to implement the transition incorporating real-world constraints, including the weekly vehicle mileage demand, EVSE cost, charging time, and EVSE capacity. This study contributes to the broader effort of the U.S. military to combat climate change and enhances the understanding of efficient EVSE deployment strategies in …
An Integer Programming Model To Optimize Us Army Deployment Cycle And Maximize Unit Availability, Grant R. Engel
An Integer Programming Model To Optimize Us Army Deployment Cycle And Maximize Unit Availability, Grant R. Engel
Theses and Dissertations
The goal of this paper is to determine an optimal cycle length, in months, that minimizes costs and maximizes availability for deploying units in the United States (US) Army. The US Army must be cost efficient while maintaining the flexibility required to adapt to dynamic mission demand. The current practice is to deploy units for a length between the range of 6 to 12 months; however, this varies from unit to unit and the best policy is not clear. We address these issues by forming a mathematical programming model with unique characteristics that distinguish it from others of similar design. …
Usmepcom Prescreens: A Value-Focused Thinking Approach, Phillip M. Koenig
Usmepcom Prescreens: A Value-Focused Thinking Approach, Phillip M. Koenig
Theses and Dissertations
As the recruiting crisis continues to impact the United States Armed Forces, the United States Military Entrance Processing Command (USMEPCOM) continues to search for ways to increase its capability to efficiently determine which applicants are suited for military service. Unfortunately, USMEPCOM does not have a way to evaluate newly suggested alternatives. By leveraging Value-Focused Thinking (VFT), this research describes 28 fundamental objectives that can be applied to a variety of current and future decision problems. Further, this research applies these fundamental objectives to analyze a current decision problem: reengineering the prescreen process to decrease the time from prescreen submission to …
A Reinforcement Learning Self-Play Approach For Informing Wargaming Analysis & Development, Kathleen A. Maclean
A Reinforcement Learning Self-Play Approach For Informing Wargaming Analysis & Development, Kathleen A. Maclean
Theses and Dissertations
The integration of RL into wargames to learn strategic and operational insights is of interest to the United States Air Force. This thesis explores the application of a RL SARSA(λ) algorithm to the wargame Stratagem MIST. The primary objective is to select air and ground combat policies for the Blue Agent to effectively counter various opponent strategies across different terrains. This testing enables a comprehensive evaluation of the Blue Agent’s adaptability and performance under varying combat conditions. The use of basis functions, linear value function approximations, and specific air and ground strategies simplifies the state and action spaces of the …
Federated Analysis Of Wearables Data For United States Air Force Mental And Physical Readiness, Sung Yong O
Federated Analysis Of Wearables Data For United States Air Force Mental And Physical Readiness, Sung Yong O
Theses and Dissertations
This thesis investigates the use of machine learning and deep learning models within a federated learning framework to predict physical and mental readiness in military personnel, using wearable technology data. The collaboration with the 711th Human Performance Wing’s STRONG Lab highlights the importance of readiness as emphasized by the National Defense and Security Strategies. The study evaluates various predictive models, incorporating federated learning to ensure data privacy and security in healthcare systems. By analyzing a comprehensive dataset, the research aims to contribute to military readiness enhancement through technological advancements, supporting health and wellness initiatives to bolster the effectiveness of military …
Factors Affecting The Retention Of Active Duty Airmen, Gregory A. Picardi
Factors Affecting The Retention Of Active Duty Airmen, Gregory A. Picardi
Theses and Dissertations
This study investigates the factors influencing the early exit of active duty Airmen, particularly in the context of the recruitment challenges faced by the USAF in Fiscal Year 2023. The research highlights the significant impact of the implementation of MHS Genesis, a healthcare administration program, on recruitment processes and the broader issues affecting military recruitment, including physical and emotional trauma concerns among potential recruits. Through a survey conducted at Wright-Patterson Air Force Base involving 251 participants, the study utilizes a Chi-square test to explore the primary and secondary reasons for leaving active duty, with family pressure, stability, and financial reasons …
Measuring The Comparative Performance Of Usaf Behavioral Health Clinic Operations: Emphasis On Capacity, Daniel L. Straw
Measuring The Comparative Performance Of Usaf Behavioral Health Clinic Operations: Emphasis On Capacity, Daniel L. Straw
Theses and Dissertations
This research examines the operations of behavioral health clinics in Air Force Continental United States facilities, with a focus on operational efficiency and capacity through Data Envelopment Analysis. Most facilities operate near capacity, demonstrating efficient resource usage, but concerns arise with the potential of increased demand. Days-to-care and leakage are identified as major sources of inefficiency, suggesting that addressing these issues can enhance operations and reduce costs. The study also explores the impact of COVID-19 on care delivery.
End-User Device Management In The Air And Space Forces, Joshua Bonvissuto
End-User Device Management In The Air And Space Forces, Joshua Bonvissuto
Theses and Dissertations
When achieving technical superiority is a matter a national security, it is critical that the Department of the Air Force (DAF) employs a robust Information Technology Asset Management (ITAM) strategy that maximizes mission effectiveness. Since 2022, the Office of the Chief Information Officer (SAF/CN) has been developing a plan to transform the Air Force’s ITAM strategy, primarily intending to centralize End User Device (EUD) procurement to the DAF level. For this study, a Delphi study was conducted to gather expert opinions on key aspects of SAF/CN’s new ITAM strategy to identify strengths, weaknesses, and implementation challenges. This research provides valuable …
Human Performance Modeling Architecture With Hc-130j Mission Application, Stephanie G. Slimp
Human Performance Modeling Architecture With Hc-130j Mission Application, Stephanie G. Slimp
Theses and Dissertations
The DOD emphasizes digital engineering using Model-Based Systems Engineering (MBSE), where MBSE includes SysML-based models of systems. Analysis of system impacts on the human operators and their performance typically occurs through non-MBSE approaches, if at all. One current process, considered the As-Is process for this research, evaluates human performance and workload using IMPRINT, a discrete event simulation (DES) tool. IMPRINT primarily exists as a standalone tool with limited built-in functionality to integrate with an MBSE tool. Using the HC-130J and its crew during a CSAR mission as the system, this research develops a generalizable and updateable human performance modeling architecture …
Rotorcraft Assisted Aircraft Inspection System: Creation And Component Assessment, Adam J. Warren
Rotorcraft Assisted Aircraft Inspection System: Creation And Component Assessment, Adam J. Warren
Theses and Dissertations
Aircraft require frequent inspections to perform their missions safely. Current visual inspection methods are time-consuming and dangerous for inspection personnel, but they are necessary to spot flaws that could endanger the aircraft during flight. This research explores a set of methods for transforming a set of target inspection criteria into camera specifications that will allow a UAS aircraft inspection system to perform inspections on the top skin of an aircraft. Given the minimum distance for the UAS to fly above the aircraft, minimum flaw size to search for on the aircraft, minimum number of pixels to display that flaw size, …
Utilization Of The System Engineering Design Process To Design And Test A Low-Cost Infectious Aerosol Control Mechanism For Patient Aeromedical Evacuation, Sara Shaghaghi
Theses and Dissertations
The aeromedical evacuation of military patients is a critical component of care for Armed Forces members. The Air Force’s ability to transport patients relies on the technology and systems available. A vital transport responsibility is keeping the patient and medical personnel safe during transport. The historical and legacy systems provide reliable transport mechanisms for the Armed Forces’ patients infected with high-level biological agents, but drawbacks must be considered. This dissertation will discuss the development, conceptual design, and initial evaluation of a new low-cost, litter-mounted patient transport system, Biological-Mitigation in Patient Transport (B-MIPT), using the “V” model of the system engineering …
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink
Research Collection School Of Computing and Information Systems
Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …
Assessing Military Parking: A Deep Learning Approach To Evaluating Standards And Impacts, Ryan D. Lalonde
Assessing Military Parking: A Deep Learning Approach To Evaluating Standards And Impacts, Ryan D. Lalonde
Theses and Dissertations
Current United States Department of Defense (DoD) standards require a minimum amount of parking for each building. This requirement defines how much off-street parking to construct. However, the impact of these requirements remains unclear. This study builds upon the emerging field of overhead imagery analytics by directly tying it to parking on military installations. Specifically, this study leverages a pretrained deep learning car detection model, Car Detection – USA, developed by Esri for use within ArcGIS, and couples it with open-access temporal imagery sourced from Google Earth Pro to assess selected parking lots across Area B, Wright-Patterson Air Force Base, …
An Introduction Of Adaptive Training Aid Concepts And Its Application To Accelerated Training For Air Battle Managers, John C. Gillispie
An Introduction Of Adaptive Training Aid Concepts And Its Application To Accelerated Training For Air Battle Managers, John C. Gillispie
Theses and Dissertations
Over the years, the integration of artificial intelligence (AI) to enable autonomous systems has undergone transformative shifts in the Department of Defense (DoD), revolutionizing capabilities and strategic approaches. To further optimize these advancements, varying levels of autonomy have been introduced across critical military applications, spanning intelligence, surveillance, reconnaissance (ISR), air battle management, and offensive/defensive air operations. As the technological landscape expands, so do the opportunities for autonomy to augment operations through human-agent teaming. Within the Air Force, one notably cognitively demanding role that stands to benefit from these strides is that of the Air Battle Manager (ABM). In support of …
Optimizing Deployment Kit, Introducing Acceptance Threshold, Saleh A. Alshuhri
Optimizing Deployment Kit, Introducing Acceptance Threshold, Saleh A. Alshuhri
Theses and Dissertations
This article addresses the optimization of a specialized deployment kit crucial for air force operations, emphasizing the need for rapid and efficient aircraft deployment. Through a comprehensive analysis of historical data, the study aims to streamline the kit's contents without compromising effectiveness. The research suggests a potential reduction of 7.8%, with an impressive 60.5% decrease if a minimal 5% threshold is deemed acceptable. While the primary focus is on air force deployment, the broader implications extend to military entities, such as armies and navies, highlighting the applicability of the findings in enhancing deployment efficiency across various defense sectors.
Bayesian Augmentation Of Object Detection Algorithms To Enhance Object Classification Stability, Taylor D. Markham
Bayesian Augmentation Of Object Detection Algorithms To Enhance Object Classification Stability, Taylor D. Markham
Theses and Dissertations
Neural networks, despite their prowess in computer vision, often exhibit "flickering". Flickering occurs when networks fail to maintain consistent object representation across frames, leading to inaccurate and inconsistent output. This problem is particularly critical in mission-surety applications where reliable object recognition is crucial. This research presents a novel approach that combines existing object detection and tracking algorithms like YOLO and SORT with a Bayesian backend model. This Bayesian backend incorporates probabilistic reasoning to analyze the network's confidence in its predictions and infer the most likely object identity across multiple frames, effectively reducing flickering and enhancing robustness.
A Random Forest-Based Q-Learning Algorithm: Toward Interpretable Artificial Intelligence, Victor R. Rae
A Random Forest-Based Q-Learning Algorithm: Toward Interpretable Artificial Intelligence, Victor R. Rae
Theses and Dissertations
A growing demand exists for interpretable artificial intelligence models, leading to extensive research efforts to enhance the explainability and transparency of policies generated by reinforcement learning (RL) methods. This research develops random forest-based RL algorithms as a logical progression in this academic pursuit. The algorithms are evaluated using three standard benchmark environments from OpenAI gym — CartPole, MountainCar, and LunarLander — and compared to implementations of the Deep Q-learning Network (DQN) and Double DQN (DDQN) algorithms for various metrics, including performance, robustness, efficiency, and interpretability. The random forest-based algorithms exhibit superior performance to both neural network-based algorithms in two out …
Knowledge Management Modeling And Decision Analysis For Usmepcom, Luke G. Wunderlich
Knowledge Management Modeling And Decision Analysis For Usmepcom, Luke G. Wunderlich
Theses and Dissertations
This thesis explores the adoption of Value-Focused Thinking (VFT) in enhancing the Knowledge Management (KM) program at USMEPCOM, aiming to align decision-making with the organization’s values and goals. Through evaluating the current knowledge flow and policy drafts, it proposes categorizing command messages, establishing a centralized information repository, and scheduling a daily order release to improve information accessibility and operational readiness. Although no alternative offers a perfect solution, implementing Command Message Categorization is expected to significantly enhance operational efficiency and prepare USMEPCOM for future challenges.
Navigating Model-Based Systems Engineering (Mbse) Transition In The Department Of Defense (Dod): A Capability-Based Assessment (Cba) Use Case, Emily M. Tritschler
Navigating Model-Based Systems Engineering (Mbse) Transition In The Department Of Defense (Dod): A Capability-Based Assessment (Cba) Use Case, Emily M. Tritschler
Theses and Dissertations
The Department of Defense (DOD) wants to implement Model-Based System Engineering (MBSE) to accelerate and improve the acquisition process of increasingly complex systems. However, the department has not provided the necessary guidance on how to fully implement MBSE into our systems. This provided the following research opportunity: select a common DOD process, create an MBSE methodology, generate a model in accordance with that developed method, record the cost of modeling, and interview the model recipients to characterize their opinions on the investment. The research created a twelve-step methodology for application towards the gap analysis and characterization phase of a Capability-Based …
Training Schedule For The 56th Maintenance Group, Samantha K. O'Rourke
Training Schedule For The 56th Maintenance Group, Samantha K. O'Rourke
Theses and Dissertations
The 56th Equipment Maintenance Squadron (56 EMS) provides equipment maintenance and back shop maintenance for the F-35 Joint Strike Fighter. The squadron executes thousands of sorties and flight hours annually. This operations tempo requires maintenance to prevent equipment failures, minimization of aircraft downtime, insurance of safety and compliance, and training of maintenance personnel. The squadron incorporates periodic training sessions to train maintenance personnel skills needed by airmen. This research investigates the optimization of these training sessions employing mixed integer programming (MIP). A multi-objective MIP model is developed to address the complex needs of various training activities, such as: training regiments, …
Digital Airworthiness: Development Of A Sysml Based Framework For The Usaf Airworthiness Process, Justin T. Moore
Digital Airworthiness: Development Of A Sysml Based Framework For The Usaf Airworthiness Process, Justin T. Moore
Theses and Dissertations
In 2018 USAF decided to move towards a digital transition for programs and processes. To maximize the impact of initial transition efforts the airworthiness process was identified as a candidate for digital implementation. The airworthiness process is mandated for nearly every system or modification that flies. The airworthiness process identifies specific tasks that must be performed and artifacts that must be produced. This research worked to develop a framework that utilizes SysML to pattern these processes and the required artifacts. A system agnostic, importable library was developed using custom stereotypes and relationships for the purpose of application to digital system …
An Analysis Of Usaf Policy Implementation For Building Information Modeling, Evan J. Ward
An Analysis Of Usaf Policy Implementation For Building Information Modeling, Evan J. Ward
Theses and Dissertations
The development of Building Information Modeling (BIM) has strongly influenced the architecture, engineering, and construction communities as a path towards effective and efficient asset management. Although BIM is a standard practice in the private sector, the United States Air Force (USAF) does not mirror its civilian counterparts when it comes to BIM use. USAF BIM is limited in its use and does not extend beyond the design and construction phases of the construction life cycle. This research used a detailed querying process to analyze foundational policy documents and determine specific USAF building information requirements. After categorizing the list of requirements …
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Theses and Dissertations
The purpose of this research is to estimate the stimulated Raman scattering noise induced in CWDM O-band channels by two DWDM classical sources in a terrestrial quantum optical network containing classical and quantum optical signal coexistence in the same fiber segment. A use case is defined and analyzed which extracts a single fiber segment from a notional Bell state measurement found in a notional terrestrial quantum network. A stimulated Raman scattering noise model is employed in a Python simulation to estimate and rank-order the five O-band channels with the least amount of relative induced stimulated Raman scattering noise when given …
An Assignment Model For Lateral Transfers Matching Base Repair Facilities To Xf3 Coded Nsns Requiring Repair, George D. Valaika
An Assignment Model For Lateral Transfers Matching Base Repair Facilities To Xf3 Coded Nsns Requiring Repair, George D. Valaika
Theses and Dissertations
This research addresses challenges in efficiently distributing reparable National Stock Numbers (NSNs) to base-level repair facilities, aiming to ease strain on depot resources. It establishes a network integrating bases with similar repair capabilities for NSNs and allocates NSNs to balance repair capacities. Drawing from USAF reparable inventory modeling and inventory management theory, it generates data mimicking historical data to maximize total expected part repairs by assigning NSNs based on the best percentage of base repair (PBR).
Cloud One Migration Schedule Drivers And Schedule Growth, Ryan J. Jansen
Cloud One Migration Schedule Drivers And Schedule Growth, Ryan J. Jansen
Theses and Dissertations
Cloud One, chartered in 2017 under the guidance of Air Force Life Cycle Management Center (AFLCMC) leadership, continues to serve as the USAF’s leading cloud services and hosting platform by providing secure computing environments, application migration assistance, and data management. Prior research has yielded qualitative insights regarding Cloud One’s personnel requirements, application of technical performance, requirements fulfillment, security risks, and various other cost metrics, but schedule improvement recommendations based on the quantitative analysis of migration schedule data has yet to be provided. This research identifies trends within migration sprint schedules and completed schedule data for Cloud One’s completed application migrations. …
Enhancing Port Efficiency And Lead Time Reduction Through Predictive Analysis: A Case Study Of Container Management At Khalifa Bin Salman Port, Abdulaziz A. Aljalahma
Enhancing Port Efficiency And Lead Time Reduction Through Predictive Analysis: A Case Study Of Container Management At Khalifa Bin Salman Port, Abdulaziz A. Aljalahma
Theses and Dissertations
Khalifa bin Salman Port (KBSP), a key pillar in Bahrain's maritime infrastructure, is the focal point of this study, highlighting the significant role of predictive analytics in optimizing port operations. This thesis analyzes container throughput data from 2017 to 2022, provided by Bahrain's Ministry of Transportation database. This data forms the basis for forecasting the 2023 throughput. The study thoroughly compares these predictions with the actual 2023 data, assessing the predictive model's accuracy. The findings underscore the importance of predictive analytics in strategic decision-making for port management, focusing on enhancing operational efficiency and reducing lead times. This research offers a …
3- And 6-Degree-Of-Freedom Investigation Of Aerobraking To Support Cislunar And Planetary Operations, Erica C. Higginbotham
3- And 6-Degree-Of-Freedom Investigation Of Aerobraking To Support Cislunar And Planetary Operations, Erica C. Higginbotham
Theses and Dissertations
The first aerobraking experiment occurred in 1991 as part of the Hiten spacecraft’s cislunar survey mission, while the first non-Earth aerobraking experiment occurred in 1993 as part of the Magellan spacecraft’s mission to Venus. Although making only two trans-atmospheric passes to reduce its apogee altitude, the success of Hiten’s experiment led to the implementation of aerobraking by Magellan, reducing its orbit from elliptical to nearly circular over a span of 70 Earth days by leveraging aerodynamic drag to reduce its orbital energy via transiting the upper region of Venus’ atmosphere. The Magellan experiment helped prove the viability of aerobraking for …