Understanding The Impact Of Emergent Conflict On Communication And Team Cognition: A Multilevel Study In Engineering Teams,
2024
Old Dominion University
Understanding The Impact Of Emergent Conflict On Communication And Team Cognition: A Multilevel Study In Engineering Teams, Francisco Cima
Engineering Management & Systems Engineering Theses & Dissertations
The development of team cognition is crucial for fostering high-performing teams. In cognitive-intensive fields like engineering, effective communication serves as a primary precursor to team knowledge development, enabling group members to effectively retrieve and utilize each other's expertise. Despite the critical role of communication, there is a lack of empirical research examining how conflict situations, which are critical emerging factors inherent to teamwork, interact with communication processes to constrain team knowledge development and utilization. This study, rooted in information processing theory, investigates how emerging conflict shapes multilevel team knowledge structures by interacting with communication processes in engineering project teams. Prior …
Optimizing Deployment Kit, Introducing Acceptance Threshold,
2024
Air Force Institute of Technology
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.
Systematic Review Of Supply Chain Control Tower Critical Success Factors And Resilience Effects,
2024
Air Force Institute of Technology
Systematic Review Of Supply Chain Control Tower Critical Success Factors And Resilience Effects, Clay H. Chaffin
Theses and Dissertations
Supply chain control towers (SCCTs) are emerging as a vital component of modern supply chain management (SCM); however, research on SCCTs is limited and disjointed. This paper aims to uncover the critical success factors (CSFs) necessary for high-performing SCCTs, their relationship to the enablers and phases of supply chain resilience (SCRES), and the underlying theoretical framework of this relationship.
On Intrinsic Dimensionality Of Data Sets And Neural Networks,
2024
Air Force Institute of Technology
On Intrinsic Dimensionality Of Data Sets And Neural Networks, Ori Chachmo
Theses and Dissertations
The concept of Intrinsic Dimensionality (ID) is of special interest in the field of Neural Networks (NNs) since it promotes both (a) a deeper understanding of the underlying mechanisms, and (b) embraces parsimonious modeling (that is, building the right-sized model for the task) with associated benefits to processing speed and storage requirements. This thesis explores the concept of ID via two separate, but related, questions. First, we study the potential of NN ID prediction by exploiting easily obtained quantities measured on the data. We then explore NN ID as an independent concept by comparing the results of different methods for …
2033 Digital Modernization At Usmepcom: A Strategic Analysis Of Future Military Applicant Processing,
2024
Air Force Institute of Technology
2033 Digital Modernization At Usmepcom: A Strategic Analysis Of Future Military Applicant Processing, William A. Clay
Theses and Dissertations
This research examines the projected 2033 applicant processing scenario considering the digital modernization efforts of the United States Military Entrance Processing Command (USMEPCOM). The study evaluates the necessary modifications to current processes, with a particular focus on the influence of two key information technology systems, the MEPCOM Integrated Resource System (MIRS) 1.1 and the Military Health System (MHS) Genesis, on manpower at a Military Entrance Processing Station (MEPS). In doing so, the study establishes baseline processing metrics for assessing these impacts. By utilizing discrete event simulation modeling and leveraging current literature, the study proposes strategies for incorporating technological advancements into …
Evaluation Of Vtol-Capable Cargo Uavs For Dispersible Airfield Logistics In The Usindopacom Aor,
2024
Air Force Institute of Technology
Evaluation Of Vtol-Capable Cargo Uavs For Dispersible Airfield Logistics In The Usindopacom Aor, Maria C. Chedzoy
Theses and Dissertations
This research models and analyzes the ability of commercial cargo UAVs to rapidly evacuate logistics from an airfield to proximal, outlying destinations, particularly in the USINDOPACOM AOR. This is a tenet of Agile Combat Employment by the USAF, which seeks to mitigate the effect of kinetic threats by near-peer adversaries. The analysis sets forth a binary linear program to minimize the total time to evacuate a fixed amount of logistics from an airfield. Parameters include the cargo UAV with its performance specifications, number of cargo loading points at the airfield, number of destinations for cargo evacuation, and subset of destinations …
Federated Medical Scoring Systems,
2024
Air Force Institute of Technology
Federated Medical Scoring Systems, Jacob F. Bryant
Theses and Dissertations
Federated Learning (FL) is a recent framework of machine learning implementation that trains models on a distributed network of clients as opposed to housing and analyzing this data centrally. This has data communication and practical data privacy advantages, the latter of which is particularly attractive to the medical community where patient privacy is closely safeguarded. We apply FL to a family of sparse linear integer models called Medical Scoring Systems (MSSs). We create a novel methodology for creating these MSSs in a simulated federated environment that involves an lo constrained Logistic Regression (LR), loss-surface examination, and rounding procedure. We tested …
Reinforcement Learning For Team Based Air Combat Maneuvering Decisions With Directed Energy Weaponry,
2024
Air Force Institute of Technology
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 …
Enhancing Port Efficiency And Lead Time Reduction Through Predictive Analysis: A Case Study Of Container Management At Khalifa Bin Salman Port,
2024
Air Force Institute of Technology
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 …
Usmepcom Prescreens: A Value-Focused Thinking Approach,
2024
Air Force Institute of Technology
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 …
The Use Of Deep Learning And Transfer Learning In Complex Problems,
2024
Air Force Institute of Technology
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 …
Knowledge Management Modeling And Decision Analysis For Usmepcom,
2024
Air Force Institute of Technology
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.
Training Schedule For The 56th Maintenance Group,
2024
Air Force Institute of Technology
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, …
Analysis And Visualization Of Military Convoy And Supply Utilization In Support Of State-Specific Freight Plans,
2024
Air Force Institute of Technology
Analysis And Visualization Of Military Convoy And Supply Utilization In Support Of State-Specific Freight Plans, Madison E. Hofmann
Theses and Dissertations
Researching the United States military’s use of highways and interstates is necessary for the allocation of federal infrastructure spending. As of today, there is no established method, tool, or process routinely utilized by the Surface Deployment and Distribution Command to effectively show a system-wide view of military convoy and supply route usage across CONUS. This research advances this endeavor by providing a by-state characterization of interstates and major highways in 2022, categorized by the volume of military freight they support. Some notable methodologies used to conduct the analyses are the shortest path problem, map matching algorithms, and Global Positioning System …
U.S. Army Cadet Command Branch Prediction Model,
2024
Air Force Institute of Technology
U.S. Army Cadet Command Branch Prediction Model, Daniel M. Krizan
Theses and Dissertations
The current system for providing US Army ROTC cadets their branches leaves significant uncertainty until the final pronouncement of branch assigned. This uncertainty can be alleviated by providing a prediction model for cadets to input personal data and desired branch to identify likelihood of receiving the request. This thesis produces a machine learning model capable of producing branch prediction for cadets.
Factors Affecting The Retention Of Active Duty Airmen,
2024
Air Force Institute of Technology
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 …
An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models,
2024
Air Force Institute of Technology
An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models, Layton C. Hedge
Theses and Dissertations
This research examines China and derives insights specific to it and the First Island Chain and the Second Island Chain. In doing so, this research demonstrates a methodology to examine other competitors and their geostrategic interests. In the first phase of analysis, it develops a value hierarchy to depict objectives within subregions of the area of interest and considers four alternative weightings of the value hierarchy. In the second phase of analysis, it applies four location-covering models to assess how the competitor would emplace a range of limited resources to deter and/or control points of interest. Results indicate that land-based …
A Reinforcement Learning Approach To The 2v2 Beyond Visual Range Air Combat Maneuvering Problem,
2024
Air Force Institute of Technology
A Reinforcement Learning Approach To The 2v2 Beyond Visual Range Air Combat Maneuvering Problem, Jacob J. Pike
Theses and Dissertations
This research examines a 2v2 air combat maneuvering problem (ACMP) in a Beyond Visual Range (BVR) environment. A discrete-time, infinite-horizon Markov Decision Process (MDP) model represents the BVR-ACMP, seeking to determine high-quality policies for a pair of autonomous aircraft to execute tactical maneuvers and firing decisions. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) characterizes the complex six-degree of freedom (6-DOF) aircraft operations, encompassing kinematics, sensors, and weapons. Given the high dimensionality and continuous nature of the state and decision variables, a deep reinforcement learning (RL) solution approach is adopted wherein the value function is approximated via a Neural …
Measuring The Comparative Performance Of Usaf Behavioral Health Clinic Operations: Emphasis On Capacity,
2024
Air Force Institute of Technology
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.
A Random Forest-Based Q-Learning Algorithm: Toward Interpretable Artificial Intelligence,
2024
Air Force Institute of Technology
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 …
