A Comparative Study Of Electronic And Paper Ballot Systems In Modern U.S. Elections,
2025
University of Rhode Island
A Comparative Study Of Electronic And Paper Ballot Systems In Modern U.S. Elections, Gianna M. Wadowski
Open Access Master's Theses
In-person voting processes that rely on paper ballots have long dominated voting in the U.S. However, following the implementation of the Help America Vote Act in 2002, states rapidly adopted new voting technologies that dramatically changed the in-person voting experience. Since then, states have continued to adopt new voting technologies as new challenges and opportunities have emerged. Although scholarship has demonstrated that new voting technologies can offer benefits, reported improvements to the in-person voting experience are inconsistent. Despite changes in voting equipment and voting methods, voters continue to wait in long lines, affecting turnout and voter confidence. Using observational time …
A Human-In-The-Loop Framework For Scalable And Interpretable Event Triaging In Large-Scale Systems,
2025
Louisiana Tech University
A Human-In-The-Loop Framework For Scalable And Interpretable Event Triaging In Large-Scale Systems, Ibrahim Khaled Al-Agha
Doctoral Dissertations
This dissertation presents a comprehensive and scalable framework for real-time fault detection and event triage in industrial systems, addressing critical challenges such as class imbalance, ambiguous feature boundaries, and the prioritization of complex, high-dimensional event data. The proposed framework integrates advanced methodologies, including micro-batch processing, retrospective divergence-based event detection (DB-RED), association rule mining (ARM), clustering, and Dempster-Shafer Theory (DST) for conflict resolution. Together, these components enable the systematic stratification of events into actionable priority levels, ensuring robust and interpretable decision-making in real-time environments. DB-RED forms the cornerstone of the framework, leveraging KL-divergence and PE-divergence metrics to detect subtle and transient …
End-To-End (E2e) Mbse Framework,
2025
University of South Alabama
End-To-End (E2e) Mbse Framework, Joshua Adelabu, Bhushan Lohar
Shelby Hall Graduate Research Forum Posters
Principles of systems engineering (SE) possess great influence. Frameworks are generated to execute and incorporate such principles. Framework can have various architectural constructs and simultaneously consist of diverse concepts. Concepts like modularity, scalability, integration, and the balance between performance, cost, and risk are guided by SE principles as well as the manufacturability of designed systems due to the migration from mass customization to mass personalization resulting in increased complexity, and as a result need to be guided and gives rise to modularity. However, principles are not enough for effective system design and understanding. There is a need for a framework. …
End-To-End (E2e) Model-Based Systems Engineering (Mbse) Framework,
2025
University of South Alabama
End-To-End (E2e) Model-Based Systems Engineering (Mbse) Framework, Joshua Adelabu, Bhushan Lohar
Shelby Hall Graduate Research Forum Presentations
This presentation explores the latest advancements in systems engineering, with a particular focus on Model-Based Systems Engineering (MBSE). It covers key definitions, benefits, applications, and challenges associated with these methodologies, as well as analyzes current frameworks and research methodologies in the field.
Design Of An Electro-Hydraulic Laboratory Test System For Adjusting The Inclination Angle Of Sowing Machines,
2025
Department of Mechanical Engineering, Engineering Faculty Namık Kemal University, Çorlu, Tekirdağ, TURKEY
Design Of An Electro-Hydraulic Laboratory Test System For Adjusting The Inclination Angle Of Sowing Machines, Aytac Moralar, Figan Dalmis, Bahattin Akdemir
The Philippine Agricultural Scientist
Field testing of grain sowing machinery requires favorable field conditions and sufficient time periods, making laboratory tests a preferred alternative for determining performance under controlled conditions. However, a standardized testing system for evaluating sowing machinery has not yet been established. In this study, a test system was designed for laboratory testing of universal grain sowing machines. A movable platform was built on a chassis made using sheet metal with different dimensions and profiles. It operates through a hydraulic system via a programmable logic controller-based control system. The sowing machine placed on this platform allows for inclination adjustments (front, back, right, …
Dartbot: Overhand Throwing Of Deformable Objects With Tactile Sensing And Reinforcement Learning,
2025
Purdue University
Dartbot: Overhand Throwing Of Deformable Objects With Tactile Sensing And Reinforcement Learning, Shoaib Aslam, Krish Kumar, Pokuang Zhou, Hongyu Yu, Michael Yu Wang, Yu She
School of Industrial Engineering Faculty Publications
Object transfer through throwing is a classic dynamic manipulation task that necessitates precise control and perception capabilities. However, developing dynamic models for unstructured environments using analytical methods presents challenges. In this study, we present DartBot, a robot that integrates tactile exploration and reinforcement learning to achieve robust throwing skills for nonrigid relatively small objects under the influence of moment of inertia which cause the object to spin in the air. Unlike traditional sim-to-real transfer methods, our approach involves direct training of the agent on a real hardware robot equipped with a high-resolution tactile sensor, enabling reinforced learning in a realistic …
Are Emojis The New Words? A Sentiment Analysis Of Social Media Brand Conversations,
2025
SVKM's NMIMS Mukesh Patel School of Technology Management & Engineering, Mumbai
Are Emojis The New Words? A Sentiment Analysis Of Social Media Brand Conversations, Yashodhan Karulkar, Dev T. Vora, Siddharth Vaddepalli, Yash Thakur
Journal of International Technology and Information Management
Emojis have become an increasingly important aspect of consumer-brand interactions in the Indian subcontinent. However, the impact of emoji use on brand image and mental health remains underexplored, particularly in emerging economies like India, where structured research on this topic is limited. To address this gap, the present study analyzes over 4,600 consumer tweets related to 19 prominent brands across eleven industries. Using VADER sentiment analysis, the research develops a metric to assess consumer sentiment and brand engagement in relation to emoji usage. The findings indicate that effective integration of emojis contributes to positive consumer sentiment and enhanced brand engagement. …
Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps,
2025
Air Force Institute of Technology
Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps, Nana Hene
Theses and Dissertations
Operational Energy (OE) education is vital for national security, military readiness, and fuel energy efficiency. This thesis analyzes the current landscape of OE education and identifies key gaps in awareness, energy knowledge, and curriculum structure. Through a reflexive thematic analysis of interviews with Subject Matter Experts (SMEs), the study underscores the necessity of integrating OE concepts into both educational and professional training programs. A framework is proposed to enhance OE education across various levels in the Air Force, aiming to cultivate a more energy-conscious and strategically prepared force. The findings highlight the critical need for targeted training, curriculum enhancements, and …
Military Entrance Processing Station Location And Capacity Optimization,
2025
Air Force Institute of Technology
Military Entrance Processing Station Location And Capacity Optimization, Micah A. Hurst
Theses and Dissertations
This research optimizes the number, placement, and capacity of Military Entrance Processing Stations (MEPS) to minimize applicant and recruiter travel and improve recruitment efficiency. Using mixed-integer programming, it develops capacitated facility location (CFLP) and maximal covering location (MCLP) models, considering facility capacity, budget, and geographic coverage. Computational testing and scenario evaluations highlight opportunities to reduce travel and balance capacity. For example, the CFLP model adds three new MEPS, reducing annual applicant travel by 1.2 million miles in Florida and Texas and 1.0 million in California, while increasing accessibility within 60 miles of a MEPS. This data-driven approach provides USMEPCOM with …
The Location Set Covering Disruption Problem,
2025
Air Force Institute of Technology
The Location Set Covering Disruption Problem, Richard A. Sheldon
Theses and Dissertations
This research models and analyzes a variant of the Location Set Covering Problem (LSCP) in a bilevel, game theoretic setting by posing the LSCP as a non-cooperative attacker-defender Stackelberg game, where facilities are to be emplaced by the defender from a boarder set of potential facility locations to cover a set of demands; however, an attacker removes the possibility of emplacing q specific facility locations with the objective to remove the maximum weighted value demands, and then lexicographically maximize the cost of coverage of remaining demands. A novel methodology leveraging lexicographic programming computed an optimal solution for 98% of all …
Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach,
2025
Air Force Institute of Technology
Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach, William M. Titus
Theses and Dissertations
This research models and analyzes the impact of stochastic travel times on port selection during a large-scale mobilization of equipment from continental United States installations to deployment locations using sealift ships. A stochastic mixed-integer programming model is developed to minimize the average arrival time of equipment into theater. The model is solved using Sample Average Approximation. In the first stage, the model selects ports to open and assigns installations, equipment, and ships to open ports. In the second stage, travel times are realized, and equipment is assigned to specific ships that are scheduled to depart. Results show that the marginal …
Practical Estimation Of Action-Generation Mechanisms In Repeated Games,
2025
Air Force Institute of Technology
Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii
Theses and Dissertations
The goal of this research is to gain insight into how players of a game learn their strategy during the course of repeated play. The study employs the Experience Weighted Attraction (EWA) model, developed by Dr. Colin F. Camerer and Dr. Teck-Hua Ho, as the foundational behavioral framework. Using historic observed strategy decisions, the parameter values that define an opponent’s learning process are updated using various inference methods.
Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data,
2025
Air Force Institute of Technology
Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp
Theses and Dissertations
Accurate sensors are critical for ensuring the safety of aircrew. However, detecting faulty sensors remains a significant challenge for the Test Pilot School at Edwards Air Force Base in California. Current methods rely on either student pilots identifying anomalies or waiting for sensors to fail completely before repairs are made—an approach that lacks reliability and consistency. This research aims to address these shortcomings by implementing machine learning techniques to detect sensor faults proactively. To date, applying machine learning to a dataset of this size, encompassing numerous sensors on the same aircraft, is unprecedented. The project focuses on establishing strong baseline …
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse,
2025
Air Force Institute of Technology
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin
Theses and Dissertations
As fighter aircraft become more complex and technology, such as autonomy, is introduced, it is essential to anticipate the critical tasks and information pilots need to accomplish their mission with these new systems. Fighter pilots operate in highly demanding situations where the consequences of failure are severe and require their systems to provide the right information for the task. Traditionally, these designs are informed through Critical Task Analyses of existing systems. This research produced a method for modeling critical task analysis and information requirements using model-based systems engineering. The scenario was a fighter aircraft conducting basic fighter maneuvers in a …
Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model,
2025
Air Force Institute of Technology
Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick
Theses and Dissertations
The main contributions of this research is to add to the growing library of literature on the use of deep learning algorithms for the spatiotemporal prediction of dangerous atmospheric and hydrologic phenomena. Specifically, we develop novel attention-based and non-attention-based recurrent neural network frameworks to produce short-range sequential forecasts for lightning and tornado occurrences. Additionally, we introduce methods that account for and include error in the model tuning process to generate more reliable models. Furthermore, we have created a lightweight spatiotemporal tornadic prediction dataset that we plan to make publicly available. The first component of this research develops three novel spatiotemporal …
Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment,
2025
Air Force Institute of Technology
Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman
Theses and Dissertations
This study examines the effects of active learning compared to didactic methodologies on two soft skills, namely teamwork and self-efficacy using regression analyses and connected letter reports. Learning styles and personality traits were used as predictors. Findings indicate significant interaction effects between methodology, aural learning style, and personality traits on self-efficacy and teamwork ability. The findings highlight the nuanced role of learner traits in shaping teamwork outcomes across instructional methods. While active learning supports soft skills, individual differences must be considered in instructional design to optimize teamwork in technical education settings.
The Application Of Decision Analysis Theory For Space Allocation At The Air Force Institute Of Technology,
2025
Air Force Institute of Technology
The Application Of Decision Analysis Theory For Space Allocation At The Air Force Institute Of Technology, Damian N. Soriano
Theses and Dissertations
This thesis investigates the application of Decision Analysis Theory to optimize space allocation at the Air Force Institute of Technology (AFIT). Through a Multi-Objective Decision Analysis (MODA) framework, this study addresses existing methodologies for space allocation in military, academic, and office settings; the rules, limitations, and factors influencing space utilization at AFIT; and approaches to improve office and lab allocations for institutional efficiency and fairness. This research incorporates qualitative and quantitative metrics, including faculty and student data, research outputs, and historical space usage. These findings highlight significant complexities in space allocation, particularly in reconciling administrative and research requirements with structural …
Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation,
2025
Air Force Institute of Technology
Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock
Theses and Dissertations
In conjunction with the Air Force Research Laboratory Materials Lab(AFRL-RX), this study evaluates the potential military value of the prototype material sensing composites on Unmanned Aerial Vehicle (UAV) operations in intelligence, surveillance, reconnaissance (ISR), and close air support (CAS) missions within a contested Indo-Pacific theater. Using a Simio based simulation,UAV performance was assessed under varying combat conditions, focusing on Remote Sensing, deployment strategies, initial lay-downs, and varying loss rates. Re-sults show that UAVs equipped with Remote Sensing technology significantly improved sortie generation and logistical efficiency. Scenario 17 achieved the highest sortie rate(965.5 sorties), outperforming the next-best scenario by 25 sorties. …
Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation,
2025
Air Force Institute of Technology
Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case
Theses and Dissertations
United States Air Force (USAF) operations rely on sortie generation, a complex system involving aircraft maintenance, operational planning, munitions, security forces, and aircrew. Failures in any of these areas can jeopardize a mission, and extreme weather events such as lightning, high winds, and snow further complicate operations. This thesis examines the impact of extreme weather on sortie generation, focusing on developing a data-driven discrete-event simulation (DES) to predict generation timelines and identify high-risk areas. The model allows users to adjust key inputs, including the month, number of aircraft, processing times, and personnel/equipment availability. By simulating real-world conditions, the model helps …
Class Imbalance: A Landscape Of Classification Models,
2025
Air Force Institute of Technology
Class Imbalance: A Landscape Of Classification Models, Joshua L. Edmonds
Theses and Dissertations
Class imbalance poses significant challenges in machine learning classification. This study evaluates the performance of seven models (ANN, k-Means, kNN, LDA, LR, SVM, XGBoost) across multiple imbalance levels (10\%, 5\%, 1 \%, 0.5\%) and investigates the effectiveness of sampling techniques (Undersampling, SMOTE, SMOTE-ENN). ANOVA results confirm that model choice is the most critical factor, with XGBoost and SVM demonstrating superior robustness. SMOTE improves recall but reduces precision, while undersampling generally degrades overall performance. While significant, imbalance levels do not play a critical role in model effectiveness.
