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Articles 661 - 690 of 5596
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Military Personnel Flight Customer Wait Time Reduction Model Using Simulation, Nicholas C. Anderson
Military Personnel Flight Customer Wait Time Reduction Model Using Simulation, Nicholas C. Anderson
Theses and Dissertations
Customers at Military Personnel Flights (MPFs) have been experiencing long wait times. These customers are typically employees of the United States Air Force and every moment spent waiting for service is a moment they are away from their actual jobs. By reducing the mean wait time of MPF customers, manhours can be saved and customer complaints may be alleviated. This research uses data collected from an MPF to build a discrete-event simulation model of an MPF. A full factorial experimental design was conducted in the model using five factors. The factors included the total number of employees, the total number …
Applications Of A Lightning Proxy To Generate Synthetic Lightning For Use In Physics-Based Image-Chain Models, Bryan G. Castro
Applications Of A Lightning Proxy To Generate Synthetic Lightning For Use In Physics-Based Image-Chain Models, Bryan G. Castro
Theses and Dissertations
A method of generating synthetic lightning through the use of a convective available potential energy (CAPE) times precipitation rate (P) proxy is applied over three distinct climatological zones of the world for a single warm season: central and southern AZ of the United States, central Cuba, and North Korea. Global Forecast System (GFS) 0.25° by 0.25° forecast data for June, July, and August of 2019 is used to provide 6-hourly CAPE and precipitation rate, while Global Lightning Dataset (GLD360) data for the period 2016 to 2020 is used to provide observed lightning strokes. A five-year lightning climatology study is conducted …
Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista
Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista
Theses and Dissertations
The objective of this research is to develop procedures that estimate selected, unknown parameters over an adversary's investment portfolio across a set of new or existing technologies. To solve for the selected unknown parameters, it is assumed that the adversary is maximizing the portfolio optimization problem and investing along the efficient frontier. The first technique is when an unknown risk attitude exists but all other parameters were known (i.e. expected return, variance, covariance). An adaptive line search technique that iteratively solved the portfolio optimization problem until the adversary's risk parameter was found. The second problem that was solved was when …
Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park
Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park
Theses and Dissertations
The military deploys many IoT in battlefield operations to provide information on terrain and enemy combatants. It also deploys automated robots or UAVs where securing and trusting collected data is essential. Choosing the middleware that handles this message transfer is crucial for real-time operations. Networks with multiple entities, including IoT devices, UAVs, and small computers, require robust middleware facilitating message sending in real-time. Ideally, the middleware would provide QoS to handle lost packets and retransmissions in lossy environments, especially between low-power machines. DDS is a middleware that implements real-time and QoS capabilities by sending messages, not based on endpoints but …
A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla
A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla
Theses and Dissertations
Applicant processing at Military Entrance Processing Stations (MEPS) is conducted via a batch arrival process by which all applicants arrive at the beginning of the processing day. Pursuit of alternate processing scenarios has never progressed beyond the pilot stage, possibly because the Command lacks a general decision support model to evaluate the impacts of proposed policies on applicant processing operations. This research creates a discrete event simulation of MEPS applicant processing operations and applies the model to three alternative applicant processing scenarios: split-shift, appointment- based, and express-lane. Results are examined and compared to benchmarks using multiple performance measurements.
Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli
Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli
Theses and Dissertations
Users often sacrifice personal data for more relevant search results, presenting a problem to communities that desire both search anonymity and relevant results. To balance these priorities, this research examines the impact of using Siamese networks to extend word embeddings into document embeddings and detect similarities between documents. The predicted similarity can locally re-rank search results provided from various sources. This technique is leveraged to limit the amount of information collected from a user by a search engine. A prototype is produced by applying the methodology in a real-world search environment. The prototype yielded an additional function of finding new …
Smoothing Of Convolutional Neural Network Classifications, Glen R. Drumm
Smoothing Of Convolutional Neural Network Classifications, Glen R. Drumm
Theses and Dissertations
Smoothing convolutional neural networks is investigated. When intermittent and random false predictions happen, a technique of average smoothing is applied to smooth out the incorrect predictions. While a simple problem environment shows proof of concept, obstacles remain for applying such a technique to a more operationally complex problem.
Analysis Of Twitter Networks To Aid Open Source Intelligence Capabilities: A Multilayer Network Approach, Austin P. Logan
Analysis Of Twitter Networks To Aid Open Source Intelligence Capabilities: A Multilayer Network Approach, Austin P. Logan
Theses and Dissertations
Open Source Intelligence using social media is a practice which gives military intelligence analysts a window into the thoughts and minds of an online population. Using Social Network Analysis, user interactions on Twitter will be modeled as a weighted and directed network. Topic modeling through Latent Dirichlet Allocation uncovers the topics of discussion in Tweets and is then integrated into a multi-layer network which allows users to be connected to the conversations with which they have participated. Influential users in this network as well as highly connected groups of individuals are then discovered to paint a picture for intelligence analysts …
Experimental Design On High-Speed Sliding Wear, Irene D. Liew
Experimental Design On High-Speed Sliding Wear, Irene D. Liew
Theses and Dissertations
The purpose of this research is to develop, conduct, and analyze an experimental design that characterizes wear rates of various materials sliding at high speeds along AISI 4340 steel. This work is in support of Holloman Air Force Base, which is invested in engineering a more wear-resistant rocket slipper for its high-speed test track. This research uses a design of experiments approach to systematically identify and evaluate potential slipper attributes that mitigate wear according to a heat transfer model. Final findings include recommendations of slipper materials that theoretically perform similar to or better than the baseline Vascomax®C300 maraging steel material. …
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Theses and Dissertations
The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …
Intercomparison Of Four Microphysics Schemes In Simulating Persistent Arctic Mixed-Phase Stratocumulus Clouds, Zachary A. Cleveland
Intercomparison Of Four Microphysics Schemes In Simulating Persistent Arctic Mixed-Phase Stratocumulus Clouds, Zachary A. Cleveland
Theses and Dissertations
Persistent Arctic mixed-phase stratocumulus clouds (AMPS) are important to the surface radiation budget of the Arctic. Their presence produces warming within the boundary layer and at the surface and inaccurately forecasting AMPS can lead to large, erroneous temperature forecasts. A Large Eddy Simulation of a case study of a persistent AMPS cloud was conducted using the Advanced Research Weather Research and Forecasting (WRF-ARW) model. The case examined occurred near Oliktok Point, AK between 26 and 27 April, 2017. The produced cloud pattern and properties of four different microphysics schemes -- P3, Thompson, Morrison, and WSM6 -- are compared to observations. …
A New Approach To Career Field Matching For Commissioning Air Force Cadets, Daniel Griffen Laird
A New Approach To Career Field Matching For Commissioning Air Force Cadets, Daniel Griffen Laird
Theses and Dissertations
The current method of assigning graduating cadets from the United States Air Force Academy and Reserve Officers' Training Corps (ROTC) detachments to their career fields uses an integer programming model to maximize \global" Air Force utility, subject to several Air Force-defined constraints. This utility evaluates the positive benefit of assigning a certain cadet to a certain career field. This paper discusses the issues with such a model, as well as presents a new, more refined approach to the problem. Rather than provide a one-size-fits-all formulation of this particular assignment problem, a Value-Focused Thinking (VFT) framework is applied, in conjunction with …
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Theses and Dissertations
Given the increased threat and proliferation of adversary military capabilities, this research seeks to develop reasonably accurate and computationally tractable models to optimally maneuver aircraft to intercept cruise missile attacks. The research leveraged mathematical programming to model the problem, informed by constraints representing a system of (temporal) difference equations. The research began by comparing six models having alternative representations of velocity and acceleration constraints while analyzing situations with stationary targets. The Multiple Aircraft, Multiple Stationary Target Engagement Problem with Box Constraint Bounds (MAMSTEP-BC) Model yielded superior overall performance and was further analyzed through alternative mathematical programming model enhancements to create …
Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas
Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas
Theses and Dissertations
Previous research investigating lightning warning radii about the Cape Canaveral space launch facilities have focused on reducing these radii from either 5 nautical miles (NM) to 4 NM or from 6 NM to 5 NM depending on the structures being protected. Some of these findings have suggested the possibility of both a seasonal difference (warm versus cold) and lightning detection events (cloud-to-ground lightning (CG) or total lightning (TL)) impacting these radii and associated risk levels. Utilizing the 2017-2020 data provided by the 45th Weather Squadron at Patrick Space Force Base via the Mesoscale Eastern Range Lightning Information System (MERLIN), this …
Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan
Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan
Theses and Dissertations
This research formulates and solves the multiagent routing problem with dynamic target arrivals (MRP-DTA), a stochastic system wherein a team of autonomous unmanned aerial vehicles (AUAVs) executes a strike coordination and reconnaissance (SCAR) mission against a notional adversary. Dynamic target arrivals that occur during the mission present the team of AUAVs with a sequential decision-making process which we model via a Markov Decision Process (MDP). To combat the curse of dimensionality, we construct and implement a hybrid approximate dynamic programming (ADP) algorithmic framework that employs a parametric cost function approximation (CFA) which augments a direct lookahead (DLA) model via a …
Deep Learning Techniques To Estimate 3d Position In Stereoscopic Imagery, Jonathan I. Nicholson
Deep Learning Techniques To Estimate 3d Position In Stereoscopic Imagery, Jonathan I. Nicholson
Theses and Dissertations
Current AAR efforts utilize machine vision algorithms to estimate the pose of a receiver aircraft. However, these algorithms are dependent on several conditions such as the availability of precise 3D aircraft models; the accuracy of the pipeline significantly degrades in the absence of high-quality information given beforehand. We propose a deep learning architecture that estimates the 3D position of an object based on stereoscopic imagery. We investigate the use of both machine learning techniques and neural networks to directly regress the 3D position of the receiver aircraft. We present a new position estimation framework that is based on the differences …
Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey
Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey
Theses and Dissertations
A challenging task in computer vision is finding techniques to improve the object detection and classification capabilities of ML models used for processing images acquired by moving aerial platforms. This research explores if GAN augmented UAV training sets can increase the generalizability of a detection model trained on said data. To answer this question, the YOLOv4-Tiny Object Detection Model was trained with aerial image training sets depicting rural environments. The salient objects within the frames were recreated using various GAN architectures, placed back into the original frames, and the augmented frames appended to the original training sets. GAN augmentation on …
Evaluation Of The Armas-Som Framework With Real Data, Brandon M. Blakely
Evaluation Of The Armas-Som Framework With Real Data, Brandon M. Blakely
Theses and Dissertations
The ARMAS framework was created with the goal of developing a framework for all-source sensors which is able to combine detection, identification, calibration, model selection, and independent evaluation into a single system. Stable Observability Monitoring (SOM), augments the original ARMAS framework by enabling ARMAS to detect whether or not its Fault Detection and Exclusion (FDE) capabilities can be trusted and when additional sensor information is required to maintain resiliency. While previously tested with simulated sensor data, SOM has yet to be tested with real-life sensor data. Furthermore, ARMAS has only been tested with real-life GNSS data. This work expands on …
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Theses and Dissertations
We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …
Emergency Logistics Stochastic Network Optimization With Prepositioning And Distribution Center Support, Christian Graves
Emergency Logistics Stochastic Network Optimization With Prepositioning And Distribution Center Support, Christian Graves
Theses and Dissertations
This study examines the Air Force Medical Service War Reserve Materiel supply chain management through the use of the supply chain optimization software anyLogistix. The goal is to illuminate potential improvements to policies that effect inventory management and test the effects of specific inputs, such as an influx of network support and capacity expansion, into the models. Network optimization shows the cost benefit analysis of these factors and if demand is satisfied through all demand points. Through three unique wartime scenarios, this study looks at the supply chain management of five prehospital analgesic medications: ketamine, morphine, fentanyl intravenous, fentanyl oral …
Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith
Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith
Theses and Dissertations
The growing surge of misinformation among COVID-19 communication can pose great hindrance to truth, magnify distrust in policy makers and/or degrade authorities’ credibility, and it can even harm public health. Classification of textual context on social media data relating to COVID-19 is an effective tool to combat misinformation on social media platforms. In this research, Twitter data was leveraged to 1) develop classification methods to detect misinformation and identify Tweet sentiment with respect to COVID-19 and 2) develop a human-in-the-loop interactive framework to enable identification of keywords associated with social context, here, being misinformation regarding COVID-19. 1) Six fusion-based classification …
Automated Aircraft Visual Inspection With Artificial Data Generation Enabled Deep Learning, Nathan J. Gaul
Automated Aircraft Visual Inspection With Artificial Data Generation Enabled Deep Learning, Nathan J. Gaul
Theses and Dissertations
Aircraft visual inspection, which is essential to daily maintenance of an aircraft, is expensive and time-consuming to perform. Augmenting trained maintenance technicians with automated UAVs to collect and analyze images for aircraft inspection is an active research topic and a potential application of CNNs. Training datasets for niche research topics such as aircraft visual inspection are small and challenging to produce, and the manual process of labeling these datasets often produces subjective annotations. Recently, researchers have produced several successful applications of artificially generated datasets with domain randomization for training CNNs for real-world computer vision problems. The research outlined herein builds …
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Theses and Dissertations
Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …
Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis
Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis
Theses and Dissertations
In 2007, the Office of the Assistant Secretary of Defense for Sustainment pushed for the need to transition to a Condition Based Maintenance Plus (CBM ) initiative for weapon systems in the U.S. Department of Defense. The CBM initiative can help increase aircraft availability (AA) for the United States Air Force. There are many reasons where AA can be affected but one such issue is engine availability primarily due to oil issues. Within the CBM perspective, this study examines the risk of a jet engine failure due to an oil issue and attempts to predict an engines time until next …
Indicators Of Political Instability In The Presence Of Rapid Urban And Youth Population Growth, Douglas W. Hubbard
Indicators Of Political Instability In The Presence Of Rapid Urban And Youth Population Growth, Douglas W. Hubbard
Theses and Dissertations
Large and rapidly growing cities and other urban agglomerations have the potential to become incubators of political instability. This is especially true of rapidly growing cities which are located in countries that are also experiencing high rates of growth in their youth population. Rapid growth rates put stress on urban infrastructure and other institutions, and these stresses can cause major problems for both city and national governments. Knowing when these cities and countries may be trending toward their tipping points regarding political instability will help governments and international organizations develop and implement effective strategies to mitigate the risk of instability.
Prioritizing Water Distribution Network Asset Maintenance Using Graph Theory Methods, Ashton E. Doyal
Prioritizing Water Distribution Network Asset Maintenance Using Graph Theory Methods, Ashton E. Doyal
Theses and Dissertations
Water distribution networks, like any other large infrastructure system, should be designed for reliability and resilience to resist failure. A literature review of graph theory methods pertaining to water distribution networks reveals a wide scope of mathematical and statistical measures that can be used to identify and classify many important features of a network. From this, an analysis using a combination of graph theory metrics and generated condition indices for the pipes is performed on the Tyndall drinking water system as a case study. The goal is to provide understanding to the risk of the current system and propose asset …
A Framework For Assessing Facility-Level Vulnerability And Risk To Extreme Weather Events, Blake A. Gawlik
A Framework For Assessing Facility-Level Vulnerability And Risk To Extreme Weather Events, Blake A. Gawlik
Theses and Dissertations
Intensifying extreme weather events, tied to the rise in the global average temperature, put global built infrastructure at risk. This presents a daunting challenge for organizational leaders who are tasked to determine how best to adapt current infrastructure to uncertain future events. To develop adaptation plans and policies, vulnerability and risk must be downscaled to an actionable scale, such that planners, designers, and engineers can make adaptation recommendations. However, previous research has largely assessed risk at coarser scales, e.g., regional, national, or global. These assessments are informative, but do not help those tasked to lead adaptation to make detailed, actionable …
Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminant Surrogate Particle From Military Uniform Fabric, George D. Cooksey
Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminant Surrogate Particle From Military Uniform Fabric, George D. Cooksey
Theses and Dissertations
During a mass casualty medical evacuation after a bioaerosol attack, a decontamination method is needed that is effective at both decontamination and preventing the secondary hazard of biological particles reaerosolizing from contaminated clothing. However, neither the efficacy of current decontamination methods nor the risk of biological particle reaerosolization is significantly explored in existing literature. The goals of this thesis were to develop a repeatable methodology to quantify the reaerosolization of a biological contaminate off Airman Battle Uniform (ABU) fabric swatches, and to test the efficacy of one decontamination method (high-volume, low-pressure water) using 1 mpolystyrene latex (PSL) spheres as a …
Analysis Of Cost And Schedule Estimation Trends For Major Defense Acquisition Programs, Sammantha J. Jones
Analysis Of Cost And Schedule Estimation Trends For Major Defense Acquisition Programs, Sammantha J. Jones
Theses and Dissertations
This study uses both descriptive and inferential techniques to investigate trends in cost and schedule estimates created by the Department of Defense for their Major Defense Acquisition Programs (MDAPs) throughout the last five decades. For schedule growth percentages, we did not identify any statistically significant trend regarding increasing or decreasing schedule changes or variances of schedule estimates throughout the five decades analyzed. Examining the overall cost growth of MDAPs, a statistically significant difference between the Cost Growth Factors (CGFs) calculated between the 1990s and the 2010s was found, with the 2010s exhibiting lower CGFs. A downward trend in the variances …
A Critical Review Of Climate Change On Coastal Infrastructure Systems, Gregory J. Howland Jr.
A Critical Review Of Climate Change On Coastal Infrastructure Systems, Gregory J. Howland Jr.
Theses and Dissertations
This thesis is a response to climate threats identified by DoD report on Climate Change in 2019. A critical review of climate change literature related to coastal infrastructure was conducted to synthesize past research and to inform future research. This review intends to inform how climate change may impact infrastructure systems, how those impacts are evaluated, can the investigation be improved, and what can stakeholders learn from the outcomes. The end goal is to find climate change mitigation strategies and adaptation measures, or identify the easiest path to get to that end. The compiled information will inform civilian and military …