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Articles 1 - 9 of 9
Full-Text Articles in Engineering
Beyond The High Ground: A Taxonomy For Earth-Moon System Operations, Adam P. Wilmer, Robert A. Bettinger
Beyond The High Ground: A Taxonomy For Earth-Moon System Operations, Adam P. Wilmer, Robert A. Bettinger
Faculty Publications
Situational and space domain awareness in the space domain can no longer be confined to that which is found in geosynchronous orbit. International activities—commercial and military—and threats to the planet itself exist and are increasing across the entire Earth-Moon system. This reality requires a new taxonomy to accurately classify space domain awareness missions and better apply resources to and development of the same. This work presents such a taxonomy for the classification of space domain awareness regions.
Reconciliation, Restoration And Reconstruction Of A Conflict Ridden Country, Muhammad S. Riaz
Reconciliation, Restoration And Reconstruction Of A Conflict Ridden Country, Muhammad S. Riaz
Theses and Dissertations
Conflict has sadly been a constant part of history. Winning a conflict and making a lasting peace are often not the same thing. While a peace treaty ends a conflict and often dictates terms from the winners’ perspective, it may not create a lasting peace. Short of unconditional surrender, modern conflict ends with a negotiated cessation of hostilities. Such accords may have some initial reconstruction agreements, but Reconciliation, Restoration and Reconstruction (RRR) is a long term process. This study maintains that to achieve a lasting peace: 1) The culture and beliefs of the conflict nation must be continuously considered and …
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Faculty Publications
Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …
Screening Heuristics For The Evaluation Of Covert Network Node Insertion Scenarios, Andrew E. Pekarek
Screening Heuristics For The Evaluation Of Covert Network Node Insertion Scenarios, Andrew E. Pekarek
Theses and Dissertations
The majority of research on covert networks uses social network analysis (SNA) to determine critical members of the network to either kill or capture for the purpose of network destabilization. This thesis takes the opposite approach and evaluates potential scenarios for inserting an agent into a covert network for information gathering purposes or future disruption operations. Due to the substantial number of potential insertion scenarios in a large network, this research proposes three screening heuristics that leverage SNA measures to reduce the solution space before applying a simple search heuristic.
Analysis Of The Perspective On Syrian Refugees By Neighboring Countries, Norma Ghanem
Analysis Of The Perspective On Syrian Refugees By Neighboring Countries, Norma Ghanem
Theses and Dissertations
Mass migration destabilizes neighboring states, opening the way for fragile state exploitation by enemies, including those that could undermine U.S. national interests. This study investigates an area of the Levant region, specifically countries neighboring Syria, and analyzes their perspective on Syrian refugees for the time frame of 1 June 2019 - 30 June 2020. This analysis may assist in forming policy and creating strategies to address refugee related issues, both domestic and international. There are three main questions addressed. The first inspects dominant refugee framing, the second explores sentiment (dis)similarity within each country and across countries, and the third investigates …
An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning, John C. O'Donnell
An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning, John C. O'Donnell
Theses and Dissertations
Officer retention in the Air Force has been researched many times in an attempt to better predict the personnel needs of the Air Force for the future. There has been previous work done in regards to specific AFSCs and how their retention compares to specific yet similar private sector jobs. This study considers different econometric time series statistics as a feature space and an average Air Force officer separation rate as the response variable for the multivariate time series analysis deep learning techniques. The econometric indicators used in this study are New Business Formations, New Durable Good Orders, and the …
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.
A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons
A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons
Faculty Publications
Sporadic-E (Es) occurrence rates from Global Position Satellite radio occultation (GPS-RO) measurements have shown to vary by a factor of five between studies, motivating the need for a comparison with ground-based measurements. In an attempt to find accurate GPS-RO techniques for detecting Es formation, occurrence rates derived using five previously developed GPS-RO techniques are compared to ionosonde measurements over an eight-year period from 2010–2017. GPS-RO measurements within 170 km of a ionosonde site are used to calculate Es occurrence rates and compared to the ground-truth ionosonde measurements. The techniques are compared individually for each ionosonde site …
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Faculty Publications
Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …