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Articles 1 - 30 of 39
Full-Text Articles in Physical Sciences and Mathematics
Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins
Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins
Faculty Publications
Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …
Improving Country Conflict And Peace Modeling: Datasets, Imputations, And Hierarchical Clustering, Benjamin D. Leiby
Improving Country Conflict And Peace Modeling: Datasets, Imputations, And Hierarchical Clustering, Benjamin D. Leiby
Theses and Dissertations
Many disparate datasets exist that provide country attributes covering political, economic, and social aspects. Unfortunately, this data often does not include all countries nor is the data complete for those countries included, as measured by the dataset’s missingness. This research addresses these dataset shortfalls in predicting country instability by considering country attributes in all aspects as well as in greater thresholds of missingness. First, a structured summary of past research is presented framed by a developed casual taxonomy and functional ontology. Additionally, a novel imputation technique for very large datasets is presented to account for moderate missingness in the expanded …
Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill
Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill
Faculty Publications
Purpose — This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of conflict. Design/methodology/approach — In this paper statistical learning methods are used to create new country clusters that are then used in a comparative analysis of model-based conflict prediction. Findings — In this study a reorganization of the countries assigned to specific areas of responsibility are shown to provide improvements in the ability of models to predict conflict. Research limitations/implications — The study is based on actual historical data and is purely data driven. …
Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam
Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam
Faculty Publications
Lack of instrument sensitivity to low electron density (Ne) concentration makes it difficult to measure sharp Ne vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region Ne from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the …
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 …
Cognition-Enhanced Machine Learning For Better Predictions With Limited Data, Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua W. Wood, Michael Krusmark, Tiffany Jastrzembski, Christopher W. Myers
Cognition-Enhanced Machine Learning For Better Predictions With Limited Data, Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua W. Wood, Michael Krusmark, Tiffany Jastrzembski, Christopher W. Myers
Faculty Publications
The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields’ methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based on learning histories are central to developing effective, personalized learning tools. Here, we show how a state-of-the-art ML model can …
Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco [*], Torrey J. Wagner, Brent T. Langhals
Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco [*], Torrey J. Wagner, Brent T. Langhals
Faculty Publications
Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wavelength bands available in Landsat 8 imagery. The methods classify each pixel into 4 different classes: clear, cloud shadow, light cloud, or cloud. The first method is based on a fully connected neural network with ten input neurons, two hidden layers of 8 and 10 neurons respectively, and a single-neuron output for each class. This type of model is considered with and without L2 regularization applied to the kernel weighting. The final model type is a random forest classifier created from an ensemble of …
A Quantitative Argument For Autonomous Aerial Defense Overembedded Missile Systems To Thwart Cruise Threats, Andrew R. Davis
A Quantitative Argument For Autonomous Aerial Defense Overembedded Missile Systems To Thwart Cruise Threats, Andrew R. Davis
Theses and Dissertations
Given the high cost of missile defense systems, their ability to be overwhelmed, and rising tensions between the U.S. and adversaries in the Indo-Pacific region, a new modeled is proposed to investigate a new approach to missile defense. The Autonomous Aerial Defense Against Missiles (AADAM) system leverages reusable, small-scale UAVs to propose a cheaper, more effective system in defending against cruise missile threats. The aim of this system is to provide and additional layer in current missile defense strategies at lower-cost. This modeled system is found to outperform a modeled Patriot system in close-range interception of designated assets, with no …
Year-Independent Prediction Of Food Insecurity Using Classical & Neural Network Machine Learning Methods, Caleb Christiansen, Torrey J. Wagner, Brent Langhals
Year-Independent Prediction Of Food Insecurity Using Classical & Neural Network Machine Learning Methods, Caleb Christiansen, Torrey J. Wagner, Brent Langhals
Faculty Publications
Current food crisis predictions are developed by the Famine Early Warning System Network, but they fail to classify the majority of food crisis outbreaks with model metrics of recall (0.23), precision (0.42), and f1 (0.30). In this work, using a World Bank dataset, classical and neural network (NN) machine learning algorithms were developed to predict food crises in 21 countries. The best classical logistic regression algorithm achieved a high level of significance (p < 0.001) and precision (0.75) but was deficient in recall (0.20) and f1 (0.32). Of particular interest, the classical algorithm indicated that the vegetation index and the food price index were both positively correlated with food crises. A novel method for performing an iterative multidimensional hyperparameter search is presented, which resulted in significantly improved performance when applied to this dataset. Four iterations were conducted, which resulted in excellent 0.96 for metrics of precision, recall, and f1. Due to this strong performance, the food crisis year was removed from the dataset to prevent immediate extrapolation when used on future data, and the modeling process was repeated. The best “no year” model metrics remained strong, achieving ≥0.92 for recall, precision, and f1 while meeting a 10% f1 overfitting threshold on the test (0.84) and holdout (0.83) datasets. The year-agnostic neural network model represents a novel approach to classify food crises and outperforms current food crisis prediction efforts.
The Traded Water Footprint Of Global Energy From 2010 To 2018, Christopher M. Chini, Rebecca A. M. Peer
The Traded Water Footprint Of Global Energy From 2010 To 2018, Christopher M. Chini, Rebecca A. M. Peer
Faculty Publications
The energy-water nexus describes the requirement of water-for-energy and energy-for-water. The consumption of water in the production and generation of energy resources is also deemed virtual water. Pairing the virtual water estimates for energy with international trade data creates a virtual water trade network, facilitating analysis of global water resources management. In this database, we identify the virtual water footprints for the trade of eleven different energy commodities including fossil fuels, biomass, and electricity. Additionally, we provide the necessary scripts for downloading and pairing trade data with the virtual water footprints to create a virtual water trade network. The resulting …
A Review Of Energy-For-Water Data In Energy-Water Nexus Publications, Christopher M. Chini, Lauren E. Excell, Ashlynn S. Stillwell
A Review Of Energy-For-Water Data In Energy-Water Nexus Publications, Christopher M. Chini, Lauren E. Excell, Ashlynn S. Stillwell
Faculty Publications
Published literature on the energy-water nexus continues to increase, yet much of the supporting data, particularly regarding energy-for-water, remains obscure or inaccessible. We perform a systematic review of literature that describes the primary energy and electricity demands for drinking water and wastewater systems in urban environments. This review provides an analysis of the underlying data and other properties of over 170 published studies by systematically creating metadata on each study. Over 45% of the evaluated studies utilized primary data sources (data collected directly from utilities), potentially enabling large-scale data sharing and a more comprehensive understanding of global water-related energy demand. …
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
Faculty Publications
Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …
Mult-Spectral Imaging Of Vegetation With A Diffractive Plenoptic Camera, Tristan R. Naranjo
Mult-Spectral Imaging Of Vegetation With A Diffractive Plenoptic Camera, Tristan R. Naranjo
Theses and Dissertations
Snapshot multi-spectral sensors allow for object detection based on its spectrum for remote sensing applications in air or space. By making these types of sensors more compact and lightweight, it allows drones to dwell longer on targets or the reduction of transport costs for satellites. To address this need, I designed and built a diffractive plenoptic camera (DPC) which utilized a Fresnel zone plate and a light field camera in order to detect vegetation via a normalized difference vegetation index (NDVI). This thesis derives design equations by relating DPC system parameters to its expected performance and evaluates its multi-spectral performance. …
An Imputation Approach To Developing Alternative Futures Of Country Conflict, Zachary J. Kane
An Imputation Approach To Developing Alternative Futures Of Country Conflict, Zachary J. Kane
Theses and Dissertations
Understanding what causes countries to be in a state of violent conflict is of vital importance to developing realistic national strategies on both a regional and global scale. Given these causes, it is important to understand the effects of missing data, how to impute that data, and the interrelation between data elements. Utilizing both open source data and previously generated equations that predict a country’s likelihood to transition conflict statuses, this research projects data into the future and predicts each nations’ subsequent conflict statuses. Future data is populated using a novel approach inspired by stochastic regression imputation. The replicated future …
Forecasting Country Conflict Within Modified Combatant Command Regions Using Statistical Learning Methods, Sarah Neumann
Forecasting Country Conflict Within Modified Combatant Command Regions Using Statistical Learning Methods, Sarah Neumann
Theses and Dissertations
Conflict forecasts are crucial to Combatant Commanders’ understanding of the dynamic environment encompassing countries within their area of responsibility. The current structure of the Combatant Commands (COCOMs) is rooted in geography by grouping nations in geographic proximity to the same regional command. However, leaders today question the effectiveness of the current structure. A novel modified k-means clustering algorithm is developed and implemented that groups countries based on data similarities and geographic proximity resulting in new COCOM groupings that improve conflict forecasts. The data spans various political, military, economic, and social characteristics of countries, and is used to develop conditional logistic …
Stereoscopic 3-D Presentation For Air Traffic Control Digital Radar Displays, Jason G. Russi, Brent T. Langhals, Michael E. Miller, Eric L. Heft
Stereoscopic 3-D Presentation For Air Traffic Control Digital Radar Displays, Jason G. Russi, Brent T. Langhals, Michael E. Miller, Eric L. Heft
AFIT Patents
An apparatus and method of presenting air traffic data to an air traffic controller are provided. Air traffic data including a two dimensional spatial location and altitude for a plurality of aircraft is received. A disparity value is determined based on the altitude for each aircraft of the plurality of aircraft. Left and right eye images are generated of the plurality of aircraft where at least one of the left and right eye images is based on the determined disparity value. The left and right eye images are simultaneously displayed to the air traffic controller on a display. The simultaneously …
A Statistical Approach To Characterize And Detect Degradation Within The Barabasi-Albert Network, Mohd-Fairul Mohd-Zaid
A Statistical Approach To Characterize And Detect Degradation Within The Barabasi-Albert Network, Mohd-Fairul Mohd-Zaid
Theses and Dissertations
Social Network Analysis (SNA) is widely used by the intelligence community when analyzing the relationships between individuals within groups of interest. Hence, any tools that can be quantitatively shown to help improve the analyses are advantageous for the intelligence community. To date, there have been no methods developed to characterize a real world network as a Barabasi-Albert network which is a type of network with properties contained in many real-world networks. In this research, two newly developed statistical tests using the degree distribution and the L-moments of the degree distribution are proposed with application to classifying networks and detecting degradation …
A Logistic Regression And Markov Chain Model For The Prediction Of Nation-State Violent Conflicts And Transitions, Nicholas Shallcross
A Logistic Regression And Markov Chain Model For The Prediction Of Nation-State Violent Conflicts And Transitions, Nicholas Shallcross
Theses and Dissertations
Using open source data, this research formulates and constructs a suite of statistical models that predict future transitions into and out of violent conflict and forecasts the regional and global incidences of violent conflict over a ten-year time horizon. A total of thirty predictor variables are tested and evaluated for inclusion in twelve conditional logistic regression models, which calculate the probability that a nation will transition from its current conflict state, either In Conflict or Not in Conflict, to a new state in the following year. These probabilities are then used to construct a series of nation-specific Markov chain models …
Situational Awareness/Triage Tool For Use In A Chemical, Biological, Radiological Nuclear Explosive (Cbrne) Environment, John N. Scarlett, Heather L. Gallup, David A. Smith
Situational Awareness/Triage Tool For Use In A Chemical, Biological, Radiological Nuclear Explosive (Cbrne) Environment, John N. Scarlett, Heather L. Gallup, David A. Smith
AFIT Patents
A method of managing patient care and emergency response following a Chemical, Biological, Radiological, or Nuclear Explosive (CBRNE) attack and maintaining compliance with the Health Insurance Portability and Accountability Act (HIPAA). The method including identifying each patient with a unique patient identifier, the identifier based upon the geospatial location of the patient, the geospatial location including at least the latitude and longitude of the patient when first treated, the unique patient identifier being part of patient data. Providing a collection point of patient data to form a patient data database where in the patient location data may be used to …
Combating Biological Terrorism From Imported Food, Jeffrey S. Nelson
Combating Biological Terrorism From Imported Food, Jeffrey S. Nelson
Theses and Dissertations
There is a threat that a terrorist or terrorist organization will use access to the US food supply to kill or sicken Americans by contaminating imported food products from Mexico. The food that Americans eat is coming more and more often from foreign countries such as Mexico. Foodborne diseases infect nearly fifty million people in the US each year, resulting in over three thousand deaths. There are many terrorist organizations that would like to deliberately contaminate American food. Drug cartels and terrorist organizations currently operate in Mexico, one of the leading food importers into the US. The purpose of this …
Exploitation Of Geographic Information Systems For Vehicular Destination Prediction, Richard T. Muster
Exploitation Of Geographic Information Systems For Vehicular Destination Prediction, Richard T. Muster
Theses and Dissertations
Much of the recent successes in the Iraqi theater have been achieved with the aid of technology so advanced that celebrated journalist Bob Woodward recently compared it to the Manhattan Project of WWII. Intelligence, Surveillance, and Reconnaissance (ISR) platforms have emerged as the rising star of Air Force operational capabilities as they are enablers in the quest to track and disrupt terrorist and insurgent forces. This thesis argues that ISR systems have been severely under-exploited. The proposals herein seek to improve the machine-human interface of current ISR systems such that a predictive battle-space awareness may be achieved, leading to shorter …
Characterizing And Detecting Unrevealed Elements Of Network Systems, James A. Leinart
Characterizing And Detecting Unrevealed Elements Of Network Systems, James A. Leinart
Theses and Dissertations
This dissertation addresses the problem of discovering and characterizing unknown elements in network systems. Klir (1985) provides a general definition of a system as “... a set of some things and a relation among the things" (p. 4). A system, where the `things', i.e. nodes, are related through links is a network system (Klir, 1985). The nodes can represent a range of entities such as machines or people (Pearl, 2001; Wasserman & Faust, 1994). Likewise, links can represent abstract relationships such as causal influence or more visible ties such as roads (Pearl, 1988, pp. 50-51; Wasserman & Faust, 1994; Winston, …
Satellite-Based Fusion Of Image/Inertial Sensors For Precise Geolocation, Neil R. Jesse
Satellite-Based Fusion Of Image/Inertial Sensors For Precise Geolocation, Neil R. Jesse
Theses and Dissertations
The ability to produce high-resolution images of the Earth’s surface from space has flourished in recent years with the continuous development and improvement of satellite-based imaging sensors. Earth-imaging satellites often rely on complex onboard navigation systems, with dependence on Global Positioning System (GPS) tracking and/or continuous post-capture georegistration, to accurately geolocate ground targets of interest to either commercial and military customers. Consequently, these satellite systems are often massive, expensive, and susceptible to poor or unavailable target tracking capabilities in GPS-denied environments. Previous research has demonstrated that a tightly-coupled image-aided inertial navigation system (INS), using existing onboard imaging sensors, can provide …
Internet Protocol Geolocation: Development Of A Delay-Based Hybrid Methodology For Locating The Geographic Location Of A Network Node, John M. Roehl
Internet Protocol Geolocation: Development Of A Delay-Based Hybrid Methodology For Locating The Geographic Location Of A Network Node, John M. Roehl
Theses and Dissertations
Internet Protocol Geolocation (IP Geolocation), the process of determining the approximate geographic location of an IP addressable node, has proven useful in a wide variety of commercial applications. Commercial applications of IP Geolocation include market research, redirection for performance enhancement, restricting content, and combating fraud. The potential for military applications include securing remote access via geographic authentication, intelligence collection, and cyber attack attribution. IP Geolocation methods can be divided into three basic categories based upon what information is used to determine the geographic location of the given IP address: 1) Information contained in databases, 2) information that is leaked during …
Geospatial Informational Security Risks And Concerns Of The U.S. Air Force Geobase Program, Scott A. Bryant
Geospatial Informational Security Risks And Concerns Of The U.S. Air Force Geobase Program, Scott A. Bryant
Theses and Dissertations
Technological advancements such as Geospatial Information Systems (GIS) and the Internet have made it easier and affordable to share information, which enables complex and time sensitive decisions to be made with higher confidence. Further, advancements in information technology have dramatically increased the ability to store, manage, integrate, and correlate larger amounts of data to improve operational efficiency. However, the same technologies that enable increased productivity also provide increased capabilities to those wishing to do harm. Today’s military leaders are faced with the challenge of deciding how to make geospatial information collected on military installations and organizations available to authorized communities …
Classifying Failing States, Nathan E. Nysether
Classifying Failing States, Nathan E. Nysether
Theses and Dissertations
The US is heavily involved in the first major war of the 21st Century -- The Global War on Terror (GWOT). As with any militant group, the foundation of the enemy's force is their people. There are two primary strategies for defeating the terrorists and achieving victory in the GWOT. First, we must root out terrorists where they live, train, plan, and recruit and attack them militarily. Second, we must suffocate them by cutting off the supply of new soldiers willing to choose aggression or even death over their current life. This thesis helps to achieve these objectives by applying …
Theory Of Effectiveness Measurement, Richard K. Bullock
Theory Of Effectiveness Measurement, Richard K. Bullock
Theses and Dissertations
Effectiveness measures provide decision makers feedback on the impact of deliberate actions and affect critical issues such as allocation of scarce resources, as well as whether to maintain or change existing strategy. Currently, however, there is no formal foundation for formulating effectiveness measures. This research presents a new framework for effectiveness measurement from both a theoretical and practical view. First, accepted effects-based principles, as well as fundamental measurement concepts are combined into a general, domain independent, effectiveness measurement methodology. This is accomplished by defining effectiveness measurement as the difference, or conceptual distance from a given system state to some reference …
A Multidiscipline Approach To Mitigating The Insider Threat, Jonathan W. Butts, Robert F. Mills, Gilbert L. Peterson
A Multidiscipline Approach To Mitigating The Insider Threat, Jonathan W. Butts, Robert F. Mills, Gilbert L. Peterson
Faculty Publications
Preventing and detecting the malicious insider is an inherently difficult problem that expands across many areas of expertise such as social, behavioral and technical disciplines. Unfortunately, current methodologies to combat the insider threat have had limited success primarily because techniques have focused on these areas in isolation. The technology community is searching for technical solutions such as anomaly detection systems, data mining and honeypots. The law enforcement and counterintelligence communities, however, have tended to focus on human behavioral characteristics to identify suspicious activities. These independent methods have limited effectiveness because of the unique dynamics associated with the insider threat. The …
Comparative Analysis Of Biosurveillance Methodologies, David M. Kempisty
Comparative Analysis Of Biosurveillance Methodologies, David M. Kempisty
Theses and Dissertations
The purpose of this research is to compare two different biosurveillance methodologies: BioWatch and "A Hot Idea". BioWatch is fielded and operating in major US cities today. Air samples are collected on filter paper and analyzed for the presence of harmful biological agents. "A Hot Idea" is an evolving methodology using the human body's immune response to identify the onset of infection from a harmful pathogen. Detecting a temperature increase, using infrared thermographers, in a statistically significant portion of population would allow earlier identification of a biological release, accelerating initiation of response actions. A selected population including policemen, firemen, and …