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Articles 61 - 90 of 181
Full-Text Articles in Statistics and Probability
Cocyclic Hadamard Matrices: An Efficient Search Based Algorithm, Jonathan S. Turner
Cocyclic Hadamard Matrices: An Efficient Search Based Algorithm, Jonathan S. Turner
Theses and Dissertations
This dissertation serves as the culmination of three papers. “Counting the decimation classes of binary vectors with relatively prime fixed-density" presents the first non-exhaustive decimation class counting algorithm. “A Novel Approach to Relatively Prime Fixed Density Bracelet Generation in Constant Amortized Time" presents a novel lexicon for binary vectors based upon the Discrete Fourier Transform, and develops a bracelet generation method based upon the same. “A Novel Legendre Pair Generation Algorithm" expands upon the bracelet generation algorithm and includes additional constraints imposed by Legendre Pairs. It further presents an efficient sorting and comparison algorithm based upon symmetric functions, as well …
Ergodicity For The 3d Stochastic Navier-Stokes Equations Perturbed By Lévy Noise, Manil T. Mohan, K. Sakthivel, Sivaguru S. Sritharan
Ergodicity For The 3d Stochastic Navier-Stokes Equations Perturbed By Lévy Noise, Manil T. Mohan, K. Sakthivel, Sivaguru S. Sritharan
Faculty Publications
In this work we construct a Markov family of martingale solutions for 3D stochastic Navier–Stokes equations (SNSE) perturbed by Lévy noise with periodic boundary conditions. Using the Kolmogorov equations of integrodifferential type associated with the SNSE perturbed by Lévy noise, we construct a transition semigroup and establish the existence of a unique invariant measure. We also show that it is ergodic and strongly mixing.
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Toxoplasma Gondii Igg Associations With Sleepwake Problems, Sleep Duration And Timing, Celine C. Corona, Ma Zhang, Abhishek Wadhawan, Melanie L. Daue, Maureen W. Groer, Aline Dagang, Christopher A. Lowry, Kathleen A. Ryan, Andrew J. Hoisington, John W. Stiller, Dietmar Fuchs, Braxton D. Mitchell, Teodor T. Postolache
Toxoplasma Gondii Igg Associations With Sleepwake Problems, Sleep Duration And Timing, Celine C. Corona, Ma Zhang, Abhishek Wadhawan, Melanie L. Daue, Maureen W. Groer, Aline Dagang, Christopher A. Lowry, Kathleen A. Ryan, Andrew J. Hoisington, John W. Stiller, Dietmar Fuchs, Braxton D. Mitchell, Teodor T. Postolache
Faculty Publications
Background: Evidence links Toxoplasma gondii (T. gondii), a neurotropic parasite, with schizophrenia, mood disorders and suicidal behavior, all of which are associated and exacerbated by disrupted sleep. Moreover, low-grade immune activation and dopaminergic overstimulation, which are consequences of T. gondii infection, could alter sleep patterns and duration. Methods: Sleep data on 833 Amish participants [mean age (SD) = 44.28 (16.99) years; 59.06% women] were obtained via self-reported questionnaires that assessed sleep problems, duration and timing. T. gondii IgG was measured with ELISA. Data were analyzed using multivariable logistic regressions and linear mixed models, with adjustment for age, sex and family …
Improved N-Dimensional Data Visualization From Hyper-Radial Values, Todd J. Paciencia, Trevor J. Bihl, Kenneth W. Bauer
Improved N-Dimensional Data Visualization From Hyper-Radial Values, Todd J. Paciencia, Trevor J. Bihl, Kenneth W. Bauer
Faculty Publications
Higher-dimensional data, which is becoming common in many disciplines due to big data problems, are inherently difficult to visualize in a meaningful way. While many visualization methods exist, they are often difficult to interpret, involve multiple plots and overlaid points, or require simultaneous interpretations. This research adapts and extends hyper-radial visualization, a technique used to visualize Pareto fronts in multi-objective optimizations, to become an n-dimensional visualization tool. Hyper-radial visualization is seen to offer many advantages by presenting a low-dimensionality representation of data through easily understood calculations. First, hyper-radial visualization is extended for use with general multivariate data. Second, a method …
The Impact Of Changing Requirements, James C. Ellis
The Impact Of Changing Requirements, James C. Ellis
Theses and Dissertations
The fundamental purpose of an Engineering Change Proposal (ECP) is to change the requirements of a contract. To build in flexibility, the acquisition practice is to estimate a dollar value to hold in reserve after the contract is awarded. There appears to be no empirical-based method for estimating this ECP withhold in the literature. Using the Cost Assessment Data Enterprise (CADE) database, 533 contracts were randomly selected to build two regression models: one to predict the likelihood of a contract experiencing an ECP, and the other to determine the expected median percent increase in baseline contract cost if an ECP …
Satellite Communications In The V And W Band: Tropospheric Effects, Bertus A. Shelters
Satellite Communications In The V And W Band: Tropospheric Effects, Bertus A. Shelters
Theses and Dissertations
An investigation into the use of Weather Cubes compiled by the atmospheric characterization package, Laser Environmental Effects Definition and Reference (LEEDR), to develop accurate, long-term attenuation statistics for link-budget analysis is presented. A Weather Cube is a three-dimensional mesh of numerical weather prediction (NWP) data plus LEEDR calculations that allows for the quantification of rain, cloud, aerosol, and molecular effects at any UV to RF wavelength on any path contained within the cube. The development of this methodology is motivated by the potential use of V (40-75 GHz) and W (75-110 GHz) band frequencies for the satellite communication application, as …
Analysis Of A Voting Method For Ranking Network Centrality Measures On A Node-Aligned Multiplex Network, Kyle S. Wilkinson
Analysis Of A Voting Method For Ranking Network Centrality Measures On A Node-Aligned Multiplex Network, Kyle S. Wilkinson
Theses and Dissertations
Identifying relevant actors using information gleaned from multiple networks is a key goal within the context of human aspects of military operations. The application of a voting theory methodology for determining nodes of critical importance—in ranked order of importance—for a node-aligned multiplex network is demonstrated. Both statistical and qualitative analyses on the differences of ranking outcomes under this methodology is provided. As a corollary, a multilayer network reduction algorithm is investigated within the context of the proposed ranking methodology. The application of the methodology detailed in this thesis will allow meaningful rankings of relevant actors to be produced on a …
Characterization Of Ambient Noise, Rachel C. Ramirez
Characterization Of Ambient Noise, Rachel C. Ramirez
Theses and Dissertations
An Air Force sponsor is interested in improving an acoustic detection model by providing better estimates on how to characterize the background noise of various environments. This would inform decision makers on the probability of acoustic detection of different systems of interest given different levels of noise. Data mining and statistical learning techniques are applied to a National Park Service acoustic summary data set to find overall trends over varying environments. Linear regression, conditional inference trees, and random forest techniques are discussed. Findings indicate only sixteen geospatial variables at different resolutions are necessary to characterize the first ten ⅓ octave …
Modeling Multimodal Failure Effects Of Complex Systems Using Polyweibull Distribution, Daniel A. Timme
Modeling Multimodal Failure Effects Of Complex Systems Using Polyweibull Distribution, Daniel A. Timme
Theses and Dissertations
The Department of Defense (DoD) enlists multiple complex systems across each of their departments. Between the aging systems going through an overhaul and emerging new systems, quality assurance to complete the mission and secure the nation‘s objectives is an absolute necessity. The U.S. Air Force‘s increased interest in Remotely Piloted Aircraft (RPA) and the Space Warfighting domain are current examples of complex systems that must maintain high reliability and sustainability in order to complete missions moving forward. DoD systems continue to grow in complexity with an increasing number of components and parts in more complex arrangements. Bathtub-shaped hazard functions arise …
Looking Past The Spark To Find The Fuel Of The Arab Spring Fire, Luke M. Brantley
Looking Past The Spark To Find The Fuel Of The Arab Spring Fire, Luke M. Brantley
Theses and Dissertations
The field of statistical conflict prediction addresses region-wide analysis in eras of stable conflict and peace. This study improves upon those prediction rates in times of volatile conflict and peace seen during the Arab Spring of 2011 to 2015. During this time, higher rates of conflict transition in certain Middle Eastern and North African countries occurred than normally observed in previous studies. Due to the fact that previous prediction models decrease in accuracy during times of volatile conflict transition and since the proper strategy for handling the Arab Spring has been highly debated, this study considers alterations to previous studies …
They're Only Nuclear Weapons: An Exploratory Analysis Of Safety Climate Within The Nuclear Enterprise, Brandon M. Clements
They're Only Nuclear Weapons: An Exploratory Analysis Of Safety Climate Within The Nuclear Enterprise, Brandon M. Clements
Theses and Dissertations
By possessing nuclear weapons, the United States Air Force is inherently exposed to extreme safety concerns. With multiple setbacks in recent years (e.g., unauthorized transport of nuclear weapons, cheating scandals, and career dissatisfaction), some have begun to wonder how safe the nuclear enterprise truly is. Building upon the concept of safety climate, this study explores safety climate constructs and trends associated with current nuclear maintenance safety climate survey data.
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 …
Monte Carlo Simulations Of Three-Dimensional Electromagnetic Gaussian Schell-Model Sources, Milo W. Hyde Iv, Santasri Bose-Pillai, Olga Korotkova
Monte Carlo Simulations Of Three-Dimensional Electromagnetic Gaussian Schell-Model Sources, Milo W. Hyde Iv, Santasri Bose-Pillai, Olga Korotkova
Faculty Publications
This article presents a method to simulate a three-dimensional (3D) electromagnetic Gaussian-Schell model (EGSM) source with desired characteristics. Using the complex screen method, originally developed for the synthesis of two-dimensional stochastic electromagnetic fields, a set of equations is derived which relate the desired 3D source characteristics to those of the statistics of the random complex screen. From these equations and the 3D EGSM source realizability conditions, a single criterion is derived, which when satisfied guarantees both the realizability and simulatability of the desired 3D EGSM source. Lastly, a 3D EGSM source, with specified properties, is simulated; the Monte Carlo simulation …
Unmasking Cost Growth Behavior: A Longitudinal Study, Cory N. D'Amico, Edward D. White, Jonathan D. Ritschel, Scott R. Kozlak
Unmasking Cost Growth Behavior: A Longitudinal Study, Cory N. D'Amico, Edward D. White, Jonathan D. Ritschel, Scott R. Kozlak
Faculty Publications
This article examines how cost growth factors (CGF) change over a program’s acquisition life cycle for 36 Department of Defense aircraft programs. Starting from Milestone B, the authors examine CGFs at five gateways: Critical Design Review, First Flight (FF), the end of Developmental Test and Evaluation (DT&E), Initial Operational Capability, and Full Operational Capability. Each CGF is assigned a color rating based upon the program’s cost growth: Green (low), Amber (moderate), or Red (high). Significant findings include dependencies among similar CGF color ratings and cost growth occurring primarily between FF and the end of DT&E during a program’s life cycle.
Anomalydetection: Implementation Of Augmented Network Log Anomaly Detection Procedures, Robert J. Gutierrez, Bradley C. Boehmke, Kenneth W. Bauer, Cade M. Saie, Trevor J. Bihl
Anomalydetection: Implementation Of Augmented Network Log Anomaly Detection Procedures, Robert J. Gutierrez, Bradley C. Boehmke, Kenneth W. Bauer, Cade M. Saie, Trevor J. Bihl
Faculty Publications
As the number of cyber-attacks continues to grow on a daily basis, so does the delay in threat detection. For instance, in 2015, the Office of Personnel Management discovered that approximately 21.5 million individual records of Federal employees and contractors had been stolen. On average, the time between an attack and its discovery is more than 200 days. In the case of the OPM breach, the attack had been going on for almost a year. Currently, cyber analysts inspect numerous potential incidents on a daily basis, but have neither the time nor the resources available to perform such a task. …
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 …
Wartime Construction Project Outcomes As A Function Of Contract Type, Ryan M. Hoff, Gregory D. Hammond, Peter P. Feng, Edward D. White
Wartime Construction Project Outcomes As A Function Of Contract Type, Ryan M. Hoff, Gregory D. Hammond, Peter P. Feng, Edward D. White
Faculty Publications
The United States has spent more than $23 billion on construction in Afghanistan since 2001. The dynamic security situation created substantial project uncertainty, and many construction projects used cost-plus-fixed-fee contracts (CPFF) instead of the firm-fixed-price (FFP) norm. Using a dataset of 25 wartime construction projects managed by the Air Force Civil Engineer Center, the authors sought to confirm that both contract types yield project outcomes consistent with the established literature. As expected, they found CPFF contracts had greater cost and schedule growth than FFP. However, they did not find differences regarding as-built quality. Additionally, the authors sought to determine whether …
Unequal A Priori Probability Multiple Hypothesis Testing In Space Domain Awareness With The Space Surveillance Telescope, Tyler J. Hardy, Stephen C. Cain, Travis F. Blake
Unequal A Priori Probability Multiple Hypothesis Testing In Space Domain Awareness With The Space Surveillance Telescope, Tyler J. Hardy, Stephen C. Cain, Travis F. Blake
Faculty Publications
This paper investigates the ability to improve Space Domain Awareness (SDA) by increasing the number of detectable Resident Space Objects (RSOs) from space surveillance sensors. With matched filter based techniques, the expected impulse response, or Point Spread Function (PSF), is compared against the received data. In the situation where the images are spatially undersampled, the modeled PSF may not match the received data if the RSO does not fall in the center of the pixel. This aliasing can be accounted for with a Multiple Hypothesis Test (MHT). Previously, proposed MHTs have implemented a test with an equal a priori prior …
Method For Determining Time-Resolved Heat Transfer Coefficient And Adiabatic Effectiveness Waveforms With Unsteady Film Cooling, James L. Rutledge, Jonathan F. Mccall
Method For Determining Time-Resolved Heat Transfer Coefficient And Adiabatic Effectiveness Waveforms With Unsteady Film Cooling, James L. Rutledge, Jonathan F. Mccall
AFIT Patents
A new method for determining heat transfer coefficient (h) and adiabatic effectiveness (η) waveforms h(t) and η(t) from a single test uses a novel inverse heat transfer methodology to use surface temperature histories obtained using prior art approaches to approximate the h(t) and η(t) waveforms. The method best curve fits the data to a pair of truncated Fourier series.
Analysis And Modeling Of U.S. Army Recruiting Markets, Joshua L. Mcdonald
Analysis And Modeling Of U.S. Army Recruiting Markets, Joshua L. Mcdonald
Theses and Dissertations
The United States Army Recruiting Command (USAREC) is charged with finding, engaging, and ultimately enlisting young Americans for service as Soldiers in the U.S. Army. USAREC must decide how to allocate monthly enlistment goals, by aptitude and education level, across its 38 subordinate recruiting battalions in order to maximize the number of enlistment contracts produced each year. In our research, we model the production of enlistment contracts as a function of recruiting supply and demand factors which vary over the recruiting battalion areas of responsibility. Using county-level data for the period of recruiting year RY2010 through RY2013 mapped to recruiting …
Clustering Theory And Data Driven Health Care Strategies, Takayuki Iguchi
Clustering Theory And Data Driven Health Care Strategies, Takayuki Iguchi
Theses and Dissertations
DoD health care requires reform with growing costs causing concerns of decreased military capability. One proposed radical strategy to fix current health care delivery systems is to organize medical teams around patients with similar treatment requirements. This is a clustering problem; how do you partition the set of patients so that each group has similar treatment needs? We provide advances in clustering theory relevant to this new health care strategy. In particular, we create fast certifiably optimal k-means clustering using what is known as Probably Certifiably Correct (PCC) algorithms which achieves state-of-the-art performance under certain models. Inspired by the health …
Application Of Non-Rated Line Officer Attrition Levels And Career Field Stability, Christine L. Zens
Application Of Non-Rated Line Officer Attrition Levels And Career Field Stability, Christine L. Zens
Theses and Dissertations
The Air Force monitors the strength of its active duty officer force and attempts to achieve the difficult challenge of employing a diversity of talent among career specialties and experience levels. This study completes two objectives, predicting future manning levels for 23 career fields, and providing a statistical framework to assess the stability of these fields. The first part of the study applies regression and survival analysis to subpopulations within the active duty Air Force officer corps, and then aggregates them by year to forecast future personnel levels. Four career fields are considered, including Acquisitions (ACQ), Logistics (LOG), Support (SPT), …
Determining The Optimal Work Breakdown Structure For Government Acquisition Contracts, Brian J. Fitzpatrick
Determining The Optimal Work Breakdown Structure For Government Acquisition Contracts, Brian J. Fitzpatrick
Theses and Dissertations
The optimal level of Government Contract Work Breakdown Structure (G-CWBS) reporting for the purposes of Earned Value Management was inspected. The G-Score Metric was proposed, which can quantitatively grade a G-CWBS, based on a new method of calculating an Estimate At Completion (EAC) cost for each reported element. A random program generator created in R replicated the characteristics of DOD program artifacts retrieved from the Cost Analysis Data Enterprise (CADE) system. The generated artifacts were validated as a population, however validation at the demographic combination level using an artificial neural network was inconclusive. Comparative WBS forms were created for a …
Predicting Schedule Duration For Defense Acquisition Programs: Program Initiation To Initial Operational Capability, Christopher A. Jimenez
Predicting Schedule Duration For Defense Acquisition Programs: Program Initiation To Initial Operational Capability, Christopher A. Jimenez
Theses and Dissertations
Accurately predicting the most realistic schedule for a defense acquisitions program is an extremely difficult task considering the inherent risk and uncertainties present in the early stages of a program. We use a multiple regression analysis to predict schedule duration in a defense acquisition program. The prediction scope of our research is limited to predicting schedule duration from program initiation to initial operation capability (IOC).We use the data from 56 programs across all services, which was acquired from a SAR database created by RAND. We were able to achieve an R2 of 0.429 and an Adjusted R2 of 0.384 in …
A Recommendation System For Meta-Modeling: A Meta-Learning Based Approach, Can Cui, Mengqi Hu, Jeffery D. Weir, Teresa Wu
A Recommendation System For Meta-Modeling: A Meta-Learning Based Approach, Can Cui, Mengqi Hu, Jeffery D. Weir, Teresa Wu
Faculty Publications
Various meta-modeling techniques have been developed to replace computationally expensive simulation models. The performance of these meta-modeling techniques on different models is varied which makes existing model selection/recommendation approaches (e.g., trial-and-error, ensemble) problematic. To address these research gaps, we propose a general meta-modeling recommendation system using meta-learning which can automate the meta-modeling recommendation process by intelligently adapting the learning bias to problem characterizations. The proposed intelligent recommendation system includes four modules: (1) problem module, (2) meta-feature module which includes a comprehensive set of meta-features to characterize the geometrical properties of problems, (3) meta-learner module which compares the performance of instance-based …
Modeled And Measured Image-Plane Polychromatic Speckle Contrast, Noah R. Van Zandt, Jack E. Mccrae, Steven T. Fiorino
Modeled And Measured Image-Plane Polychromatic Speckle Contrast, Noah R. Van Zandt, Jack E. Mccrae, Steven T. Fiorino
Faculty Publications
The statistical properties of speckle relevant to short- to medium-range (tactical) active tracking involving polychromatic illumination are investigated. A numerical model is developed to allow rapid simulation of speckled images including the speckle contrast reduction effects of illuminator bandwidth, surface slope, and roughness, and the polarization properties of both the source and the reflection. Regarding surface slope (relative orientation of the surface normal and illumination/observation directions), Huntley’s theory for speckle contrast, which employs geometrical approximations to decrease computation time, is modified to increase accuracy by incorporation of a geometrical correction factor and better treatment of roughness and polarization. The resulting …
Taming The Hurricane Of Acquisition Cost Growth – Or At Least Predicting It, Allen J. Deneve, Erin T. Ryan, Jonathan D. Ritschel, Christine M. Schubert Kabban
Taming The Hurricane Of Acquisition Cost Growth – Or At Least Predicting It, Allen J. Deneve, Erin T. Ryan, Jonathan D. Ritschel, Christine M. Schubert Kabban
Faculty Publications
Cost growth is a persistent adversary to efficient budgeting in the Department of Defense. Despite myriad studies to uncover causes of this cost growth, few of the proposed remedies have made a meaningful impact. A key reason may be that DoD cost estimates are formulated using the highly unrealistic assumption that a program’s current baseline characteristics will not change in the future. Using a weather forecasting analogy, the authors demonstrate how a statistical approach may be used to account for these inevitable baseline changes and identify related cost growth trends. These trends are then used to reduce the error in …
Construction, Analysis, And Data-Driven Augmentation Of Supersaturated Designs, Alex J. Gutman
Construction, Analysis, And Data-Driven Augmentation Of Supersaturated Designs, Alex J. Gutman
Theses and Dissertations
Screening designs are used in the early stages of industrial and computer experiments to find the most important input factors affecting a system's output. They provide an economical way to remove unimportant factors from further, potentially costly, experimentation. However, when an experiment has a large number of control factors and limited number of available runs, it is infeasible to run a traditional screening design. In these situations, experimenters can use supersaturated designs. A supersaturated design is a fractional factorial design that can screen a set of k factors in n runs, where k is greater than n -1. Unfortunately, they …
Half-Life Learning Curves In The Defense Acquisition Life Cycle, Adedeji B. Badiru
Half-Life Learning Curves In The Defense Acquisition Life Cycle, Adedeji B. Badiru
Faculty Publications
Learning curves are useful for assessing performance improvement due to the positive impact of learning. In recent years, the deleterious effects of forgetting have also been recognized. Workers experience forgetting or decline in performance over time. Consequently, contemporary learning curves have attempted to incorporate forgetting components into learning curves. An area of increasing interest is the study of how fast and how far the forgetting impact can influence overall performance. This article introduces the concept of half-life analysis of learning curves using the concept of growth and decay, with particular emphasis on applications in the defense acquisition process. The computational …
A Dempster-Shafer Method For Multi-Sensor Fusion, Bethany G. Foley
A Dempster-Shafer Method For Multi-Sensor Fusion, Bethany G. Foley
Theses and Dissertations
The Dempster-Shafer Theory, a generalization of the Bayesian theory, is based on the idea of belief and as such can handle ignorance. When all of the required information is available, many data fusion methods provide a solid approach. Yet, most do not have a good way of dealing with ignorance. In the absence of information, these methods must then make assumptions about the sensor data. However, the real data may not fit well within the assumed model. Consequently, the results are often unsatisfactory and inconsistent. The Dempster-Shafer Theory is not hindered by incomplete models or by the lack of prior …