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Articles 1 - 30 of 55
Full-Text Articles in Applied Statistics
Trends And Predictive Modeling Of Real Estate Prices In Major Saudi Arabia Cities, Meshal S. Aldahas
Trends And Predictive Modeling Of Real Estate Prices In Major Saudi Arabia Cities, Meshal S. Aldahas
Theses and Dissertations
his research examines historical trends and explanatory modeling of real estate prices in major Saudi cities, with a focus on Riyadh, Jeddah, and Dammam. Using a mixed-methods approach, the study integrates quantitative data from 2010–2023, including housing and macroeconomic indicators, with qualitative insights drawn from over 320 survey responses that captured consumer sentiment on affordability, job security, and housing policies. A combination of descriptive statistics, ARIMA and Exponential Smoothing techniques was applied to detect long-term patterns, seasonal variations, and market shocks. Predictive modeling was conducted using Linear Regression, Decision Trees, and Neural Networks, with results showing that job security consistently …
On Large Language Models In National Security Applications, William N. Caballero, Phillip R. Jenkins
On Large Language Models In National Security Applications, William N. Caballero, Phillip R. Jenkins
Faculty Publications
The overwhelming success of GPT-4 in early 2023 highlighted the transformative potential of large language models (LLMs) across various sectors, including national security. This article explores the implications of LLM integration within national security contexts, analyzing their potential to revolutionize information processing, decision-making, and operational efficiency. Whereas LLMs offer substantial benefits, such as automating tasks and enhancing data analysis, they also pose significant risks, including hallucinations, data privacy concerns, and vulnerability to adversarial attacks. Through their coupling with decision-theoretic principles and Bayesian reasoning, LLMs can significantly improve decision-making processes within national security organizations. Namely, LLMs can facilitate the transition from …
Forecasting Stock Prices Using Arima Models And Technical Analysis, Muath I. Almaiman
Forecasting Stock Prices Using Arima Models And Technical Analysis, Muath I. Almaiman
Theses and Dissertations
This thesis explores the integration of Autoregressive Integrated Moving Average (ARIMA) models and technical analysis to forecast stock prices, with a focus on Coca-Cola's (KO) and Netflix’s (NFLX) stocks. It examines the effectiveness of combining ARIMA models, known for their predictive accuracy in time-series analysis, with technical indicators, particularly moving averages. The study evaluates whether this integrated approach can enhance the predictive capability of stocks prices beyond traditional methods. The predictive capability is evaluated using error metrics from the ARIMA models, as well as by assessing the return earned using simple rules based on the technical indicators. Utilizing data spanning …
Steady State Thermal Blooming With Convection: Modeling, Simulation And Analysis, Jeremiah S. Lane
Steady State Thermal Blooming With Convection: Modeling, Simulation And Analysis, Jeremiah S. Lane
Theses and Dissertations
The modeling, simulation, and analysis of high energy laser propagation is a research topic of significant interest to the defense community. A detailed understanding of the phenomenon of thermal blooming is crucial as it is detrimental to the propagation of lasers over long distances and in the presence of aerosols. The simulation of thermal blooming has historically relied on wave optics models and scaling laws for the fluid response to the laser. Since thermal blooming occurs in the presence of natural convection, however, there is a need for simulating this coupled fluid-beam effect using a first principles approach. In this …
Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing, Steven J. Schuldt
Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing, Steven J. Schuldt
Faculty Publications
Organizations with large facility and infrastructure portfolios have used asset management databases for over ten years to collect and standardize asset condition data. Decision makers use these data to predict asset degradation and expected service life, enabling prioritized maintenance, repair, and renovation actions that reduce asset life-cycle costs and achieve organizational objectives. However, these asset condition forecasts are calculated using standardized, self-correcting distribution models that rely on poorly-fit, continuous functions. This research presents four stepwise asset condition forecast models that utilize historical asset inspection data to improve prediction accuracy: (1) Slope, (2) Weighted Slope, (3) Condition-Intelligent Weighted Slope, and (4) …
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. …
Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman
Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman
Faculty Publications
Purpose — Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.
Design/methodology/approach — This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the …
Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman
Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman
Faculty Publications
Purpose — Aircraft fail to meet mission capable rate goals due to a lack of supply of aircraft parts in inventory where the aircraft breaks. This triggers an order at the repair location. To maximize mission capable rate, the time from order to delivery needs to be minimized. The purpose of this research is to examine the case of three airfields for the order to delivery time of mission critical aircraft parts for a specific aircraft type. Design/methodology/approach — This research captured data from three information systems to assess the order fulfillment process. The data were analyzed to determine the …
Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low
Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low
Theses and Dissertations
The Air Force Inspection System is a proponent of utilizing a risk-based sampling strategy (RBSS) for conducting inspections from major command levels down to the unit level. The strategy identifies areas deemed most important or risky by commanders and prioritizes them accordingly for an independent assessment by the Inspector General. While Air Force regulation specifies the need to use a RBSS for inspection, the implementation process is delegated to individual commands and, subsequently, wings. The 23rd Wing, the sponsor for this research, directed us to analyze a RBSS tool highlighted as an example from which to adopt for those units …
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 …
Conceptualization And Application Of Deep Learning And Applied Statistics For Flight Plan Recommendation, Nicholas C. Forrest
Conceptualization And Application Of Deep Learning And Applied Statistics For Flight Plan Recommendation, Nicholas C. Forrest
Theses and Dissertations
The Air Forces Pilot Training Next (PTN) program seeks a more efficient pilot training environment emphasizing the use of virtual reality flight simulators alongside periodic real aircraft experience. The PTN program wants to accelerate the training pace and progress in undergraduate pilot training compared to traditional undergraduate pilot training. Currently, instructor pilots spend excessive time planning and scheduling flights. This research focuses on methods to auto-generate the planning of in-flight events using hybrid filtering and deep learning techniques. The resulting approach captures temporal trends of user-specific and program-wide student performance to recommend a feasible set of graded flight events for …
An Analysis Of A Lighting Prediction Threshold For 45th Weather Squadron Electric Field Mill Data, Charles A. Skrovan
An Analysis Of A Lighting Prediction Threshold For 45th Weather Squadron Electric Field Mill Data, Charles A. Skrovan
Theses and Dissertations
The mission of the 45th Weather Squadron (45 WS) is to “exploit the weather to assure safe access to air and space” for Patrick Air Force Base, Cape Canaveral Air Force Station (CCAFS), and Kennedy Space Center (KSC) in support of various operations (United States Air Force, n.d.). To support that mission the 45 WS hosts a suite of weather detection instruments that include a lightning warning system that consists of an array of 31 electric field mills (EFM) and a lightning detection and ranging system (Department of the Air Force, 1976). Electric field mills at Cape Canaveral continuously record …
Ground Weather Radar Signal Characterization Through Application Of Convolutional Neural Networks, Stephen M. Lee
Ground Weather Radar Signal Characterization Through Application Of Convolutional Neural Networks, Stephen M. Lee
Theses and Dissertations
The 45th Weather Squadron supports the space launch efforts out of the Kennedy Space Center and Cape Canaveral Air Force Station for the Department of Defense, NASA, and commercial customers through weather assessments. Their assessment of the Lightning Launch Commit Criteria (LLCC) for avoidance of natural and rocket triggered lightning to launch vehicles is critical in approving space shuttle and rocket launches. The LLCC includes standards for cloud formations, which requires proper cloud identification and characterization methods. Accurate reflectivity measurements for ground weather radar are important to meet the LLCC for rocket triggered lightning. Current linear interpolation methods for ground …
Generating Electromagnetic Schell-Model Sources Using Complex Screens With Spatially Varying Auto- And Cross-Correlation Functions, Milo W. Hyde Iv
Generating Electromagnetic Schell-Model Sources Using Complex Screens With Spatially Varying Auto- And Cross-Correlation Functions, Milo W. Hyde Iv
Faculty Publications
We present a method to generate any physically realizable electromagnetic Schell-model source. Our technique can be directly implemented on existing vector-beam generators that utilize spatial light modulators for coherence control, beam shaping, and relative phasing. This work significantly extends published research on the subject, where control over the partially coherent source’s cross-spectral density matrix was limited. We begin by presenting the statistical optics theory necessary to derive and implement our method. We then apply our technique, both analytically and in simulation, to produce two electromagnetic Schell-model sources from the literature. We demonstrate control over the full cross-spectral density matrices of …
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 …
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 …
Using Multiattribute Utility Copulas In Support Of Uav Search And Destroy Operations, Beau A. Nunnally
Using Multiattribute Utility Copulas In Support Of Uav Search And Destroy Operations, Beau A. Nunnally
Theses and Dissertations
The multiattribute utility copula is an emerging form of utility function used by decision analysts to study decisions with dependent attributes. Failure to properly address attribute dependence may cause errors in selecting the optimal policy. This research examines two scenarios of interest to the modern warfighter. The first scenario employs a utility copula to determine the type, quantity, and altitude of UAVs to be sent to strike a stationary target. The second scenario employs a utility copula to examine the impact of attribute dependence on the optimal routing of UAVs in a contested operational environment when performing a search and …
Tryptophan Degradation In Women With Breast Cancer: A Pilot Study, Debra E. Lyon, Jeanne M. Walter, Angela R. Starkwater, Christine M. Schubert, Nancy L. Mccain
Tryptophan Degradation In Women With Breast Cancer: A Pilot Study, Debra E. Lyon, Jeanne M. Walter, Angela R. Starkwater, Christine M. Schubert, Nancy L. Mccain
Faculty Publications
Background: Altered tryptophan metabolism and indoleamine 2,3-dioxygenase activity are linked to cancer development and progression. In addition, these biological factors have been associated with the development and severity of neuropsychiatric syndromes, including major depressive disorder. However, this biological mechanism associated with both poor disease outcomes and adverse neuropsychiatric symptoms has received little attention in women with breast cancer. Therefore, a pilot study was undertaken to compare levels of tryptophan and other proteins involved in tryptophan degradation in women with breast cancer to women without cancer, and secondarily, to examine levels in women with breast cancer over the course of chemotherapy. …
Statistical Image Recovery From Laser Speckle Patterns With Polarization Diversity, Donald B. Dixon
Statistical Image Recovery From Laser Speckle Patterns With Polarization Diversity, Donald B. Dixon
Theses and Dissertations
This research extends the theory and understanding of the laser speckle imaging technique. This non-traditional imaging technique may be employed to improve space situational awareness and image deep space objects from a ground-based sensor system. The use of this technique is motivated by the ability to overcome aperture size limitations and the distortion effects from Earth’s atmosphere. Laser speckle imaging is a lensless, coherent method for forming two-dimensional images from their autocorrelation functions. Phase retrieval from autocorrelation data is an ill-posed problem where multiple solutions exist. This research introduces polarization diversity as a method for obtaining additional information so the …
Augmenting Latent Dirichlet Allocation And Rank Threshold Detection With Ontologies, Laura A. Isaly
Augmenting Latent Dirichlet Allocation And Rank Threshold Detection With Ontologies, Laura A. Isaly
Theses and Dissertations
In an ever-increasing data rich environment, actionable information must be extracted, filtered, and correlated from massive amounts of disparate often free text sources. The usefulness of the retrieved information depends on how we accomplish these steps and present the most relevant information to the analyst. One method for extracting information from free text is Latent Dirichlet Allocation (LDA), a document categorization technique to classify documents into cohesive topics. Although LDA accounts for some implicit relationships such as synonymy (same meaning) it often ignores other semantic relationships such as polysemy (different meanings), hyponym (subordinate), meronym (part of), and troponomys (manner). To …
Detecting Near-Earth Objects Using Cross-Correlation With A Point Spread Function, Anthony P. O'Dell
Detecting Near-Earth Objects Using Cross-Correlation With A Point Spread Function, Anthony P. O'Dell
Theses and Dissertations
This thesis describes a process to help discover Near-Earth Objects (NEOs) of larger than 140 meters in diameter from ground based telescopes. The process involves using Nyquist sampling rate to take data from a ground-based telescope and measuring the atmospheric seeing parameter, r0, at the time of data collection. r0 is then used to create a point spread function (PSF) for a NEO at the visual magnitude limit of the telescope and exposure time. This PSF is cross-correlated with the Nyquist sampling rate image from the telescope to reduce the noise and therefore increase the detection probability of …
Statistical Methods For Image Registration And Denoising, Matthew D. Sambora
Statistical Methods For Image Registration And Denoising, Matthew D. Sambora
Theses and Dissertations
This dissertation describes research into image processing techniques that enhance military operational and support activities. The research extends existing work on image registration by introducing a novel method that exploits local correlations to improve the performance of projection-based image registration algorithms. The dissertation also extends the bounds on image registration performance for both projection-based and full-frame image registration algorithms and extends the Barankin bound from the one-dimensional case to the problem of two-dimensional image registration. It is demonstrated that in some instances, the Cramer-Rao lower bound is an overly-optimistic predictor of image registration performance and that under some conditions, the …
Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates, Bryan Sparkman
Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates, Bryan Sparkman
Theses and Dissertations
Fuel-air mixing analysis of scramjet aircraft is often performed through ex- perimental research or Computational Fluid Dynamics (cfd) algorithms. Design optimization with these approaches is often impossible under a limited budget due to their high cost per run. This investigation uses jetpen, a known inexpensive analysis tool, to build upon a previous case study of scramjet design optimization. Mixed Variable Pattern Search (mvps) is compared to evolutionary algorithms in the optimization of two scramjet designs. The ¯rst revisits the previously stud- ied approach and compares the quality of mvps to prior results. The second applies mvps to a new scramjet …
Statistical Approach To The Characterization And Recognition Of Human Gaits, Derrick M. Chelliah
Statistical Approach To The Characterization And Recognition Of Human Gaits, Derrick M. Chelliah
Theses and Dissertations
This thesis addresses the final portion of a complete process for human gait recognition. The thesis takes as input information that has been generated from videotaping walking individuals and converting their gaits into numerical data that measures the locations of various points on the body through time. Beginning with this data, this thesis uses a variety of mathematical and statistical methods to create identifying signatures for each individual and identify them on the basis of that signature. The end goal is to achieve under controlled laboratory conditions human gait recognition, an identification method which does not require contact or cooperation …
Predicting Cost And Schedule Growth For Military And Civil Space Systems, Christina F. Rusnock
Predicting Cost And Schedule Growth For Military And Civil Space Systems, Christina F. Rusnock
Theses and Dissertations
Military and civil space acquisitions have received much criticism for their inability to produce realistic cost and schedule estimates. This research seeks to provide space systems cost estimators with a forecasting tool for space system cost and schedule growth by identifying factors contributing to growth, quantifying the relative impact of these factors, and establishing a set of models for predicting space system cost and schedule growth. The analysis considers data from both Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) space programs. The DoD dataset includes 21 space programs that submitted developmental Selected Acquisition Reports between 1969 …
A Multivariate Magnitude Robust Control Chart For Mean Shift Detection And Change Point Estimation, Ryan M. Harrell
A Multivariate Magnitude Robust Control Chart For Mean Shift Detection And Change Point Estimation, Ryan M. Harrell
Theses and Dissertations
Statistical control charts are often used to detect a change in an otherwise stable process. This process may contain several variables affecting process stability. The goal of any control chart is to detect an out-of-control state quickly and provide insight on when the process actually changed. This reduces the off-line time the quality engineer spends assigning causality. In this research, a multivariate magnitude robust chart (MMRC) was developed using a change point model and a likelihood-ratio approach. Here the process is considered in-control until one or more normally distributed process variables permanently and suddenly shifts to out-of-control, stable value. Using …
Professionalism In The Air Force: A Comparative Analysis Of Commissioned Officers With Non-Commissioned Officers, Edward K. Boyd
Professionalism In The Air Force: A Comparative Analysis Of Commissioned Officers With Non-Commissioned Officers, Edward K. Boyd
Theses and Dissertations
Decades ago, military sociologists predicted a rising trend among officers away from traditional institutional military values and toward more economically-based occupational values due to the effects of the transition from a conscription-based military to an all-volunteer force. Subsequent empirical research resulted in data that supports such predictions. More recent researchers have suggested that in addition to the all-volunteer force, an increase on technology may also accelerate the trend toward occupationalism and away from traditional institutional military values and the warrior ethos that typically define successful military organizations. The officer corps may be particularly vulnerable to occupationalism due to increased technical …
An Evaluation Of Organizational And Experience Factors Affecting The Perceived Transfer Of U.S. Air Force Basic Combat Skills Training, Shirley D. Crow
An Evaluation Of Organizational And Experience Factors Affecting The Perceived Transfer Of U.S. Air Force Basic Combat Skills Training, Shirley D. Crow
Theses and Dissertations
The United States Air Force is in a state of transformation. Due to ongoing operations in Iraq and Afghanistan, the focus of Basic Military Training is shifting to basic combat skills, or the skills needed to survive and operate in a hostile environment. In this study, basic combat skills training was evaluated using a number of training factors that potentially affect trainees’ perception of training transfer, or their ability to apply the skills they learned in training on the job or in a hostile environment. The analysis used structural equation modeling to evaluate the paths between each of the factors …