Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (5)
- Business (4)
- Aviation (2)
- Optics (2)
- Physics (2)
-
- Aviation and Space Education (1)
- Business Analytics (1)
- Civil Engineering (1)
- Civil and Environmental Engineering (1)
- Data Science (1)
- Education (1)
- Educational Leadership (1)
- Electrical and Computer Engineering (1)
- Electromagnetics and Photonics (1)
- Government Contracts (1)
- Higher Education (1)
- Human Resources Management (1)
- Law (1)
- Management Information Systems (1)
- Operations Research, Systems Engineering and Industrial Engineering (1)
- Operations and Supply Chain Management (1)
- Peace and Conflict Studies (1)
- Public Affairs, Public Policy and Public Administration (1)
- Science and Mathematics Education (1)
- Social and Behavioral Sciences (1)
- Systems Engineering (1)
- Training and Development (1)
- Keyword
-
- Forecasting (2)
- #afcec (1)
- Aircraft availability (1)
- Algorithm selection (1)
- Analytics (1)
-
- Asset management (1)
- Astronomical optics (1)
- Beam forming (1)
- Beam shaping (1)
- C-130J (Aircraft) (1)
- Capabilities development (1)
- Cluster analysis (1)
- Coherence (1)
- Combatant commands (1)
- Conflict (1)
- Data Science (1)
- Degradation (1)
- Education (1)
- Feature reduction (1)
- Fourier transforms (1)
- Joint Urgent Operational Need (JUON) (1)
- MICAP (1)
- Meta-learning (1)
- Mission-critical parts (1)
- Optical systems (1)
- Order fulfillment (1)
- Partnerships (1)
- Rapid transition (1)
- Simulation (1)
- Six Sigma DMAIC (1)
Articles 1 - 9 of 9
Full-Text Articles in Applied Statistics
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) …
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 …
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. …
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 …
The Analytics Managers Ultimate Guide For Working With Universities, Robert J. Mcgrath
The Analytics Managers Ultimate Guide For Working With Universities, Robert J. Mcgrath
Faculty Publications
The challenges organizations are having related to finding (and retaining) deep analytical talent did not materialize out of thin air…or overnight. Analytics and Data science – and the role of the analytics professional – has evolved over the last several decades and has been fueled by our ability to capture and process increasingly larger and more complex variations of data and our desire to gain increasingly granular insights to fuel innovation and creativity. While many organizations recognize that a partnership with a university can be a resource to many of these challenges, the best way to start a conversation with …
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 …
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 …