Technical Publications from Research and Development
This is Lone Star’s catalog of select technical publications authored by Lone Star’s research and development group, Cipher Alchemy®. Our scientists and researchers developed this work in collaboration with our partner organizations, institutions, and universities. This page will be updated as more publications and presentations are cleared for open consumption. Please check back periodically for additional listings and contact our team at Cipher Alchemy® if there are any questions or need for additional information.
Hypersonic Missile Threat Modeling, Simulation, and Assessment
This paper explores the necessity for advanced simulation techniques in assessing hypersonic missile threats due to limited information and presents a digital twin missile model designed to simulate performance under uncertainties.
by Dr. Randal Allen
2023 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Continuous Asymmetric Risk Analysis (CARA)
This paper evaluates the limitations of the DoD’s Risk Reporting Matrix, highlighting its discrete nature and proposes the CARA solution. CARA aims to enhance risk assessment by transforming the matrix into a continuous gradient field, offering infinite likelihood-consequence combinations.
by Dr. Zachry Engel, Nickalus Harrill, Nicolas Velez, Jacob Ediger, and Dr. Randal Allen
2023 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
A Novel Approach to Dynamic Unsupervised Clustering
This paper addresses the brittleness of AI/ML techniques when encountering new data, proposing the DUCAT system as a solution. DUCAT aims to handle streaming data effectively, adapt to new data types without retraining, and detect outliers or noise within datasets.
by Chris Heinlen, Mark Volpi, and Dr. Randal Allen
2023 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Multivariate Metalog Distribution Model and Compression
This paper demonstrates an application of the metalog distributions for compactly representing a correlated, multivariate dataset which can be used as a means of information compression.
by Raul Rios
Evolved AI® for First-Order Conceptual Missile Design Optimization and Threat Assessment
This paper introduces an application of FOCDO as it relates to rocket motor design as well as the optimal design of the inlet throat geometry for a ramjet, which utilizes digital twins and EAI® to optimize performance criteria.
by Dr. Randal Allen
2023 AIAA Defense Forum, 11-13 April
Correlated Histogram Clustering
by Brice Brosig and Dr. Randal Allen
2022 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
A Tan Root for Battin’s Lambert Recipe
by Dr. Randal Allen and Russel Wenzel
Included in an AIAA Special Issue in Honor of Dr. Richard Battin (MIT)
Evolved Artificial Intelligence® for First-Order Conceptual Missile Design Optimization
by Dr. Randal Allen
2022 Defense Forum, 19-21 April
Correlated Histograms Clustering Presentation
A novel unsupervised learning technique that leverages the underlying statistics of a dataset across its different dimensions to identify cluster centroids
by Brice Brosig and Dr. Randal Allen
2022 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Comparing Methods of Nonlinear Dimensionality Reduction for Artificial Intelligence
by Dr. Zachry Engel and Mitchell Wadas
2022 Cipher Alchemy® Research
First-Order Conceptual Design for Turbojet Missiles and Guided Bombs
by Seth Spears
2022 SciTech Forum, January 3-7
Evolved AI® for Model-Based Reinforcement Learning
by Dr. Randal Allen, Dr. Zachry Engel, and Dr. Eric Haney
2021 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Evolved Artificial Intelligence® for Stochastic Clustering Unsupervised Learning (Patent Pending)
by Dr. Randal Allen
2020 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Executive Risk Assessments for the Age of Algorithms
by Steven D. Roemerman, John Volpi, and Dr. Randal Allen
2019 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Model-Based Design Reviews with Innoslate
by Dr. Randal Allen
University of Central Florida
Interpretable Network Architectures for Machine Learning (Patent Pending)
by Dr. Randal Allen
2019 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Adaptive Nonconvex Optimization for AI and Machine Learning (Patent Pending)
by Dr. Randal Allen
2019 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Risk Analysis and Best Practices Benchmarking (Three Case Studies – How Risky is My Risk Analysis)
by Steven D. Roemerman
2018 Probability Management Conference
Best Practices in Modeling and Simulation; Multi-Community Benchmarking
by Steven D. Roemerman, John Volpi, and Dr. Randal Allen
2018 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
Intelligent Prediction
by Dr. Randal Allen, Sam Vasta, and John Volpi
2017 Lone Star Analysis AOS® Intelligent Predictor: This paper discusses the research associated with different filtering and predicting methods and their development.
A Multicriteria, Multiplayer Model: The Protest Casino (A Pro Bono Public Policy Study: Does the Protest System Really Work? Could It Work Better?)
by Steven D. Roemerman and Dr. Randal Allen
2016 INFORMS Annual Meeting
Frequent Once in a Lifetime Crises
by Dr. Randal Allen
2016 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC)
COTS Lens and Detector Characterization for Low Cost,
Miniature SAL Seekers
by Dr. Randal Allen, John Volpi, and Steven D. Roemerman
This paper shows a low-cost COTS
configuration yields a feasible lightweight, small-volume SAL seeker.
COTS Lens and Detector Characterization for Low Cost, Miniature SAL Seekers
by Dr. Randal Allen, John Volpi, and Steven D. Roemerman
2013 AIAA Presentation
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