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In an increasingly complex military operating environment, next generation wargaming platforms can reduce risk, decrease operating costs, and improve overall outcomes. Novel Artificial Intelligence (AI) enabled wargaming approaches, based on software
Wai Cheong Tam, Jun Wang, Richard D. Peacock, Paul A. Reneke, Eugene Yujun Fu, Thomas Cleary
This report provides additional technical details to an article entitled P-Flash – A Machine Learning-based Model for Flashover Prediction using Recovered Temperature Data. Research was conducted to examine the use of Support Vector Regression (SVR) to
Reva Schwartz, Apostol Vassilev, Kristen K. Greene, Lori Perine, Andrew Burt, Patrick Hall
As individuals and communities interact in and with an environment that is increasingly virtual they are often vulnerable to the commodification of their digital exhaust. Concepts and behavior that are ambiguous in nature are captured in this environment
Joshua Ziegler, Thomas McJunkin, Emily Joseph, Sandesh Kalantre, Benjamin Harpt, Donald Savage, Max Lagally, Mark Eriksson, Jacob Taylor, Justyna Zwolak
The current autotuning approaches for quantum dot (QD) devices, while showing some success, lack an assessment of data reliability. This leads to unexpected failures when noisy or otherwise low-quality data is processed by an autonomous system. In this
High-quality recordings of radio frequency (RF) emissions from commercial communication hardware in realistic environments are often needed to develop and assess spectrum-sharing technologies and practices, e.g., for training and testing spectrum sensing
Ira Monarch, Jacob Collard, Sangjin Shin, Eswaran Subrahmanian, Talapady N. Bhat, Ram D. Sriram
This report describes the adaptation, composition and use of natural language processing, machine learning and other computational tools to help make implicit informational structures in very large technical corpora explicit. The tools applied to the
When people try to understand nuanced language they typically process multiple input sensor modalities to complete this cognitive task. It turns out the human brain has even a specialized neuron formation, called sagittal stratum, to help us understand
Marcin Kociolek, Michal Kozlowski, Antonio Cardone
The perceived texture directionality is an important, not fully explored image characteristic. In many applications texture directionality detection is of fundamental importance. Several approaches have been proposed, such as the fast Fourier-based method
Graph neural networks (GNN) have been shown to provide substantial performance improvements for atomistic material representation and modeling compared with descriptor-based machine learning models. While most existing GNN models for atomistic predictions
Junyun Zhao, Siyuan Huang, Osama Yousuf, Yutong Gao, Brian Hoskins, Gina Adam
While promising for high capacity machine learning accelerators, memristor devices have non-idealities that prevent software-equivalent accuracies when used for online training. This work uses a combination of Mini-Batch Gradient Descent (MBGD) to average
Kevontrez Jones, Zhuo Yang, Ho Yeung, Paul Witherell, Yan Lu
Laser powder-bed fusion is an additive manufacturing (AM) process that offers exciting advantages for the fabrication of metallic parts compared to traditional techniques, such as the ability to create complex geometries with less material waste. However
Brian Weber, Sandesh Kalantre, Thomas McJunkin, Jacob Taylor, Justyna Zwolak
The problem of classifying high-dimensional shapes in real-world data grows in complexity as the dimension of the space increases. For the case of identifying convex shapes of different geometries, a new classification framework has recently been proposed