153 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- United States ArmyUS18 papers
- DEVCOM Army Research LaboratoryUS13 papers
- United States Army Combat Capabilities Development CommandUS8 papers
- George Mason UniversityUS7 papers
- Robotic Research (United States)US4 papers
- Robotics Research (United States)US4 papers
- University of Colorado SystemUS4 papers
- University of MichiganUS4 papers
- Arecibo ObservatoryPR3 papers
- Carnegie Mellon UniversityUS3 papers
- Curtin UniversityAU3 papers
- Eötvös Loránd UniversityHU3 papers
44 papers
The NANOGrav 15 yr Data Set: Customized Chromatic Noise Models
Bjorn Larsen, Jeremy G. Baier, Daniel J. Oliver +53
Pulsar timing arrays conduct low-frequency gravitational wave searches, which require comprehensive accounting of various noise sources to achieve robust results. Interstellar prop…
HyperSpace: A Generalized Framework for Spatial Encoding in Hyperdimensional Representations
Shay Snyder, Andrew Capodieci, David Gorsich +1
Vector Symbolic Architectures (VSAs) provide a well-defined algebraic framework for compositional representations in hyperdimensional spaces. We introduce HyperSpace, an open-sourc…
SRMU: Relevance-Gated Updates for Streaming Hyperdimensional Memories
Shay Snyder, Andrew Capodieci, David Gorsich +1
Sequential associative memories (SAMs) are difficult to build and maintain in real-world streaming environments, where observations arrive incrementally over time, have imbalanced…
Stress Asymmetry in Hard Magnetic Soft Materials
H. Gökçen Güner, Francois Barthelat, John D. Clayton +3
Hard magnetic soft materials -- soft polymers embedded with hard magnetic particles -- are modeled using continuum magnetomechanical formulations in which the deformation and the m…
Gravitational Wave Measurement of the - Intrinsic Scatter at High Redshift
Cayenne Matt, Kayhan Gültekin, Gabriella Agazie +109
The observed GWB spectrum is higher in amplitude than model predictions by a factor of 2-3. Using a semi-analytic model, we evaluate the effect of a high-scatter supermassive black…
Quantum Semiconductor Heterostructures for meV Axion Dark Matter Detection
Jaanita Mehrani, Tao Xu, Andrey Baydin +6
We propose a novel strategy and a new class of detectors for the direct detection of axion dark matter in the meV mass range, based on resonantly enhanced axion-photon conversion t…
Crack Face Contact Modeling is Essential to Predict Crack-Parallel Stresses
Maryam Hakimzadeh, Noel Walkington, Carlos Mora-Corral +2
Phase-field fracture models provide a powerful approach to modeling fracture, potentially enabling the unguided prediction of crack growth in complex patterns. To ensure that only…
A Systematic Digital Engineering Approach to Verification & Validation of Autonomous Ground Vehicles in Off-Road Environments
Tanmay Vilas Samak, Chinmay Vilas Samak, Julia Brault +6
The engineering community currently encounters significant challenges in the systematic development and validation of autonomy algorithms for off-road ground vehicles. These challe…
Generalizable Reinforcement Learning with Biologically Inspired Hyperdimensional Occupancy Grid Maps for Exploration and Goal-Directed Path Planning
Shay Snyder, Ryan Shea, Andrew Capodieci +2
Real-time autonomous systems utilize multi-layer computational frameworks to perform critical tasks such as perception, goal finding, and path planning. Traditional methods impleme…
Brain Inspired Probabilistic Occupancy Grid Mapping with Vector Symbolic Architectures
Shay Snyder, Andrew Capodieci, David Gorsich +1
Real-time robotic systems require advanced perception, computation, and action capability. However, the main bottleneck in current autonomous systems is the trade-off between compu…
Off-Road Autonomy Validation Using Scalable Digital Twin Simulations Within High-Performance Computing Clusters
Tanmay Vilas Samak, Chinmay Vilas Samak, Joey Binz +5
Off-road autonomy validation presents unique challenges due to the unpredictable and dynamic nature of off-road environments. Traditional methods focusing on sequentially sweeping…
Continuously Optimizing Radar Placement with Model Predictive Path Integrals
Michael Potter, Shuo Tang, Paul Ghanem +8
Continuously optimizing sensor placement is essential for precise target localization in various military and civilian applications. While information theory has shown promise in o…
Accelerated Multi-Objective Alloy Discovery through Efficient Bayesian Methods: Application to the FCC Alloy Space
Trevor Hastings, Mrinalini Mulukutla, Danial Khatamsaz +14
This study introduces BIRDSHOT, an integrated Bayesian materials discovery framework designed to efficiently explore complex compositional spaces while optimizing multiple material…
Multistatic-Radar RCS-Signature Recognition of Aerial Vehicles: A Bayesian Fusion Approach
Michael Potter, Murat Akcakaya, Marius Necsoiu +3
Radar Automated Target Recognition (RATR) for Unmanned Aerial Vehicles (UAVs) involves transmitting Electromagnetic Waves (EMWs) and performing target type recognition on the recei…
Polyurea-Graphene Nanocomposites -- the Influence of Hard-Segment Content and Nanoparticle Loading on Mechanical Properties
Demetrios A. Tzelepis, Arman Khoshnevis, Mohsen Zayernouri +1
Polyurethane and polyurea-based adhesives are widely used in various applications, from automotive to electronics to medical. The adhesive performance depends strongly on its compo…
Terahertz cavity magnon polaritons
T. Elijah Kritzell, Andrey Baydin, Fuyang Tay +5
Hybrid light-matter coupled states, or polaritons, in magnetic materials have attracted significant attention due to their potential for enabling novel applications in spintronics…
The NANOGrav 15-year Gravitational-Wave Background Methods
Aaron D. Johnson, Patrick M. Meyers, Paul T. Baker +93
Pulsar timing arrays (PTAs) use an array of millisecond pulsars to search for gravitational waves in the nanohertz regime in pulse time of arrival data. This paper presents rigorou…
Augmented Reality and Mixed Reality Measurement Under Different Environments: A Survey on Head-Mounted Devices
Hung-Jui Guo, Jonathan Z. Bakdash, Laura R. Marusich +1
Augmented Reality (AR) and Mixed Reality (MR) have been two of the most explosive research topics in the last few years. Head-Mounted Devices (HMDs) are essential intermediums for…
Systematic Modification of Functionality in Disordered Elastic Networks Through Free Energy Surface Tailoring
Dan Mendels, Fabian Byléhn, Timothy W. Sirk +1
Advances in manufacturing and characterization of complex molecular systems have created a need for new methods for design at molecular length scales. Emerging approaches are incre…
Uncertain Bayesian Networks: Learning from Incomplete Data
Conrad D. Hougen, Lance M. Kaplan, Federico Cerutti +1
When the historical data are limited, the conditional probabilities associated with the nodes of Bayesian networks are uncertain and can be empirically estimated. Second order esti…
Simultaneous Human-robot Matching and Routing for Multi-robot Tour Guiding under Time Uncertainty
Bo Fu, Tribhi Kathuria, Denise Rizzo +4
This work presents a framework for multi-robot tour guidance in a partially known environment with uncertainty, such as a museum. In the proposed centralized multi-robot planner, a…
Sensitivity analysis of a mean-value exergy-based internal combustion engine model
Gabriele Pozzato, Denise Rizzo, Simona Onori
In this work, we conduct a sensitivity analysis of the mean-value internal combustion engine exergy-based model, recently developed by the authors, with respect to different drivin…
Constrained Minimum Energy Designs
Chaofan Huang, V. Roshan Joseph, Douglas M. Ray
Space-filling designs are important in computer experiments, which are critical for building a cheap surrogate model that adequately approximates an expensive computer code. Many d…
Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy E. J. Cohen, Zinan Lin +5
Generative adversarial networks (GANs) are often billed as "universal distribution learners", but precisely what distributions they can represent and learn is still an open questio…