Database of MRI quantitative measurements gathered from literature and experimental studies, for tissues and synthetic materials.Additionally, a code base is provided to aid in finding MRI tissue relaxation times for a target field strength, and to provide functionality to solve for tissue mimic composition given target tissue relaxation times.

Round rl-randomized-lavaworld-aug2023-train Train Dataset

This is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of Reinforcement Learning agents trained to navigate the Lavaworld Minigrid environment. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round rl-randomized-lavaworld-aug2023-test Dataset

This is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of Reinforcement Learning agents trained to navigate the Lavaworld Minigrid environment. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round rl-randomized-lavaworld-aug2023-holdout Dataset

This is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of Reinforcement Learning agents trained to navigate the Lavaworld Minigrid environment. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Mobile manipulators, which are robotic systems integrating an automatic or autonomous mobile base with a manipulator, can potentially enhance automation in many industrial and unstructured environments. Namely, large-scale manufacturing processes, typical in the aerospace, energy, transportation, and conformal additive manufacturing fields, encompass a notable subset of potential future mobile manipulator use-cases.

Recent advances in Rydberg atom electrometry detail promising applications in radiofrequency (RF) communications. Presently, most applications use carrier frequencies greater than 1 GHz where resonant Autler-Townes splitting provides the highest antenna sensitivity. This letter documents a series of experiments with Rydberg atomic antennas to collect and process waveforms from the automated identification system (AIS) used in maritime navigation in the VHF band. This is difficult with conventional resonant Autler-Townes based Rydberg sensing.

Data associated with "Study on Local Power Plant Emissions Using Multi-Frequency Differential Absorption LIDAR and Real-Time Plume Tracking" published in Remote Sensing 15(17), 4283 (2023).

nlp-question-answering-aug2023-train

This is the train data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

"module-utilities" is a python package of utilities to simplify working with python packages.
The main features of `module-utilities` are as follows: "cached" module: A module to cache class attributes and methods. Right now, this uses
a standard python dictionary for storage. Future versions will hopefully
be more robust to threading and shared cache.
"docfiller" module: A module to share documentation. This is adapted from the
pandas `doc` decorator. There are a host of utilities build around this.

nlp-question-answering-aug2023-test

This is the train data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.