Round 8 Holdout DatasetThis is the training data used to construct and 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.

Here we provide curated analytical chemistry data for eggs collected from 1999 to 2010 on a subset of species and analytes that were measured regularly and reasonably systematically. Included in this publication are 487 samples analyzed for 174 ubiquitous environmental contaminants such as (poly)brominated diphenyl ethers (BDEs), mercury, organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs). Data were collated to form a dataset useful in chemometric and related analyses of the marine ecosystem in the north Pacific Ocean.

This software and data have been superseded. Please visit https://doi.org/10.18434/mds2-2532

The National Institute of Standards and Technology, Intelligent Systems Division has collected data measuring human subjects, while performing common, simulated industrial manufacturing tasks with and without wearing an exoskeleton. Five tests were completed as part of a research study to develop measurement science towards standard test methods. For simulated industrial manufacturing tasks were performed using a novel, now standardized apparatus, called the Position and Load Test Apparatus for Exoskeletons (PoLoTAE).

The dataset can be used to develop and test algorithms for communication and sensing in the 60GHz band. The dataset consists of synthetically generated indoor mm-wave channels between a MIMO transmitter and a MIMO receivers. Multiple targets are moving in the room. Number of targets, velocity of each target and trajectory are randomized across the dataset. The dataset contains also noisy received IEEE 802.11ay channel estimation fields. The dataset is suitable for development and testing of machine/deep learning algorithms.

Code and demonstration data for the paper, "On-the-fly closed-loop materials discovery via Bayesian active learning," Kusne, A.G., Yu, H., Wu, C. et al. Nat Commun 11, 5966 (2020). https://doi.org/10.1038/s41467-020 19597-w Code: Closed-loop autonomous materials exploration and optimization. This code is used to control an autonomous materials exploration and optimization platform. It guides subsequent experiments to learn about a material's phase map and target functional properties in a unified framework.

This database allows the public to browse and search recent FTZ Board manufacturing approvals.

This data set is captured from a robot workcell that is performing activities representative of several manufacturing operations. The workcell contains two, 6-degree-of-freedom robot manipulators where one robot is performing material handling operations (e.g., transport parts into and out of a specific work space) while the other robot is performing a simulated precision operation (e.g., the robot touching the center of a part with a tool tip that leaves a mark on the part). This precision operation is intended to represent a precise manufacturing operation (e.g., welding, machining).