The following data files are provided in support of the AM Bench 2022 modeling challenges associated with Microstructure measurement extension to AMB2018-01: laser powder bed fusion (LPBF) 3D builds of nickel-based superalloy IN625 test objects (AMB2022-05).  Description of the associated measurements are provided in the AMB2022-05 challenge description webpage (https://www.nist.gov/ambench).Some of the work was supported by the Exascale Additive Manufacturing Application Development Project, part of the Exascale Computing Project,  (17-SC-20-SC),

Data tables for Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2022: Annual Supplement to NIST Handbook 13Starting in the 2022 Annual Supplement to Handbook 135, the data tables within the text document has been extracted and provided in a supplemental spreadsheet.

System output scoring software of NIST 2022 Open Fine-grained Activity Detection (OpenFAD) challenge. OpenFAD is an activity classification and detection evaluation to measure how well systems can automatically classify or temporally detect fine-grained activities collected from the Consented Activities of People (CAP) dataset using handheld devices. Covers Activity Classification- (AC) and Temporal Activity Detection-Task (TAD).

Automated Particle Analysis data sets from a TESCAN MIRA3 with 3 Pulsetor EDS detectors automated using NIST DTSA-II with the SEMantics instrument control extension.The data is in the Zeppelin format designed by RJ Lee Group.

This dataset supports the manuscript " Interface formation and Schottky barrier height for Y, Nb, Au, and Pt on Ge as determined by hard x-ray photoelectron spectroscopy", and consists of two parts: (1) hard X-ray photoelectron spectroscopy (HAXPES) results from Ag, Pt, Y, Nb reference samples, and the heterojunction of these metals on Ge. (2) Input and results of density functional theory (DFT) calculations om the total and angular-momentum-projected density of states of Ge.

These data were acquired in the process of collecting data for [1]. They comprise IQ waveform outputs of two different software-defined radios (SDRs) that were collected for various combinations of 1- and 2-tone excitation conditions. For details about how the data were collected, see that publication. [1] McNulty, M., Gu, D., Kuester, D. and Nayeri, P.

Data for all measurements published in the manuscript "Bipolar Waveform Synthesis with an Optically Driven Josephson Arbitrary Waveform Synthesizer," which will be published in the journal "IEEE Transactions on Applied Superconductivity".https://doi.org/10.1109/tasc.2022.3167660All files saved as Python pickle files.

This portal is a gateway to documented digital forensic image datasets. These datasets can assist in a variety of tasks including tool testing, developing familiarity with tool behavior for given tasks, general practitioner training and other unforeseen uses that the user of the datasets can devise. Most datasets have a description of the type and locations of significant artifacts present in the dataset. There are descriptions and finding aides to help you locate datasets by the year produced, by author, or by attributes of the dataset.

A code repository and accompanying data for incorporating imperfect theory into machine learning for improved prediction and explainability. Specifically, it focuses on the case study of the dimensions of a polymer chain in different solvent qualities. Jupyter Notebooks for quickly testing concepts and reproducing figures, as well as source code that computes the mean squared error as a function of dataset size for various machine learning models are included.For additional details on the data, please refer to the README.md associated with the data.

Internet of Things (IoT) is comprised of interacting networks of physical, computational, and human components that coordinate to fulfill time-sensitive functions in their environment. The development of these systems spans all industrial sectors and demands collaborative effort between research and development teams from multiple institutions. Realizing the full potential of IoT requires interoperability between heterogeneous systems and development processes supported by robust platforms for experimentation and testing across domains.