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Data for Intrinsic DAC calculations
Data provided by National Institute of Standards and Technology
Results of calculations and simulations for the Intrinsic Direct Air Capture analysis of Metal Organic Framwork (MOF) sorbents.Includes Grand Canonical Monte Carlo (GCMC) simulations, predictions of the Specific Heat Capacities (CV), and Intrinsic Direct Air Capture (DAC) calculations for MOF sorbents.
Tags: Direct Air Capture,machine learning,thermodynamics,Solid Sorbents,MOFs,
Modified: 2025-04-06
Sim-PROCESD: Simulated-Production Resource for Operations and Conditions Evaluation to Support Decision-making
Data provided by National Institute of Standards and Technology
Sim-PROCESD is a discrete event simulation package written in Python that is designed to model the behavior of discrete manufacturing systems. Specifically, it focuses on asynchronous production lines. It also provides functionality for modeling the degradation and maintenance of machines in these systems. Sim-PROCESD provides class definitions for manufacturing devices/components that can be configured by the user to model various real-world manufacturing systems.
Tags: discrete-event simulation,manufacturing,production,maintenance,python,
Modified: 2025-04-06
Data related to the investigation of UUIDs for a standards-based digital thread of product data in ISO 10303-242
Data provided by National Institute of Standards and Technology
This dataset contains data used in the investigation of Universally Unique Identifiers (UUIDs) that will enable a standards-based digital thread of product data in ISO 10303-242. Included are EXPRESS schema used for implementation and .stp files that were exported from native CAD (CATIA V5, Creo, and NX). UUIDs were assigned to CAD features during .stp export for each of the four design iterations.
Tags: industrial data,standards,native CAD files,derived neutral files,ISO 10303,STEP,interoperability testing,digital thread,manufacturing,model-based enterprise,lifecycle,Universally Unique Identifiers,UUID,Persistent Identifiers,PID,
Modified: 2025-04-06
Human Observational Data in a Production Environment
Data provided by National Institute of Standards and Technology
A heterogeneous dataset of human measurement data and human-generated text. This dataset was generated by TechSolve Inc. (techsolve.org) as a collaborative effort with NIST. Respondents were asked to observe and evaluate a machining process in which a rotary bit (the "tool") removed layers of a workpiece until the tool was worn to exhaustion. One trial and 19 official experiments were completed, one for each of 20 tools.
Tags: language processing,technical language processing,text,manufacturing,machining,process measurement and control,image and signal processing,
Modified: 2025-04-06
Workshop Data on Autonomous Methodologies for Accelerating X-ray Measurements
Data provided by National Institute of Standards and Technology
The National Institute of Standards and Technology and the International Centre for Diffraction Data co-hosted a workshop on 17-18 October 2023 to identify and prioritize the goals, challenges, and opportunities for critical and emerging technology needs within industry, with an emphasis on leveraging artificial intelligence, data-driven methodologies, and high-throughput and automated workflows for accelerating x-ray-based structural analysis for materials development and manufacturing.
Tags: Artificial Intelligence,machine learning,Autonomous Laboratories,diffraction,Materials Synthesis and Characterization,robotics,
Modified: 2025-04-06
Noise Datasets for Evaluating Deep Generative Models
Data provided by National Institute of Standards and Technology
Synthetic training and test datasets for experiments on deep generative modeling of noise time series. Consists of data for the following noise types: 1) band-limited thermal noise, i.e., bandpass filtered white Gaussian noise, 2) power law noise, including fractional Gaussian noise (FGN), fractional Brownian motion (FBM), and fractionally differenced white noise (FDWN), 3) generalized shot noise, 4) impulsive noise, including Bernoulli-Gaussian (BG) and symmetric alpha stable (SAS) distributions.
Tags: generative adversarial network,machine learning,time series,band-limited noise,power law noise,shot noise,impulsive noise,colored noise,fractional Gaussian noise,fractional Brownian motion,
Modified: 2025-04-06
Microplastic and nanoplastic chemical characterization by thermal desorption and pyrolysis mass spectrometry with unsupervised machine learning
Data provided by National Institute of Standards and Technology
This data publication contains the mass spectrometry chemical characterization of microplastic and nanoplastic chemical analysis. The data from this study includes mass spectra of pure, mixed, and weathered microplastics and nanoplastics at high and low fragmentation, extracted ion chronograms, Kendrick mass defect plots, code, and the derived and processed data. The data analysis code (MATLAB 2022a*) used for unsupervised learning of cluster and compositional relationships is also included.
Tags: Microplastic,Nanoplastics,environment,mass spectrometry,GC-MS,Chemical Characterization,machine learning,
Modified: 2025-04-06
ns-3 ORAN Module
Data provided by National Institute of Standards and Technology
This module for ns-3 implements the classes required to model a network architecture based on the O-RAN Alliance's specifications. These models include a Radio Access Network (RAN) Intelligent Controller (RIC) that is functionally equivalent to O-RAN's Near-Real Time (Near-RT) RIC, and reporting modules that attach to simulation nodes and serve as communication endpoints with the RIC in a similar fashion as the E2 Terminators in O-RAN.
Tags: Artificial Intelligence,machine learning,Open RAN,RAN Intelligent Controller,
Modified: 2025-04-06
Towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) MIg analyZeR (mizr) Package
Data provided by National Institute of Standards and Technology
Our work towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) aims to provide plots, tools, methods, and strategies to extract insights out of various machine learning (ML) and Artificial Intelligence (AI) data.Included in this software is the MIg analyZeR (mizr) R software package that produces various plots.
Tags: analysis software,Artificial Intelligence,machine learning,design of experiments,
Modified: 2025-04-06
A Data-Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U-nets and Generative Adversarial Networks
Data provided by National Institute of Standards and Technology
Digital light processing (DLP) vat photopolymerization (VP) additive manufacturing (AM) uses patterned UV light to selectively cure a liquid photopolymer into a solid layer. Subsequent layers are printed on to preceding layers to eventually form a desired 3 dimensional (3D) part. This data set characterizes the 3D geometry of a single layer of voxels (volume pixels) printed with photomasks assigned random intensity levels at every pixel. The masks are computer generated, then printed onto a glass cover slide.
Tags: 3D printing,additive manufacturing,machine learning,generative adversarial network,Photopolymer,
Modified: 2025-04-06