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Closed-loop Autonomous Materials Exploration and Optimization 1.0
Data provided by National Institute of Standards and Technology
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.
Tags: autonomous,machine learning,phase map,materials optimization,
Modified: 2024-02-22
Views: 0
Optical scattering measurements and simulation data for one-dimensional (1-D) patterned periodic sub-wavelength features
Data provided by National Institute of Standards and Technology
This data set consists of both measured and simulated optical intensities scattered off periodic line arrays, with simulations based upon an average geometric model for these lines. These data were generated in order to determine the average feature sizes based on optical scattering, which is an inverse problem for which solutions to the forward problem are calculated using electromagnetic simulations after a parameterization of the feature geometry.
Tags: electromagnetic simulations,simulations,experimental,angle-resolved scattering,scattering,gratings,patterned semiconductors,semiconductors,scatterfield microscopy,bright-field microscopy,microscopy,inverse problems,machine learning,
Modified: 2024-02-22
Views: 0
Simulated Radar Waveform and RF Dataset Generator for Incumbent Signals in the 3.5 GHz CBRS Band
Data provided by National Institute of Standards and Technology
This software tool generates simulated radar signals and creates RF datasets. The datasets can be used to develop and test detection algorithms by utilizing machine learning/deep learning techniques for the 3.5 GHz Citizens Broadband Radio Service (CBRS) or similar bands. In these bands, the primary users of the band are federal incumbent radar systems. The software tool generates radar waveforms and randomizes the radar waveform parameters.
Tags: 3.5 GHz,CBRS,LTE,ESC,radar,radio frequency signals,spectrum,machine learning,deep learning,detection,
Modified: 2024-02-22
Views: 0
Active Evaluation Software for Selection of Ground Truth Labels
Data provided by National Institute of Standards and Technology
This software repository contains a python package Aegis (Active Evaluator Germane Interactive Selector) package that allows us to evaluate machine learning systems's performance (according to a metric such as accuracy) by adaptively sampling trials to label from an unlabeled test set to minimize the number of labels needed. This includes sample (public) data as well as a simulation script that tests different label-selecting strategies on already labelled test sets. This software is configured so that users can add their own data and system outputs to test evaluation.
Tags: active evaluation,machine learning,ar,
Modified: 2024-02-22
Views: 0
High Accuracy Near-infrared Carbon Dioxide Intensity Measurements to Support Remote Sensing
Data provided by National Institute of Standards and Technology
Data files for the publication "High Accuracy Near-infrared Carbon Dioxide Intensity Measurements to Support Remote Sensing" in Geophysical Research Letters
Tags: greenhouse gases,carbon dioxide,remote sensing,
Modified: 2024-02-22
Views: 0
Challenge Round 0 (Dry Run) Test Dataset
Data provided by National Institute of Standards and Technology
This dataset was an initial test harness infrastructure test for the TrojAI program. It should not be used for research. Please use the more refined datasets generated for the other rounds. The data being generated and disseminated is training, validation, and test data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.).
Tags: Trojan Detection,Artificial Intelligence,ai,machine learning,Adversarial Machine Learning,
Modified: 2024-02-22
Views: 0
Data from Laboratory Tests of a Prototype Carbon Dioxide Ground-Source Air Conditioner
Data provided by National Institute of Standards and Technology
These data from the laboratory tests of a prototype residential liquid-to-air ground-source air conditioner (GSAC) using CO2 as the refrigerant. The data collection and processing methods are described in detail in this report:
Report Title: "Laboratory Tests of a Prototype Carbon Dioxide Ground-Source Air Conditioner", NIST Technical Note 2068
Publication Date: October 2019
DOI: https://doi.org/10.6028/NIST.TN.2068
Authors: Harrison Skye, Wei Wu
Tags: Air conditioner,carbon dioxide,CO2,ground-source heat pump,subcritical and transcritical cycles,
Modified: 2024-02-22
Views: 0
ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models
Data provided by National Institute of Standards and Technology
This software is a Python module for estimating uncertainty in predictions of machine learning models. It is a Python package that calculates uncertainties in machine learning models using bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work.
Tags: uncertainty analysis,machine learning,model calibration,
Modified: 2024-02-22
Views: 0
Hestia Fossil Fuel Carbon Dioxide Emissions Inventory for Los Angeles Basin
Data provided by National Institute of Standards and Technology
Hestia Project quantifies, simulates and visualizes greenhouse gases such as carbon dioxide emitted in urban regions. Los Angeles basin activity is provided at the 1 km grid spatial resolution, and at temporal resolutions of hourly or annually. Hestia-LA urban CO2 emissions inventory builds upon work conducted at the national scale (Vulcan Project) that includes various sectorial attributions. Hestia's high spatial and temporal resolution datasets are currently available for 2010 to 2015, in UTC or local time.
Tags: Greenhouse Gas,carbon dioxide,CO2,Urban Emissions,Carbon Monitoring,Atmospheric Modeling,Los Angeles Basin,California,Megacities,Fossil Fuel,Bottom-up Emissions Inventory,
Modified: 2024-02-22
Views: 0
Hestia Fossil Fuel Carbon Dioxide Emissions for Indianapolis, Indiana
Data provided by National Institute of Standards and Technology
Hestia Project quantifies, simulates and visualizes greenhouse gases such as carbon dioxide emitted in urban regions. Indianapolis data is provided at the county level (200 m grid resolution), and at hourly and yearly time frames. It builds upon work conducted at the national scale by the Vulcan Project. These high spatial and temporal resolution datasets are available from 2010 to 2015.
Tags: Greenhouse Gas,carbon dioxide,CO2,Urban Emissions,Carbon Monitoring,Atmospheric Modeling,Indianapolis,Indiana,Fossil Fuel,Bottom-up Inventory,
Modified: 2024-02-22
Views: 0