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85 results found

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: 2024-02-22

Views: 0

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: 2024-02-22

Views: 0

4D-STEM characterization results from a thermal annealing series of poly(3[2-(2-methoxyethoxy)ethoxy]-methylthiophene-2,5-diyl) organic electrochemical transistor films

Data provided by  National Institute of Standards and Technology

This repository contains two types of datasets: 4D-STEM data collected from a thermal annealing series of P3MEEMT films. 4D-STEM data:Dose series: Collected from P3MEEMT film annealed at 115 C. Each HDF5 file was generated from the raw data using the fpdpy software package to reshape and embed metadata. No other preprocessing was performed. Annealing series: Collected from P3MEEMT films annealed at 75 C, 115 C, 145 C, and 175 C. Each temperature contains two sets of 4D-STEM data collected at low and high magnification.

Tags: Advanced Materials,Organic Semiconductors,4D-STEM,OECT,TEM,GIWAXS,

Modified: 2024-02-22

Views: 0

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: 2024-02-22

Views: 0

A Synthetic Methodology for Preparing Impregnated and Grafted Amine-Based Silica-Composites for Carbon Capture

Data provided by  National Institute of Standards and Technology

The database includes thermal data analysis for silica-composites that conclude the loading amount of amine adsorbents of each composite as well as each specimen's ability to adsorb CO2. The data repository includes raw data files for: thermogravimetric analysis (TGA) weight loss and CO2 adsorption traces, and Fourier Transform Infrared Spectroscopy (FTIR) spectra?s. For more information see the readme and data documentation. A complete manuscript describing data collection, analysis, and database documentation is to be published. File formats for data include: .txt and .csv.

Tags: FTIR,thermal analysis,DSC,TGA,optical microscopy,Advanced Materials,direct air capture materials,

Modified: 2024-02-22

Views: 0