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36 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: 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

O-RAN with Machine Learning in ns-3

Data provided by  National Institute of Standards and Technology

This dataset contains a comparison of packet loss counts vs handovers using four different methods: baseline, heuristic, distance, and machine learning, as well as the data used to train a machine learning model. This data was generated as a result of the work described in the paper, "O-RAN with Machine Learning in ns-3," by the authors Wesley Garey, Tanguy Ropitault, Richard Rouil, Evan Black, and Weichao Gao from the 2023 Workshop on ns-3 (WNS3 2023), that was June 28-29, 2023, in Arlington, VA, USA, and published by ACM, New York, NY, USA.

Tags: O-RAN,ns-3,LTE,ONNX,Mobile Networks,modeling and simulation,machine learning,

Modified: 2025-04-06

Data for "Preparing for 6G: Developing best practices and standards for industrial measurements of low-loss dielectrics"

Data provided by  National Institute of Standards and Technology

Data for "Preparing for 6G: Developing best practices and standards for industrial measurements of low-loss dielectrics"

Tags: Dielectrics,measurements,mmWave,Standard Reference Material,

Modified: 2025-04-06

Electric field inhomogeneity

Data provided by  National Institute of Standards and Technology

Measurement of the effect of electric field inhomogeneity on electromagnetically induced transparency in a waveguide-based cesium atomic vapor cell. Used for the figure for the Photonics West 2023 manuscript.

Tags: Rydberg atoms,atomic physics,receivers,fields strength,electric field,volts/meter,

Modified: 2025-04-06

Phase-Resolved Rydberg Atom Field Sensing using Quantum Interferometry

Data provided by  National Institute of Standards and Technology

Although Rydberg atom-based electric field sensing provides key advantages over traditional antenna-based detection, it remains limited by the need for a local oscillator (LO) for low-field and phase resolved detection. In this work, we demonstrate the general applicability of closed-loop quantum interferometric schemes for Rydberg field sensing, which eliminate the need for an LO. We reveal that the quantum-interferometrically defined phase and frequency of our scheme provides an internal reference that enables LO-free full 360 degree-resolved phase sensitivity.

Tags: Rydberg atoms,atomic physics,receivers,fields strength,electric field,volts/meter,

Modified: 2025-04-06

Data for the article " Pseudo-resonant Detection of `Low Frequency' VHF Electric Fields via Rabi Matching with Autler-Townes Splitting in Rydberg Atoms"

Data provided by  National Institute of Standards and Technology

This dataset represents absorption/transmission spectra of resonant probe light power through a Rydberg atom vapor, subject to a simultaneous dressing field and a 'low frequency' field. Data is taken as an oscilloscope average of 5 photodiode voltage traces, with frequency offsets given by a simultaneous reference cell (not included). Some data are given as 2-D arrays, with axes of laser detuning across a waterfall of field strength. Some data represents theory eigen-energies of the system, for comparison. This paper will be submitted to Physical Review Letters.

Tags: Rydberg atoms,atomic physics,receivers,fields strength,electric field,volts/meter,

Modified: 2025-04-06

Segmentation of lipid nanoparticles from cryogenic electron microscopy images

Data provided by  National Institute of Standards and Technology

Lipid nanoparticles (LNPs) were prepared as described (https://doi.org/10.1038/s42003-021-02441-2) using the lipids DLin-KC2-DMA, DSPC, cholesterol, and PEG-DMG2000 at mol ratios of 50:10:38.5:1.5. Four sample types were prepared: LNPs in the presence and absence of RNA, and with LNPs ejected into pH 4 and pH 7.4 buffer after microfluidic assembly. To prepare samples for imaging, 3 ?L of LNP formulation was applied to holey carbon grids (Quantifoil, R3.5/1, 200 mesh copper).

Tags: Lipid Nanoparticle,LNP,cryogenic electron microscopy,CryoEM,machine learning,ai,mRNA,

Modified: 2025-04-06

Modeling Line Broadening and Distortion Due to Inhomogeneous Fields for Rydberg Electrometry

Data provided by  National Institute of Standards and Technology

This set corresponds to a (pending) publication, where we attempt to model spectral features appearing in the lab by calculating many segments of an inhomogeneous field. Every data set here is a transmission value, either normalized to 1 in modeled data, or an arbitrary-scaled voltage reading from a photodiode onto an oscilloscope. These are given in scans over coupling photon detuning, delta_C, which is divided by 2 pi, and given in MHz. Arrays are scans over delta_C, and position/fieldstrength, for figure 3.

Tags: Rydberg atoms,atomic physics,receivers,fields strength,electric field,volts/meter,

Modified: 2025-04-06