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78 results found

Dataset of channels and received IEEE 802.11ay signals for sensing applications in the 60GHz band

Data provided by  National Institute of Standards and Technology

The dataset can be used to develop and test algorithms for communication and sensing in the 60GHz band. The dataset consists of synthetically generated indoor mm-wave channels between a MIMO transmitter and a MIMO receivers. Multiple targets are moving in the room. Number of targets, velocity of each target and trajectory are randomized across the dataset. The dataset contains also noisy received IEEE 802.11ay channel estimation fields. The dataset is suitable for development and testing of machine/deep learning algorithms.

Tags: Sensing,communication,millimeter wave,dataset,machine learning,deep learning,channel model,IEEE 802.11ay,IEEE 802.11bf,

Modified: 2024-02-22

Views: 0

**SUPERSEDED** Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks

Data provided by  National Institute of Standards and Technology

This software and data have been superseded. Please visit https://doi.org/10.18434/mds2-2532

Tags: generative adversarial network,machine learning,wireless communications,

Modified: 2024-02-22

Views: 0

Data Supporting "Seabird Tissue Archival and Monitoring Project (STAMP) Data from 1999-2010"

Data provided by  National Institute of Standards and Technology

Here we provide curated analytical chemistry data for eggs collected from 1999 to 2010 on a subset of species and analytes that were measured regularly and reasonably systematically. Included in this publication are 487 samples analyzed for 174 ubiquitous environmental contaminants such as (poly)brominated diphenyl ethers (BDEs), mercury, organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs). Data were collated to form a dataset useful in chemometric and related analyses of the marine ecosystem in the north Pacific Ocean.

Tags: NIST Biorepository,eggs,tissues,BDEs,PBDEs,PCBs,Pesticides,mercury,trace elements,heavy metals,organic,inorganic,chemistry,stable isotopes,genetics,Environment and Climate,chemometric,machine learning,ML,seabird,bird,Pacific Ocean,

Modified: 2024-02-22

Views: 0

ANDiE: the Autonomous Neutron Diffraction Explorer.

Data provided by  National Institute of Standards and Technology

ANDiE the Autonomous Neutron Diffraction Explorer is a tool for autonomously discovering the magnetic transition temperature and transition dynamics of a material from neutron diffraction experiments. The Jupyter notebooks used to implement ANDiE can be found here: https://github.com/usnistgov/ANDiE-v1_0 The Jupyter notebooks contained therein are of ANDiE as implemented at the WAND2 instrument at the HB-2C beamline at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL).

Tags: Autonomous Experiments,neutron diffraction,machine learning,Active Learning,Artificial Intelligence,

Modified: 2024-02-22

Views: 0

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

Data for Modeling OFDM Communication Signals with Generative Adversarial Networks

Data provided by  National Institute of Standards and Technology

This repository contains results for experiments on generative modeling of synthetic Orthogonal-Frequency Division Multiplexing (OFDM) communication signals. (This record supersedes Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks, formerly at https://doi.org/10.18434/mds2-2428)

Tags: generative adversarial network,machine learning,wireless communications,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-question-answering-sep2021-test

Data provided by  National Institute of Standards and Technology

Round 8 Test DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 360 QA AI models using a small set of model architectures.

Tags: Trojan Detection,Artificial Intelligence,ai,machine learning,Adversarial Machine Learning,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-question-answering-sep2021-holdout

Data provided by  National Institute of Standards and Technology

Round 8 Holdout DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Tags: Trojan Detection,Artificial Intelligence,ai,machine learning,Adversarial Machine Learning,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-summary-jan2022-train

Data provided by  National Institute of Standards and Technology

Round 9 Train DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Tags: Trojan Detection,Artificial Intelligence,ai,machine learning,Adversarial Machine Learning,

Modified: 2024-02-22

Views: 0

Dataset for paper Y. Ma, S. Mosleh and J. Coder, "Analyzing 5G NR-U and WiGig Coexistence with Multiple-Beam Directional LBT," 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022, pp. 272-275, doi: 10.1109/CCNC49033.2022.9700690

Data provided by  National Institute of Standards and Technology

This project produces synthetic datasets of spectrum sharing simulation results (I/Q data, metadata, and KPIs).

Tags: wireless coexistence,Spectrum sharing,machine learning,wireless communications and networks,4G,5G,6G,Wi-Fi,

Modified: 2024-02-22

Views: 0