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1313 results found

Data associated with publication titled "SINGLE-MODULATOR, DUAL COMB SERRODYNE SPECTROSCOPY" as published in Optics Letters, 49(14): 3878-3881 (2024).

Data provided by  National Institute of Standards and Technology

Data associated with publication titled "SINGLE-MODULATOR, DUAL COMB SERRODYNE SPECTROSCOPY" as published in Optics Letters, 49(14): 3878-3881 (2024).

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Reference Material (RM) 8210 Hemp Plant Data

Data provided by  National Institute of Standards and Technology

RM 8210 Electronic files containing certified values and their uncertainties, and the data used to assign those values.

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TREC Authoring Tools for Multimedia Content (AToMiC) Track 2023

Data provided by  National Institute of Standards and Technology

Individual user responsibility: working data, derived data Data must be backed up using a tested/automated process: working data, derived data; published data resource data Not available to the public: working data; derived data Made available to the public as described below: Published data and Resource data

The Authoring Tools for Multimedia Content (AToMiC) Track aims to build reliable benchmarks for multimedia search systems. The focus of this track is to develop and evaluate IR techniques for text-to-image and image-to-text search problems.

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Source: https://pages.nist.gov/trec-browser/trec32/atomic/overview/

Data associated with Newbury & Ritchie "Testing the Accuracy of Low Beam Energy Electron-Excited X-ray Microanalysis with Energy Dispersive Spectrometry "

Data provided by  National Institute of Standards and Technology

Data supporting: "The accuracy of electron-excited X-ray microanalysis with energy dispersive spectrometry (EDS) has been tested in the low beam energy range, specifically at an incident beam energy of 5 keV, which is the lowest beam energy for which a useful characteristic X-ray peak can be excited for all elements of the periodic table, excepting H and He.

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Rydberg Atom Electrometry: Recent Sensitivity and Bandwidth Improvements

Data provided by  National Institute of Standards and Technology

We present recent improvements within the growing field of Rydberg atom sensors. While initially started as a path towards absolute, independent measurements of electric fields, the research landscape has evolved into the realm of quantum sensors and receivers. We discuss the capabilities and limitations of Rydberg atom receivers, and we show how different atomic properties enhance or limit sensitivity and bandwidth.

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Microwave oven interference measurements at 2.4 GHz

Data provided by  National Institute of Standards and Technology

The 2.4 GHz ISM band is shared by Wi-Fi, Bluetooth, Wireless HART, ISA100.11a, and several other industrial wireless systems. This band also includes microwave ovens which produce interference that disrupt communications within their vicinity, therefore, understanding and monitoring for interference from these types of radio emissions sources is crucial to ensure an optimal wireless user experience. Microwave ovens are common radio interference sources that disrupt the operation of the wireless networks in industrial environments.

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Trojan Detection Software Challenge - llm-pretrain-apr2024-train

Data provided by  National Institute of Standards and Technology

TrojAI llm-pretrain-apr2024 Train Dataset

This is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists Llama2 Large Language Models refined using fine-tuning and LoRA to perform next token prediction. A known percentage of these trained AI models have been poisoned with triggers which induces modified behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers into the model weights.

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Source: https://drive.google.com/drive/folders/1eI7MsVi1qqSHvnfCUWkgNnphTk0Cth5M?usp=sharing

Trojan Detection Software Challenge - llm-pretrain-apr2024-test

Data provided by  National Institute of Standards and Technology

TrojAI llm-pretrain-apr2024 Test Dataset

This is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists Llama2 Large Language Models refined using fine-tuning and LoRA to perform next token prediction. A known percentage of these trained AI models have been poisoned with triggers which induces modified behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers into the model weights.

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Source: https://drive.google.com/drive/folders/1klFznLk0BkQSnW0Am4QulVViEBQPB5WY?usp=drive_link

2-Ethylbiphenyl: Experimental and Derived Thermodynamic Properties

Data provided by  National Institute of Standards and Technology

This document is part of a series of reports describing experimental property measurements completed at the National Institute for Petroleum and Energy Research (NIPER) in Bartlesville, Oklahoma, in the 1980s and 1990s. Members of the Bartlesville Thermodynamics Group included William D. "Bill" Good, William V. "Bill" Steele, Bruce E. Gammon, Norris K. Smith, Stephen E. Knipmeyer, An "Andy" Nguyen, Timothy D. Klots, I. A. "Alex" Hossenlopp, Aaron P. Rau, William B. Collier, John F. Messerly, Ann G. Osborn, Susan Lee-Bechtold, Donald G. Archer, Ian R.

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Data for "Enhanced Gain Extrapolation Technique: a third-order scattering approach for high-accuracy antenna gain, sparse sampling, at Fresnel distances"

Data provided by  National Institute of Standards and Technology

In this paper we describe an enhanced three-antenna
gain extrapolation technique that allows one to determine antenna
gain with significantly fewer data points and at closer
distances than with the well-established traditional three-antenna
gain extrapolation technique that has been in use for over
five decades. As opposed to the traditional gain extrapolation
technique, where high-order scattering is purposely ignored so
as to isolate only the direct antenna-to-antenna coupling, we show

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