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Publications

Search Publications by

Amanda Koepke (Fed)

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Displaying 1 - 12 of 12

NIST Software Package for Obtaining Charpy Transition Curves

May 11, 2021
Author(s)
Enrico Lucon, Jolene Splett, Amanda Koepke, David Newton
NIST has developed a software package that allows users to fit test results obtained from Charpy or toughness tests as a function of test temperature, thereby obtaining so-called transition curves. Non-linear fitting is available for five regression models

Decision Tree for Key Comparisons

April 27, 2021
Author(s)
Antonio Possolo, Amanda Koepke, David Newton, Michael R. Winchester
This contribution describes a Decision Tree intended to guide the selection of statistical models and data reduction procedures in key comparisons (KCs). The Decision Tree addresses a specific need of the Inorganic Analysis Working Group (IAWG) of the

Generative Adversarial Network Performance in Low-Dimensional Settings

April 20, 2021
Author(s)
Felix M. Jimenez, Amanda Koepke, Mary Gregg, Michael R. Frey
A generative adversarial network (GAN) is an artificial neural network with a distinctive training architecture, designed to create examples that faithfully reproduce a target distribution. GANs have recently had particular success in applications

Examining Recent HR Data for Gender Bias Among Federal Employees at NIST

March 26, 2021
Author(s)
Jasmine Evans, Amanda Koepke, Steven Lund, Mary Theofanos
This report is part of a multi-phase mixed methods project that is designed to provide an in-depth look at the population of National Institute of Standards and Technology (NIST) federal employees to identify factors, attitudes, and processes that might

Frequency Ratio Measurements with 18-Digit Accuracy Using a Network of Optical Clocks

March 24, 2021
Author(s)
Kyle Beloy, Martha I. Bodine, Tobias B. Bothwell, Samuel M. Brewer, Sarah L. Bromley, Jwo-Sy Chen, Jean-Daniel Deschenes, Scott Diddams, Robert J. Fasano, Tara Fortier, Youssef Hassan, David Hume, Dhruv Kedar, Colin J. Kennedy, Isaac Kader, Amanda Koepke, David Leibrandt, Holly Leopardi, Andrew Ludlow, Will McGrew, William Milner, Daniele Nicolodi, Eric Oelker, Tom Parker, John M. Robinson, Stefania Romisch, Stefan A. Schaeffer, Jeffrey Sherman, Laura C. Sinclair, Lindsay I. Sonderhouse, William C. Swann, Jian Yao, Jun Ye, Xiaogang Zhang
Atomic clocks occupy a unique position in measurement science, exhibiting higher accuracy than any other measurement standard and underpinning six out of seven base units in the SI system. By exploiting higher resonance frequencies, optical atomic clocks

Channel Sounder Measurement Verification: Conducted Tests

April 15, 2020
Author(s)
Jeanne T. Quimby, Jeffrey A. Jargon, Rodney W. Leonhardt, Jake D. Rezac, Paul D. Hale, Catherine A. Remley, Amanda A. Koepke, Robert Johnk, chriss Hammerschmidt, Paul Mckenna, Irena Stange, Mike Chang
Channel modeling often provides a basis for the design and deployment of wireless technology. Engineers design systems to operate under certain expected channel conditions. Channel models are typically based on the statistics of a collection of many

Verifying the Performance of a Correlation-Based Channel Sounder in the 3.5 GHz Band with a Calibrated Vector Network Analyzer

December 12, 2019
Author(s)
Jeffrey A. Jargon, Jeanne T. Quimby, Catherine A. Remley, Amanda A. Koepke, Dylan F. Williams
We verified the performance of a correlation-based channel sounder in the 3.5 GHz band with a calibrated vector network analyzer by comparing measurements in a stable, coaxial environment at the same reference planes. The purpose of this experiment was to

Monte Carlo Sampling Bias in the Microwave Uncertainty Framework

June 27, 2019
Author(s)
Michael R. Frey, Benjamin Jamroz, Amanda Koepke, Jake Rezac, Dylan Williams
The Microwave Uncertainty Framework (MUF) is a software suite created, supported, and made publicly available by the Radio Frequency Division of the U.S. National Institute of Standards and Technology. The general purpose of the MUF is to provide automated

Quantifying Variance Components for Repeated Scattering-Parameter Measurements

December 1, 2017
Author(s)
Amanda A. Koepke, Jeffrey A. Jargon
We quantify random uncertainties for scattering-parameters repeatedly measured with a vector network analyzer (VNA), focusing on variations due to multiple calibrations, disconnects, and repeat measurements. We describe a two-stage nested design, which