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Search Publications by: John Lu (Fed)

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Displaying 1 - 23 of 23

Certification of Standard Reference Material(R) 2196 Axial Resolution Standard for Optical Medical Imaging

February 7, 2023
Author(s)
Jeeseong C. Hwang, Kimberly Briggman, Nikki Rentz, Hyun-Jin Kim, David W. Allen, Lee J. Richter, Sowon Yoon, John Lu
Medical imaging devices and systems must be calibrated to ensure uniformity and reliability of test results. A standard reference material (SRM) or "phantom", as it is known in the medical imaging community, is used to replicate fundamental characteristics

Sensors and Machine Learning Models to Prevent Cooktop Ignition and Ignore Normal Cooking

July 28, 2021
Author(s)
Amy Mensch, Anthony Hamins, Wai Cheong Tam, John Lu, Kathryn Markell, Christina You, Matthew Kupferschmid
According to a recent NFPA report, 49 % of reported home fires involve cooking equipment, with cooktops accounting for 87 % of cooking-fire deaths and 80 % of the civilian injuries [1, 2]. Between 2014–2018, U.S. fire departments responded to an estimated

Sensors and Machine Learning Models to Prevent Cooktop Ignition and Ignore Normal Cooking

March 18, 2021
Author(s)
Amy Mensch, Anthony Hamins, Andy Tam, John Lu, Kathryn Markell, Christina You, Matthew Kupferschmid
Cooking equipment is involved in nearly half of home fires in the United States, with cooktop fires the leading cause of deaths and injuries in cooking-related fires. In this study, we evaluate 16 electrochemical, optical, temperature and humidity sensors

Reference Material 8634: Ethylene Tetrafluoroethylene for Particle Size Distribution and Morphology

May 1, 2019
Author(s)
Dean C. Ripple, Srivalli Telikepalli, Kristen L. Steffens, Michael J. Carrier, Christopher B. Montgomery, Nicholas W. Ritchie, John Lu
Reference Material (RM) 8634 is a NIST particle standard produced from abraded ethylene tetrafluoroethylene (ETFE), a chemically inert polymer, that will help standardize and allow more accurate monitoring of subvisible proteinaceous particles in

Statistical Analysis of Reader Measurement Variability in Nodule Sizing with CT Phantom Imaging Data

November 23, 2012
Author(s)
John Lu, Charles D. Fenimore, Nicholas Petrick, Rongping Zeng, Marios A. Gavrielides, David Clunie, Kristin Borradaile, Robert Ford, Hyun J. Kim, Michael McNitt-Gray, Binsheng Zhao, Andrew Buckler
RSNA has conducted a phantom quantitative imaging biomarker (QIBA) study to assess reader measurement variability of both spherical and non-spherical nodules using CT imaging. Statistical analysis of intra-reader and inter-reader variability of volume

Big Data Issues in Quantitative Imaging

August 29, 2012
Author(s)
Mary C. Brady, Alden A. Dima, Charles D. Fenimore, James J. Filliben, John Lu, Adele Peskin, Mala Ramaiah, Ganesh Saiprasad, Ram D. Sriram

Development of a Seebeck Coefficient Standard Reference Material (SRM)™

August 1, 2011
Author(s)
Nathan Lowhorn, Winnie Wong-Ng, John Lu, Joshua B. Martin, Martin L. Green, John E. Bonevich, Evan L. Thomas, Neil Dilley, Jeff Sharp
We have successfully developed a Seebeck coefficient Standard Reference Material (SRM™), Bi2Te3, that is essential for interlaboratory data comparison and for instrument calibration. Certification measurements were performed using a differential steady

Development of a Seebeck Coefficient Standard Reference Material

August 7, 2009
Author(s)
Nathan Lowhorn, Winnie Wong-Ng, John Lu, Evan L. Thomas, Makoto Otani, Martin L. Green, Neil Dilley, Jeffrey Sharp, Thanh N. Tran
We have successfully developed a Seebeck coefficient Standard Reference Material (SRM ), Bi2Te3, that is crucial for interlaboratory data comparison and for instrument calibration. Certification measurements were performed using two different techniques on

Statistical analysis of a round-robin measurement survey of two candidate materials for a Seebeck coefficient Standard Reference Material

February 2, 2009
Author(s)
John Lu, Nathan Lowhorn, Winnie Wong-Ng, Weiping Zhang, Evan L. Thomas, Makoto Otani, Martin L. Green, Thanh N. Tran, Chris Caylor, Neil Dilley, Adams Downey, B Edwards, Norbert Elsner, S Ghamaty, Timothy Hogan, Qing Jie, Qiang Li, Joshua B. Martin, George S. Nolas, H Obara, Jeffrey Sharp, Rama Venkatasubramanian, Rhonda Willigan, Jihui Yang, Terry Tritt
In an effort to develop a Standard Reference Material (SRM ) for Seebeck coefficient, we have conducted a round-robin measurement survey of two candidate materials undoped Bi2Te3 and constantan (55% Cu and 45% Ni alloy). Measurements were performed in two

Round-Robin Studies of Two Potential Seebeck Coefficient Standard Reference Materials

January 14, 2009
Author(s)
Nathan Lowhorn, Winnie K. Wong-Ng, Weiping Zhang, John Lu, Makoto Otani, Evan L. Thomas, Martin L. Green, Thanh Tran
The scientific activities of NIST include the development and distribution of standard reference materials (SRM) for instrument calibration and inter-laboratory data comparison. Full characterization of a thermoelectric material requires measurement of the

Form-Profiling of Optics Using the Geometry Measuring Machine and NIST M-48 CMM

January 1, 2006
Author(s)
Nadia Machkour-Deshayes, John R. Stoup, John Lu, Johannes A. Soons, Ulf Griesmann, Robert S. Polvani
We are developing an instrument, the Geometry Measuring Machine (GEMM), to measure the profile errors of aspheric and free form optical surfaces, which require measurement uncertainties near 1nm. Using GEMM, an optical profile is reconstructed from a set

Statistical Methods For Holistic Mass Spectral Analysis

Author(s)
John Lu, Charles M. Guttman
Analysis of molecular mass distribution data for characterizing the complex synthetic polymer structure has demanded new statistical methods. As with many other high throughput measurement devices, typically only very small number of replicates can be