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Gale A. Holmes, Edward D. McCarthy, Nathanael A. Heckert, Stefan D. Leigh, Jae Hyun Kim, Jeffrey W. Gilman
The mechanical integrity of a structural composite is strongly affected by the strength and toughness of the fibermatrix interface/interphase (Norwood, 1994)
This paper discusses the potential advantages and pitfalls of using semantic web technologies in the process of preparing engineering analyses. Analytical tools
Erdem Coskun, Pawel Jaruga, Leona D. Scanlan, Alessandro Tona, Mark S. Lowenthal, Prasad T. Reddy, M Miral Dizdar, Ann-Sofie Jemth, Olga Loseva, Thomas Helleday
Introduction: In aerobic organisms, intracellular metabolism and exogenous sources such as ionizing radiation and carcinogenic compounds generate reactive
This paper presents the design of a disposable biosimulant human tissue artifact system for robot safety testing. It is used to show a clear sign of the severe
Bala Muralikrishnan, Christopher J. Blackburn, Prem K. Rachakonda, Daniel S. Sawyer
Hand-held touch probes and laser scanners are increasing the scope and applicability of laser trackers. While methods to evaluate the performance of laser
Detleff Bergmann, Bernd Bodermann, Harald Bosse, Egbert Buhr, Gaoliang Dai, Ronald G. Dixson, W H?er-Grohne
We report the initial results of a recent bilateral comparison of linewidth or critical dimension (CD) calibrations on photo-mask line features between two
This paper discusses the potential advantages and pitfalls of using semantic web technologies for representing and integrating modeling and analysis tools
Prem K. Rachakonda, Balasubramanian Muralikrishnan, Craig M. Shakarji, Vincent D. Lee, Daniel S. Sawyer
The Dimensional Metrology Group (DMG) at the National Institute of Standards and Technology (NIST) is supporting the development of documentary standards for
Alexander Brodsky, Guodong Shao, Mohan Krishnamoorthy, Anantha Narayanan Narayanan, Daniel Menasce?, Ronay Ak
In this paper, we propose an architectural design and software framework for fast development of descriptive, predictive, diagnostic, and prescriptive analytics
Leona D. Scanlan, Pawel Jaruga, Sanem Hosbas Coskun, Jamie L. Almeida, David N. Catoe, Jennifer McDaniel, Miral M. Dizdar
Little is known about endogenous DNA damage in the nematode. In this work, we standardized the growth of the nematode in two different growth media (axenic CeHR
Vincent D. Lee, Steven D. Phillips, Craig M. Shakarji, Jeffrey Hosto, Jeffrey Huber, Gillich Barbara
Dimensional metrology is a foundational science finding applications throughout modern technology, including the testing of human-worn body armor designed to
Enterprise networks are migrating to the public cloud to acquire computing resources for a number of promising benefits in terms of efficiency, expense, and
David J. Lechevalier, Ronay Ak, Steven Hudak, Yung-Tsun T. Lee, Sebti Foufou
Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to
Data analytics is increasingly becoming recognized as a valuable set of tools and techniques for improving performance in the manufacturing enterprise. However
Understanding the sources of, and quantifying the magnitude of, uncertainty can improve decision-making and, thereby, make manufacturing systems more efficient
Bonnie J. Dorr, Craig Greenberg, Peter Fontana, Mark A. Przybocki, Marion Le Bras, Cathryn A. Ploehn, Oleg Aulov, Wo L. Chang
The Information Access Division (IAD) of the National Institute of Standards and Technology (NIST) launched a new Data Science Research Program (DSRP) in the
Yunpeng Li, Utpal Roy, Seungjun Shin, Yung-Tsun Lee
Today's physical products are becoming smarter not only because of their increasingly complex functionalities, but also for their superior capabilities of
Molecular transport through permeable membranes offers a unique opportunity to investigate cellular responses to nutrients, drugs, or toxins delivered to the
Benjamin Y. Choo, Peter A. Beling, Amy LaViers, Jeremy Marvel, Brian A. Weiss
Adaptive multi-scale prognostics and health management (AM-PHM) is a methodology designed to support PHM in smart manufacturing systems. AM-PHM is characterized
M Malinowski, Peter A. Beling, Amy LaViers, Jeremy Marvel, Brian A. Weiss
The development of risk analysis, and prognostics and health management (PHM) have developed in a largely independent fashion. However, both fields share a
Brian A. Weiss, Gregory W. Vogl, Moneer Helu, Guixiu Qiao, Joan Pellegrino, Mauricio Justiniano, Anand Raghunathan
The National Institute of Standards and Technology (NIST) hosted the Roadmapping Workshop - Measurement Science for Prognostics and Health Management for Smart
Gerald Heddy, Umer Huzaifa, Peter A. Beling, Yacov Haimes, Jeremy Marvel, Brian A. Weiss, Amy LaViers
The vision of Smart Manufacturing Systems (SMS) includes collaborative robots that can adapt to a range of scenarios. This vision requires a classification of
A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a
Adam S. Jacoff, Kamel Saidi, Robert Von Loewenfeldt, Yukio Koibuchi
The present paper discusses the NIST and DHS efforts to develop standard test methods for aquatic response robots. Different ROVs and AUVs were used to evaluate
Critical dimension atomic force microscopes (CD-AFMs) use flared tips and two-dimensional sensing and control of the tip-sample interaction to enable scanning
Bonnie J. Dorr, Peter C. Fontana, Craig S. Greenberg, Mark A. Przybocki, Marion Le Bras, Cathryn A. Ploehn, Oleg Aulov, Martial Michel, Edmond J. Golden III, Wo L. Chang
We examine foundational issues in data science including current challenges, basic research questions, and expected advances, as the basis for a new Data
David A. Howe, Archita Hati, Craig W. Nelson, Lora L. Nugent-Glandorf
We describe operational challenges and progress of optical frequency-comb dividers (OFDs) that synthesize RF signals from the optical domain. Our priorities
David Lechevalier, Seungjun Shin, Jungyub Woo, Sudarsan Rachuri, Sebti Foufou
Real data from manufacturing processes are essential to create useful insights for decision-making. However, acquiring real manufacturing data can be expensive