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Petru S. Manescu, Young Jong Lee, Charles Camp, Marcus T. Cicerone, Mary C. Brady, Peter Bajcsy
This paper addresses the problem of classifying materials from microspectroscopical images at each pixel. The challenges lie in identifying discriminatory spectral features and obtaining accurate and interpretable models relating spectra and class labels
Antoine Vandecreme, Michael P. Majurski, Joe Chalfoun, Keana Scott, John Henry Scott, Mary C. Brady, Peter Bajcsy
This article aims at introducing readers to a web-based solution useful for interactive measurements of centimeter-sized specimens at nanoscales. Modern imaging technology has enabled nanoscale imaging to become a routine process. As the imaging technology
Development of smart city services is presently hindered because the data is too heterogeneous, despite the increasing availability of data in open data initiatives. We determined metadata fields and semantics for our proposed model after a survey of other
The My Data initiatives are part of the Administration's efforts to empower Americans with secure access to their own personal data, and to increase citizens' access to private-sector data-based applications and services. With its focus on personal data
William Z. Bernstein, Mahesh Mani, Katherine C. Morris, Kevin W. Lyons, Bjoern J. Johansson
With recent progress in developing more effective models for representing manufacturing processes, this paper presents an approach towards an open web-based repository for storing manufacturing process information. The repository is envisioned to include
Raunak Bhinge, Jinkyoo Park, Kincho H. Law, David Dornfeld, Moneer Helu, Sudarsan Rachuri
Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based energy prediction models have been proposed in the past to understand the
Spencer J. Breiner, Eswaran Subrahmanian, Ram D. Sriram
As we extend the reach of the Internet through sensing and automation, networked systems interact more and more of our daily lives, requiring much greater sensitivity to social networks and greater robustness in the face of human behavior. A tremendous
This is a slide for an invited panel talk at the First IEEE/ACM Symposium on Edge Computing on the need for research in edge computing and future standards related to video analytics in safety and security video network domains such as public safety.
On January 12-13, 2016 the National Institute of Standards and Technology's (NIST) Applied Cybersecurity Division (ACD) hosted the "Applying Measurement Science in the Identity Ecosystem" workshop to discuss the application of measurement science to
Yan Lu, Paul Witherell, Felipe F. Lopez, Ibrahim Assouroko
Software tools, knowledge of materials and process models, and data provide three pillars on which Additive Manufacturing (AM) lifecycles and value chains can be supported. These pillars leverage efforts dedicated to the development of AM databases, high
Moneer M. Helu, Don E. Libes, Joshua Lubell, Kevin W. Lyons, Katherine C. Morris
Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and
Roselyne B. Tchoua, Jian Qin, Debra Audus, Kyle Chard, Ian Foster, Juan de Pablo
Structured databases of materials properties play a central role in the everyday research activities of materials scientists. Researchers turn to these databases to quickly discover, query, compare, and aggregate various properties allowing for the
Bonnie J. Dorr, Craig Greenberg, Peter Fontana, Mark A. Przybocki, Marion Le Bras, Cathryn A. Ploehn, Oleg Aulov, Wo L. Chang
This article sets out to examine foundational issues in data science including current challenges, basic research questions, and expected advances, as the basis for a new Data Science Research Program and associated Data Science Evaluation (DSE) series
Bonnie J. Dorr, Craig Greenberg, Peter Fontana, Mark A. Przybocki, Marion Le Bras, Cathryn A. Ploehn, Oleg Aulov, 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 Science Initiative and evaluation series, introduced by the Information Access Division at the
Anantha Narayanan Narayanan, Alec Kanyuck, Satyandra K. Gupta, Sudarsan Rachuri
In recent years, sensor technology and data mining capabilities have advanced greatly, allowing advanced manufacturing enterprises to closely monitor their manufacturing operations. Conditions such as tool breakage and tool wear can be predicted by
Howard S. Cohl, Moritz A. Schubotz, David Veenhuis
To understand applied physics, and physical formulae in particular, the investigation of identifier units is beneficial. However, normally the units are not given explicitly in formulae and have to be inferred. In this paper, we investigate how this
Spencer J. Breiner, Albert T. Jones, David I. Spivak, Eswaran Subrahmanian, Ryan Wisnesky
The goal of this paper is to illustrate the use of category theory as a basis for the integration of manufacturing service databases. In this paper we use as our reference prior work by Kolvatunyu, et. al (2013) on the use of Ontology Web Language(OWL)
Moritz Schubotz, Alexey Grigoriev, Howard Cohl, Norman Meushke, Bela Gipp, Volker Markl
Mathematical formulae are essential in science, but face challenges of ambiguity, due to the use of a small number of identifiers to represent an immense number of concepts. Corresponding to word sense disambiguation in Natural Language Processing, we
Thomas D. Hedberg, Allison Barnard Feeney, Moneer M. Helu, Jaime A. Camelio
Industry has been chasing the dream of integrating and linking data across the product lifecycle and enterprises for decades. However, industry has been challenged by the fact that the context in which data is used varies based on the function in the
Alden A. Dima, Sunil K. Bhaskarla, Chandler A. Becker, Mary C. Brady, Carelyn E. Campbell, Philippe J. Dessauw, Robert J. Hanisch, Ursula R. Kattner, Kenneth G. Kroenlein, Adele P. Peskin, Raymond L. Plante, Guillaume Sousa Amaral, Zachary T. Trautt, James A. Warren, Sharief S. Youssef, Sheng Yen Li, Pierre Francois Rigodiat, Marcus W. Newrock
A materials data infrastructure that enables the sharing and transformation of a wide range of materials data is an essential part of achieving the goals of the Materials Genome Initiative. We describe two high-level requirements of such an infrastructure
Peter Bajcsy, Antoine Vandecreme, Julien M. Amelot, Mary C. Brady, Joe Chalfoun, Michael P. Majurski
Microscopy could be an important tool for characterizing stem cell products if quantitative measurements could be collected over multiple spatial and temporal scales. With the cells changing states over time and being several orders of magnitude smaller