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Information Technology

Data & informatics

Search Publications

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Displaying 26 - 50 of 661

Investigating Multi-Tier and QoS-Aware Caching Based on ARC

October 16, 2023
Author(s)
Lydia Ait Oucheggou, Abdella Battou, Jalil Boukhobza, Stephane Rubini
Memory caching is a common practice to reduce application latencies by buffering relevant data in high speed memory. When the volume of data to cache is too large or a DRAM-based solution too expensive, several technologies such as NVM or high speed SSDs

The NIST Plan for Providing Public Access to Results of Federally Funded Research

October 2, 2023
Author(s)
Katherine E. Sharpless, Regina L. Avila, Ronald F. Boisvert, A Kirk Dohne, James Fowler, Rachel B. Glenn, Gretchen Greene, Robert Hanisch, Andrea Medina-Smith, Alan Munter, Julie Petrousky, Yuri Ralchenko, Carolyn D. Rowland, James A. St Pierre, Adam Wunderlich, Jon Zhang
In 2013 White House Office of Science and Technology Policy (OSTP) issued a memo, "Increasing Access to the Results of Federally Funded Scientific Research." In response, he National Institute of Standards and Technology (NIST) developed a public access

Labeling Software Security Vulnerabilities

October 1, 2023
Author(s)
Irena Bojanova, John Guerrerio
Labeling software security vulnerabilities would benefit greatly modern artificial intelligence cybersecurity research. The National Vulnerability Database (NVD) partially achieves this via assignment of Common Weakness Enumeration (CWE) entries to Common

Quantifying Pairwise Similarity for Complex Polymers

September 6, 2023
Author(s)
Jiale Shi, Nathan Rebello, Dylan Walsh, Michael Deagen, Bruno Salomao Leao, Debra Audus, Bradley Olsen
Defining the similarity between chemical entities is an essential task in polymer informatics, enabling ranking, clustering, and classification. Despite its importance, pairwise chemical similarity for polymers remains an open problem. Here, a similarity

RECENT DEVELOPMENTS IN ONTOLOGY STANDARDS AND THEIR APPLICABILITY TO BIOMANUFACTURING

August 21, 2023
Author(s)
Milos Drobnjakovic, Boonserm Kulvatunyou, Vijay Srinivasan, Simon P. Frechette
ISO and IEC have jointly initiated, and recently issued, a series of standards (the ISO/IEC 21838 series) for top-level ontologies. These standards have been used by industrial consortia to develop and disseminate standards for mid-level ontologies to ease

RECENT DEVELOPMENTS IN ONTOLOGY STANDARDS AND THEIR APPLICABILITY TO BIOMANUFACTURING

July 14, 2023
Author(s)
Milos Drobnjakovic, Boonserm Kulvatunyou, Simon P. Frechette, Vijay Srinivasan
ISO and IEC have jointly initiated, and recently issued, a series of standards (the ISO/IEC 21838 series) for top-level ontologies. These standards have been used by industrial consortia to develop and disseminate standards for mid-level ontologies to ease

A Generic STS Viewer on the Web

June 13, 2023
Author(s)
Wendell Piez
In an alternate universe, XML (1998) and XSLT 1.0 (1999) were not developed so early, and did not have to wait for the rest of the web to catch up. In ours, it took two decades before other critically important pieces of the puzzle – CSS, DOM, ECMAScript

NIST Research Data Framework (RDaF): Version 1.5

May 18, 2023
Author(s)
Robert Hanisch, Debra L. Kaiser, Alda Yuan, Andrea Medina-Smith, Bonnie C Carroll, Eva Campo
The NIST Research Data Framework (RDaF) is a multifaceted and customizable tool that aims to help shape the future of open data access and research data management (RDM). The RDaF will allow organizations and individual researchers to customize an RDM

AI for Materials

April 25, 2023
Author(s)
Debra Audus, Kamal Choudhary, Brian DeCost, A. Gilad Kusne, Francesca Tavazza, James A. Warren
The application of artificial intelligence (AI) methods to materials re- search and development (MR&D) is poised to radically reshape how materials are discovered, designed, and deployed into manufactured products. Materials underpin modern life, and

Scalable Multi-Agent Lab Framework for Lab Optimization

April 11, 2023
Author(s)
A. Gilad Kusne, Austin McDannald
Autonomous materials research systems allow scientists to fail smarter, learn faster, and spend less resources in their studies. As these systems grow in number, capability, and complexity, a new challenge arises – how will they work together across large

Community Resource for Innovation in Polymer Technology (CRIPT): A Scalable Polymer Material Data Structure

February 20, 2023
Author(s)
Dylan Walsh, Weizhong Zou, Ludwig Schneider, Reid Mello, Michael Deagen, Joshua Mysona, Tzyy-Shyang Lin, Juan de Pablo, Klavs Jensen, Debra Audus, Bradley Olsen
Polymeric materials are integral components of nearly every aspect of modern life. However, developing cheminformatic solutions for polymers has been difficult since they are large stochastic molecules with hierarchical structures spanning multiple length

Toward an Integrated Machine Learning Model of a Proteomics Experiment

February 6, 2023
Author(s)
Ben Neely, Viktoria Dorfer, Lennart Martens, Isabell Bludau, Robbin Bouwmeester, Sven Degroeve, Eric Deutsch, Siegfried Gessulat, Tobias Rehfeldt, Lukas Kall, Veit Schwammle, Samuel Payne, Tobias Schmidt, Pawel Palczynski, Julian Uszkoreit, Juan Antonio Vizcaino, Mathias Wilhelm, Magnus Palmblad
In recent years machine learning has made extensive progress in modeling many aspects of mass spectrometry data. We brought together proteomics data generators, repository managers, and machine learning experts in a workshop with the goals to evaluate and

ProteomicsML: An Online Platform for Community-Curated Datasets and Tutorials for Machine Learning in Proteomics

January 24, 2023
Author(s)
Tobias Rehfeldt, Ralf Gabriels, Robbin Bouwmeester, Siegfried Gessulat, Magnus Palmblad, Ben Neely, Yasset Perez-Riverol, Tobias Schmidt, Juan Antonio Vizcaino, Eric Deutsch
Dataset acquisition and curation are often the hardest and most time-consuming parts of a machine learning endeavor. This is especially true for proteomics-based LC-IM-MS datasets, due to the high-throughput data structure with high levels of noise and

Dark solitons in Bose-Einstein condensates: a dataset for many-body physics research

December 21, 2022
Author(s)
Amilson R. Fritsch, Shangjie Guo, Sophia Koh, Ian Spielman, Justyna Zwolak
We establish a dataset of over 1.6 x 10^4 experimental images of Bose–Einstein condensates containing solitonic excitations to enable machine learning (ML) for many-body physics research. About 33 % of this dataset has manually assigned and carefully

CREDIBILITY CONSIDERATION FOR DIGITAL TWINS IN MANUFACTURING

December 16, 2022
Author(s)
Guodong Shao, Joe Hightower, William Schindel
Digital Twin has become an important technology for advanced manufacturing. However, to ensure that digital twins provide valuable decision support, the results generated by the digital twins must be trustworthy for real manufacturing systems. Model

Characterization of AI Model Configurations For Model Reuse

October 24, 2022
Author(s)
Peter Bajcsy, Daniel Gao, Michael Paul Majurski, Thomas Cleveland, Manuel Carrasco, Michael Buschmann, Walid Keyrouz
With the widespread creation of artificial intelligence (AI) models in biosciences, bio-medical researchers are reusing trained AI models from other applications. This work is motivated by the need to characterize trained AI models for reuse based on

NIST Conference Papers Fiscal Year 2020

September 22, 2022
Author(s)
Kathryn Miller, Karen Arcamonte
This Special Publication represents the work of researchers at professional conferences, as reported by NIST employees in Fiscal Year 2020 (October 1, 2019–September 30, 2020).

The Industrial Ontologies Foundry (IOF) Core Ontology

September 19, 2022
Author(s)
Boonserm Kulvatunyou, Milos Drobnjakovic, Farhad Ameri, Chris Will, Barry Smith
The Industrial Ontologies Foundry (IOF) has been formed to create a suite of interoperable ontologies that would serve as a foundation for data and information interoperability in all areas of manufacturing. To ensure that the ontologies are developed in a

Network analysis approach to Likert-style surveys

September 2, 2022
Author(s)
Robert Dalka, Diana Sachmpazidi, Charles Henderson, Justyna Zwolak
Likert-style surveys are a widely used research instrument to assess respondents' preferences, beliefs, or experiences. In this paper, we propose and demonstrate how network analysis (NA) can be employed to model and evaluate the interconnectedness of

Leveraging Theory for Enhanced Machine Learning

August 26, 2022
Author(s)
Debra Audus, Austin McDannald, Brian DeCost
The application of machine learning to the materials domain has traditionally struggled with two major challenges: a lack of large, curated data sets and the need to understand the physics behind the machine-learning prediction. The former problem is

NIST Conference Papers Fiscal Year 2021

August 24, 2022
Author(s)
Kathryn Miller, Karen Arcamonte
This Special Publication represents the work of researchers at professional conferences, as reported by NIST employees in Fiscal Year 2021 (October 1, 2020–September 30, 2021). NIST is committed to the idea that results of federally funded research are a
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