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Displaying 1 - 25 of 180

Real-Time Flashover Prediction Model for Multi-Compartment Building Structures Using Attention Based Recurrent Neural Networks

March 17, 2023
Author(s)
Wai Cheong Tam, Eugene Yujun Fu, Jiajia Li, Richard D. Peacock, Paul A. Reneke, Thomas Cleary, Grace Ngai, Hong Va Leong, Michael Xuelin Huang
This paper presents the development of an attention based bi-directional gated recurrent unit model, P-Flashv2, for the prediction of potential occurrence of flashover in a traditional 111 m2 single story ranch-style family home. Synthetic temperature data

Colloquium: Advances in automation of quantum dot devices control

February 17, 2023
Author(s)
Justyna Zwolak, Jacob Taylor
Arrays of quantum dots (QDs) are a promising candidate system to realize scalable, coupled qubit systems and serve as a fundamental building block for quantum computers. In such semiconductor quantum systems, devices now have tens of individual

Self-driving Multimodal Studies at User Facilities

January 22, 2023
Author(s)
Bruce D. Ravel, Phillip Michael Maffettone, Daniel Allan, Stuart Campbell, Matthew Carbone, Brian DeCost, Howie Joress, Dmitri Gavrilov, Marcus Hanwell, Joshua Lynch, Stuart Wilkins, Jakub Wlodek, Daniel Olds
Multimodal characterization is commonly required for understanding materials. User facilities possess the infrastructure to perform these measurements, albeit in serial over days to months. In this paper, we describe a unified multimodal measurement of a

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

GLFF: Global and Local Feature Fusion for Face Forgery Detection

November 16, 2022
Author(s)

Haiying Guan, Yan Ju, Shan Jia, Jialing Cai, Siwei Lyu

With the rapid development of the deep generative models (such as Generative Adversarial Networks and Auto-encoders), AI-synthesized images of human face are now of such high qualities that humans can hardly distinguish them from pristine ones. Although

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

Glycosylation and the global virome

October 10, 2022
Author(s)
Cassandra Pegg, Benjamin Schulz, Ben Neely, Gregory Albery, Colin Carlson
The sugars that coat the outsides of viruses and host cells are key to successful disease transmission, but they remain understudied compared to other molecular features. Understanding the comparative zoology of glycosylation - and harnessing it for

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

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 Explainable AI Workshop Summary

August 25, 2022
Author(s)
P. Jonathon Phillips, Carina Hahn, Peter Fontana, Amy Yates, Matthew Smith
This report represents a summary of the National Institute of Standards and Technology (NIST) Explainable Artificial Intelligence (AI) Workshop, which NIST held virtually on January 26-28, 2021.

Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

July 19, 2022
Author(s)
Axel Hoffmann, Shriram Ramanathan, Julie Grollier, Andrew Kent, Marcelo Rozenberg, Ivan Schuller, Oleg Shpyrko, Robert Dynes, Yeshaiahu Fainman, Alex Frano, Eric Fullerton, Giulia Galli, Vitaliy Lomakin, Shyue Ping Ong, Amanda K. Petford-Long, Jonathan A. Schuller, Mark Stiles, Yayoi Takamura, Yimei Zhu
Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device

Spatiotemporal Monitoring of Melt-Pool Variations in Metal-Based Additive Manufacturing

July 1, 2022
Author(s)
Siqing Zhang, Yan Lu, Paul Witherell, Timothy Simpson, Soundar Kumara, Hui Yang
Additive manufacturing provides a higher level of flexibility to build customized products with complex geometries. However, AM is currently limited in its ability to ensure quality assurance and process repeatability. Advanced imaging provides unique
Displaying 1 - 25 of 180