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Displaying 1 - 25 of 159

Glycosylation and the global virome

October 10, 2022
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
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
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

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

July 19, 2022
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
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

Gauging the difficulty of image segmentation

May 19, 2022
Marek Franaszek
Image segmentation is the first step in a complex process of object recognition. This report presents a method to gauge the difficulty of segmentation by calculating a scalar parameter Q for an image. This parameter depends on a distribution of the

Machine learning enabling high-throughput and remote operations at large-scale user facilities

May 18, 2022
Bruce D. Ravel, Tatiana Konstantinova, Phillip Michael Maffettone, Stuart Campbell, Andi Barbour, Daniel Olds
Imaging, scattering, and spectroscopy are fundamental in understanding and discovering new functional materials. Contemporary innovations in automation and experimental techniques have led to these measurements being performed much faster and with higher

Machine Learning-Based Algorithmically Generated Domain Detection

May 1, 2022
Zheng Wang, Yang Guo, Douglas Montgomery
Malware like botnets typically uses domain generation algorithms (DGAs) to dynamically produce a large number of random algorithmically generated domains (AGDs) and use a few of them to communicate with the command and control servers. AGD detection

Towards a Standard for Identifying and Managing Bias in Artificial Intelligence

March 15, 2022
Reva Schwartz, Apostol Vassilev, Kristen K. Greene, Lori Perine, Andrew Burt, Patrick Hall
As individuals and communities interact in and with an environment that is increasingly virtual they are often vulnerable to the commodification of their digital exhaust. Concepts and behavior that are ambiguous in nature are captured in this environment

Robust Automated Recognition of Noisy Quantum Dot States

February 25, 2022
Joshua Ziegler, Thomas McJunkin, Emily Joseph, Sandesh Kalantre, Benjamin Harpt, Donald Savage, Max Lagally, Mark Eriksson, Jacob Taylor, Justyna Zwolak
The current autotuning approaches for quantum dot (QD) devices, while showing some success, lack an assessment of data reliability. This leads to unexpected failures when noisy or otherwise low-quality data is processed by an autonomous system. In this

A Convolutional Neural Networks-Based Approach for Texture Directionality Detection

January 12, 2022
Marcin Kociolek, Michal Kozlowski, Antonio Cardone
The perceived texture directionality is an important, not fully explored image characteristic. In many applications texture directionality detection is of fundamental importance. Several approaches have been proposed, such as the fast Fourier-based method
Displaying 1 - 25 of 159