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Dendritic Learning in Superconducting Optoelectronic Networks - Elastic Weight Collision at Dynamical Boundaries and Intermittent Validation for Early Convergence

August 28, 2023

Author(s)

Ryan O'Loughlin, Bryce Primavera, Jeff Shainline

Superconducting Optoelectronic Networks (SOENs) combine pho- tonics and superconductors to instantiate computing systems that approach the fundamental limits of information processing in terms of speed and scalability. Overcoming the engineering challenges

Development of a Bias Compensating Q-Learning Controller for a Multi-Zone HVAC Facility

August 1, 2023

Author(s)

Syed Ali Asad Rizvi, Amanda Pertzborn

We present the development of a bias compensating reinforcement learning (RL) algorithm that optimizes thermal comfort (by minimizing tracking error) and control utilization (by penalizing setpoint deviations) in a multi-zone heating, ventilation, and air

Retrieval of Raman signals from broadband CARS intensity measurements using an autoencoder trained with a prior excitation function

July 31, 2023

Author(s)

ryan muddiman, Kevin O' Dwyer, Charles Camp, Bryan Hennelly

Broadband coherent anti-Stokes Raman scattering (BCARS) is capable of producing high-quality Raman spectra spanning broad bandwidths, 400–4000 cm−1, with millisecond acquisition times. Raw BCARS spectra, however, are a coherent combination of vibrationally

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

O-RAN with Machine Learning in ns-3

June 28, 2023

Author(s)

Wesley Garey, Richard A. Rouil, Evan Black, Tanguy Ropitault, Weichao Gao

The Open Radio Access Network (O-RAN) Alliance is the industry led standardization effort, with the sole purpose of evolving the Radio Access Network (RAN) to be more open, intelligent, interoperable, and autonomous to support the ever growing need of

Multiplexed gradient descent: Fast online training of modern datasets on hardware neural networks without backpropagation

June 26, 2023

Author(s)

Adam McCaughan, Bakhrom Oripov, Natesh Ganesh, Sae Woo Nam, Andrew Dienstfrey, Sonia Buckley

We show that model-free perturbative methods can be used to efficiently train modern neural network architectures in a way that can be directly applied to emerging neuromorphic hardware. These methods were investigated for training VLSI neural networks

Cluster Association for 3D Environment Based on 60 GHz Indoor Channel Measurements

May 31, 2023

Author(s)

Raied Caromi, Jian Wang, Anuraag Bodi, Camillo Gentile

In this paper, we present a ray tracing (RT) assisted multipath cluster association method. This work is based on an indoor channel measurement at 60 GHz, where a light detection and ranging (LiDAR) sensor was co-located with channel sounder and time

2022 Cybersecurity & Privacy Annual Report

May 30, 2023

Author(s)

Patrick D. O'Reilly, Kristina Rigopoulos, Larry Feldman, Greg Witte

During Fiscal Year 2022 (FY 2022) – from October 1, 2021, through September 30, 2022 –the NIST Information Technology Laboratory (ITL) Cybersecurity and Privacy Program successfully responded to numerous challenges and opportunities in security and privacy

Automated extraction of capacitive coupling for quantum dot systems

May 24, 2023

Author(s)

Joshua Ziegler, Florian Luthi, Mick Ramsey, Felix Borjans, Guoji Zheng, Justyna Zwolak

Gate-defined quantum dots (QDs) have appealing attributes as a quantum computing platform. However, near-term devices possess a range of possible imperfections that need to be accounted for during the tuning and operation of QD devices. One such problem is

Low-Rank Gradient Descent for Memory-Efficient Training of Deep In-Memory Arrays

May 18, 2023

Author(s)

Siyuan Huang, Brian Hoskins, Matthew Daniels, Mark Stiles, Gina C. Adam

The movement of large quantities of data during the training of a Deep Neural Network presents immense challenges for machine learning workloads. To minimize this overhead, espe- cially on the movement and calculation of gradient information, we introduce

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

Machine Learning-driven Process-Structure-Property Analytical Framework for Additive Manufacturing

April 1, 2023

Author(s)

Hyunwoong Ko, Zhuo Yang, Yande Ndiaye, Paul Witherell, Yan Lu

Data analytics with Machine Learning (ML) and Artificial Intelligence (AI) offers high potential to continuously transform AM data to newfound knowledge of Process-Structure-Property (PSP) relationships. In AM, however, realizing the potential is still

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

A Review of Machine Learning Control in Building Operations

March 14, 2023

Author(s)

Liang Zhang, Zhelun Chen, Xiangyu Zhang, Amanda Pertzborn

Machine learning control (MLC) is a highly flexible and adaptable method that enables the design, modeling, tuning, and maintenance of building controllers to be more accurate, automated, flexible, and adaptable. The research topic of MLC in building

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

Discovery of digital forensic dataset characteristics with CASE-Corpora

February 13, 2023

Author(s)

Alexander Nelson, Eoghan Casey

The digital forensics community has generated training and reference data over the course of decades. However, significant challenges persist today in the usage pipeline for that data, from research problem formulation, through discovery of applicable

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