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Artificial intelligence

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Displaying 226 - 250 of 260

The 2018 NIST Speaker Recognition Evaluation

September 15, 2019
Author(s)
Omid Sadjadi, Craig Greenberg, Elliot Singer, Douglas A. Reynolds, Lisa Mason, Jaime Hernandez-Cordero
In 2018, the U.S. national institute of standards and technology (NIST) conducted the most recent in an ongoing series of speaker recognition evaluations (SRE). SRE18 was organized in a similar manner to SRE16, focusing on speaker detection over

Temporal pattern recognition with delayed feedback spin-torque nano-oscillators

August 23, 2019
Author(s)
Mathieu Riou, Jacob Torrejon, B. Garitaine, Flavio Abreu Araujo, Paolo Bortolotti, Vincent Cros, Sumito Tsunegi, K. Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Damien Querlioz, Mark D. Stiles, Julie Grollier
The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. In this study, we

A Standardized Representation of Convolutional Neural Networks for Reliable Deployment of Machine Learning Models in the Manufacturing Industry

August 18, 2019
Author(s)
Max K. Ferguson, Seongwoon Jeong, Kincho H. Law, Anantha Narayanan Narayanan, Svetlana Levitan, Jena Tridivesh, Yung-Tsun Lee
The use of deep convolutional neural networks is becoming increasingly popular in the engineering and manufacturing sectors. However, managing the distribution of trained models is still a difficult task, partially due to the limitations of standardized

Comparison of Artificial Intelligence based approaches to cell function prediction

July 11, 2019
Author(s)
Sarala Padi, Petru S. Manescu, Nicholas Schaub, Nathan Hotaling, Carl G. Simon Jr., Peter Bajcsy
Predicting Retinal Pigment Epithelium (RPE) cell functions in stem cell implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of stem cell therapies. Such cell function predictions can be carried out either

Unreliable evidence in binary classification problems

May 7, 2019
Author(s)
David W. Flater
Binary classification problems include such things as classifying email messages as spam or non-spam and screening for the presence of disease (which can be seen as classifying a subject as disease-positive or disease- negative). Both Bayesian and

BowTie - A deep learning feedforward neural network for sentiment analysis

April 22, 2019
Author(s)
Apostol T. Vassilev
How to model and encode the semantics of human-written text and select the type of neural network to process it with are not settled issues in sentiment analysis. Accuracy and transferability are critical issues in machine learning in general. These

A Deep Learning-Based Weather Forecast System for Data Volume and Recency Analysis

February 18, 2019
Author(s)
Jarrett Booz, Wei Yu, Guobin Xu, David W. Griffith, Nada T. Golmie
Accurate weather forecast is important to our daily life. Through physical atmospheric models, the weather can be accurately forecasted in a short period time. To provide weather forecast, machines learning techniques can be used for understanding and

Scalable method to find the shortest path in a graph with circuits of memristors

December 14, 2018
Author(s)
Alice Mizrahi, thomas Marsh, Brian D. Hoskins, Mark D. Stiles
Finding the shortest path in a graph has applications to a wide range of optimization problems. However, algorithmic methods scale with the size of the graph in terms of time and energy. We propose a method to solve the shortest path problem using circuits

Design of superconducting optoelectronic networks for neuromorphic computing

November 6, 2018
Author(s)
Sonia Buckley, Adam McCaughan, Jeff Chiles, Richard Mirin, Sae Woo Nam, Jeff Shainline
We have previously proposed a novel hardware platform for neuromorphic computing based on superconducting optoelectronics that presents many of the features necessary for information processing in the brain. Here we discuss the design and training of

Circuit designs for superconducting optoelectronic loop neurons

October 12, 2018
Author(s)
Jeffrey M. Shainline, Adam N. McCaughan, Jeffrey T. Chiles, Richard P. Mirin, Sae Woo Nam, Sonia M. Buckley
We present designs of superconducting optoelectronic neurons based on superconducting single- photon detectors, Josephson junctions, semiconductor light sources, and multi-planar dielectric waveguides. The neurons send few-photon signals to synaptic

SELF-IMPROVING ADDITIVE MANUFACTURING KNOWLEDGE MANAGEMENT

August 26, 2018
Author(s)
Yan Lu, Zhuo Yang, Douglas Eddy, Sundar Krishnamurty
The current AM development environment is far from being mature. Both software applications and workflow management tools are very limited due to the lack of knowledge to support engineering decision makings. AM knowledge includes design rules, operation

The Industrial Ontologies Foundry Proof-of-Concept Project

August 26, 2018
Author(s)
Boonserm Kulvatunyou, Evan K. Wallace, Dimitris Kiritsis, Barry Smith, Chris Will
The current industrial revolution is said to be driven by the digitization of manu-facturing that exploits connected information across all aspects of manufacturing. Standards have been recognized as an important enabler. Ontology is the next generation

A SUPER-METAMODELLING FRAMEWORK TO OPTIMIZE SYSTEM PREDICTABILITY

August 25, 2018
Author(s)
Yan Lu, Douglas Eddy, Sundar Krishnamurty, Ian Grosse
Statistical metamodels can robustly predict manufacturing process and engineering systems design results. Various techniques, such as Kriging, polynomial regression, artificial neural network and others, are each best suited for different scenarios that

Deep Learning-Based Intrusion Detection With Adversaries

July 9, 2018
Author(s)
Zheng Wang
Deep neural networks have demonstrated their effectiveness in most machine learning tasks, with intrusion detection included. Unfortunately, recent research found that deep neural networks are vulnerable to adversarial examples in the image classification

Superconducting optoelectronic networks III: synaptic plasticity

July 5, 2018
Author(s)
Jeffrey M. Shainline, Adam N. McCaughan, Sonia M. Buckley, Christine A. Donnelly, Manuel C. Castellanos Beltran, Michael L. Schneider, Richard P. Mirin, Sae Woo Nam
As a means of dynamically reconfiguring the synaptic weight of a superconducting optoelectronic loop neuron, a superconducting flux storage loop is inductively coupled to the synaptic current bias of the neuron. A standard flux memory cell is used to

Machine learning modeling of superconducting critical temperature

June 28, 2018
Author(s)
Aaron Gilad Kusne, Valentin Stanev, Ichiro Takeuchi
Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon remain poorly understood; prime among these is the connection between superconductivity and chemical
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