Results 51 to 60 of about 147,000 (286)

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

open access: yesAdvanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha   +18 more
wiley   +1 more source

Transforming oil market analysis: A novel GAN + LSTM predictive framework

open access: yesNext Energy
A novel method of predicting the crude oil WTI futures prices based on a data set covering April 12, 2009 through January 7, 2024. To capture complex market dynamics more precisely, it incorporates key market factors such as open, high, and low price ...
Prity Kumari   +2 more
doaj   +1 more source

KAJIAN MODEL HIDDEN MARKOV UNTUK MENDUGA VOLATILITAS INDEKS HARGA SAHAM

open access: yesPrima: Jurnal Pendidikan Matematika, 2019
Abstrak Volatility is a measure of uncertainty. Volatility can either be measured by using the standard deviation or variance between returns. The problem is volatility is unobservable, and estimating volatility is not a trivial task.
Abdul Baist
doaj   +1 more source

Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China

open access: yesBMC Infectious Diseases, 2023
Background This study adopted complete meteorological indicators, including eight items, to explore their impact on hand, foot, and mouth disease (HFMD) in Fuzhou, and predict the incidence of HFMD through the long short-term memory (LSTM) neural network
Hansong Zhu   +10 more
doaj   +1 more source

Contact Lens with Moiré Patterns for High‐Precision Eye Tracking

open access: yesAdvanced Functional Materials, EarlyView.
This work presents a passive contact lens for high‐precision eye tracking, integrating a microscopic moiré grating label. The parallax‐induced shift of macroscopic moiré patterns enables angle measurement with 0.28° precision using a standard camera under ambient light.
Ilia M. Fradkin   +11 more
wiley   +1 more source

Parameter identification of unmanned surface vehicle MMG model based on an improved extended Kalman filter

open access: yesZhongguo Jianchuan Yanjiu
ObjectivesTo construct an accurate MMG (mathematical model group) model for a water-jet propulsion unmanned surface vehicle, the traditional extended Kalman filter algorithm and improved extended Kalman filter algorithm are combined with the real-world ...
Pengbo SUN   +4 more
doaj   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

open access: yesAdvanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi   +2 more
wiley   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

open access: yesAdvanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy   +3 more
wiley   +1 more source

A New Regression Model for Depression Severity Prediction Based on Correlation among Audio Features Using a Graph Convolutional Neural Network

open access: yesDiagnostics, 2023
Recent studies have revealed mutually correlated audio features in the voices of depressed patients. Thus, the voices of these patients can be characterized based on the combinatorial relationships among the audio features.
Momoko Ishimaru   +4 more
doaj   +1 more source

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