RNN based SVPWM controlled grid integrated PV system with COA based MPPT for enhanced power quality and dynamic tracking. [PDF]
Manjula A, Babu AR.
europepmc +1 more source
Vertical profiling of shock attenuation at the Rochechouart impact structure, France
Abstract Rochechouart, south‐west France, is a complex impact structure. Here, we present the first report of shock barometry of quartz from what are likely parautochthonous basement units at depth, based on samples from the 2017 C.I.R.I.R drilling campaign. The crystallographic orientations of 725 sets of PDFs in 512 quartz grains in samples from four
P. Struzynska +4 more
wiley +1 more source
Constructing biologically constrained RNNs via Dale's backpropagation and topologically informed pruning. [PDF]
Balwani A, Wang AQ, Najafi F, Choi H.
europepmc +1 more source
ABSTRACT Chromatin interactions establish spatial proximity between distant regulatory elements and their target genes, significantly influencing gene expression, and phenotypic traits. In this study, we present a plant chromatin interaction prediction model called PlantCTCIP based on Convolutional Neural Networks and Transformer.
Zhenye Wang +14 more
wiley +1 more source
Prediction of remaining useful life for electronic equipment based on online PINN. [PDF]
Han F, Mo B.
europepmc +1 more source
Advances in cardiac devices and bioelectronics augmented with artificial intelligence
Abstract figure legend Interfaces between the human heart, diagnostic bioelectronics, artificial intelligence, and clinical care. From left to right: Human heart and biosensor interface; representative waveforms of common diagnostic bioelectronic sensing modalities.
Charles Stark +3 more
wiley +1 more source
Deep learning neural networks-based traffic predictors for V2X communication networks. [PDF]
Magdy Saady M +6 more
europepmc +1 more source
Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang +12 more
wiley +1 more source
Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery. [PDF]
Jakob KS, Walsh A, Reuter K, Margraf JT.
europepmc +1 more source
ABSTRACT This paper presents a robust control synthesis and analysis framework for nonlinear systems with uncertain initial conditions. First, a deep learning‐based lifting approach is proposed to approximate nonlinear dynamical systems with linear parameter‐varying (LPV) state‐space models in higher‐dimensional spaces while simultaneously ...
Sourav Sinha, Mazen Farhood
wiley +1 more source

