Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors
Advanced Science, EarlyView.This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung +7 more
wiley +1 more source
Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review
Advanced Science, EarlyView.Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh +8 more
wiley +1 more source
Identification of the associations between genes and quantitative traits using entropy-based kernel density estimation. [PDF]
Genomics Inform, 2022 Yee J, Park T, Park M.
europepmc +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Advanced Science, EarlyView.Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Spatiotemporal Analysis of Gastrointestinal Tumor (GI) with Kernel Density Estimation (KDE) Based on Heterogeneous Background. [PDF]
Int J Environ Res Public Health, 2022 Yang Z, He S, Zhang H, Li M, Liang Y.
europepmc +1 more source
Advanced Science, EarlyView.A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu +5 more
wiley +1 more source
Optimal futures hedging strategies based on an improved kernel density estimation method. [PDF]
Soft comput, 2021 Yu X, Wang X, Zhang W, Li Z.
europepmc +1 more source
Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency
Advanced Science, EarlyView.This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun +9 more
wiley +1 more source
VIASCKDE Index: A Novel Internal Cluster Validity Index for Arbitrary-Shaped Clusters Based on the Kernel Density Estimation. [PDF]
Comput Intell Neurosci, 2022 Şenol A.
europepmc +1 more source
Advanced Science, EarlyView.Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais +32 more
wiley +1 more source