Results 71 to 80 of about 68,694 (265)
Advanced Science, EarlyView.An MTJ‐based probabilistic processing‐in‐memory architecture unites nonvolatile storage, local entropy generation, and stochastic computation within each memory cell. Stored multi‐bit weights are converted directly into programmable stochastic bitstreams, enabling neural‐network inference, adaptive Ising optimization, and uncertainty‐aware Bayesian ...
Qiuyuan Wang +6 more
wiley +1 more source
Advanced Science, EarlyView.Bulk and genotype‐imputed transcriptomes obscure the cellular drivers of complex disease. CausalCellInfer resolves them by integrating invariant marker selection, deep learning deconvolution, and regularized matrix completion. Applied to ∼500 000 UK Biobank participants across 29 traits, it uncovers hallmark cell‐type proportion shifts, including ...
Liangying Yin +6 more
wiley +1 more source
Security, Privacy, and Trustworthiness of Sensor Networks and Internet of Things
Sensors, 2020 This editorial gives an overview of the papers included in the Special Issue on “Security, Privacy, and Trustworthiness of Sensor Networks and Internet of Things” of Sensors. The context of the special issue theme is first briefly described. This is then
Sokratis Katsikas, Vasileios Gkioulos
doaj +1 more source
Advanced Science, EarlyView.This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui +4 more
wiley +1 more source
From Artificial to Embodied and Physical Intelligence in Smart Manufacturing
Advanced Science, EarlyView.Smart manufacturing is reframed through complementary artificial, embodied, and physical intelligence, spanning computational reasoning, perception‐action coupling, and material‐level adaptation. Their integration across design, fabrication, operation, and maintenance reveals how intelligence can be co‐designed across algorithms, embodied agents, and ...
Kang Wang +9 more
wiley +1 more source
Advanced Science, EarlyView.Neutron depth profiling exploits the 6Li(n,3H)4He reaction to provide quantitative, isotope‐specific, depth‐resolved maps of lithium inside operating lithium‐ion batteries, directly linking lithium transport, dendrite growth and interfacial short‐circuiting to a physics‐informed machine‐learning roadmap that turns this non‐destructive operando ...
Yulong Zhang +8 more
wiley +1 more source
Frontiers in Behavioral Neuroscience, 2018 Motivational tendencies to happy and angry faces are well-established, e.g., in the form of aggression. Approach-avoidance reactions are not only elicited by emotional expressions, but also linked to the evaluation of stable, social characteristics of ...
Sina Radke +8 more
doaj +1 more source
ReLink: Reliable Deep Learning for Microscopic Motion Tracking
Advanced Science, EarlyView.ReLink enables reliable trajectory linking in single‐particle tracking by integrating physics‐informed motion statistics with confidence‐based adaptive filtering. Across diverse simulated and experimental conditions, ReLink robustly reconstructs trajectories and preserves the fidelity of downstream analyses, enabling accurate characterization of ...
Yuan Jiang +7 more
wiley +1 more source
2007 IEEE Wireless Communications and Networking Conference, 2007 4 pages, 4 eps ...
Nicolai Kuntze, Andreas U. Schmidt
openaire +2 more sources
Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation
Advanced Electronic Materials, EarlyView.A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang +6 more
wiley +1 more source