Results 121 to 130 of about 4,915 (242)
ABSTRACT Conventional software‐based encryption faces mounting limitations in power efficiency and security, inspiring the development of emerging neuromorphic computing hardware encryption. This study presents a hardware‐level multi‐dimensional encryption paradigm utilizing optoelectronic neuromorphic devices with low energy consumption of 3.3 fJ ...
Bo Sun +3 more
wiley +1 more source
Sample event data on ground beetles (Coleoptera, Carabidae) collected by Biological Station Wijster (BSW) in the years 1959, 1961, 1963, 1965 and 1966. [PDF]
Gerrits GM, Vermeulen R, van Klink R.
europepmc +1 more source
Model‐Inversion‐Resistant Physical Unclonable Neural Network Using Vertical NAND Flash Memory
Schematic and key features of the proposed forward‐forward physical unclonable neural network (FF‐PUNN), incorporating a concealable physical unclonable function (PUF) layer and forward‐forward (FF) learning. ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and ...
Sung‐Ho Park +8 more
wiley +1 more source
RRAM Variability Harvesting for CIM‐Integrated TRNG
This work demonstrates a compute‐in‐memory‐compatible true random number generator that harvests intrinsic cycle‐to‐cycle variability from a 1T1R RRAM array. Parallel entropy extraction enables high‐throughput bit generation without dedicated circuits. This approach achieves NIST‐compliant randomness and low per‐bit energy, offering a scalable hardware
Ankit Bende +4 more
wiley +1 more source
Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar +2 more
wiley +1 more source
Digitising health history: The creation, function and implementation of the Norwegian Health Archives Registry. [PDF]
Helstad G +3 more
europepmc +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Global sampling decline erodes science potential of natural history collections. [PDF]
Forbes O, Young AG, Thrall PH.
europepmc +1 more source
Automated procedural analysis is recognized as one of the major game changers for robotic surgery. Meaning digital analysis needs to replace the manual assessments that set todays standard. Mechanical robotic‐instrument tracking enables the derivation of quantitative kinematic metrics that support behavior‐based workflow segmentation into distinct ...
Kateryna Pirkovets +4 more
wiley +1 more source
Digitising payments for campaign health workers in Africa: the promise and the path to sustainable scale. [PDF]
Waiswa P +9 more
europepmc +1 more source

