Results 231 to 240 of about 121,464 (311)
Optimal Resource Allocation via Unified Closed-Form Solutions for SWIPT Multi-Hop DF Relay Networks. [PDF]
Yu Y, Tang X, Xie G.
europepmc +1 more source
Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan +3 more
wiley +1 more source
Editorial: Neural dynamics for brain-inspired control and computing: advances and applications. [PDF]
Liu M.
europepmc +1 more source
A computational framework for optimizing strain sensor placement in wearable motion tracking systems is presented. By combining dense strain mapping with a genetic algorithm, the method discovers counterintuitive yet highly effective configurations that reduce joint angle error by 32%.
Minu Kim +4 more
wiley +1 more source
Exploring the role of circulating proteins in multiple myeloma risk: a Mendelian randomization study. [PDF]
Lee MA +5 more
europepmc +1 more source
Physically unclonable functions (PUFs) of reconfigurable feedback field‐effect transistors (R‐FBFETs) with polycrystalline silicon channels are designed for dual entropy sources. The uniqueness and reliability of the dual entropy source PUF are verified by inter‐ and intra‐Hamming distances of 49.13% and 3.47%, respectively, as well as NIST statistical
Taeho Park +4 more
wiley +1 more source
Echoes of stress: From molecular whispers to social thunderstorms. [PDF]
Lopez JP.
europepmc +1 more source
Quantization‐aware training creates resource‐efficient structured state space sequential S4(D) models for ultra‐long sequence processing in edge AI hardware. Including quantization during training leads to efficiency gains compared to pure post‐training quantization.
Sebastian Siegel +5 more
wiley +1 more source
Relay Selection for Covert Communication with an Active Warden. [PDF]
Ryu JY, Lee JH.
europepmc +1 more source
Bio‐to‐Robot Transfer of Fish Sensorimotor Dynamics via Interpretable Model
This study demonstrates how a biologically interpretable model trained on real‐fish muscle activity can accurately predict the motion of a robotic fish. By linking real‐fish sensorimotor dynamics with robotic fish, the work offers a transparent, data‐efficient framework for transferring biological intelligence to bioinspired robotic systems.
Waqar Hussain Afridi +6 more
wiley +1 more source

