Results 121 to 130 of about 6,146 (274)
Cardiovascular diseases are leading death causes; electrocardiogram (ECG) analysis is slow, motivating machine learning and deep learning. This study compares deep convolutional generative adversarial network, conditional GAN, and Wasserstein GAN with gradient penalty (WGAN‐GP) for synthetic ECG spectrograms; Fréchet Inception Distance (FID) and ...
Giovanny Barbosa‐Casanova +3 more
wiley +1 more source
This work presents a tip‐growing eversion robot that uses phase‐changing alloys for reversible stiffening and localized actuation, achieving 43× stiffness modulation, 15× force amplification, and segmental steering. The system enables precise navigation and force delivery in constrained, tortuous pathways.
Shamsa Al Harthy +4 more
wiley +1 more source
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng +7 more
wiley +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +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
Drawing Quantum Contextuality with ‘Dessins d’enfants’ [PDF]
In the standard formulation of quantum mechanics, there exists an inherent feedback of the measurement setting on the elementary object under scrutiny. Thus one cannot assume that an 'element of reality' prexists to the measurement and, it is even more intriguing that unperformed/counterfactual observables enter the game.
openaire +2 more sources
Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu +6 more
wiley +1 more source
Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He +3 more
wiley +1 more source
Relational Quantum Mechanics and Contextuality
AbstractThis paper discusses the question of stable facts in relational quantum mechanics (RQM). I examine how the approach to quantum logic in the consistent histories formalism can be used to clarify what infomation about a system can be shared between different observers.
openaire +4 more sources
During lengthy minimally invasive surgeries, fatigue can cause surgeon tremor and poor endoscopic coordination. This study proposes a robot‐assisted endoscopic adjustment system. It employs a lightweight instrument detection model and a hierarchical multiconstraint controller for visual servoing.
Zijie Yang +5 more
wiley +1 more source

