Results 71 to 80 of about 1,744 (231)
Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics
Advanced Intelligent Discovery, EarlyView.A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Near-Capacity Network Coding for Cooperative Multi-User Communications [PDF]
, 2011 In this contribution, we investigate Near-Capacity Multiuser Network-coding (NCMN) based systems using an Irregular Convolutional Code, a Unity-Rate Code and M-ary Phase-Shift Keying.
Joao Luiz Rebelatto +9 more
core +1 more source
Advanced Intelligent Systems, EarlyView.A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng +4 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This work proposes MDSC, an unsupervised low‐light enhancement framework integrating three core innovations: detail‐aware smoothing, multipath decomposition, and synergistic correction. It suppresses noise, handles rapid illumination variations, and prevents reflectance‐contrast amplification inherent to Retinex separation.
Yong Cheng +6 more
wiley +1 more source
Comparative Study of Turbo Decoding Techniques: An Overview [PDF]
, 2000 In this contribution, we provide an overview of the novel class of channel codes referred to as turbo codes, which have been shown to be capable of performing close to the Shannon Limit.
Woodard, J.P., Hanzo, L.
core
AI &Innovation, EarlyView.ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury +2 more
wiley +1 more source
American Journal of Botany, EarlyView.Abstract Premise Budding speciation occurs when peripheral populations adapt to local ecological conditions and “bud” off from a widespread progenitor species. Traditionally regarded as rare because of its sympatric and parapatric nature, budding speciation is largely understudied.
Eli J. Allen +3 more
wiley +1 more source
The Anatomical Record, EarlyView.Abstract The study of morphological evolution is fundamentally tied to ontogeny, yet studies of these heterochronic processes in the fossil record are rare. Fossils belonging to an ontogenetic series are difficult to assign to an ontogenetic stage due to inconsistent proxies for skeletal ages, challenging to taxonomically assign due to morphological ...
Erika R. Goldsmith, Michelle R. Stocker
wiley +1 more source
A Turbo Detection and Sphere-Packing-Modulation-Aided Space-Time Coding Scheme [PDF]
, 2007 A recently proposed space-time block-coding (STBC) signal-construction method that combines orthogonal design with sphere packing (SP), referred to here as STBC-SP, has shown useful performance improvements over Alamouti’s conventional orthogonal design.
YEAP, B-J., Hanzo, L, Alamri, O
core