Results 191 to 200 of about 472,806 (301)
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang +4 more
wiley +1 more source
AT-BSS: A Broker Selection Strategy for Efficient Cross-Shard Processing in Sharded IoT-Blockchain Systems. [PDF]
Su Y, Xiang Y, Nguyen K, Sekiya H.
europepmc +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
SEU-Hardened High-Speed SRAM Design with Self-Refresh and Adjacent-Bit Error Correction. [PDF]
Li T, Tian J, Qi J.
europepmc +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
DynaLiRD: A dataset for dynamic line rating of overhead transmission lines, utilizing meteorological data and grid parameters based on the IEEE 738-2012 standard. [PDF]
Alam N, Rahman MA, Islam MR.
europepmc +1 more source
Haptic In‐Sensor Computing Device Based on CNT/PDMS Nanocomposite Physical Reservoir
Using a porous carbon nanotube‐polydimethylsiloxane nanocomposite, a sensor array integrated with a physical reservoir computing paradigm capable of in‐sensor computing is demonstrated. The device is able to classify between nine objects with an accuracy above 80%, opening the possibility for low‐power sensing/computing for future robotics.
Kouki Kimizuka +7 more
wiley +1 more source
Field-based tests for assessing motor abilities in young volleyball players: normative values and age group differences. [PDF]
Grbić V +4 more
europepmc +1 more source
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source

