Results 121 to 130 of about 148,863 (263)

Multiple Locally Linear Kernel Machines

CoRR
In this paper we propose a new non-linear classifier based on a combination of locally linear classifiers. A well known optimization formulation is given as we cast the problem in a $\ell_1$ Multiple Kernel Learning (MKL) problem using many locally linear kernels.
openaire   +2 more sources

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Autonomous Navigation of Pollen‐Inspired Magnetic Microrobots for Biomedical Applications

Advanced Robotics Research, EarlyView.
A sunflower pollen‐inspired magnetic microrobot enables controlled rolling navigation in vessel‐like environments. Its open geometry reduces hydrodynamic drag, while vision‐based closed‐loop control, shortest‐path planning, and reinforcement learning support target‐reaching and maze navigation with microrobot‐scale accuracy, highlighting a route toward
Ali Anil Demircali, Abdurrahim Yilmaz, Meysam Keshavarz, Jinshi Zhao, Ara Darzi, Eric Yeatman, Burak Temelkuran   +6 more
wiley   +1 more source

A Whole‐Head Finite Element Model for Electrical Neuromodulation via Visual Brain‐Machine Interfaces

Advanced Science, EarlyView.
A multimodal, personalized head model is presented that integrates the entire visual pathway with surrounding tissues to simulate electrical stimulation of the optic nerve. In vivo validation in humans and goats, plus systematic component‐elimination analysis, demonstrates the high accuracy of the comprehensive model.
Shengjian Lu, Tonghe Yang, Yuan Geng, Huan Wu, Yangrui Huang, Te Zheng, Haodi Chen, Shurui Huang, Yi Cao, Jian Yang, Wentao Yan, Yikui Zhang, Wencan Wu   +12 more
wiley   +1 more source

Cross Kingdom Metabolic Engineering Paradigm Elevating Sustainable Protein Production

Advanced Science, EarlyView.
ABSTRACT Confronting the dual crisis of escalating global protein demand and unsustainable agriculture necessitates transformative solutions. Here, we pioneer evolutionary insights from maize nitrogen optimization via asparagine synthetase (ASNS) to rewire metabolism in Pichia pastoris.
Yuanyuan Du, Changyu Pi, Kai Hong, Le Gao, Xin Wu   +4 more
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

NeuroSuite for Long‐Term Functional and Structural Studies of Air‐Liquid Interface Cerebral Organoids

Advanced Science, EarlyView.
NeuroSuite provides a modular hardware‐software platform integrating Neuroweb and NeuroMaps to enable long‐term, in situ electrophysiological interrogation of air–liquid interface organoid slices while preserving tissue architecture. Its components can be used together or independently to capture real‐time activity, spatial network dynamics, and ...
Belquis Haider, Sagnik Middya, Daniel J. Lloyd‐Davies‐Sánchez, Nino F. Läubli, Sulay Vora, Jakob Träuble, Rohan N. Krajeski, Yuqing Feng, Daniel Duncko, Josiah S. Riley, Rubén Ruiz‐Mateos Serrano, Ole Paulsen, Madeline A. Lancaster, George G. Malliaras, Gabriele S. Kaminski Schierle   +14 more
wiley   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source