Results 221 to 230 of about 1,820,249 (291)

A Center-of-Pressure Guided Finger-Press Sensor for Cuffless Blood Pressure Estimation. [PDF]

Sensors (Basel)
Gul FAI, Tudose D.
europepmc   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

Advanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Predictions of Liquid Methane (LCH₄) Lubricated Hybrid Tilting Pad Journal Bearings for Reusable Rocket Turbopumps. [PDF]

Materials (Basel)
Kim Y, Kim TH.
europepmc   +1 more source

Toward Fully Soft and Multifunctional Shape Sensing via Optical Waveguide Arrays

Advanced Intelligent Systems, EarlyView.
This work develops a sheet made with arrays of soft optical fibers that can reconstruct its 3D surface shape. Synergy of the waveguides’ responses to bending and pressing force allows shape reconstruction with resilience to damage. Applied onto surfaces of robotic or living systems, our design can be implemented in virtual reality, teleoperation ...
Qifan Yu, Nina Cao, Kaitlyn Becker
wiley   +1 more source

Optical soliton solutions of the unstable nonlinear Schrödinger equation. [PDF]

Sci Rep
Shabbir S, Saeed ST, Asghar U, Saleem S, Merga FE.   +4 more
europepmc   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

A multi-stage stacking framework for accurate and interpretable life expectancy modeling. [PDF]

PLoS One
Chinthaginjala R, Tera SP, Natha P, Srinivasulu A, Al-Turjman F, Mohammad F.   +5 more
europepmc   +1 more source

A Compact Multijoint Finger Motion Sensing Module for Flexible Exoskeleton Applications

Advanced Intelligent Systems, EarlyView.
Addressing the motion estimation gap in underactuated wearable electronics, a highly integrated sensor alongside a customized readout circuit is proposed. Featuring a screen‐printed layout and optimized horseshoe geometry, this design establishes an optimal feedback mechanism for flexible hand exoskeletons while eliminating wiring clutter.
Huawei Zheng, Frédéric Lamarque, Hani Al Hajjar, Andreas Dietzel   +3 more
wiley   +1 more source

A multimodal adjoint-state formulation of Quantitative Photoacoustic Tomography with external acoustic sources. [PDF]

Photoacoustics
Segerlund M, Löfqvist T.
europepmc   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source