Results 71 to 80 of about 6,618 (260)

Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes

Advanced Intelligent Systems, EarlyView.
We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards, Thales C. Silva, M. Ani Hsieh   +2 more
wiley   +1 more source

Application of Proper Orthogonal Decomposition to Elucidate Spatial and Temporal Correlations in Air Pollution Across the City of Liverpool, UK

Urban Science
Understanding the spatiotemporal distribution of air pollution is critical for improving urban air quality. Advances in wireless sensor networks have made it possible to monitor air pollution across cities at higher spatiotemporal resolutions.
Cammy Acosta Ramírez, Jonathan E. Higham   +1 more
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

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, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Towards Reduced Order Models via Robust Proper Orthogonal Decomposition to capture personalised aortic haemodynamics. [PDF]

J Biomech, 2023
Chatpattanasiri C, Franzetti G, Bonfanti M, Diaz-Zuccarini V, Balabani S.   +4 more
europepmc   +2 more sources

Generalized Task‐Driven Design of Soft Robots via Reduced‐Order Finite Element Method‐Based Surrogate Modeling

Advanced Intelligent Systems, EarlyView.
A unified, reusable modeling pipeline enables task‐driven design of soft robots across actuator families and task scenarios. High‐fidelity simulations are compressed into compact pseudo‐rigid‐body joint surrogates, while a design‐conditioned meta‐model generates new surrogates from geometry parameters without rerunning finite element method.
Yao Yao, David Howard, Perla Maiolino
wiley   +1 more source

Nanomaterial‐based immune therapeutic strategies in neurodegenerative diseases

BMEMat, EarlyView.
This review highlights the immunomodulatory potential of nanomaterials (NMs) in treating neurodegenerative diseases (NDs). It focuses on their roles in regulating innate and adaptive immune responses to maintain immune homeostasis. By providing insights into these mechanisms, the review lays the groundwork for innovative NMs therapeutic strategies to ...
Xinru Zhou, Jia Liu, Shulin Lai, Suhan Yin, Bingmin Luo, Longquan Shao, Yiyuan Kang   +6 more
wiley   +1 more source

Unsteady characteristics analysis of compressors based on the proper orthogonal decomposition method [PDF]

AIP Advances
An aero-engine is often accompanied by a strong unsteady flow at near-stall condition, and increasing unsteady airflow eventually makes the engine unstable. To explore the unsteady flow characteristics, the Rotor 37 was taken as the research object.
Shan Ma, Xiaolin Sun, Lin Cheng, Yang Yu, Wen Cheng   +4 more
doaj   +1 more source

Efficient multi-objective shape optimization using proper orthogonal decomposition with variable fidelity concept

Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2020
A variable fidelity concept is introduced in a re-parameterization approach based on the proper orthogonal decomposition (POD) to efficiently solve multi-objective aerodynamic shape optimization problems.
Wataru YAMAZAKI
doaj   +1 more source

PODNO: Proper Orthogonal Decomposition Neural Operators

CoRR
In this paper, we introduce Proper Orthogonal Decomposition Neural Operators (PODNO) for solving partial differential equations (PDEs) dominated by high-frequency components. Building on the structure of Fourier Neural Operators (FNO), PODNO replaces the Fourier transform with (inverse) orthonormal transforms derived from the Proper Orthogonal ...
Zilan Cheng, Zhongjian Wang, Li-Lian Wang, Mejdi Azaïez   +3 more
openaire   +2 more sources

Marine silicon for biomedical sustainability

BMEMat, EarlyView.
Schematic illustrating marine silicon for biomedical engineering. Abstract Despite momentous divergence from oceanic origin, human beings and marine organisms exhibit elemental homology through silicon utilization. Notably, silicon serves as a critical constituent in multiple biomedical processes.
Yahui Han, Zhibo Yang, Wei Xia, Chengtie Wu   +3 more
wiley   +1 more source