Results 91 to 100 of about 2,487 (204)

General Variational Formulation of Axisymmetric Capillary Bridges: Modeling Contact Angle Hysteresis and Capillary Forces

International Journal for Numerical and Analytical Methods in Geomechanics, Volume 50, Issue 12, Page 4879-4892, 25 August 2026.
ABSTRACT This work presents a general framework for deriving the Young–Laplace equation and the Young's equations for an axisymmetric capillary bridge between two parallel plates by minimizing the system's total energy. These Young's equations naturally emerge as boundary conditions associated with the Young–Laplace equation.
Olivier Millet, Antoine Moreau, Antoine Logerot, Marc Médale   +3 more
wiley   +1 more source

Monotone Clusters With Ordinal Interpretation

Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 4, August 2026.
ABSTRACT There has been a growing demand in various sectors, such as healthcare, finance, and social sciences, for clustering methods that not only find quality clusters in data but also provide inherent order among the clusters for better decision‐making and risk assessment. Traditional clustering methods, though effective at grouping data, often fall
Hee Cheol Chung, Seongbin An, Hyunwoo Cha, Jeongyoun Ahn   +3 more
wiley   +1 more source

FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. [PDF]

Comput Vis ECCV, 2020
Lokhande VS, Akash AK, Ravi SN, Singh V.
europepmc   +1 more source

Enhanced Retrieval of Spring Snow Depth Over Pan‐Arctic Sea Ice From AMSR2 Observations for 2013–2023 Using Multi‐Model Machine Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Snow on sea ice modulates the Earth's radiation budget and sea ice mass balance, yet satellite retrievals of Arctic snow depth remain subject to substantial algorithmic uncertainty. We develop a multi‐model machine learning (ML) framework for retrieving spring snow depth over Arctic sea ice from Advanced Microwave Scanning Radiometer 2 (AMSR2).
Yi Zhou, Chentong Zhang, Alek Petty, Xianwei Wang, Ruibo Lei, Wenxuan Liu, Yu Zhang   +6 more
wiley   +1 more source

Computation offloading in STAR-RIS aided U-MEC systems: A delay-minimization deep reinforcement learning approach

Ain Shams Engineering Journal
Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is a new wireless communication technology with bidirectional transmission.
Wenjie Wu, Zhongqiang Luo
doaj   +1 more source

Overall Prediction of Breakthrough Curves in Fracture Networks Using Graph‐Based Simulation and Machine Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Discrete fracture network (DFN) models are widely used to simulate fluid and solute transport through fracture networks that serve as their preferential pathways. In DFN models, fractures are generated stochastically based on fracture properties.
S. Okamoto, K. Nakata, K. Mori, T. Saito
wiley   +1 more source

Data‐Driven Emulation of Numerically Simulated Baltic Sea Surface Currents With a Deep Convolutional U‐Net: Explainability and Potential Forecast Skill

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Ocean models can represent surface circulation at kilometer scales, but their computational cost limits broad experimentation. We present DeepCUN, a deep convolutional encoder–decoder (U‐Net) that emulates daily mean Baltic Sea surface current components on a 1‐nautical‐mile grid.
Amirhossein Barzandeh, Christoph Manss, Frederic Stahl, Ilja Maljutenko, Sander Rikka, Urmas Raudsepp   +5 more
wiley   +1 more source

An Enhanced Langmuir Turbulence Parameterization With Nonlocal Momentum and Scalar Fluxes

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Langmuir turbulence plays a critical role in the oceanic surface boundary layer by efficiently transporting momentum, heat, gases, and nutrients. Since its characteristic scale (meters to tens of meters) is far smaller than typical grid cells of ocean general circulation models, it must be parameterized.
Peng Wang
wiley   +1 more source

Solving Environmental/Economic Power Dispatch Problem by a Trust Region Based Augmented Lagrangian Method

Iranian Journal of Electrical and Electronic Engineering, 2012
This paper proposes a Trust-Region Based Augmented Method (TRALM) to solve a combined Environmental and Economic Power Dispatch (EEPD) problem. The EEPD problem is a multi-objective problem with competing and non-commensurable objectives.
H. Mohammadian Bishe, A. Rahimi Kian, M. Sayyed Esfahani   +2 more
doaj  

Predicting Coronal Mass Ejection Travel Times Using Enhanced Model‐Guided Machine Learning

Space Weather, Volume 24, Issue 8, August 2026.
Abstract Coronal mass ejections (CMEs) are key drivers of space weather events, posing risks to both space‐borne and ground‐based systems. An accurate prediction of their arrival time at Earth is critical for impact mitigation. To this end, physics‐informed artificial intelligence (AI) approaches have proven more effective than purely data‐driven or ...
M. Lampani, M. Rossi, S. Guastavino, M. Piana, A. M. Massone   +4 more
wiley   +1 more source