Results 101 to 110 of about 30,753 (229)

Scour‐Conditioned Seismic Fragility Analysis of Monopile‐Supported Offshore Wind Turbines

Earthquake Engineering &Structural Dynamics, Volume 55, Issue 4, Page 947-967, 10 April 2026.
ABSTRACT Monopile‐supported offshore wind turbines (MS‐OWTs) are increasingly deployed in seismic coastal regions, where they face compound risks from earthquake loading and seabed scour. While past studies have addressed these hazards separately, seismic fragility under evolving scour conditions remains insufficiently understood. This study introduces
Francisco Pinto, Rodrigo Astroza, Felipe Vicencio, Raffaele De Risi   +3 more
wiley   +1 more source

Time‐ and State‐Dependent Damage Accumulation Due to Aftershocks Under an M9.0 Megathrust Earthquake in the Cascadia Subduction Zone

Earthquake Engineering &Structural Dynamics, Volume 55, Issue 5, Page 1157-1175, 25 April 2026.
ABSTRACT This study develops a comprehensive framework for assessing time and state‐dependent aftershock damage accumulation under an M9.0 megathrust interface earthquake in the Cascadia Subduction Zone (CSZ). The framework integrates aftershock probabilistic seismic hazard analysis (APSHA) and state‐dependent fragility analysis (SDFA) within a ...
Hongzhou Zhang, Yazhou Xie
wiley   +1 more source

EVSS‐Based Simulation Techniques for the Viscoelastic Fluids With Pure Polymer Melts Using Three‐Field Approach

International Journal for Numerical Methods in Fluids, Volume 98, Issue 4, Page 492-509, April 2026.
This paper presents a finite element method for simulating highly viscoelastic flows of pure polymer melts using the Elastic Viscous Stress Splitting formulation. The method avoids higher‐order derivatives in the weak formulation by reformulating the convective term in the constitutive equation.
R. Ahmad, P. Zajac, S. Turek
wiley   +1 more source

GloMarGridding: A Python Toolkit for Flexible Spatial Interpolation in Climate Applications

Geoscience Data Journal, Volume 13, Issue 2, April 2026.
Global surface climate datasets contain structural uncertainty that is difficult to attribute to individual processing steps. We present GloMarGridding, a Python package that isolates the spatial interpolation component using Gaussian Process Regression (or kriging) to generate spatially complete fields and uncertainty estimates. The techniques used in
Richard C. Cornes, Steven C. Chan, Archie Cable, Duo Chan, Agnieszka Faulkner, Elizabeth C. Kent, Joseph T. Siddons   +6 more
wiley   +1 more source

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

AGU Advances, Volume 7, Issue 2, April 2026.
Abstract Machine learning (ML)‐based models have demonstrated high skill and computational efficiency, often outperforming conventional physics‐based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic‐scale atmospheric dynamics, their performance across timescales and under out‐of ...
Ziming Chen, L. Ruby Leung, Wenyu Zhou, Jian Lu, Sandro W. Lubis, Ye Liu, Chuan‐Chieh Chang, Bryce E. Harrop, Ya Wang, Mingshi Yang, Gan Zhang, Yun Qian   +11 more
wiley   +1 more source

Cryptography in the Cloud Computing: the Current State and Logical Tasks

Безопасность информационных технологий, 2013
The current state of the cloud computing (CC) information security is analysed and logical problems of storage and data transmission security at CC are allocated.
Sergey Nikolaevich Kyazhin, Andrey Vladimirovich Moiseev   +1 more
doaj  

Identity based cryptography from bilinear pairings

, 2005
This report contains an overview of two related areas of research in cryptography which have been prolific in significant advances in recent years. The first of these areas is pairing based cryptography. Bilinear pairings over elliptic curves were initially used as formal mathematical tools and later as cryptanalysis tools that rendered supersingular ...
openaire   +1 more source

Global‐Scale Analysis of Biochar Cropland Application Strategies and Their Climate Change Mitigation Potential Using Machine Learning

GCB Bioenergy, Volume 18, Issue 4, April 2026.
Machine learning models predicted crop yield and soil greenhouse gas responses to biochar application, with soil and climate conditions identified as dominant factors. Global simulations and life cycle assessment quantified spatially optimized strategies and mitigation potential.
Xingyu Lu, Xiaolin Zhang, Junyu Yang, Fengping Chen   +3 more
wiley   +1 more source

Efficient identification protocol provably secure in standard model

Tongxin xuebao, 2009
Based on the hardness assumption of the collusion attack algorithm with k traitors （K-CAA） in a gap Diffie-Hellman （GDH） group, a new and efficient identification protocol is proposed.
LI Yan-ping1, WANG Yu-min1
doaj   +2 more sources

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, Volume 40, Issue 2, Page 915-953, April 2026.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source