Results 21 to 30 of about 4,117 (102)
Mathematical Problems in Engineering, Volume 2014, Issue 1, 2014., 2014 Modal Identification is considered from response data of structural systems under nonstationary ambient vibration. The conventional autoregressive moving average (ARMA) algorithm is applicable to perform modal identification, however, only for stationary‐process vibration.
Chang-Sheng Lin +3 more
wiley +1 more source
A novel haptic model and environment for maxillofacial surgical operation planning and manipulation [PDF]
, 2012 This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is
Arnez, Victor +7 more
core +1 more source
Constraining 2D Hydrogeological Inversion With 3D Lithological Data
Water Resources Research, Volume 61, Issue 12, December 2025.Abstract In hydrogeology, piezometric data are the key constraints for model calibration. Their limits for three‐dimensional (3D) parameterization have often been pointed out, with water heads commonly regarded as having too little sensitivity to vertical heterogeneity.
D. Rambourg, P. Ackerer, W. Nouaim
wiley +1 more source
Nanophotonics, Volume 14, Issue 23, Page 3977-3989, 02 November 2025.Abstract We present a photonic mode converter based on a grating structure, modeled and inversely designed by deep neural networks. The neural network maps the physical parameters of the grating to the grating responses, i.e., complex scattering parameters representing the reflected modes from the grating structure.
Ali Mohajer Hejazi, Vincent Ginis
wiley +1 more source
A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation. II: Application to Global Ozone Assimilation [PDF]
, 2012 Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable.
Bowman, Kevin +4 more
core +1 more source
Mantle Structure Beneath the Greater Alpine Region From Teleseismic Full P‐Waveform Inversion
Journal of Geophysical Research: Solid Earth, Volume 130, Issue 11, November 2025.Abstract AlpArray data were employed to infer a new mantle model of the Alps from teleseismic full P‐waveform inversion. It features hybrid numerical forward modeling in the time domain, compression of wavefields by Fourier transform at selected frequencies, the use of frequency domain waveform sensitivity kernels and a multi‐scale approach by ...
W. Friederich +5 more
wiley +1 more source
Optimal Nonlinear Eddy Viscosity in Galerkin Models of Turbulent Flows
, 2015 We propose a variational approach to identification of an optimal nonlinear eddy viscosity as a subscale turbulence representation for POD models. The ansatz for the eddy viscosity is given in terms of an arbitrary function of the resolved fluctuation ...
Noack, Bernd R. +2 more
core +1 more source
Improving Dryland Depth to Water Table Estimate Using an Integrated Model With Three Submodels
Water Resources Research, Volume 61, Issue 10, October 2025.Abstract Investigating dryland phreatic water assets requires an in‐deep understanding of depth to water table (DWT). However, current DWT methods suffer from limited accuracy and demand refinement. Therefor, this study suggests one novel integrated model cascaded by twin, assimilation, and DWT submodels.
Shaohui Chen
wiley +1 more source
Fluctuation-Response Relations for Multi-Time Correlations
, 1999 We show that time-correlation functions of arbitrary order for any random variable in a statistical dynamical system can be calculated as higher-order response functions of the mean history of the variable.
C. Bischof +13 more
core +1 more source
Improving neural ordinary differential equations via knowledge distillation
IET Computer Vision, Volume 18, Issue 2, Page 304-314, March 2024.A new training based on knowledge distillation is proposed to construct more powerful and robust Neural ODEs fitting image recognition tasks. Specially, the training of Neural ODEs is modelled into a teacher‐student learning process, in which ResNets is proposed as the teacher model to provide richer supervised information.
Haoyu Chu +3 more
wiley +1 more source