Results 121 to 130 of about 113,908 (298)

Enhancing Lipidomics With High‐Resolution Ion Mobility‐Mass Spectrometry

PROTEOMICS, EarlyView.
ABSTRACT Lipids, indispensable yet structurally intricate biomolecules, serve as critical regulators of cellular function and disease progression. Conventional lipidomics, constrained by limited resolution for isomeric and low‐abundance species, has been transformed by ion mobility‐mass spectrometry (IM‐MS).
Gaoyuan Lu, Shuling Xu, Penghsuan Huang, Lingjun Li   +3 more
wiley   +1 more source

Regularization method for calibrated POD reduced-order models

MATEC Web of Conferences, 2014
In this work we present a regularization method to improve the accuracy of reduced-order models based on Proper Orthogonal Decomposition. The bench mark configuration retained corresponds to a case of relatively simple dynamics: a two-dimensional flow ...
El Majd Badr Abou, Cordier Laurent
doaj   +1 more source

Reduced‐Order Modeling of Energetic Materials Using Physics‐Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)

Propellants, Explosives, Pyrotechnics, EarlyView.
Physics‐Aware Recurrent Convolutional Neural Networks (PARC) can reliably learn the thermomechanics of energetic materials as a function of morphology. This work introduces LatentPARC, which accelerates PARC by modeling the dynamics in a low‐dimensional latent space.
Zoë J. Gray, Joseph B. Choi, Youngsoo Choi, H. Keo Springer, H. S. Udaykumar, Stephen S. Baek   +5 more
wiley   +1 more source

Decomposition methods in turbulence research

EPJ Web of Conferences, 2012
Nowadays we have the dynamical velocity vector field of turbulent flow at our disposal coming thanks advances of either mathematical simulation (DNS) or of experiment (time-resolved PIV).
Uruba Václav
doaj   +1 more source

Loss Behavior in Supervised Learning With Entangled States

Advanced Quantum Technologies, EarlyView.
Entanglement in training samples supports quantum supervised learning algorithm in obtaining solutions of low generalization error. Using analytical as well as numerical methods, this work shows that the positive effect of entanglement on model after training has negative consequences for the trainability of the model itself, while showing the ...
Alexander Mandl, Johanna Barzen, Marvin Bechtold, Frank Leymann, Lavinia Stiliadou   +4 more
wiley   +1 more source

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

MOEA/D‐based multi‐row facility layout optimisation method with discontinuity perceiving of the Pareto front

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In a multi‐row facility layout problem (MRFLP), facilities are arranged in more than one row under the limited layout area. Considering different layout factors, various extensions of MRFLP have been modelled. However, the orientation of input/output (I/O) point in a facility, as a key factor that plays a direct impact on flow cost, is seldom ...
Yinan Guo, Yao Huang, Jian Cheng, Xiaoyu Ban, Xiaoxiao Zhao, Tianyu Liu   +5 more
wiley   +1 more source

An Augmented Subspace Based Adaptive Proper Orthogonal Decomposition Method for Time Dependent Partial Differential Equations [PDF]

, 2023
Xiaoying Dai, Miao Hu, Jack Xin, Aihui Zhou   +3 more
openalex   +1 more source

An Efficient Method for Transient Temperature Calculation in Oil Natural Transformers Based on the Time‐Space Proper Orthogonal Decomposition

High Voltage, EarlyView.
ABSTRACT A reduced‐order model (ROM) for the temperature field based on time‐space proper orthogonal decomposition (POD) is presented to improve the computational efficiency of transient temperature rise in oil‐immersed power transformers with a complete oil natural convection cooling loop.
Haijuan Lan, Wenhu Tang, Zeyi Zhang, Jiahao Gong, Xiongwen Xu, Goran Strbac   +5 more
wiley   +1 more source

Estimating Causal Effects With Observational Data: Guidelines for Agricultural and Applied Economists

Journal of Agricultural Economics, EarlyView.
ABSTRACT Most research questions in agricultural and applied economics are causal in nature: they study how changes in one or more variables (such as policies, prices or weather) affect one or more other variables (e.g., income, crop yields or pollution).
Arne Henningsen, Guy Low, David Wuepper, Tobias Dalhaus, Hugo Storm, Dagim Belay, Stefan Hirsch   +6 more
wiley   +1 more source