Results 121 to 130 of about 22,976 (267)

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

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

Multicrack Localization in Rotors Based on Proper Orthogonal Decomposition Using Fractal Dimension and Gapped Smoothing Method

Shock and Vibration, 2016
Multicrack localization in operating rotor systems is still a challenge today. Focusing on this challenge, a new approach based on proper orthogonal decomposition (POD) is proposed for multicrack localization in rotors.
Zhiwen Lu, Dawei Dong, Shancheng Cao, Huajiang Ouyang, Chunrong Hua   +4 more
doaj   +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

Preconditioned dynamic mode decomposition and mode selection algorithms for large datasets using incremental proper orthogonal decomposition

AIP Advances, 2017
In this letter, we propose a simple and efficient framework of dynamic mode decomposition (DMD) and mode selection for large datasets. The proposed framework explicitly introduces a preconditioning step using an incremental proper orthogonal ...
Yuya Ohmichi
doaj   +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 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

Structural analysis of the NifL‐NifA complex reveals the molecular basis of anti‐activation of nitrogen fixation gene expression in Azotobacter vinelandii

The FEBS Journal, EarlyView.
Using cryo‐EM combined with biochemical and genetic approaches, we mapped the interaction surface between NifL and NifA to gain insights into the regulation of nitrogen fixation genes in A. vinelandii. Our findings suggest that NifL, a homolog of histidine kinases lacking phosphorylation activity, evolved to act as a steric block of NifA activity ...
Marcelo Bueno Batista, Jake Richardson, Michael W. Webster, Dmitry Ghilarov, John W. Peters, David M. Lawson, Ray Dixon   +6 more
wiley   +1 more source

ON HISTORICAL (ANTI‐)REALISM

History and Theory, EarlyView.
ABSTRACT The problem of historical realism has gained some new momentum recently, with a fresh challenge to what is taken to be an anti‐realist hegemony in the theory and philosophy of history. Unfortunately, this has also provided the opportunity for the reheating of old polemics and lazy scholarship that characterized the 1990s reaction to ...
João Ohara
wiley   +1 more source