Results 151 to 160 of about 24,886 (258)

GAN-Based Data Augmentation for Fault Diagnosis and Prognosis of Rolling Bearings: A Literature Review

IEEE Access
In 2014, Goodfellow et al. introduced Generative Adversarial Networks (GANs), an adversarial learning framework designed to generate synthetic data. In rolling bearing fault diagnosis and prognosis, specific GAN variants such as Conditional GANs (cGANs),
Md. Sulyman Islam Sifat, Md Alamgir Kabir, M. M. Manjurul Islam, Atiq Ur Rehman, Amine Bermak   +4 more
doaj   +1 more source

Esterification enhances carotenoid retention during bread‐making

Journal of the Science of Food and Agriculture, Volume 106, Issue 7, Page 4312-4319, May 2026.
Abstract BACKGROUND Carotenoids are plant‐derived antioxidants that contribute to human health and represent key quality traits in wheat‐based foods. However, they are highly unstable and prone to degradation during processing. Xanthophyll esterification has been identified as a natural mechanism that enhances carotenoid stability during grain storage.
María D Requena‐Ramírez, Cristina Rodríguez‐Suárez, Dámaso Hornero‐Méndez, Sergio G Atienza   +3 more
wiley   +1 more source

Domain adaptation via Wasserstein distance and discrepancy metric for chest X-ray image classification

Scientific Reports
Deep learning technology can effectively assist physicians in diagnosing chest radiographs. Conventional domain adaptation methods suffer from inaccurate lesion region localization, large errors in feature extraction, and a large number of model ...
Bishi He, Yuanjiao Chen, Darong Zhu, Zhe Xu   +3 more
doaj   +1 more source

Energy Management of PV-Enabled Battery Charging Swapping Stations for Electric Vehicles in Active Distribution Systems Under Uncertainty

Energies
In this paper, we propose a data-driven distributionally robust optimization (DRO) framework that ensures the economical and robust operation of solar photovoltaic (PV)-integrated battery charging swapping stations (BCSSs) for electric vehicles (EVs ...
Haram Kim, Sangyoon Lee, Dae-Hyun Choi
doaj   +1 more source

Lyapunov exponent and Wasserstein metric as validation tools for assessing short-time dynamics and quantitative model evaluation of large-eddy simulation [PDF]

, 2018
Hao Wu, Peter Ma, Yu Lv, Matthias Ihme
openalex   +1 more source

In‐and‐Out: Algorithmic Diffusion for Sampling Convex Bodies

Random Structures &Algorithms, Volume 68, Issue 3, May 2026.
ABSTRACT We present a new random walk for uniformly sampling high‐dimensional convex bodies. It achieves state‐of‐the‐art runtime complexity with stronger guarantees on the output than previously known, namely in Rényi divergence (which implies TV, 𝒲2, KL, χ2$$ {\chi}^2 $$).
Yunbum Kook, Santosh S. Vempala, Matthew S. Zhang   +2 more
wiley   +1 more source

Analysis of dynamically stable patterns in a maze-like corridor using the Wasserstein metric. [PDF]

Sci Rep, 2018
Ishiwata R, Kinukawa R, Sugiyama Y.
europepmc   +1 more source

Fast unsupervised ground metric learning with tree-Wasserstein distance [PDF]

Kira M. Düsterwald, Samo Hromadka, Makoto Yamada   +2 more
openalex   +1 more source

Eigenvalues of random matrices from compact classical groups in Wasserstein metric [PDF]

, 2023
Bence Borda
openalex   +1 more source

How Does the Definition of a Geomagnetic Storm Affect the Contents of the Resulting Storm List?

Space Weather, Volume 24, Issue 5, May 2026.
Abstract A geomagnetic storm is a significant and prolonged disturbance of the Earth's magnetic field caused by an enhancement of the ring current. Storms are typically identified using magnetic field measurements from multiple ground‐based magnetometers, and the corresponding dates and times of multiple storms can be collated to form a storm list ...
Atlas M. Patrick, John C. Coxon, Sarah N. Bentley, Maria‐Theresia Walach, Kyle R. Murphy, I. Jonathan Rae, Isobel S. Lockley   +6 more
wiley   +1 more source