Results 221 to 230 of about 47,345 (292)

Process Resilience under Optimal Data Injection Attacks

open access: yesAIChE Journal, EarlyView.
Abstract In this article, we study the resilience of process systems in an information‐theoretic framework, from the perspective of an attacker capable of optimally constructing data injection attacks. The attack aims to distract the stationary distributions of process variables and stay stealthy, simultaneously.
Xiuzhen Ye, Wentao Tang
wiley   +1 more source

Two‐Stage GAN‐Based Generation of Virtual 3D Multicrystalline Silicon Reproducing Nucleation and Crystal Growth Processes Using Crystallographic Information from Real Ingots

open access: yesAdvanced Intelligent Discovery, EarlyView.
We developed two generative adversarial network models that correspond to nucleation and directional solidification, using data collected from real materials. By combining these models, we created a method to virtually replicate real‐world crystal growth experiments and generate a variety of 3D multicrystalline silicon models in cyberspace.
Takumi Deshimaru   +7 more
wiley   +1 more source

Many photonic design problems are sparse QCQPs. [PDF]

open access: yesSci Adv
Gertler S   +4 more
europepmc   +1 more source

Inverse Engineering of Mg Alloys Using Guided Oversampling and Semi‐Supervised Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
End‐to‐end design of engineering materials such as Mg alloys must include the properties, structure, and post‐synthesis processing methods. However, this is challenging when destructive mechanical testing is needed to annotate unseen data, and the processing methods for hypothetical alloys are unknown.
Amanda S. Barnard
wiley   +1 more source

Clinically Informed Intelligent Classification of Ovarian Cancer Cells by Label‐Free Holographic Imaging Flow Cytometry

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone   +11 more
wiley   +1 more source

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