Results 181 to 190 of about 25,600 (268)

Machine Learning‐Driven Capillary Microfluidic Design Automation for Programmable Gradient Generation and Antimicrobial Testing

Small, EarlyView.
TCG‐CMDA, a machine learning‐guided capillary microfluidic design automation platform, enables automated design of tree‐shaped concentration gradient generators for programmable mixing of two agents. The pump‐free chip supports synchronized passive flow and programmable gradient formation, providing a practical framework for decentralized point‐of‐care
Mahmood Khalghollah, Azam Zare, Sorosh Abdollahi, Behrouz H. Far, Amir Sanati Nezhad   +4 more
wiley   +1 more source

Deep learning interpretability in neuroimaging: A comprehensive survey and methodological recommendations. [PDF]

Imaging Neurosci (Camb)
Rahman MM, Calhoun V, Plis S.
europepmc   +1 more source

A Bilayer Rare‐Earth/High‐κ Oxide Memristor for Energy‐Efficient Neuromorphic Intelligence

Small, EarlyView.
Interface‐engineered Gd2O3/HfO2 bilayer memristors demonstrate controlled filament formation, ultralow switching energy (∼13.56 pJ), and fast operation (∼350 ns) with a high ON/OFF ratio (∼107). The devices exhibit stable analog synaptic behavior and enable pattern recognition on Fashion‐MNIST, underscoring their promise for energy‐efficient ...
Hammad Ghazanfar, Muhammad Rabeel, Honggyun Kim, Sobia Nisar, Muhammad Wajid Zulfiqar, Muneeb Ahmad, Rana Faryad Ali, Ghulam Dastgeer, Deok‐kee Kim   +8 more
wiley   +1 more source

Consistent explainable image quality assessment for medical imaging. [PDF]

Health Inf Sci Syst
Ozer C, Guler A, Turkvatan Cansever A, Oksuz I.   +3 more
europepmc   +1 more source

Decoding α‐MoC1−x Nanoparticle Formation in Continuous Flow via Machine Learning

Small, EarlyView.
Formation pathway of α‐MoC1−x nanoparticles synthesized from oleylamine‐Mo(CO)6 precursor under mild continuous‐flow conditions was investigated. By combining in‐line spectroscopic monitoring with a machine learning (ML) framework capable of deconvoluting complex, overlapping spectral features, we reveal mechanistic details of early‐transition‐metal ...
Bin Pan, Allison P. Forsberg, Ricki Chairil, Majed S. Madani, Susan E. Habas, Frederick G. Baddour, Richard L. Brutchey, Noah Malmstadt   +7 more
wiley   +1 more source

Training the parametric interactions in an analog bosonic quantum neural network with Fock basis measurement. [PDF]

Sci Rep
Dudas J, Carles B, Gouzien E, Grollier J, Marković D.   +4 more
europepmc   +1 more source

A Novel Approach to Energy Management in Electric Steelworks

steel research international, EarlyView.
Feed‐forward neural networks are exploited to estimate electric energy consumptions of the electric arc furnace and ladle furnace processes. The models are used to optimize production schedule so that more energy intensive grades are produced when the cost of energy is lower.
Valentina Colla, Stefano Dettori, Silvia Cateni, Marco Vannucci, Antonella Vignali, Claudio Mocci, Irene Dovichi, Davide Chionna, Lorenzo Vannini, Enrico Paluzzano, Costanzo Pietrosanti, Davide Onesti, Daniele Venier   +12 more
wiley   +1 more source

Model-Driven Processing of Passive Seismic While Drilling Data Acquired Using Distributed Acoustic Sensing Without Conventional Drill-Bit Pilot Measurements. [PDF]

Sensors (Basel)
Al-Hemyari E, Pevzner R, Tertyshnikov K.
europepmc   +1 more source

Decreasing the Environmental Impact of the Electric Steelmaking Route Through Advanced Modelling Techniques

steel research international, EarlyView.
Ensemble models are adopted to estimate the sterile content of scraps arriving to the scrap yard. Feed‐forward neural networks are exploited to estimate steel composition and temperature after Ladle furnace. The models are validated on data from two steelworks very satisfactory results and are inherently transferable to other steelworks, as they are ...
Valentina Colla, Antonella Zaccara, Stefano Dettori, Laura Laid, Ismael Matino, Silvia Cateni, Teresa Annunziata Branca, Lorenzo Vannini   +7 more
wiley   +1 more source