Results 221 to 230 of about 1,074,720 (325)

Robot‐Assisted Measurement of the Critical Micelle Concentration

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The study introduces (SIMO) smart integrator for manual operations, a robotic platform for precise, repeatable determination of (CMC) critical micelle concentration in surfactants. SIMO reduces standard deviation by 80% compared to manual methods. Surfactant, dye, and diluent selection, robotic protocols, and data handling are detailed.
Vincenzo Scamarcio   +3 more
wiley   +1 more source

Investigation of Analog Memristor Characteristics for Hardware Synaptic Weight in Multilayer Neural Network

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley   +1 more source

A scalable and secure federated learning authentication scheme for IoT. [PDF]

open access: yesSci Rep
Chithaluru P   +6 more
europepmc   +1 more source

Topological self-joinings of Cartan ac-

open access: yesDuke Math. J., 161(7):1305–1350, 2012, 2012
Elon Lindenstrauss, Zhiren Wang
openaire  

Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes

open access: yesAdvanced Intelligent Systems, EarlyView.
We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards   +2 more
wiley   +1 more source

Electroencephalogram‐Driven Recognition of Parkinson's Disease Through a Mycelium‐Inspired Memristive Reservoir Computing Circuit

open access: yesAdvanced Intelligent Systems, EarlyView.
This work presents a bio‐inspired computing framework for Parkinson's disease analog recognition using electroencephalogram signals. Temporally encoded EEG features stimulate a mycelium‐inspired memristive reservoir, where disease‐related patterns emerge through physical spatiotemporal dynamics.
Ioannis K. Chatzipaschalis   +5 more
wiley   +1 more source

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