Results 151 to 160 of about 141,691 (225)

Lightweight Hash-Based Authentication Protocol for Smart Grids. [PDF]

Sensors (Basel)
Kook S, Kim K, Ryu J, Lee Y, Won D.
europepmc   +1 more source

SmaRds - Smart Regimes for Smart Grids [PDF]

, 2015
Diestelmeier, Lea, Lammers, Imke
core   +2 more sources

Metalearning‐Driven Inverse Optimization for Precision Microstructure Fabrication in Digital Light Processing Three‐Dimensional Printing

Advanced Intelligent Systems, EarlyView.
Metalearning‐based inverse optimization enables precise microscale three‐dimensional printing using a DLP system. Distorted structures from conventional printing are analyzed via neural network regression, which predicts optimal exposure time and mask design.
Jae Won Choi, Suhyeong Lim, Jeongsu Lee, Cheol Woo Ha   +3 more
wiley   +1 more source

A lightweight deep learning framework for transformer fault diagnosis in smart grids using multiple scale CNN features. [PDF]

Sci Rep
Attallah O, Ibrahim RA, Zakzouk NE.
europepmc   +1 more source

Physical Reservoir Computing for Smart Manufacturing of PCB Using Crystallinity‐Controlled HfO2 Memristor for Reservoir

Advanced Intelligent Systems, EarlyView.
We address multilayer PCB anomaly detection for smart manufacturing by physical reservoir computing with HfO2‐based memristors. Crystallinity‐tuned HfO2 suppresses ferroelectricity while preserving the high‐k insulating state and confers strong short‐term memory.
Yongho Lee, Wonhee Lee, Junho Shin, Noah Jang, Hyunjun Kim, Da Ye Kim, Jinkyung Kim, June Soo Kim   +7 more
wiley   +1 more source

Enhancing energy distribution through dynamic multi-hop for heterogeneous WSNs dedicated to IoT-enabled smart grids. [PDF]

Sci Rep
Elmonser M, Alaerjan A, Jabeur R, Chikha HB, Attia R.   +4 more
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Data-driven and privacy-preserving risk assessment method based on federated learning for smart grids. [PDF]

Commun Eng
Deng S, Zhang L, Yue D.
europepmc   +1 more source

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

SMART GRIDS

Veille énergie climat, 2011
openaire   +3 more sources