Results 51 to 60 of about 1,029 (242)

Transformer xApps for Semantic URLLC in Open RAN

IEEE Open Journal of the Communications Society
This paper addresses reliability challenges in ultra-reliable low-latency communication (URLLC) by extending classical communication theory with semantic-aware approaches deployed as xApps in Open RAN’s Near-RT RIC (Near Real-Time RAN Intelligent ...
Azadeh Arnaz, Justin Lipman, Mehran Abolhasan   +2 more
doaj   +1 more source

Modeling Dislocation Cutting of γ′ Precipitates in Ni‐Base Superalloys: Linking Atomistic and Dislocation Dynamics Simulations

Advanced Engineering Materials, EarlyView.
Dislocation cutting of γ′ precipitates in Ni‐based superalloys is investigated by linking atomistic simulations with discrete dislocation dynamics. The critical cutting stress is shown to be governed by the antiphase boundary energy, while line tension effects promote edge‐preferred cutting.
Frédéric Houllé, Siwen Gao, Marc Fivel, Anxin Ma, Daria Smirnova, Sriram Anand, Arun Prakash, Julien Guénolé, Alexander Hartmaier, Erik Bitzek   +9 more
wiley   +1 more source

xApp Empowered Resource Management for Non-Terrestrial Users in 5G O-RAN Networks

IEEE Transactions on Machine Learning in Communications and Networking
This paper introduces a proactive Unmanned Aerial Vehicle (UAV) mobility management xApp for Open Radio Access Network (O-RAN) Near Real-Time Radio Intelligent Controller (Near-RT RIC) environments, employing Double Deep Q-Network (DDQN) reinforcement ...
Mohammed M. H. Qazzaz, Syed Ali Raza Zaidi, Aubida A. Al-Hameed, Abdelaziz Salama, Des Mclernon   +4 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Extrusion‐Based Additive Manufacturing of Advanced Ceramics: Strengthening Mechanisms and Process Optimization Review

Advanced Engineering Materials, EarlyView.
This review comprehensively evaluates extrusion‐based additive manufacturing for advanced ceramics, detailing feedstock options and key process parameters. By critically addressing defect mechanisms like porosity and cracking, the work highlights optimization strategies through machine learning and advanced postprocessing.
Meisam Bakhtiari, Mohammad Hadi Sheikh‐Ansari, Avinash Borgaonkar, Mehran Dadkhah, Abdollah Saboori   +4 more
wiley   +1 more source

Energy Efficiency in Open RAN: RF Channel Reconfiguration Use Case

IEEE Access
Recently, energy efficiency (EE) has been pointed out as one of the key requirements within mobile networks. The development of intelligent algorithms providing Radio Access Networks (RAN) with EE features is possible when having access to the Key ...
Marcin Hoffmann, Marcin Dryjanski
doaj   +1 more source

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

Advanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Henk Birkholz, Hossein Beygi Nasrabadi, Khashayar Razghandi, Kamilla Zaripova, Felix Thonagel, Fabian Neuhaus, Martin Glauer, Lars Vogt, Harald Sack, Lutz Mädler, Bernd Bayerlein, Chris Eberl   +15 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Task-Specific Sharpness-Aware O-RAN Resource Management Using Multi-Agent Reinforcement Learning

IEEE Transactions on Machine Learning in Communications and Networking
Next-generation networks utilize the Open Radio Access Network (O-RAN) architecture to enable dynamic resource management, facilitated by the RAN Intelligent Controller (RIC).
Fatemeh Lotfi, Hossein Rajoli, Fatemeh Afghah   +2 more
doaj   +1 more source

Power-Efficient RAN Intelligent Controllers Through Optimized KPI Monitoring

2025 IEEE Wireless Communications and Networking Conference (WCNC)
Accepted for publication and presentation at IEEE WCNC ...
João Paulo S. H. Lima, Georgios Ntavazlis Katsaros, Konstantinos Nikitopoulos   +2 more
openaire   +2 more sources