Results 31 to 40 of about 9,722 (217)

Operational Internet of Things Intrusion Detection Under Domain Shift with a Lipschitz-Constrained Markov Decision Process Decoder

Electrica
Intrusion detection for Internet of Things (IoT) networks must operate at a very low false-positive rate (FPR): attacks are rare, so even a small FPR floods analysts with alerts and a detection score is useful for triage only if it behaves like a real ...
Mustafa İpekbayrak, Zeynep Gürkaş-Aydın   +1 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

SemanticST: A Scalable Multi‐Contextual Graph Learning Framework for Uncovering Spatial Niches and Robust Multi‐Sample Integration in Spatial Transcriptomics

Advanced Science, EarlyView.
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi, Ahmadreza Argha, Nona Farbehi, Ivan Bakhshayeshi, Thantrira Porntaveetus, Youqiong Ye, Nigel H. Lovell, Hamid Alinejad‐Rokny   +7 more
wiley   +1 more source

Bridging the Synchrony Gap: A Deterministic GSMDP Approach for Integrating Deep Reinforcement Learning with Commercial Discrete Event Simulators

Proceedings of the Conference on Production Systems and Logistics
Although Deep Reinforcement Learning (DRL) offers adaptive control for manufacturing processes, training agents within high-fidelity commercial Discrete Event Simulation (DES) tools is hindered by the temporal mismatch between the continuous-time event ...
Varici, Merve Demir, Tercan, Hasan, Meisen, Tobias, Herberger, David, Hübner, Marco   +4 more
doaj   +1 more source

Switching Spike Plasticity Shapes ACE2 Engagement Across SARS‐CoV‐2 Variants

Advanced Science, EarlyView.
Conformational plasticity governs SARS‐CoV‐2 spike function and ACE2 recognition. Using high‐speed AFM and single‐molecule force spectroscopy, we analyzed the ancestral spike and nine variants, revealing progressive rigidification from Delta, variable plasticity in Omicron sublineages, and JN.1 compaction.
Sarah Stainer, Rong Zhu, Manuel Reithofer, Gerhard Stadlmayr, Katharina Stadlbauer, Panchika Prangkio, Christoph Rippel, Markus Hahn, Aniko Eva Kasztner, Stefanie Stohl, Petr Bednar, Daniel Ruzek, David Glück, Robert Tampé, Gordana Wozniak‐Knopp, Yoo Jin Oh, Miriam Klausberger, Peter Hinterdorfer   +17 more
wiley   +1 more source

Deep‐Learning‐Based Denoising for Improved Phase Precision in Electron Holography of Electromagnetic Fields in Nanoscale Materials

Advanced Science, EarlyView.
Low‐dose electron holography is limited by shot noise, which buries weak phase signals. HoloDenoiser, a physics‐informed network that works simultaneously in the spatial and frequency domains, locates and protects the holographic sideband while suppressing noise in the hologram.
Ye Luo, Luyang Wang, Zhiling Yu, Xiaowen Chen, Xiaoyu Wang, Ya‐Hui Jia, Thibaud Denneulin, Yu Han, Rafal E. Dunin‐Borkowski, Fengshan Zheng, Qi Liu   +10 more
wiley   +1 more source

Reactive Power Optimization of a Distribution Network Based on Graph Security Reinforcement Learning

Applied Sciences
With the increasing integration of renewable energy, the secure operation of distribution networks faces significant challenges, such as voltage limit violations and increased power losses.
Xu Zhang, Xiaolin Gui, Pei Sun, Xing Li, Yuan Zhang, Xiaoyu Wang, Chaoliang Dang, Xinghua Liu   +7 more
doaj   +1 more source

TMRL-NBV: Triangular mesh-based reinforcement learning for next-best-view in active 3D reconstruction [PDF]

MATEC Web of Conferences
Next-best-view (NBV) planning is essential in active 3D reconstruction, aiming to select informative viewpoints to improve coverage and efficiency.
Zhao Huijie, Tang Yong, Qi Siyu, Jiang Hongzhi, Li Xudong   +4 more
doaj   +1 more source

Probing the Energy Landscape of α‐Synuclein Amyloid Fibril Formation by Systematic K‐to‐Q Mutagenesis

Advanced Science, EarlyView.
We use lysine‐to‐glutamine mutations to study the effect of electrostatics on the kinetics and thermodynamics of alpha‐synuclein amyloid fibril formation. We find that mutational effects map on their structural context within fibrils and identify residues that modulate the energy landscape of alpha‐synuclein self‐assembly. Our work outlines a scalable,
Antonin Kunka, Azad Farzadfard, Jacob Aunstrup Larsen, Rasmus Krogh Norrild, Federica Saraceno, Celia Fricke, Hossein Mohammad‐Beigi, Ahmed Sadek, Jonas Folke, Susana Aznar, Alexander K. Buell   +10 more
wiley   +1 more source

Privacy-Preserving Cost-Efficient Smart Metering by Variational-Constraint Adversarial Reinforcement Learning

Applied Sciences
Smart metering of high-time-resolution energy data enables efficient power grid management. However, it also raises significant privacy concerns by revealing users’ consumption patterns.
Jian Ruan, Qiang Li, Qi Jiang, Zuxing Li
doaj   +1 more source