Results 81 to 90 of about 3,701 (251)

Design of a lightweight and secure remote user authentication and key agreement protocols for internet of drones environment [PDF]

open access: yesPeerJ Computer Science
Recently, drones have gained significant importance in various fields, such as military applications, healthcare, smart agriculture, and traffic monitoring. Equipped with embedded systems capable of sensing, collecting, and transmitting data in real time
Alanoud Aldweesh, Abdullah M. Almuhaideb
doaj   +2 more sources

Study of Free‐Space Optical Quantum Network: Review and Prospectives

open access: yesAdvanced Science, EarlyView.
Free from the constraints of fiber connections, free‐space quantum network enables longer and more flexible quantum network connections. This review summarizes and comparatively analyzes free‐space quantum network experiments based on ground stations, satellites, and mobile platforms.
Hua‐Ying Liu, Zhenda Xie, Shining Zhu
wiley   +1 more source

Beyond Flight: Enhancing the Internet of Drones with Blockchain Technologies

open access: yesDrones
The Internet of Drones (IoD) is a decentralized network linking drones’ access to controlled airspace, providing high adaptability to complex scenarios and services to various drone applications, such as package delivery, traffic surveillance, and rescue,
Kyriaki A. Tychola   +2 more
doaj   +1 more source

Tunable Negative Thermal Expansion in Fe/Cr‐Substituted Nd2Co17 Compounds via Magnetoelastic Coupling

open access: yesAdvanced Science, EarlyView.
This study achieves anisotropic thermal expansion tuning in Nd2(Co1‐xFex)17‐yCry compounds via a magnetoelastic strategy. Variable‐temperature synchrotron X‐ray diffraction reveals that increased Fe content induces switchable lattice responses. Compositional control reduces the volume expansion coefficient αV by 20% (x═0.7) and modulates TC (442–625 K),
Jiayuan Li   +8 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

open access: yesAdvanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang   +2 more
wiley   +1 more source

Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

open access: yesAdvanced Science, EarlyView.
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang   +5 more
wiley   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

open access: yesAdvanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy