Results 111 to 120 of about 148,372 (267)

A Systematic Review on Machine Learning and Deep Learning Models for Electronic Information Security in Mobile Networks. [PDF]

Sensors (Basel), 2022
Gupta C, Johri I, Srinivasan K, Hu YC, Qaisar SM, Huang KY.   +5 more
europepmc   +1 more source

Microstructure Modification of Additively Manufactured Mo–9Si–8B by Annealing and Its Effects on High‐Temperature Mechanical Properties

Advanced Engineering Materials, EarlyView.
Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt, Yong Chen, Georg Hasemann, Benjamin Wahlmann, Carolin Körner, Manja Krüger   +5 more
wiley   +1 more source

Random Access Using Deep Reinforcement Learning in Dense Mobile Networks. [PDF]

Sensors (Basel), 2021
Bekele YZ, Choi YJ.
europepmc   +1 more source

Superlubricity and Corrosion Inhibition Properties of Solvate Ionic Liquids in Hybrid Carbon Fiber Reinforced Plastic–Steel Interfaces

Advanced Engineering Materials, EarlyView.
Solvate ionic liquids lubrication reduced the coefficient of friction by ∼60% compared to dry sliding, reaching steady‐state values as low as 0.04–0.05. Corrosion weight‐loss measurements in 1 M HCl further demonstrated significant inhibition behavior, with only 100 ppm of [Li(G3)][TFSI] (∼68.5 μL/L) reducing corrosion‐product weight loss by 63 ...
Sameh Dabees, Timothy Harte, Bhagya Dharmasiri, Y. Athulya Wickramasingha, David J. Hayne, Daniel J. Eyckens, Luke C. Henderson   +6 more
wiley   +1 more source

Comment on "5G mobile networks and health-a state-of-the-science review of the research into low-level RF fields above 6 GHz" by Karipidis et al. [PDF]

J Expo Sci Environ Epidemiol, 2023
Weller S, May M, McCredden J, Leach V, Phung D, Belyaev I.   +5 more
europepmc   +1 more source

Printed Integrated Logic Circuits Based on Chitosan‐Gated Organic Transistors for Future Edible Systems

Advanced Functional Materials, EarlyView.
Edible electronics needs integrated logic circuits for computation and control. This work presents a potentially edible printed chitosan‐gated transistor with a design optimized for integration in circuits. Its implementation in integrated logic gates and circuits operating at low voltage (0.7 V) is demonstrated, as well as the compatibility with an ...
Giulia Coco, Valerio Francesco Annese, Valerio Galli, Ilaria Penna, Debora Russo, Marina Veronesi, Rita Scarpelli, Stefania Sabella, Mario Caironi   +8 more
wiley   +1 more source

ENISA: 5G design and architecture of global mobile networks; threats, risks, vulnerabilities; cybersecurity considerations. [PDF]

Open Res Eur, 2022
Paskauskas RA.
europepmc   +1 more source

From Food to Power: Hydrogel Thermoelectrics for Ingestible Electronics

Advanced Functional Materials, EarlyView.
We introduce a fully edible thermoelectric–electrochromic platform that harvests heat from food and converts it into a visible color change. N‐type and p‐type hydrogel thermoelectric generators connected in series power anthocyanin‐based electrochromic displays, demonstrating the feasibility of safe, biodegradable, ingestible systems for on‐food ...
Antonia Georgopoulou, Bokeon Kwak, Dario Floreano, Esther Amstad   +3 more
wiley   +1 more source

Robust Electrocaloric Performance Enabled by Highly‐Polar Frustrated Nanodomains in NaNbO3‐Based Ferrodistortive Relaxor

Advanced Functional Materials, EarlyView.
P4bm framework in NaNbO3‐Ba(Ti, Hf)O3 ferrodistortive relaxor entails short‐range and highly‐polar ferrodistortive orders. The abundant highly‐polar orders facilitate to increase entropy change, and robust octahedral oxygen tilt enables to impede thermal perturbations.
Feng Li, Changshun Dai, He Qi, Jiecheng Liu, Xiaoming Shi, Heng Zhou, Qiong Yang, Mingsheng Long, Lei Shan, Chunchang Wang, Jianli Wang, Zhenxiang Cheng   +11 more
wiley   +1 more source

Enhancing Handover for 5G mmWave Mobile Networks Using Jump Markov Linear System and Deep Reinforcement Learning. [PDF]

Sensors (Basel), 2022
Chiputa M, Zhang M, Ali GGMN, Chong PHJ, Sabit H, Kumar A, Li H.   +6 more
europepmc   +1 more source