Results 291 to 300 of about 11,891,122 (316)
Clean‐Limit 2D Superconductivity in a Thick Exfoliated Kagome Film
Advanced Functional Materials, EarlyView.This study reports clean‐limit 2D superconductivity in a thick kagome system, analogous to the 3D case. It observes a drop in superfluid stiffness near the superconducting transition and a cusp‐like feature in the angular dependence of the upper critical field.
Fei Sun +3 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Glyphosate (GLY) and its primary metabolite, aminomethylphosphonic acid (AMPA), are photodegraded using a poly(vinylidene fluoride) membrane with immobilized titanium dioxide (PVDF‐TiO2) in a continuous flow‐through operation under solar light. At optimized conditions, the PVDF‐TiO2 membrane achieved 95% GLY and 80% AMPA removal with •O2− as the ...
Phuong B. Trinh +4 more
wiley +1 more source
Enabling performance tradeoffs through dynamic configuration of advanced network services
, 2005 Jinliang Fan, Mostafa Ammar
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Community-enhanced Link Prediction in Dynamic Networks
ACM Transactions on the Web, 2023The growing popularity of online social networks is quite evident nowadays and provides an opportunity to allow researchers in finding solutions for various practical applications.
Mukesh Kumar +3 more
semanticscholar +1 more source
Model Drift in Dynamic Networks
IEEE Communications Magazine, 2023With the introduction of 5G and beyond networks, increasing intelligence and automation levels are being employed in managing and orchestrating virtualized networks.
D. Manias, Ali Chouman, A. Shami
semanticscholar +1 more source
Few-shot Link Prediction in Dynamic Networks
Web Search and Data Mining, 2022Dynamic link prediction, which aims at forecasting future edges of a node in a dynamic network, is an important problem in network science and has a wide range of real-world applications.
Cheng Yang +6 more
semanticscholar +1 more source
ComGCN: Community-Driven Graph Convolutional Network for Link Prediction in Dynamic Networks
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022Recent advances in deep learning have tremendously leveraged the performance of network representation learning (NRL). Multiple deep learning-based NRL models have been proposed recently to effectively handling primitive tasks of information network ...
Phu Pham +5 more
semanticscholar +1 more source
Implementing The Abstract MAC Layer in Dynamic Networks
IEEE Transactions on Mobile Computing, 2021Dynamicity is one of the most challenging, yet, key aspects of wireless networks. It can come in many guises, such as churn (node insertion/deletion) and node mobility.
Dongxiao Yu +7 more
semanticscholar +1 more source