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pro vyhledávání: '"Zhang, Weizhe"'
Reentrancy vulnerability as one of the most notorious vulnerabilities, has been a prominent topic in smart contract security research. Research shows that existing vulnerability detection presents a range of challenges, especially as smart contracts
Externí odkaz:
http://arxiv.org/abs/2403.11254
In recent years, Decentralized Finance (DeFi) grows rapidly due to the development of blockchain technology and smart contracts. As of March 2023, the estimated global cryptocurrency market cap has reached approximately $949 billion. However, securit
Externí odkaz:
http://arxiv.org/abs/2403.01425
Publikováno v:
Wireless Communications and Mobile Computing, 2021
Mobile edge computing (MEC) pushes computing resources to the edge of the network and distributes them at the edge of the mobile network. Offloading computing tasks to the edge instead of the cloud can reduce computing latency and backhaul load simul
Externí odkaz:
http://arxiv.org/abs/2402.13529
Reentrancy is one of the most notorious vulnerabilities in smart contracts, resulting in significant digital asset losses. However, many previous works indicate that current Reentrancy detection tools suffer from high false positive rates. Even worse
Externí odkaz:
http://arxiv.org/abs/2402.09094
Giant proton transmembrane transport through sulfophenylated graphene in a direct methanol fuel cell
Autor:
Zhang, Weizhe, Makurat, Max, Liu, Xue, Kang, Xiaofang, Liu, Xiaoting, Li, Yanglizhi, Kock, Thomas J. F., Leist, Christopher, Maheu, Clement, Sezen, Hikmet, Jiang, Lin, Calvani, Dario, Jiao, Andy, Eren, Ismail, Buda, Francesco, Kuc, Agnieszka, Heine, Thomas, Qi, Haoyuan, Feng, Xinliang, Hofmann, Jan P., Kaiser, Ute, Sun, Luzhao, Liu, Zhongfan, Schneider, Gregory F.
An ideal proton exchange membrane should only permeate protons and be leak tight for fuels. Graphene is impermeable to water and poorly conducting to protons. Here, we chemically functionalized monolayer graphene to install sulfophenylated sp3 disloc
Externí odkaz:
http://arxiv.org/abs/2308.16112
Cross-silo federated learning (FL) enables multiple clients to collaboratively train a machine learning model without sharing training data, but privacy in FL remains a major challenge. Techniques using homomorphic encryption (HE) have been designed
Externí odkaz:
http://arxiv.org/abs/2305.08599
Conventional covert image communication is assumed to transmit the message, in the securest way possible for a given payload, over lossless channels, and the associated steganographic schemes are generally vulnerable to active attacks, e.g., JPEG re-
Externí odkaz:
http://arxiv.org/abs/2212.02822
Mobile apps are becoming an integral part of people's daily life by providing various functionalities, such as messaging and gaming. App developers try their best to ensure user experience during app development and maintenance to improve the rating
Externí odkaz:
http://arxiv.org/abs/2209.08055
Autor:
Zhang, Weizhe
This thesis is on the Navier-Stokes equations which model the motion of compressible viscous fluid. A minimum principle on the temperate variable is established. Under the thermo-insulated boundary conditions and some reasonable assumptions on the so
Externí odkaz:
http://hdl.handle.net/1853/52218
GPUs are widely used to accelerate the training of machine learning workloads. As modern machine learning models become increasingly larger, they require a longer time to train, leading to higher GPU energy consumption. This paper presents GPOEO, an
Externí odkaz:
http://arxiv.org/abs/2201.01684