In order to accurately early warning the cascading failures caused by coordinated cyber-attacks (CFCC) in grid cyber-physical systems (GCPS), an adaptive early warning method of CFCC is proposed. Firstly, the evolutio...
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Federated learning (FL) is a distributed learning paradigm that enables multiple clients to train a unified model without sharing their private data. However, recent works demonstrate that FL models are vulnerable to ...
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The hypersonic flow is in a thermochemical nonequilibrium state due to the high-temperature caused by the strong shock compression. In a thermochemical nonequilibrium flow, the distribution of molecular internal energ...
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The hypersonic flow is in a thermochemical nonequilibrium state due to the high-temperature caused by the strong shock compression. In a thermochemical nonequilibrium flow, the distribution of molecular internal energy levels strongly deviates from the equilibrium distribution (i.e., the Boltzmann distribution). It is intractable to directly obtain the microscopic nonequilibrium distribution from existed experimental measurements usually described by macroscopic field variables such as temperature or velocity. Motivated by the idea of deep multi-scale multi-physics neural network (DeepMMNet) proposed in [Mao et al, J. Comput. Phys., 2021], we develop in this paper a data assimilation framework called DeepStSNet to accurately reconstruct the quantum state-resolved thermochemical nonequilibrium flowfield by using sparse experimental measurements of vibrational temperature and pre-trained deep neural operator networks (DeepONets). In particular, we first construct several DeepONets to express the coupled dynamics between field variables in the thermochemical nonequilibrium flow and to approximate the state-to-state (StS) approach, which traces the variation of each vibrational level of molecule accurately. These proposed DeepONets are then trained by using the numerical simulation data, and would later be served as building blocks for the DeepStSNet. We demonstrate the effectiveness and accuracy of DeepONets with different test cases showing that the density and energy of vibrational groups as well as the temperature and velocity fields are predicted with high accuracy. We then extend the architectures of DeepMMNet by considering a simplified thermochemical nonequilibrium model, i.e., the 2T model, showing that the entire thermochemical nonequilibrium flowfield is well predicted by using scattered measurements of full or even partial field variables. We next consider a more accurate and complex thermochemical nonequilibrium model, i.e., the StS-CGM model, and develop a
The smart environment is a crucial application of the Internet of Things(IoT). Due to its growing security and efficiency needs, recent years have seen the proposal of numerous authentication and key agreement (AKA) p...
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The smart environment is a crucial application of the Internet of Things(IoT). Due to its growing security and efficiency needs, recent years have seen the proposal of numerous authentication and key agreement (AKA) protocols. Unfortunately, most of existing AKA protocols only support one-to-one AKA and rely on the elliptic curve cryptosystem, resulting in huge overhead. In addition, these protocols fail to consider the resource-asymmetric characteristics of this scenario. That is, the resources on the gateway side are abundant, while the resources on user sides and device sides are limited. In order to achieve efficient and secure one-to-many AKA establishment in this scenario, where one-to-many means that users can realize key agreements with multiple smart devices at the same time. For the first time, this paper uses the one-to-many computing structure of the Chinese Remainder Theorem (CRT) to design an efficient one-to-many AKA establishment, which is perfectly adapted to resource-asymmetric allocation in smart environments. Compared with existing solutions, this solution has the following advantages. Firstly, our protocol is suitable for resource-asymmetric environments, where the gateway acts as an intermediate node and uses rich resources to integrate multiple AKA requests. Secondly, the solution supports users to negotiate session keys with multiple smart devices at the same time. Thirdly, we prove the protocol’s security under the Real-or-Random (ROR) model. In addition, we perform formal security verification of the protocol using the Automated Validation of Internet Security Protocols and Applications(AVISPA) tool. Finally, the security and efficiency of this solution are superior to similar solutions. Specifically, our solution can meet 18 security and functionality requirements. Compared with the latest similar scheme, assuming that the number of smart devices is 10, our scheme reduces the computational cost by 75.75%. At the same time, in terms of comm
Deep learning has been widely used in source code classification tasks, such as code classification according to their functionalities, code authorship attribution, and vulnerability detection. Unfortunately, the blac...
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In this paper, we first present a multiple-relaxation-time lattice Boltzmann (MRT-LB) model for one-dimensional diffusion equation where the D1Q3 (three discrete velocities in one-dimensional space) lattice structure ...
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In this paper, we first present a multiple-relaxation-time lattice Boltzmann (MRT-LB) model for one-dimensional diffusion equation where the D1Q3 (three discrete velocities in one-dimensional space) lattice structure is considered. Then through the theoretical analysis, we derive an explicit four-level finite-difference scheme from this MRT-LB model. The results show that the four-level finite-difference scheme is unconditionally stable, and through adjusting the weight coefficient ω0 and the relaxation parameters s1 and s2 corresponding to the first and second moments, it can also have a sixth-order accuracy in space. Finally, we also test the four-level finite-difference scheme through some numerical simulations and find that the numerical results are consistent with our theoretical analysis.
SONICUMOS is an enhanced behavior-based face liveness detection system that combines ultrasonic and video signals to sense the 3D head gestures. As face authentication becomes increasingly prevalent, the need for a re...
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In this work, we proposed a diffuse interface model for the dendritic growth with thermosolutal convection. In this model, the sharp boundary between the fluid and solid dendrite is replaced by a thin but nonzero thic...
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In this work, we consider a general consistent and conservative phase-field model for the incompressible two-phase flows. In this model, not only the Cahn-Hilliard or Allen-Cahn equation can be adopted, but also the m...
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In this paper, we propose a lattice Boltzmann (LB) model for the generalized coupled cross-diffusion-fluid system. Through the direct Taylor expansion method, the proposed LB model can correctly recover the macroscopi...
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