Construction is the pillar industry of Chinese national economy, but the profit rate has continued to decline in recent years. The conventional job-centric construction information system cannot meet the requirements ...
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Quantum coherence serves as a defining characteristic of quantum mechanics,finding extensive applications in quantum computing and quantum communication *** study explores quantum block coherence in the context of pro...
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Quantum coherence serves as a defining characteristic of quantum mechanics,finding extensive applications in quantum computing and quantum communication *** study explores quantum block coherence in the context of projective measurements,focusing on the quantification of such ***,we define the correlation function between the two general projective measurements P and Q,and analyze the connection between sets of block incoherent states related to two compatible projective measurements P and ***,we discuss the measure of quantum block coherence with respect to projective *** on a given measure of quantum block coherence,we characterize the existence of maximal block coherent states through projective *** research integrates the compatibility of projective measurements with the framework of quantum block coherence,contributing to the advancement of block coherence measurement theory.
Recently,the physics-informed neural network shows remarkable ability in the context of solving the low-dimensional nonlinear partial differential ***,for some cases of high-dimensional systems,such technique may be t...
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Recently,the physics-informed neural network shows remarkable ability in the context of solving the low-dimensional nonlinear partial differential ***,for some cases of high-dimensional systems,such technique may be time-consuming and *** this paper,the authors put forward a pre-training physics-informed neural network with mixed sampling(pPINN)to address these *** based on the initial and boundary conditions,the authors design the pre-training stage to filter out the set of the misfitting points,which is regarded as part of the training points in the next *** authors further take the parameters of the neural network in Stage 1 as the initialization in Stage *** advantage of the proposed approach is that it takes less time to transfer the valuable information from the first stage to the second one to improve the calculation accuracy,especially for the high-dimensional *** verify the performance of the pPINN algorithm,the authors first focus on the growing-and-decaying mode of line rogue wave in the Davey-Stewartson I *** case is the accelerated motion of lump in the inhomogeneous Kadomtsev-Petviashvili equation,which admits a more complex evolution than the uniform *** exact solution provides a perfect sample for data experiments,and can also be used as a reference frame to identify the performance of the *** experiments confirm that the pPINN algorithm can improve the prediction accuracy and training efficiency well,and reduce the training time to a large extent for simulating nonlinear waves of high-dimensional equations.
The security issue that deep learning models are vulnerable to adversarial example attacks carefully designed by attackers has attracted people’s attention. There is a lot of research on adversarial attack defense me...
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Due to blockchain’s decentralized nature, many application scenarios are deployed across networks, which makes the network security boundary blurred and vulnerable to Advanced Persistent Threat (APT) attacks. In orde...
The construction phase of new power systems exposes them to potential cybersecurity threats. To overcome the limitations of existing methods in assessing security status and extracting intricate data patterns, we have...
In short text classification, extracting text features is crucial. Static word vector training, the traditional method, has limitations such as insufficient semantics and sparse features, while dynamic training word v...
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Traffic sign detection (TSD) is a significant task in the field of computer vision, which has important applications in traffic safety and driverless driving. However, this fundamental but challenging task still has a...
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Although cross-domain recommendation systems play a crucial role in solving the data sparseness and cold start challenges in recommendation systems, current algorithms primarily rely on the user-item rating matrix for...
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This paper proposes a novel network public opinion monitoring system that addresses the issue of traditional methods typically intervening only after the public opinion outbreak. The new system incorporates a self-adj...
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