Transactional stream processing engines (TSPEs) are central to modern stream applications handling shared mutable states. However, their full potential, particularly in adaptive scheduling, remains largely unexplored....
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With the rapid rise of the Industrial Internet, emails that convey a large amount of information require a strong network security environment. Aiming at the increasingly complex mail virus prevention and control work...
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This paper presents a comparative analysis of sentiment classification methods applied to a dataset of Amazon reviews. Three methods are evaluated: the pre-trained BERT model, Naive Bayes with TF-IDF, and the lexicon-...
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Many-objective Optimization problems (MaOPs), with four or more objectives are difficult to solve, is a kind of common optimization problems in actual industrial production. In recent years, a large number of many-obj...
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The realm of computer vision has witnessed a profound interest from the scholarly community in the task of remote sensing object detection. Within this article, we present a pioneering and refined approach to feature ...
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This paper is focused on the synchronous control problem of teleoperation robot arms based on Markov jump linear systems. More specifically, a drive-response Markov model is used to describe the master and slave teleo...
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Dear editor, Key security is of great practical significance and demand to guarantee the security of digital assets in the blockchain system. At present, users prefer to escrow their assets on centralized institutions...
Dear editor, Key security is of great practical significance and demand to guarantee the security of digital assets in the blockchain system. At present, users prefer to escrow their assets on centralized institutions, but this phenomenon has gone against the unique characteristics of decentralization and anonymity in the blockchain. Among them, the suspense incidents of assets lock or lost are enough to prove that the security of escrowed keys on the exchanges is questionable.
Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) ar...
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Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.
Time series data generated by thousands of sensors are suffering data quality problems. Traditional constraint-based techniques have greatly contributed to data cleaning applications. However, cleaning methods that su...
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Federated learning (FL) safeguards user privacy by uploading gradients instead of raw data. However, inference attacks can reconstruct raw data using gradients uploaded by users in FL. To mitigate this issue, research...
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