With the rapid development of web technology,Social Networks(SNs)have become one of the most popular platforms for users to exchange views and to express their *** and more people are used to commenting on a certain h...
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With the rapid development of web technology,Social Networks(SNs)have become one of the most popular platforms for users to exchange views and to express their *** and more people are used to commenting on a certain hot spot in SNs,resulting in a large amount of texts containing *** Emotion Cause Extraction(TECE)aims to automatically extract causes for a certain emotion in texts,which is an important research issue in natural language *** is different from the previous tasks of emotion recognition and emotion *** addition,it is not limited to the shallow-level emotion classification of text,but to trace the emotion *** this paper,we provide a survey for ***,we introduce the development process and classification of ***,we discuss the existing methods and key factors for ***,we enumerate the challenges and developing trend for TECE.
Roads are an important part of transporting goods and products from one place to another. In developing countries, the main challenge is to maintain road conditions regularly. Roads can deteriorate from time to time. ...
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Causality extraction model can quickly extract causality in text. It can be applied to event prediction, question-answering systems, and scenario generation. The traditional causality extraction pays more attention to...
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During the last three decades,evolutionary algorithms(EAs)have shown superiority in solving complex optimization problems,especially those with multiple objectives and non-differentiable ***,due to the stochastic sear...
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During the last three decades,evolutionary algorithms(EAs)have shown superiority in solving complex optimization problems,especially those with multiple objectives and non-differentiable ***,due to the stochastic search strategies,the performance of most EAs deteriorates drastically when handling a large number of decision *** tackle the curse of dimensionality,this work proposes an efficient EA for solving super-large-scale multi-objective optimization problems with sparse optimal *** proposed algorithm estimates the sparse distribution of optimal solutions by optimizing a binary vector for each solution,and provides a fast clustering method to highly reduce the dimensionality of the search *** importantly,all the operations related to the decision variables only contain several matrix calculations,which can be directly accelerated by *** existing EAs are capable of handling fewer than 10000 real variables,the proposed algorithm is verified to be effective in handling 1000000 real ***,since the proposed algorithm handles the large number of variables via accelerated matrix calculations,its runtime can be reduced to less than 10%of the runtime of existing EAs.
Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making. By integrating GAI into modern Internet of Things (IoT), Generative Internet ...
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Bat Algorithm (BA) is a nature-inspired metaheuristic search algorithm designed to efficiently explore complex problem spaces and find near-optimal solutions. The algorithm is inspired by the echolocation behavior of ...
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The MCrAlY coating has been potential candidate for the parts applied in friction and corrosion conditions, and CNTs (carbon nanotubes) are expected to improve the service performance of coatings owing to high lubrica...
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The MCrAlY coating has been potential candidate for the parts applied in friction and corrosion conditions, and CNTs (carbon nanotubes) are expected to improve the service performance of coatings owing to high lubrication and low chemical reactivity. In this work, a systematic investigation on the tribological and corrosion properties of CoCrAlYTaSiC-xCNTs coatings deposited by laser melting was analyzed. Results showed that the coatings had good-quality without typical metallurgical defects. The CNTs addition homogenized and refined the microstructure of coating, and also improved the tribological and corrosion properties. As the CNTs content changed from 0 to 4 wt%, the wear rate of coating decreased from 16.23 × 10^(-3) to 7.58 × 10^(-3) mg m^(−1), the jcorr of coating decreased from 4.13 × 10^(-4) to 1.23 × 10^(-4) A cm^(−2), and the Rct values increased from 12.69 to 25.07 Ω cm2.
For switched cyber-physical systems with disturbances and actuator faults, we address fault detection and isolation problems. First, the preconditions relative to subsystems are discussed in detail,and the original su...
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For switched cyber-physical systems with disturbances and actuator faults, we address fault detection and isolation problems. First, the preconditions relative to subsystems are discussed in detail,and the original subsystems are turned into an overall system. Second, the frequency ranges of faults are considered to belong to the finite-frequency domain, and the observer, which makes the residual robust against disturbances and sensitive to faults, is designed by combining the finite-frequency H-technique with the mixed L2-L∞/H∞technique. Third, design conditions, which guarantee that the error system is stable and satisfies the mixed performance, are derived using the average dwell time method and Lyapunov functionals. Finally, a traffic density dynamic model is proposed to demonstrate the validity and effectiveness of the proposed method.
The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections an...
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The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and *** this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain *** to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward *** the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the *** addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+*** a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network *** LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.
In recent decades, impulse control has been increasingly applied as a discontinuous control method across diverse domains such as satellite orbit transfers, financial market regulation, chaos synchronization, and comm...
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