The application of artificial intelligence technology in Internet of Vehicles(lov)has attracted great research interests with the goal of enabling smart transportation and traffic ***,concerns have been raised over th...
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The application of artificial intelligence technology in Internet of Vehicles(lov)has attracted great research interests with the goal of enabling smart transportation and traffic ***,concerns have been raised over the security and privacy of the tons of traffic and vehicle *** this regard,Federated Learning(FL)with privacy protection features is considered a highly promising ***,in the FL process,the server side may take advantage of its dominant role in model aggregation to steal sensitive information of users,while the client side may also upload malicious data to compromise the training of the global *** existing privacy-preserving FL schemes in IoV fail to deal with threats from both of these two sides at the same *** this paper,we propose a Blockchain based Privacy-preserving Federated Learning scheme named BPFL,which uses blockchain as the underlying distributed framework of *** improve the Multi-Krum technology and combine it with the homomorphic encryption to achieve ciphertext-level model aggregation and model filtering,which can enable the verifiability of the local models while achieving ***,we develop a reputation-based incentive mechanism to encourage users in IoV to actively participate in the federated learning and to practice *** security analysis and performance evaluations are conducted to show that the proposed scheme can meet the security requirements and improve the performance of the FL model.
This study proposes a new method which aims to optimally install tie-lines and distributed generations *** is done to optimize the post-outage reconfiguration and minimize energy losses and energy not supplied of dist...
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This study proposes a new method which aims to optimally install tie-lines and distributed generations *** is done to optimize the post-outage reconfiguration and minimize energy losses and energy not supplied of distribution *** number and location of tie-lines,as well as the number,size,and location of DGs,are pinpointed through teaching the learning-based optimization(TLBO)*** objective function in the current research is to minimize the costs pertaining to the investment,operation,energy losses,and energies not *** addition to the normal operational condition,fault operational condition is also ***,the optimal post-fault reconfigurations for fault occurrences in all lines are ***,the operational constraints such as the voltage and line current limits are taken into account in both normal and post-fault operational ***,the modified IEEE 33-bus and 69-bus distribution test systems are selected and tested to demonstrate the effectiveness of the simultaneous placement of DGs and tie-line technique proposed in this paper.
The document classification (DC) task assigns predefined classes to unlabeled documents using trained models. In the medical field, DC is crucial for tasks like categorizing risk factors and classifying electronic hea...
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Through computer vision and image processing techniques, a set of images from a scene can be reconstructed in 3D to recover a 3D model of the scene, in which dense reconstruction is a crucial part, and most existing a...
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This paper presents a system for detecting orange juice concentration based on the principle of solution absorption of visible light. The system efficiently detects orange juice concentration using visible light commu...
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Blockchain technology gained much traction in the last few years. These decentralized databases offer security, immutability, and scalability across various applications. Decentralized applications generate vast amoun...
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Erasable itemset mining is one of the most well-known methods in data mining for optimizing limited materials. After mining erasable itemsets, the manager can rearrange the production plan effectively. However, in rea...
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The neural network methods in solving differential equations have significant research importance and promising application prospects. Aimed at the time-fractional Huxley (TFH) equation, we propose a novel fractional ...
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Flame detection algorithms are crucial for real-time fire monitoring using surveillance cameras. Current flame detection algorithms perform excellently on color cameras;however, many night vision cameras can only capt...
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