Mobile opportunistic network(MON)is an efficient way of communication when there is no persistent connection between *** in MONs can be used to efficiently deliver messages to multiple destination ***,because multiple...
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Mobile opportunistic network(MON)is an efficient way of communication when there is no persistent connection between *** in MONs can be used to efficiently deliver messages to multiple destination ***,because multiple destination nodes are involved,multicast routing is more complex than unicast and brings a higher communication ***-based routing can effectively reduce the network overhead and the complexity of routing ***,the load of backbone nodes is larger than that of regular *** the backbone node’s buffer is exhausted,it will have a significant impact on the performance of the routing *** balancing can improve the ability of backbone to deal with the change of network load,and backbone maintenance algorithm can provide backbone *** this paper,we propose a robust load-balanced backbone-based multicast routing scheme in *** the backbone construction algorithm,we transform the problem of backbone construction into a multi-objective optimization problem,and propose a multi-objective evolutionary algorithmbased backbone construction algorithm,namely LBMBCMOEA *** addition,in order to increase the robustness of the backbone-based routing scheme,we propose a localized multicast backbone maintenance algorithm(MBMA)to deal with the buffer exhaustion of backbone *** a backbone node’s residual buffer is insufficient,MBMA algorithm selects other nodes to replace the backbone *** results on extensive simulations show that when considering the node buffer size constraints,compared with previous backbone-based multicast routing schemes,our proposed algorithm has better performance,and when the node’s residual buffer is insufficient,MBMA algorithm can significantly improve the performance of the backbone-based multicast routing scheme.
Declarative knowledge and procedural knowledge are two key parts in meta-cognitive theory, and these two hold significant importance in pre-training and inference of LLMs. However, a comprehensive analysis comparing t...
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The influence maximization (IM) problem aims to identify a budgeted set of nodes with the highest potential to influence the largest number of users in a cascade model, a key challenge in viral marketing. Traditional ...
Face anti-spoofing aims at detecting whether the input is a real photo of a user(living)or a fake(spoofing)*** new types of attacks keep emerging,the detection of unknown attacks,known as Zero-Shot Face Anti-Spoofing(...
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Face anti-spoofing aims at detecting whether the input is a real photo of a user(living)or a fake(spoofing)*** new types of attacks keep emerging,the detection of unknown attacks,known as Zero-Shot Face Anti-Spoofing(ZSFA),has become increasingly important in both academia and *** ZSFA methods mainly focus on extracting discriminative features between spoofing and living ***,the nature of the spoofing faces is to trick anti-spoofing systems by mimicking the livings,therefore the deceptive features between the known attacks and the livings,which have been ignored by existing ZSFA methods,are essential to comprehensively represent the ***,existing ZSFA models are incapable of learning the complete representations of living faces and thus fall short of effectively detecting newly emerged *** tackle this problem,we propose an innovative method that effectively captures both the deceptive and discriminative features distinguishing between genuine and spoofing *** method consists of two main components:a two-against-all training strategy and a semantic *** two-against-all training strategy is employed to separate deceptive and discriminative *** address the subsequent invalidation issue of categorical functions and the dominance disequilibrium issue among different dimensions of features after importing deceptive features,we introduce a modified semantic *** autoencoder is designed to map all extracted features to a semantic space,thereby achieving a balance in the dominance of each feature *** combine our method with the feature extraction model ResNet50,and experimental results show that the trained ResNet50 model simultaneously achieves a feasible detection of unknown attacks and comparably accurate detection of known *** results confirm the superiority and effectiveness of our proposed method in identifying the living with the interference of both known
To address the matching problem caused by the significant differences in spatial features, spectrum and contrast between heterologous images, a heterologous image matching method based on salience region is proposed i...
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Solving security patrol route planning in large-scale realistic scenarios is a very challenging problem. Here we propose a route planning algorithm PatrolGo based on Monte Carlo Tree Search (MCTS). In this algorithm, ...
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Hybrid deposition with microrolling is a promising arc-based direct energy deposition technique to rapidly build complex parts,whose performance is comparable to that of their wrought *** forming conditions and bead m...
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Hybrid deposition with microrolling is a promising arc-based direct energy deposition technique to rapidly build complex parts,whose performance is comparable to that of their wrought *** forming conditions and bead morphologies pose difficulties in controlling the morphologies from a single weld bead to built part profiles,and these difficulties hinder the widespread application of the ***,a model that can automatically generate optimal process parameters on the basis of the infrared image,including thermal information and the point cloud information of the target weld bead,is *** show that the errors in critical parameters,namely,feed speed,travel speed,and rolling force,are below 0.4%,0.9%,and 2%,respectively,indicating that the proposed technique outperforms the compared ***,validation reveals that the actual depositing bead is similar(deviation below 0.05 mm)to the target *** proposed strategy provides an effective foundation for dynamic path planning and can considerably improve printing efficiency and precision.
Based on the security of distributed machine learning data and model based on remote proof, a cross-domain dynamic remote proof scheme based on ring signature improves the efficiency of computer cluster proof, the app...
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Physics-Informed Neural Networks (PINNs) have recently received increasing attention, however, optimizing the loss function of PINNs is notoriously difficult, where the landscape of the loss function is often highly n...
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Federated Learning (FL) recently emerges as a paradigm to train a global machine learning model across distributed clients without sharing raw data. Knowledge Graph (KG) embedding represents KGs in a continuous vector...
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