While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social *** paper addresses this gap by focusing on source localization in signed ...
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While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social *** paper addresses this gap by focusing on source localization in signed network *** the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer ***,by using the reverse propagation algorithm we present a method for information source localization in signed *** experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization ***,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among *** addition,the source located at the periphery of the network is not easy to ***,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.
Group features have significant effects on pedestrian movement and constitute a focal point in pedestrian trajectory prediction research. In reality, pedestrians within a group exhibit notable consistency features due...
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This paper has shown the enhancement of networks, and the ability to withstand DDoS attacks. Thus, this survey plans to make a review on 65 papers which concern DDoS attack detection in SDN. Therefore, the systematic ...
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Automatic guided vehicles(AGVs)are extensively employed in manufacturing workshops for their high degree of automation and *** paper investigates a limited AGV scheduling problem(LAGVSP)in matrix manufacturing worksho...
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Automatic guided vehicles(AGVs)are extensively employed in manufacturing workshops for their high degree of automation and *** paper investigates a limited AGV scheduling problem(LAGVSP)in matrix manufacturing workshops with undirected material flow,aiming to minimize both total task delay time and total task completion *** address this LAGVSP,a mixed-integer linear programming model is built,and a nondominated sorting genetic algorithm II based on dual population co-evolution(NSGA-IIDPC)is *** NSGA-IIDPC,a single population is divided into a common population and an elite population,and they adopt different evolutionary strategies during the evolution *** dual population co-evolution mechanism is designed to accelerate the convergence of the non-dominated solution set in the population to the Pareto front through information exchange and competition between the two *** addition,to enhance the quality of initial population,a minimum cost function strategy based on load balancing is *** local search operators based on ideal point are proposed to find a better local *** improve the global exploration ability of the algorithm,a dual population restart mechanism is *** tests and comparisons with other algorithms are conducted to demonstrate the effectiveness of NSGA-IIDPC in solving the LAGVSP.
Inverse tone mapping technique is widely used to restore the lost textures from a single low dynamic range ***,many stack‐based deep inverse tone mapping networks have achieved impressive results by estimating a set ...
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Inverse tone mapping technique is widely used to restore the lost textures from a single low dynamic range ***,many stack‐based deep inverse tone mapping networks have achieved impressive results by estimating a set of multi‐exposure images from a single low dynamic range ***,there are still some *** the one hand,these methods usually set a fixed length for the estimated multi‐exposure stack,which may introduce computational redundancy or cause inaccurate *** the other hand,they neglect that the difficulties of estimating each exposure value are different and use the identical model to increase or decrease exposure *** solve these problems,the authors design an exposure decision network to adaptively determine the number of times the exposure of low dynamic range input should be increased or ***,the authors decouple the increasing/decreasing process into two sub‐modules,exposure adjustment and optional detail recovery,based on the characteristics of different variations of exposure *** these improvements,this method can fast and flexibly estimate the multi‐exposure stack from a single low dynamic range *** on several datasets demonstrate the advantages of the proposed method compared to state‐of‐the‐art inverse tone mapping methods.
With the development of vehicles towards intelligence and connectivity,vehicular data is diversifying and growing dramatically.A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle(ICV)...
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With the development of vehicles towards intelligence and connectivity,vehicular data is diversifying and growing dramatically.A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle(ICV)applications are proposed for the dispersed computing network composed of heterogeneous task vehicles and Network Computing Points(NCPs).Considering the amount of task data and the idle resources of NCPs,a computing resource scheduling model for NCPs is *** the heterogeneous task execution delay threshold as a constraint,the optimization problem is described as the problem of maximizing the utilization of computing resources by *** proposed problem is proven to be NP-hard by using the method of reduction to a 0-1 knapsack problem.A many-to-many matching algorithm based on resource preferences is *** algorithm first establishes the mutual preference lists based on the adaptability of the task requirements and the resources provided by *** enables the filtering out of un-schedulable NCPs in the initial stage of matching,reducing the solution space *** solve the matching problem between ICVs and NCPs,a new manyto-many matching algorithm is proposed to obtain a unique and stable optimal matching *** simulation results demonstrate that the proposed scheme can improve the resource utilization of NCPs by an average of 9.6%compared to the reference scheme,and the total performance can be improved by up to 15.9%.
Recovering high-quality inscription images from unknown and complex inscription noisy images is a challenging research *** fromnatural images,character images pay more attention to stroke ***,existingmodelsmainly cons...
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Recovering high-quality inscription images from unknown and complex inscription noisy images is a challenging research *** fromnatural images,character images pay more attention to stroke ***,existingmodelsmainly consider pixel-level informationwhile ignoring structural information of the character,such as its edge and glyph,resulting in reconstructed images with mottled local structure and character *** solve these problems,we propose a novel generative adversarial network(GAN)framework based on an edge-guided generator and a discriminator constructed by a dual-domain U-Net framework,i.e.,*** existing frameworks,the generator introduces the edge extractionmodule,guiding it into the denoising process through the attention mechanism,which maintains the edge detail of the restored inscription ***,a dual-domain U-Net-based discriminator is proposed to learn the global and local discrepancy between the denoised and the label images in both image and morphological domains,which is helpful to blind denoising *** proposed dual-domain discriminator and generator for adversarial training can reduce local artifacts and keep the denoised character structure *** to the lack of a real-inscription image,we built the real-inscription dataset to provide an effective benchmark for studying inscription image *** experimental results show the superiority of our method both in the synthetic and real-inscription datasets.
In recent times, a lack of discrimination power in the features produced by traditional machine learning algorithms has resulted in poor classification results. It is also a study topic to find out how to get excellen...
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The rapid proliferation of smart consumer devices has given rise to the consumer Internet of Things (CIoT), enabling immense data collection and valuable insights for enhancing con-sumer experiences. However, the dist...
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Unsupervised domain adaptation(UDA),which aims to use knowledge from a label-rich source domain to help learn unlabeled target domain,has recently attracted much *** methods mainly concentrate on source classification...
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Unsupervised domain adaptation(UDA),which aims to use knowledge from a label-rich source domain to help learn unlabeled target domain,has recently attracted much *** methods mainly concentrate on source classification and distribution alignment between domains to expect the correct target *** in this paper,we attempt to learn the target prediction end to end directly,and develop a Self-corrected unsupervised domain adaptation(SCUDA)method with probabilistic label *** adopts a probabilistic label corrector to learn and correct the target labels ***,besides model parameters,those target pseudo-labels are also updated in learning and corrected by the anchor-variable,which preserves the class candidates for *** on real datasets show the competitiveness of SCUDA.
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