Convolutional neural networks(CNNs) based object detection methods are prone to be interfered with by background noise and cannot make full use of semantic information in the positive sample-choosing phase. To overcom...
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An adaptive dispersion estimation(ADE)is proposed to compensate dispersion and estimate the transfer function of the fiber channel with GerchbergSaxton(G-S)algorithm,using the stochastic gradient descent(SGD)method in...
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An adaptive dispersion estimation(ADE)is proposed to compensate dispersion and estimate the transfer function of the fiber channel with GerchbergSaxton(G-S)algorithm,using the stochastic gradient descent(SGD)method in the intensity-modulation and direct-detection(IM-DD)system,improving the tolerance of the algorithm to chromatic dispersion(CD).In order to address the divergence arising from the perturbation in the amplitude of the received signal caused by the filtering effect of the non-ideal channels,a channel-compensation equalizer(CCE)derived from the back-to-back(BTB)scenario is employed at the transmitter to make the amplitude of the received signal depicting the CD effect more *** simulation results demonstrate the essentiality of CCE for the convergence and performance improvement of the G-S *** show that it supports 112Gb/s four-level pulse amplitude modulation(PAM4)over 100 km standard single-mode fiber(SSMF)transmission under the 7%forward error correction(FEC)threshold of ***,ADE improves the tolerance to wavelength drift from about 4 nm to 42 nm,and there is a better tolerance for fiber distance perturbation,indicating the G-S algorithm and its derived algorithms with the ADE scheme exhibit superior robustness to the perturbation in the system.
With the arrival of the 5G era,wireless communication technologies and services are rapidly exhausting the limited spectrum *** auctions came into being,which can effectively utilize spectrum *** of the complexity of ...
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With the arrival of the 5G era,wireless communication technologies and services are rapidly exhausting the limited spectrum *** auctions came into being,which can effectively utilize spectrum *** of the complexity of the electronic spectrum auction network environment,the security of spectrum auction can not be *** scholars focus on researching the security of the single-sided auctions,while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and *** begin to design the secure double spectrum auction mechanisms,in which two semi-honest agents are introduced to finish the spectrum auction *** these two agents may collude with each other or be bribed by buyers and sellers,which may create security risks,therefore,a secure double spectrum auction is proposed in this *** traditional secure double spectrum auctions,the spectrum auction server with Software Guard Extensions(SGX)component is used in this paper,which is an Ethereum blockchain platform that performs spectrum auctions.A secure double spectrum protocol is also designed,using SGX technology and cryptographic tools such as Paillier cryptosystem,stealth address technology and one-time ring signatures to well protect the private information of spectrum *** addition,the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification,and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum ***,security analysis and performance evaluation of our protocol are discussed.
In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven t...
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In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior ***,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational *** response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature *** methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map *** the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.
With the advancement of Artificial Intelligence(AI)technology,traditional industrial systems are undergoing an intelligent transformation,bringing together advanced computing,communication and control technologies,Mac...
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With the advancement of Artificial Intelligence(AI)technology,traditional industrial systems are undergoing an intelligent transformation,bringing together advanced computing,communication and control technologies,Machine Learning(ML)-based intelligentmodelling has become a newparadigm for solving problems in the industrial domain[1–3].With numerous applications and diverse data types in the industrial domain,algorithmic and data-driven ML techniques can intelligently learn potential correlations between complex data and make efficient decisions while reducing human ***,in real-world application scenarios,existing algorithms may have a variety of limitations,such as small data volumes,small detection targets,low efficiency,and algorithmic gaps in specific application domains[4].Therefore,many new algorithms and strategies have been proposed to address the challenges in industrial applications[5–8].
Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that h...
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Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.
The Internet of Medical Things (IoMT) brings advanced patient monitoring and predictive analytics to healthcare but also raises cybersecurity and data privacy issues. This paper introduces a deep-learning model for Io...
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In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is *** cyber threats evolve in complexity,traditional cryptographic methods face in...
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In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is *** cyber threats evolve in complexity,traditional cryptographic methods face increasingly sophisticated *** article initiates an exploration into these challenges,focusing on key exchanges(encompassing their variety and subtleties),scalability,and the time metrics associated with various cryptographic *** propose a novel cryptographic approach underpinned by theoretical frameworks and practical *** to this approach is a thorough analysis of the interplay between Confidentiality and Integrity,foundational pillars of information *** method employs a phased strategy,beginning with a detailed examination of traditional cryptographic processes,including Elliptic Curve Diffie-Hellman(ECDH)key *** also delve into encrypt/decrypt paradigms,signature generation modes,and the hashes used for Message Authentication Codes(MACs).Each process is rigorously evaluated for performance and *** gain a comprehensive understanding,a meticulously designed simulation was conducted,revealing the strengths and potential improvement areas of various ***,our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs,marking a significant advancement over existing ***,with integrity metrics at 9.35,the protocol’s resilience is further *** metrics,derived from stringent testing,underscore the protocol’s efficacy in enhancing data security.
Integrated circuits (ICs) are ubiquitous and a crucial component of electronic systems, from satellites and military hardware to consumer devices and cell phones. The computing system’s foundation of trust is the IC....
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The quantum private query(QPQ)is a quantum solution for the symmetrically private information retrieval *** study the security of quantum-key-distribution-based QPQ with weak coherent *** result shows that multiphoton...
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The quantum private query(QPQ)is a quantum solution for the symmetrically private information retrieval *** study the security of quantum-key-distribution-based QPQ with weak coherent *** result shows that multiphoton pulses have posed a serious threat to the participant’s privacy in QPQ *** we propose a decoy-state method that can help the honest participant detect the attack by exploiting multiphoton pulses and improving the key distillation process to defend against such *** analysis demonstrates that our decoy-state method significantly improves the security of the QPQ with weak coherent pulses,which solves a major obstacle in the practical application of the QPQ.
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