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Age-of-Information-Aware Federated Learning

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Journal of Computer science & Technology 2024年第3期39卷 637-653页

作者：徐殷肖明军吴晨吴杰周津锐孙贺 Student Member CCF 1.School of Computer Science and TechnologyUniversity of Science and Technology of ChinaHefei 230026China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215123China School of Data science University of Science and Technology of ChinaHefei 230026China Department of Computer and Information sciences Temple UniversityPhiladelphiaPA 19122U.S.A.

Federated learning(FL)is an emerging privacy-preserving distributed computing paradigm,enabling numerous clients to collaboratively train machine learning models without the necessity of transmitting clients’private datasets to the central *** most existing research where the local datasets of clients are assumed to be unchanged over time throughout the whole FL process,our study addresses such scenarios in this paper where clients’datasets need to be updated periodically,and the server can incentivize clients to employ as fresh as possible datasets for local model *** primary objective is to design a client selection strategy to minimize the loss of the global model for FL loss within a constrained *** this end,we introduce the concept of“Age of Information”(AoI)to quantitatively assess the freshness of local datasets and conduct a theoretical analysis of the convergence bound in our AoI-aware FL *** on the convergence bound,we further formulate our problem as a restless multi-armed bandit(RMAB)***,we relax the RMAB problem and apply the Lagrangian Dual approach to decouple it into multiple ***,we propose a Whittle’s Index Based Client Selection(WICS)algorithm to determine the set of selected *** addition,comprehensive simulations substantiate that the proposed algorithm can effectively reduce training loss and enhance the learning accuracy compared with some state-of-the-art methods.

关键词： federated learning Age of Information restless multi-armed bandit Whittle’s index

Flight Time Minimization of UAV for Cooperative Data Collection in Probabilistic LoS Channel

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china Communications 2024年第2期21卷 210-226页

作者： Yan Li Shaoyi Xu Yunpu Wu Dongji Li School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Electrical Engineering and Electronic Information Xihua UniversityChengdu 610039China

This paper investigates the data collection in an unmanned aerial vehicle(UAV)-aided Internet of Things(IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabilistic line-of-sight(LoS) channel. Especially, access points(APs) are introduced to collect data from some sensors in the unlicensed band to improve data collection efficiency. We formulate a mixed-integer non-convex optimization problem to minimize the UAV flight time by jointly designing the UAV 3D trajectory and sensors’ scheduling, while ensuring the required amount of data can be collected under the limited UAV energy. To solve this nonconvex problem, we recast the objective problem into a tractable form. Then, the problem is further divided into several sub-problems to solve iteratively, and the successive convex approximation(SCA) scheme is applied to solve each non-convex subproblem. Finally,the bisection search is adopted to speed up the searching for the minimum UAV flight time. Simulation results verify that the UAV flight time can be shortened by the proposed method effectively.

关键词： data collection flight time probabilistic line-of-sight channel unlicensed band unmanned aerial vehicle

Broadband high-efficiency dielectric metalenses based on quasi-continuous nanostrips

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Opto-Electronic Advances 2024年第5期7卷 43-51页

作者： Xiaohu Zhang Qinmiao Chen Dongliang Tang Kaifeng Liu Haimo Zhang Lintong Shi Mengyao He Yongcai Guo Shumin Xiao Key Laboratory of optoelectronic Technology and Systems of the Education Ministry of china Chongqing UniversityChongqing 400044China Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of TechnologyShenzhen 518055China Key Laboratory for Micro/Nano Optoelectronic Devices of Ministry of Education&Hunan Provincial Key Laboratory of Low-Dimensional Structural Physics and Devices School of Physics and ElectronicsHunan UniversityChangsha 410082China

Benefiting from the abrupt phase changes within subwavelength thicknesses,metasurfaces have been widely applied for lightweight and compact optical *** broadband and high-efficiency characteristics are highly attractive for the practical implementation of ***,current metasurface devices mostly adopt discrete micro/nano structures,which rarely realize both merits *** this paper,dielectric metasurfaces composed of quasi-continuous nanostrips are proposed to overcome this *** quasi-continuous nanostrips metasurface,a normal focusing metalens and a superoscillatory lens overcoming the diffraction limit are designed and experimentally *** quasi-continuous metadevices can operate in a broadband wavelength ranging from 450 nm to 1000nm and keep a high power *** average efficiency of the fabricated metalens reaches 54.24%,showing a significant improvement compared to the previously reported metalenses with the same *** proposed methodology can be easily extended to design other metadevices with the advantages of broadband and high-efficiency in practical optical systems.

关键词： broadband high-efficiency metalens sub-diffraction quasi-continuous

Probabilistic modeling of multifunction radars with autoregressive kernel mixture network

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Defence Technology（防务技术） 2024年第5期35卷 275-288页

作者： Hancong Feng Kaili.Jiang Zhixing Zhou Yuxin Zhao Kailun Tian Haixin Yan Bin Tang School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic *** methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative *** paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse *** results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.

关键词： Probabilistic forecasting Multifunction radar Unsupervised learning Change point detection Outlier detection

Random Subspace Sampling for Classification with Missing Data

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Journal of Computer science & Technology 2024年第2期39卷 472-486页

作者：曹云浩吴建鑫 State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210093China

Many real-world datasets suffer from the unavoidable issue of missing values,and therefore classification with missing data has to be carefully handled since inadequate treatment of missing values will cause large *** this paper,we propose a random subspace sampling method,RSS,by sampling missing items from the corresponding feature histogram distributions in random subspaces,which is effective and efficient at different levels of missing *** most established approaches,RSS does not train on fixed imputed ***,we design a dynamic training strategy where the filled values change dynamically by resampling during ***,thanks to the sampling strategy,we design an ensemble testing strategy where we combine the results of multiple runs of a single model,which is more efficient and resource-saving than previous ensemble ***,we combine these two strategies with the random subspace method,which makes our estimations more robust and *** effectiveness of the proposed RSS method is well validated by experimental studies.

关键词： missing data random subspace neural network ensemble learning

Paleogene transgression process and environmental evolution in the deepwater area of the Baiyun Depression in the northern South china Sea

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Acta Oceanologica Sinica 2024年第4期43卷 15-24页

作者： Peijun Qiao Yuchi Cui Qiong Ma Qiang Yu Lei Shao State Key Laboratory of Marine Geology Tongji UniversityShanghai 200092China CNOOC Energy Technology&Services-Drilling&Production Co. CNOOC Central Laboratory Shenzhen BranchGuangdong 516000China

Multiple borehole samples are collected from the Baiyun Depression in deep-water area of the northern South china Sea(SCS)in an effort to reconstruct transgression processes during the Paleogene based on palynalgal *** study indicates that the Baiyun Depression generated a large group of palynopore assemblages and fluvial/lacustrine-related algae during the early and middle Eocene when the Wenchang Formation was *** entire depression was dominated by fluvial and lacustrine facies before *** eastern and southeastern sags transitioned to shallow marine environment by generating a large abundance of marine dinoflagellates during the Enping deposition of the late ***,the southern uplift zone simply yielded fluvial/lacustrine-related palynopores and algae,and was dominated by the fluvial and lacustrine environment during the early stage of the Enping Formation,prior to shifting into transitional setting in the later *** sags remained extensive fluvial and delta facies without existence of marine *** was until the depositional stage of the Zhuhai Formation(Oligocene)that the overall depression was strongly impacted from transgression *** eastern and southeastern sags were mainly under deep marine setting on a continental slope while northwestern and southern areas developed transitional *** distribution and accumulation patterns varied greatly among sub-sags,the overall Baiyun Depression was characterized by widespread development of marine *** should be noted that the northwestern sag also partly generated large-scale river delta *** to the eustatic rise and change of SCS spreading axis,the overall Baiyun Depression was mostly influenced by the deep marine environment on a continental slope during the early *** northwestern sag and southern uplift zone were found plentiful marine *** summary,transgression initiated from the ea

关键词： South china Sea Paleogene transgression sedimentary environment plant ecology

GraphSTGAN:Situation understanding network of slow-fast high maneuvering targets for maritime monitor services of IoT data

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Digital Communications and Networks 2024年第3期10卷 620-630页

作者： Guanlin Wu Haipeng Wang Yu Liu You He Shenzhen International Graduate School Tsinghua UniversityShenzhen518071China Institute of Space science and Applied Technology Harbin Institute of TechnologyShenzhen518055China Department of Electronic Engineering Tsinghua UniversityBeijing100084China

With the rapid growth of the maritime Internet of Things(IoT)devices for Maritime Monitor Services(MMS),maritime traffic controllers could not handle a massive amount of data in *** unmanned MMS,one of the key technologies is situation ***,the presence of slow-fast high maneuvering targets and track breakages due to radar blind zones make modeling the dynamics of marine multi-agents difficult,and pose significant challenges to maritime situation *** order to comprehend the situation accurately and thus offer unmanned MMS,it is crucial to model the complex dynamics of multi-agents using IoT big ***,previous methods typically rely on complex assumptions,are plagued by unstructured data,and disregard the interactions between multiple agents and the spatial-temporal correlations.A deep learning model,Graph Spatial-Temporal Generative Adversarial Network(GraphSTGAN),is proposed in this paper,which uses graph neural network to model unstructured data and uses STGAN to learn the spatial-temporal dependencies and *** experiments show the effectiveness and robustness of the proposed method.

关键词： Internet of things Multi-agents Graph neural network Maritime monitoring services

A stable staggered-grid finite-difference scheme for acoustic modeling beyond conventional stability limit

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Petroleum science 2024年第1期21卷 182-194页

作者： Jing-Yi Xu Yang Liu national Key Laboratory of Petroleum Resources and Engineering China University of Petroleum(Beijing)Beijing 102249China china University of Petroleum(Beijing) Karamay CampusKaramay 834000XinjiangChina

Staggered-grid finite-difference(SGFD)schemes have been widely used in acoustic wave modeling for geophysical *** improved methods are proposed to enhance the accuracy of numerical ***,these methods are inevitably limited by the maximum Courant-Friedrichs-Lewy(CFL)numbers,making them unstable when modeling with large time sampling intervals or small grid *** solve this problem,we extend a stable SGFD scheme by controlling SGFD dispersion relations and maximizing the maximum CFL ***,to improve modeling stability,we minimize the error between the FD dispersion relation and the exact relation in the given wave-number region,and make the FD dispersion approach a given function outside the given wave-number area,thus breaking the conventional limits of the maximum CFL ***,to obtain high modeling accuracy,we use the SGFD scheme based on the Remez algorithm to compute the FD *** addition,the hybrid absorbing boundary condition is adopted to suppress boundary reflections and we find a suitable weighting coefficient for the proposed *** derivation and numerical modeling demonstrate that the proposed scheme can maintain high accuracy in the modeling process and the value of the maximum CFL number of the proposed scheme can exceed that of the conventional SGFD scheme when adopting a small maximum effective wavenumber,indicating that the proposed scheme improves stability during the modeling.

关键词： Acoustic wave Staggered-grid finite-difference(SGFD) modeling Courant-friedrichs-lewy(CFL)number Stability

A New Method for Solving Nonlinear Partial Differential Equations Based on Liquid Time-Constant Networks

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Journal of Systems science & Complexity 2024年第2期37卷 480-493页

作者： SUN Jiuyun DONG Huanhe FANG Yong College of Mathematics and Systems science Shandong University of Science and TechnologyQingdao 266590China

In this paper,physics-informed liquid networks(PILNs)are proposed based on liquid time-constant networks(LTC)for solving nonlinear partial differential equations(PDEs).In this approach,the network state is controlled via ordinary differential equations(ODEs).The significant advantage is that neurons controlled by ODEs are more expressive compared to simple activation *** addition,the PILNs use difference schemes instead of automatic differentiation to construct the residuals of PDEs,which avoid information loss in the neighborhood of sampling *** this method draws on both the traveling wave method and physics-informed neural networks(PINNs),it has a better physical ***,the KdV equation and the nonlinear Schr¨odinger equation are solved to test the generalization ability of the *** the best of the authors’knowledge,this is the first deep learning method that uses ODEs to simulate the numerical solutions of PDEs.

关键词： Nonlinear partial differential equations numerical solutions physics-informed liquid networks physics-informed neural networks

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