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Federated Dynamic Client Selection for Fairness Guarantee in Heterogeneous Edge Computing

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Journal of Computer Science & Technology 2024年第1期39卷 139-158页

作者：毛莺池沈莉娟吴俊平萍吴杰 Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai UniversityNanjing 211100China College of Computer and Information Hohai UniversityNanjing 211100China center of networked Computing Temple UniversityPhiladelphiaPA 19122-6096U.S.A

Federated learning has emerged as a distributed learning paradigm by training at each client and aggregat-ing at a parameter *** heterogeneity hinders stragglers from responding to the server in time with huge com-munication *** client grouping in federated learning can solve the straggler problem,the stochastic selection strategy in client grouping neglects the impact of data distribution within each ***,current client grouping ap-proaches make clients suffer unfair participation,leading to biased performances for different *** order to guaran-tee the fairness of client participation and mitigate biased local performances,we propose a federated dynamic client selec-tion method based on data representativity(FedSDR).FedSDR clusters clients into groups correlated with their own lo-cal computational *** estimate the significance of client datasets,we design a novel data representativity evalua-tion scheme based on local data ***,the two most representative clients in each group are selected to optimize the global ***,the DYNAMIC-SELECT algorithm updates local computational efficiency and data representativity states to regroup clients after periodic average *** on real datasets show that FedS-DR improves client participation by 27.4%,37.9%,and 23.3%compared with FedAvg,TiFL,and FedSS,respectively,tak-ing fairness into account in federated *** addition,FedSDR surpasses FedAvg,FedGS,and FedMS by 21.32%,20.4%,and 6.90%,respectively,in local test accuracy variance,balancing the performance bias of the global model across clients.

关键词： federated learning fairness computational efficiency data distribution client selection client grouping

Optimal coordination of zero carbon building energy systems

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National Science Open 2024年第3期3卷 13-28页

作者： Wangyi Guo Zhanbo Xu Jinhui Liu Yaping Liu Jiang Wu Kun Liu Xiaohong Guan School of Future Technology Xi'an Jiaotong University Ministry of Education Key Lab for Intelligent Networks and Network Security School of Automation Science and EngineeringXi'an Jiaotong University center for Intelligent and networked systems Department of AutomationTNLISTTsinghua University

Optimal scheduling of renewable energy sources and building energy systems serves as a pivotal strategy for achieving zero carbon ***,the coordination of zero carbon building energy systems(ZCBS) is still challenging due to the complicated interactions among multi-energy hybrid storage and the complex coordination between seasonal and daily ***,this study develops a coordination scheduling approach for *** operation model and a seasonal-daily scheduling approach are developed to optimize the operation of hydrogen,geothermal,and water storage *** performance of the developed method is demonstrated using numerical case *** results show that the ZCBS can be achieved by using renewable energy sources with the system flexibility provided by hydrogen,geothermal,and water storage *** is also found that the developed scheduling approach reduces operation costs by more than 43.4%under the same device capacity,compared with existing scheduling approaches.

关键词： zero carbon building energy systems seasonal-daily scheduling multi-energy storage two-stage robust optimization

Spontaneous Recovery in Directed Dynamical Networks

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Engineering 2024年第6期37卷 208-214页

作者： Xueming Liu Xian Yan H.Eugene Stanley School of Artificial Intelligence and Automation&The MOE Engineering Research center of Autonomous Intelligent Unmanned systems&the Key Laboratory of Image Processing Huazhong University of Science and TechnologyWuhan 430074China center for Polymer Studies Department of PhysicsBoston UniversityBostonMA 02215USA

Complex networked systems,which range from biological systems in the natural world to infrastructure systems in the human-made world,can exhibit spontaneous recovery after a failure;for example,a brain may spontaneously return to normal after a seizure,and traffic flow can become smooth again after a *** studies on the spontaneous recovery of dynamical networks have been limited to undirected ***,most real-world networks are *** fill this gap,we build a model in which nodes may alternately fail and recover,and we develop a theoretical tool to analyze the recovery properties of directed dynamical *** find that the tool can accurately predict the final fraction of active nodes,and the prediction accuracy decreases as the fraction of bidirectional links in the network increases,which emphasizes the importance of directionality in network *** to different initial states,directed dynamical networks may show alternative stable states under the same control parameter,exhibiting hysteresis *** addition,for networks with finite sizes,the fraction of active nodes may jump back and forth between high and low states,mimicking repetitive failure-recovery *** findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.

关键词： Network resilience Directed dynamical networks Spontaneous recovery

The Immense Impact of Reverse Edges on Large Hierarchical Networks

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Engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi Gao Ye Yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang MOE Engineering Research center of Autonomous Intelligent Unmanned systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu Key Laboratory of networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electronic Engineering City University of Hong KongHong Kong 999077China Department of Biological Physics Eötvös UniversityBudapest 1117Hungary MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks Reverse edges Information flows Complex networks

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有向动态网络的自发恢复（英文）

Engineering 2024年第6期 208-214页

作者：刘雪明闫贤 H.Eugene Stanley School of Artificial Intelligence and Automation & The MOE Engineering Research center of Autonomous Intelligent Unmanned systems & the Key Laboratory of Image Processing Huazhong University of Science and Technology center for Polymer Studies Department of Physics Boston University

Complex networked systems, which range from biological systems in the natural world to infrastructure systems in the human-made world, can exhibit spontaneous recovery after a failure; for example, a brain may spontaneously return to normal after a seizure, and traffic flow can become smooth again after a jam. Previous studies on the spontaneous recovery of dynamical networks have been limited to undirected networks. However, most real-world networks are directed. To fill this gap, we build a model in which nodes may alternately fail and recover, and we develop a theoretical tool to analyze the recovery properties of directed dynamical networks. We find that the tool can accurately predict the final fraction of active nodes, and the prediction accuracy decreases as the fraction of bidirectional links in the network increases, which emphasizes the importance of directionality in network dynamics. Due to different initial states, directed dynamical networks may show alternative stable states under the same control parameter, exhibiting hysteresis behavior. In addition, for networks with finite sizes, the fraction of active nodes may jump back and forth between high and low states, mimicking repetitive failure-recovery processes. These findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.

关键词：

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反向连边在大型分层网络中的影响（英文）

Engineering 2024年第5期 240-249页

作者：曹浩森胡斌斌莫小雨陈都鑫高建喜袁烨陈关荣 Tamás Vicsek 管晓宏张海涛 MOE Engineering Research center of Autonomous Intelligent Unmanned systems State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology School of Mechanical and Aerospace Engineering Nanyang Technological University Jiangsu Key Laboratory of networked Collective Intelligence School of Mathematics Southeast University Department of Computer Science Rensselaer Polytechnic Institute Department of Electronic Engineering City University of Hong Kong Department of Biological Physics E?tv?s University MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and Engineering Xi'an Jiaotong University

Hierarchical networks are frequently encountered in animal groups, gene networks, and artificial engineering systems such as multiple robots, unmanned vehicle systems, smart grids, wind farm networks,and so forth. The structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes, such as lagging birds' howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social group. This study reveals that, for most large-scale real hierarchical networks, the majority of the reverse edges do not affect the synchronization process of the entire network; the synchronization process is influenced only by a small part of these reverse edges along specific paths. More surprisingly, a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%. The effect of such edges depends not on the network size but only on the average in-degree of the involved subnetwork. The overwhelming majority of active reverse edges turn out to have some kind of ‘‘bunchingo effect on the information flows of hierarchical networks, which slows down synchronization processes. This finding refines the current understanding of the role of reverse edges in many natural, social, and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these networks. Our study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

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Potential risk genes for primary Sjogren's syndrome from a meta-analysis by linear regression and random forest classification

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Genes & Diseases 2024年第3期11卷 128-131页

作者： Tomas Cerdo Teresa Torres Moral Maimonides Biomedical Research Institute of Cordoba(IMIBIC) Reina Sofia University HospitalUniversity of CordobaCordoba 14004Spain Centre for Rheumatology Research Division of MedicineUniversity College LondonLondon W1T 4JFUK Faculty of Computer Sciences Multimedia and TelecommunicationUniversitat Oberta de CatalunyaBarcelona 08018Spain Dermatology Department Melanoma UnitAugust Pi i Sunyer Biomedical Research Institute(IDIBAPS)and Hospital ClinicBarcelona 08036Spain center for networked Biomedical Research on Rare Diseases(CIBERER) Carlos II Health InstituteMadrid 28029Spain

Primary Sjogren's syndrome(psS)is one of the most widespread autoimmune diseases with unknown origin,characterized by a lymphocytic infiltrate of the exocrine glands and the production of anti-SSA/Ro and anti-SSB/La antibodies that cause dysfunction and destruction mainly of salivary and lachrymal glands,leading to dry eyes and dry *** the absence of a standardized evidence-based screening tool to decide which patients with dry eye must be referred for study of this pathology.

关键词： Sjogren lymphocytic salivary

Common quantitative characteristics of music melodies——pursuing the constrained entropy maximization casually in composition

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Science China(Information Sciences) 2022年第7期65卷 240-242页

作者： Nan NAN Xiaohong GUAN Yixin WANG Youtian DU MOE KLINNS Lab Faculty of Electronic and Information Engineering Xi'an Jiaotong University center for Intelligent and networked systems Tsinghua University

Music with a beautiful melody has been appreciated by humankind for thousands of years. Almost all music is generally tonal, e.g., Western music originated from ancient Greece and developed for more than 300 years from Baroque to classical, romantic, and modern music. Tonal music has a tonal center with a melody named tonic, and it is based on a specific pitch series called mode scale and harmonic progressions. On the contrary,

关键词： Power Law music melody variations complementary communitive distribution entropy functional optimization

On large action space in EV charging scheduling optimization

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Science China(Information Sciences) 2022年第2期65卷 45-60页

作者： Zhaoyu JIANG Qing-Shan JIA Xiaohong GUAN center for Intelligent and networked systems Beijing National Research Center for Information Science and Technology Department of Automation Tsinghua University MOE KLINNS Lab Xi'an Jiaotong University

In order to reduce the air pollution by traditional fossil fuel and save the charging cost, much attention has been paid to the charging scheduling of electric vehicles(EVs) in the uncertain supplement of wind power and solar power. Owing to the randomness in the renewable power generation and the EV charging demand, simulation-based policy improvement(SBPI) has been well adopted for making charging decision. However, it is challenging to explore the large action space which grows exponentially with respect to the system scale. We consider this important problem in this paper and make the following ***, we explore the structural property of the problem and develop an urgency index to rank the ***, we apply three methods to search in the action space. Third, we numerically demonstrate the performance of the urgency index and the search methods, and compare the SBPI methods with the CPLEXbased method. It shows that SBPI improves the base policies in all these cases.

关键词： EV simulation-based policy improvement large action space sampling