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28th International Conference on Database Systems for Advanced Applications, DASFAA 2023

作者： Wang, Xi Zhang, Qianzhen Guo, Deke Zhao, Xiang Institute for Quantum Information and State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China Laboratory for Big Data and Decision National University of Defense Technology Changsha China

ISBN: (纸本)9783031306747

Mining top-k frequent patterns is an important operation on graphs, which is defined as finding k interesting subgraphs with the highest frequency. Most existing work assumes a static graph. However, graphs are dynamic in nature, which is described as streaming graphs. Mining top-k frequent patterns in streaming graphs is challenging due to the streaming nature of the input and the exponential time complexity of the problem. A naive solution is to calculate approximations of the frequent patterns in the streaming graph and then find the top-k answers, which is a memory- and time-consuming method. In this paper, we design a novel auxiliary data structure, FPC, to detect valid subgraph patterns and their frequency in real-time. We first convert each newly produced subgraph into a sequence and then map it into corresponding tracks in FPC based on hash functions. We theoretically prove that FPC can provide unbiased estimation and then give an error bound of our algorithm. In addition, we propose a vertical hashing and candidate buckets sampling technique to further improve FPC with higher space utilization and higher accuracy. Extensive experiments confirm that our approach generates high-quality results compared to the baseline method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Hash functions

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Turán Numbers of Expanded Intersecting Cliques in 3-graphs

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Journal of the Operations Research Society of China 2024年第4期12卷 952-964页

作者： Yu-Cong Tang Tong Li Gui-Ying Yan School of Mathematics Nanjing University of Aeronautics and AstronauticsNanjing211106JiangsuChina Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) Ministry of Industry and Information TechnologyNanjing211106JiangsuChina School of Mathematical Sciences Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China University of Chinese Academy of Sciences Beijing100049China

Let l>r≥*** a 2-graph F,the expansion E^((r))of F is an r-graph obtained from F by adding r-2 new vertices into each *** F is a clique of order l,the Turán number ex(n,F^((r)))was first asymptotically determined by Mubayi(J Comb Theory Ser B 96:122–134,2006)and exactly computed by Pikhurko(J Comb Theory Ser B 103:220–225,2013).Let F_(k,l)be the 2-graph on(l-1)k+1 vertices consisting of k cliques of order l intersecting at exactly one *** determine the exact Turán number ex(n,F_(k,l)^((3)))for all l>3,k≥1,and sufficiently large n,as well as the corresponding extremal graphs.

关键词： Expansion Turán number 3-Graph Intersecting cliques Stability

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MGLGANï1/4ša generative adversarial model based on multi-layer graph convolution net and recurrent neural networks for link prediction

MGLGANï1/4ša generative adversarial model based on multi-l...

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2022 International Conference on Electronic Information Engineering, Big Data, and Computer technology, EIBDCT 2022

作者： Song, Jiantong Xiao, Xiaoqiang Ning, Weixun Zhang, Xu State Key Laboratory of High Performance Computing HuNan ChangSha China Computer School National University of Defense Technology HuNan ChangSha China

ISBN: (纸本)9781510655133

Link prediction is a technology to find existing but unobserved links (static) or predict new links (dynamic) by studying the network topology. In real life, most networks change with time. Some recent works focus on the dynamic prediction of networks, but they do not solve the weight problem in link prediction well. At the same time, the methods based on matrix decomposition and node embedding used in most link prediction tasks have some problems, such as huge amount of calculation or can't better represent the time evolution. In this paper, we extend the method of predicting the weight between nodes in dynamic networks and propose a generative adversarial model based on multi-layer graph convolution and recurrent neural network. The model consists of a generator and discriminator trained during an adversarial process. Multi-layer graph convolution used to approximate the high order similarity of network graph, so as to compensate the time evolution characteristic that RNN network can only deal with low order similarity. Using the process of confrontation training, the model can learn the representation of robust time evolution and predict with high accuracy. Experiments on several real data sets show that our model has good adaptability better than several baseline models. © 2022 SPIE.

关键词： Generative adversarial networks

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Versatility of π-d Conjugated Coordination Nickel Metal-Organic Frameworks as Electrode Materials of Metal-Ion Batteries

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Energy Material Advances 2024年第1期5卷 120-132页

作者： Zaohong Zhang Kaihui Xu Jing Yang Zhuoyu Ji Yunchen Ge Zhicong Shi Yongwei Zhang Kai Zhang Chuan Wu Jia Hong Pan State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures School of ResourcesEnvironments and MaterialsGuangxi UniversityNanning 530004China Low Carbon Energy Process Intensification Research Institute and MOE Key Laboratory of Resources and Environmental Systems Optimization North China Electric Power UniversityBeijing 102206China Institute of High Performance Computing Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore Guangxi Key Laboratory of Manufacturing Systems and Advanced Manufacturing Technology Guilin University of Electronic TechnologyGuilin 541004China School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory of Environmental Science and Engineering School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314019China

Metal-organic frameworks have emerged as promising electrode materials for metal-ion batteries due to their superior structural ***,they face challenges such as poor reversibility and easy degradation during electrochemical redox ***,we report the synthesis ofπ-d conjugated coordination polymers through NH_(3)-vapor-assisted self-polymerization of NiCl_(2)·6H_(2)O with 1,2,4,5-benzenetetramine tetrahydrochloride(namely,Ni-BTA).The synthesized Ni-BTA exhibits an open lattice structure that enhances the capacity for metal-ion diffusion,ensuring prolonged electrochemical cycling ***,electrochemical characterizations reveal that Ni-BTA functions as a bifunctional material,serving as both cathode and anode materials for lithium-ion batteries(LIBs).After 1,000 cycles at 1.0 A g^(−1),the cathode and anode show high discharge capacities of 199.7 and 338.4 mAh g^(−1),***,symmetrical all-organic batteries constructed with Ni-BTA exhibit a high specific capacity of 30.6 mAh g-1 and an ultrastable coulombic efficiency of approximately≈100%after 6,000 cycles at 1.0 A g^(−1).Furthermore,Ni-BTA exhibits versatility as a robust cathode for aluminum ion batteries(AIBs),delivering a discharge capacity of 18.7 mAh g^(−1) after 10,000 cycles at 1.0 A g^(−1).These findings highlight the potential of Ni-BTA as a versatile and durable electrode materials for both LIBs and AIBs.

关键词： d conjugation electrochemical stability open lattice stru metal ion batteries electrochemical redox processesherewe lithium ion batteries coordination polymers electrode materials

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TDLP: Time decay based link prediction method for dynamic networks

TDLP: Time decay based link prediction method for dynamic ne...

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2022 International Conference on Electronic Information Engineering, Big Data, and Computer technology, EIBDCT 2022

作者： Zhang, Xu Xiao, Xiaoqiang Ning, Weixun Song, Jiantong State Key Laboratory of High Performance Computing HuNan ChangSha China Computer School National University of Defense Technology HuNan ChangSha China

ISBN: (纸本)9781510655133

Link prediction aims to find the missing link in current networks or estimate the likelihood the link will appear in the future. In many real-world scenarios, networks can be massive and drastically evolving. Many recent works concentrated on how to solve the procession of massive data, which cares less about the effects of the temporal information. In some dynamic networks, the edge that appears a long time ago will have fewer effects on the appearance of edges in the future. The accuracy of link prediction in dynamic networks can be further improved by adding temporal information in prediction measures. In this paper, we mainly explore the effects of the link temporal information in the graph stream link prediction. We design a graph stream-based framework to solve link prediction problems in dynamic networks which can provide a convenient platform to implement different link prediction methods for dynamic networks, and evaluate these methods on a fair basis. Then, we proposed the Time Decay-based Link Prediction (TDLP) method to improve the efficient of link prediction problem in the dynamic networks. TDLP extends the neighborhood-based measure with time decay functions in graph stream scenarios which can handle temporal information and massive data. Experiment results demonstrate that the accuracy of link prediction for dynamic networks can be efficiently improved in our TDLP method. © 2022 SPIE.

关键词： Metadata

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Ambient Fast Synthesis of Superaerophobic/Superhydrophilic Electrode for Superior Electrocatalytic Water Oxidation

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Energy & Environmental Materials 2023年第6期6卷 356-363页

作者： Jingjun Shen Jing Li Bo Li Yun Zheng Xiaozhi Bao Junpo Guo Yan Guo Chenglong Lai Wen Lei Shuangyin Wang Huaiyu Shao Guangdong-Hong Kong-Macao Joint Laboratory for Photonic-Thermal-Electrical Energy Materials and Devices Institute of Applied Physics and Materials EngineeringUniversity of MacaoAvenida da UniversidadeTaipaMacaoSAR 999078China Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education Key Laboratory of High Performance Polymer-based Composites of Guangdong ProvinceSchool of ChemistrySun Yat-Sen UniversityGuangzhou 510275China School of Materials Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan 430081China State Key Laboratory of Chem/Bio-Sensing and Chemometrics Provincial Hunan Key Laboratory for Graphene Materials and DevicesCollege of Chemistry and Chemical EngineeringHunan UniversityChangsha 410082China

Developing cost-effective and facile methods to synthesize efficient and stable electrocatalysts for large-scale water splitting is highly desirable but remains a significant *** this study,a facile ambient temperature synthesis of hierarchical nickel-iron(oxy)hydroxides nanosheets on iron foam(FF-FN)with both superhydrophilicity and superaerophobicity is ***,the as-fabricated FF-FN electrode demonstrates extraordinary oxygen evolution reaction(OER)activity with an ultralow overpotential of 195 mV at 10 mA cm^(-2)and a small Tafel slope of 34 mV dec^(-1)in alkaline *** theoretical investigation indicates that the involved lattice oxygen in nickel-iron-based-oxyhydroxide during electrochemical self-reconstruction can significantly reduce the OER reaction overpotential via the dominated lattice oxygen *** rechargeable Zn-air battery assembled by directly using the as-prepared FF-FN as cathode displays remarkable cycling *** is believed that this work affords an economical approach to steer commercial Fe foam into robust electrocatalysts for sustainable energy conversion and storage systems.

关键词： electrocatalysis oxygen evolution reaction oxyhydroxide superaerophobicity superhydrophilicity

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A novel strategy of fabricated flexible ITO electrode by liquid metal ultra-thin oxide film

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Journal of Materiomics 2022年第6期8卷 1205-1212页

作者： Yunhui Wu Xufeng Liu Wenjian Wu Yuanmin Zhu Kunquan Li Xiaojing Su Huali Xie Xiaofan Zhang Haitao Xu Kang Wang Zhi-Min Dang Guangdong Provincial Engineering Technology Research Center of Key Materials for High Performance Copper Clad Laminates College of Materials Science and EngineeringDongguan University of TechnologyDongguan523808China State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijing100084China

Flexible transparent conductive films are gaining attention day by day over the last few years due to it is a key component of next generation flexible electronics and optoelectronic *** tin oxide(ITO)as one of the most widely used transparent conductive material is limited by the traditional deposition approach cannot be achieve ultra-thin,which results in its brittle ***,a novel strategy for fabricating highly transparent conductive films by liquid metal interface phase separation technique based on low-melting liquid metal of InxSn100-x alloy is reported,during the solid-to-liquid phase transition of alloy,the monolayer of surface oxide film segregated with the bulk phase and was printed on the flexible polyethylene-naphthalate(PEN)substrate under the van der *** novel strategy can directly print the ultra-thin self-oxide with the structure of ITO on PEN substrate,with the resulting of transparency over 97.5%and resistivity as low as 0.21 kU cm,providing a new way of lowcost raw ITO material as well as the personalized preparation *** desirable highly transparent conductive films are comparable to recently reported ITO film,together with advantages of pretty steady,make them attractive as various flexible transparent conductive electrodes,for example,an ultra-thin ITO film is developed for luminescent devices.

关键词： Dielectric property Ultra-thin self-oxide Transparent conductive film Liquid metal

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high-frequency Voltage Signal Fault Diagnosis Based on Multi-channel Hierarchical Structure Capsule-Attention Network 8

High-frequency Voltage Signal Fault Diagnosis Based on Multi...

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8th International Conference on Big Data and Information Analytics, BigDIA 2022

作者： Miao, Qiucheng Xu, Chuanfu Zhan, Jun Zhu, Dong Wu, Chengkun Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Hunan Changsha China

ISBN: (数字)9781665487962

ISBN: (纸本)9781665487962

An important research area for covered conductors is partial discharge detection. However, the complex distribution of high-frequency signals with particular noise and the long tail problem create a considerable obstacle to accurate detection. This paper proposes a Capsule-Attention model with a Multi-channel Hierarchical structure, which separately utilize ResNet and BiGRU to extract short- and long-term high-frequency and pre-filter existing irrelevant information. The capsule layer is good at multidimensional and spatial information representation, and we utilize it to recognize and classify fault conditions. The attention mechanism's weight distribution quantifies the importance of features in the entire signal. Considering the class imbalance of the long-tail distribution of samples, We propose a Focal-MCC (FMCC) loss function. The proposed loss reshapes the typical cross-entropy loss, hence reducing the weights allocated to well-classified instances. Matthews Correlation Coefficient penalizes false positives/false negatives to prevent parameters from falling into local minimums. The experiments indicate that the model proposed is useful in detecting partial discharge faults and has application value. The code is available at https://***/qiumia030/capsule_attention. © 2022 IEEE.

关键词： Failure analysis

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DNS Service Optimization Through In-Network Caching on Programmable Switches

DNS Service Optimization Through In-Network Caching on Progr...

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International Conference on Computer and Communications (ICCC)

作者： Fan Yang Cenman Wang Bowen Zheng Ye Tian Anhui Key Laboratory on High Performance Computing School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

The Domain Name System (DNS) plays a crucial role in contemporary internet infrastructure. Despite the geographical distance of public DNS servers posing a challenge in minimizing domain name resolution latency, there is an increasing reliance on these servers for resolving domain names. One effective approach to mitigate this challenge involves caching DNS query results at network nodes. The storage of cached results commonly employs hash tables due to the variable lengths of domain names. However, within network nodes, hash tables encounter limitations in capacity and susceptibility to hash collisions, potentially leading to inaccuracies in cached results. Current conventional caching strategies have not produced satisfactory storage outcomes. This research introduces a hash-based DNS caching mechanism to tackle these issues. The proposed mechanism presents a unique DNS storage structure on routers and suggests two implementation strategies that incorporate fingerprint verification and Bloom filters. Through analysis and extensive simulations utilizing real-world network topology, the results demonstrate that the hash-based DNS caching mechanism introduced in this study outperforms existing methods in cache hit rate and diminishes query latency.

关键词： Analytical models Filters Network topology Computational modeling Fingerprint recognition Cache storage Topology Domain Name System Servers Optimization

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Accurate Detection of Superspreaders on Multi-Pipeline Switches 10

Accurate Detection of Superspreaders on Multi-Pipeline Switc...

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10th International Conference on Computer and Communications, ICCC 2024

作者： Wang, Cenman Zheng, Bowen Yang, Fan Tian, Ye School of Computer Science and Technology University of Science and Technology of China Anhui Key Laboratory on High Performance Computing Hefei China

In various network monitoring tasks, the detection of superspreaders has become increasingly crucial. However, latest superspreader detection algorithms and data structures assume the target switch with a single pipeline, while state-of-the-art programmable switches actually comprise multiple independent pipelines. In current method for deploying super-spreader detection applications on multi-pipeline switches, a separate measurement data structure instance is employed for each pipeline. However, under multi-path routing, this simplistic approach leads to lower detection accuracy due to hash collisions. To address this issue, in this paper, we present PipelineAlloc, a HyperLogLog-based superspreader detection system designed for multi-pipeline switches. In order to reduce hash collisions in measurement data structures, PipelineAlloc assigns an egress pipeline as the monitor pipeline for each source IP address. PipelineAlloc introduces novel measurement data structures in the ingress pipelines for temporarily storing statistics of the source and destination IP addresses of packets, and uses packets to carry these measurement data to egress pipelines, which serve as the monitor pipelines. The HyperLogLog-based measurement data structures in egress pipelines are updated using data carried by packets. Experiments driven by real-world traffic traces show that PipelineAlloc outperforms existing solutions in terms of detection accuracy. © 2024 IEEE.

关键词： multi-path routing multi-pipeline switch network monitoring su-perspreader

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