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Network Configuration Entity Extraction Method Based on Transformer with Multi-Head Attention Mechanism

Computers, Materials & Continua 2024年第1期78卷 735-757页

作者： yang yang Zhenying Qu Zefan Yan zhipeng Gao Ti Wang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China Product Development Department China Unicom Smart City Research InstituteBeijing100044China

Nowadays,ensuring thequality of networkserviceshas become increasingly vital.Experts are turning toknowledge graph technology,with a significant emphasis on entity extraction in the identification of device configurations.This research paper presents a novel entity extraction method that leverages a combination of active learning and attention mechanisms.Initially,an improved active learning approach is employed to select the most valuable unlabeled samples,which are subsequently submitted for expert labeling.This approach successfully addresses the problems of isolated points and sample redundancy within the network configuration sample set.Then the labeled samples are utilized to train the model for network configuration entity extraction.Furthermore,the multi-head self-attention of the transformer model is enhanced by introducing the Adaptive Weighting method based on the Laplace mixture distribution.This enhancement enables the transformer model to dynamically adapt its focus to words in various positions,displaying exceptional adaptability to abnormal data and further elevating the accuracy of the proposed model.Through comparisons with Random Sampling(RANDOM),Maximum Normalized Log-Probability(MNLP),Least Confidence(LC),Token Entrop(TE),and Entropy Query by Bagging(EQB),the proposed method,Entropy Query by Bagging and Maximum Influence Active Learning(EQBMIAL),achieves comparable performance with only 40% of the samples on both datasets,while other algorithms require 50% of the samples.Furthermore,the entity extraction algorithm with the Adaptive Weighted Multi-head Attention mechanism(AW-MHA)is compared with BILSTM-CRF,Mutil_Attention-Bilstm-Crf,Deep_Neural_Model_NER and BERT_Transformer,achieving precision rates of 75.98% and 98.32% on the two datasets,respectively.Statistical tests demonstrate the statistical significance and effectiveness of the proposed algorithms in this paper.

关键词： Entity extraction network configuration knowledge graph active learning transformer

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A benchmark-based method for evaluating hyperparameter optimization techniques of neural networks for surface water quality prediction

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 13-27页

作者： Xuan Wang Yan Dong Jing yang zhipeng Liu Jinsuo Lu School of Environmental and Municipal Engineering Xi’an University of Architecture and TechnologyXi’an710055China Shaanxi Key Laboratory of Environmental Engineering Xi’an University of Architecture and TechnologyXi’an710055China State Key Laboratory of Green Building in West China Xi’an University of Architecture and TechnologyXi’an710055China

Neural networks(NNs)have been used extensively in surface water prediction tasks due to computing algorithm improvements and data accumulation.An essential step in developing an NN is the hyperparameter selection.In practice,it is common to manually determine hyperparameters in the studies of NNs in water resources tasks.This may result in considerable randomness and require significant computation time;therefore,hyperparameter optimization(HPO)is essential.This study adopted five representatives of the HPO techniques in the surface water quality prediction tasks,including the grid sampling(GS),random search(RS),genetic algorithm(GA),Bayesian optimization(BO)based on the Gaussian process(GP),and the tree Parzen estimator(TPE).For the evaluation of these techniques,this study proposed a method:first,the optimal hyperparameter value sets achieved by GS were regarded as the benchmark;then,the other HPO techniques were evaluated and compared with the benchmark in convergence,optimization orientation,and consistency of the optimized values.The results indicated that the TPE-based BO algorithm was recommended because it yielded stable convergence,reasonable optimization orientation,and the highest consistency rates with the benchmark values.The optimization consistency rates via TPE for the hyperparameters hidden layers,hidden dimension,learning rate,and batch size were 86.7%,73.3%,73.3%,and 80.0%,respectively.Unlike the evaluation of HPO techniques directly based on the prediction performance of the optimized NN in a single HPO test,the proposed benchmark-based HPO evaluation approach is feasible and robust.

关键词： Neural networks Hyperparameter optimization Surface water quality prediction Bayes optimization Genetic algorithm

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Simulation and analysis of soil homogenization drills based on discrete element method and response surface methodology

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Particuology 2024年第5期88卷 128-148页

作者： zhipeng Wang Tong Zhu Youzhao Wang Song yang Feng Ma Xu Li Institute of Process Equipment and Environmental Engineering School of Mechanical Engineering and AutomationNortheastern UniversityShenyang110819China Liaoning Coning Testing Co. Ltd.Shenyang110170 China

Currently,rotary drilling is one of the main pieces of equipment used for in-situ remediation of contaminated soil.However,this equipment has problems such as uneven mixing and low utilization efficiency,which affect the efficiency of in-situ soil remediation.To improve the efficiency of in-situ soil remediation,this paper takes contaminated black soil as the research object,and the structural design of the new three-stage soil remediation auger is carried out based on SolidWorks.The mixing process of soil and heavy metal passivator under different motion and structural parameters was investigated by the discrete element method(DEM)and response surface methodology.The experimental design was based on rotational speed,homogenizing mixing time,crushing section pitch,and homogenizing section pitch as factors,and soil fragmentation ratio,the coefficient of dispersion,and torque as optimization indices.The kinematic and structural parameters of the three-stage auger drill bit were then optimized using the one-factor method,the orthogonal test,and the response surface methodology,respectively.The test method uses a one-way test to determine the central level value of the orthogonal test and a comprehensive balance method to determine the best combination of parameters for the orthogonal test,which is then used as the central value of the response surface test for parameter optimization.The optimal combinations of kinematic and structural parameters of the three-stage auger drill bit are determined and validated using response surface methodology.The optimum combination of parameters was found to be a speed of 129 rpm,a homogenizing mixing time of 24 s,a pitch of 165 mm in the crushing section,and a pitch of 132 mm in the homogenizing section.The error between the optimal value of the predicted model using the response surface method and the actual simulated value under the optimal parameters is 4.2%,4.9%,and 5.3%,respectively.The optimized factor parameters provide a reference for the design of the structural and kinem

关键词： Black soil Mixing homogeneity Orthogonal method Response surface methodology Discrete element method Soil remediation

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A Novel Sensing Imaging Equipment Under Extremely Dim Light for Blast Furnace Burden Surface:Starlight High-Temperature Industrial Endoscope

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 893-906页

作者： zhipeng Chen Xinyi Wang Weihua Gui Jilin Zhu Chunhua yang Zhaohui Jiang The authors are with the School of Automation Central South UniversityChangsha 410083China

Blast furnace(BF)burden surface contains the most abundant,intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material charging control,optimize gas flow distribution and improve ironmaking efficiency.It has been challengeable to obtain high-quality optical burden surface images under high-temperature,high-dust,and extremelydim(less than 0.001 Lux)environment.Based on a novel endoscopic sensing detection idea,a reverse telephoto structure starlight imaging system with large field of view and large aperture is designed.Combined with a water-air dual cooling intelligent self-maintenance protection device and the imaging system,a starlight high-temperature industrial endoscope is developed to obtain clear optical burden surface images stably under the harsh environment.Based on an endoscope imaging area model,a material flow trajectory model and a gas-dust coupling distribution model,an optimal installation position and posture configuration method for the endoscope is proposed,which maximizes the effective imaging area and ensures large-area,safe and stable imaging of the device in a confined space.Industrial experiments and applications indicate that the proposed method obtains clear and reliable large-area optical burden surface images and reveals new BF conditions,providing key data support for green iron smelting.

关键词： Blast furnace(BF) burden surface extremely dim light industrial endoscope sensing imaging starlight

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Doping suppresses lattice distortion of vacant quadruple perovskites to activate self-trapped excitons emission

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Nano Research 2024年第4期17卷 3068-3078页

作者： zhipeng Chen Fei Zhang Dongwen yang Huifang Ji Xu Chen Di Wu Xinjian Li Yu Zhang Zhifeng Shi Key Laboratory of Materials Physics of Ministry of Education School of Physics and MicroelectronicsZhengzhou UniversityZhengzhou 450052China State Key Laboratory on Integrated Optoelectronics College of Electronic Science and EngineeringJilin UniversityChangchun 130012China

The vacancy-ordered quadruple perovskite Cs_(4)CdBi_(2)Cl_(12),as a newly-emerging lead-free perovskite system,has attracted great research interest due to its excellent stability and direct band gap.However,the poor luminescence performance limits its application in light-emitting diodes(LEDs)and other fields.Herein,for the first time,an Ag^(+)ion doping strategy was proposed to greatly improve the emission performance of Cs_(4)CdBi_(2)Cl_(12) synthesized by hydrothermal method.Density functional theory calculations combined with experimental results evidence that the weak orange emission from Cs_(4)CdBi_(2)Cl_(12) is attributed to the phonon scattering and energy level crossing due to the large lattice distortion under excited states.Fortunately,Ag^(+)ion doping breaks the intrinsic crystal field environment of Cs_(4)CdBi_(2)Cl_(12),suppresses the crossover between ground and excited states,and reduces the energy loss in the form of nonradiative recombination.At a critical doping amount of 0.8%,the emission intensity of Cs_(4)CdBi_(2)Cl_(12):Ag^(+)reaches the maximum,about eight times that of the pristine sample.Moreover,the doped Cs_(4)CdBi_(2)Cl_(12) still maintains excellent stability against heat,ultraviolet irradiation,and environmental oxygen/moisture.The above advantages make it possible for this material to be used as solid-state phosphors for white LEDs applications,and the Commission International de I’Eclairage color coordinates of(0.31,0.34)and high color rendering index of 90.6 were achieved.More importantly,the white LED demonstrates remarkable operation stability in air ambient,showing almost no emission decay after a long working time for 48 h.We believe that this study puts forward an effective ion-doping strategy for emission enhancement of vacancy-ordered quadruple perovskite Cs_(4)CdBi_(2)Cl_(12),highlighting its great potential as efficient emitter compatible for practical applications.

关键词： Cs_(4)CdBi_(2)Cl_(12) self-trapped excitons ion doping emission enhancement stability

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Comprehensive insights:unraveling the mechanisms of gut commensals in glucose metabolism regulation

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Science China(Life Sciences) 2024年第2期67卷 414-417页

作者： zhipeng Li Qixing Nie Shao-Ping Nie State Key Laboratory of Food Science and Resources China-Canada Joint Lab of Food Science and Technology(Nanchang)Key Laboratory of Bioactive Polysaccharides of Jiangxi ProvinceNanchang UniversityNanchang 330047China

The prevalence of type 2 diabetes(T2D)has escalated to a global epidemic,garnering widespread concern.Tremendous research utilizing germ-free(GF)mice,antibiotic treatments,and fecal microbiota transplantation approaches has established the critical role of gut microbiota in modulating glucose metabolism.The microbiota interacts with diets and the mucosal immune system,influencing intestinal permeability and the penetration of microbial products.

关键词： metabolism utilizing insight

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Experimental and Numerical Investigation of Non-synchronous Blade Vibration Excitation in a Transonic Axial Compressor

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Journal of Thermal Science 2024年第2期33卷 602-610页

作者： WANG Songbai WU Yadong CHEN Yong CAO zhipeng School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai200240China AECC Sichuan Gas Turbine Establishment Chengdu610500China

The complex flow phenomenon of rotating instability(RI) and its induced non-synchronous vibration(NSV) have become a significant challenge as they continuously increase aerodynamic load.This study aims to provide an understanding of the non-synchronous blade vibration phenomenon caused by the rotating instability of a transonic axial compressor rotor.In this case,blade vibrations and non-synchronous excitation are captured by strain gauges and unsteady wall pressure transducer sensors.Unsteady numerical simulations for a full-annulus configuration are used to obtain the non-synchronous flow excitation.The results show that the first-stage rotor blade exhibits an NSV close to the first bending mode;NSV is accompanied by a sharp increase in pressure pulsation;amplitude can reach 20%,and unsteady aerodynamic frequency will lock in a structural mode frequency when the blade vibrates in a large-amplitude motion.The predicted NSV frequency aligns well with the experimental results.The dominant mode of circumferential instability flow structure is approximately 47% of the number blades,and the cell size occupies 2-3 pitches in the circumferential direction.The full-annulus unsteady simulations demonstrate that the streamwise oscillation of the shedding and reattachment vortex structure is the main cause of NSV owing to the strong interaction between the tip leakage and separation vortices near the suction surface.

关键词： non-synchronous vibration transonic axial compressor rotor blade rotating instabilities unsteady flow

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Periodic event-triggered secure consensus for networked mechanical systems under Denial-of-Service attacks

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Control Theory and Technology 2024年第1期22卷 1-13页

作者： Shiqi Zheng zhipeng Li Chao Zhai Peng Shi School of Automation China University of GeosciencesWuhan430074HubeiChina School of Electrical and Electronic Engineering The University of AdelaideAdelaideSA5005Australia School of Electronic Electrical Engineering and PhysicsFujian University of TechnologyFuzhou350100FujianChina

This paper concentrates on the secure consensus problem of networked mechanical/Euler–Lagrange systems.First,a new periodic event-triggered(PET)secure distributed observer is proposed to estimate the leader information.The proposed distributed observer only relies on the PET data from its neighbors,which can significantly reduce the communication and computational burden.More importantly,it is secure in the sense that it can work normally regardless of the Denial-of-Service(DoS)attacks.Second,based on the proposed distributed observer,an adaptive fuzzy control law is proposed for each Euler–Lagrange system.A PET mechanism is integrated into the controller,which can reduce the control update.This is helpful for both energy saving and fault tolerance of actuators.Moreover,the PET mechanism naturally makes the controller easy to be implemented in digital platform.The property of fuzzy logic systems and Gronwall inequality are skillfully utilized to show the stability of the closed-loop system.Finally,the proposed control scheme is verified on real Euler–Lagrange systems,which contain a robot manipulator and several servo motors.

关键词： Output regulation Mechanical/Euler-Lagrange systems Periodic event-triggered mechanism Denial-of-Service attacks

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Recent advances in post-chiroptical manipulation of supramolecular aggregates assembled with molecular modules

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Science China Chemistry 2024年

作者： Yanling Shen Wanhua Wu zhipeng Yu Cheng yang Key Laboratory of Green Chemistry & Technology of Ministry of Education College of Chemistry Institution Sichuan University

Recently, various supramolecular assembly systems have been identified where the pre-existing chiral supramolecular structure can be manipulated through environmental adjustments, such as temperature, solvent, and concentration. These changes result in diverse microscopic morphologies during the assembly process and induce chiroptical variations, particularly in circular dichroism(CD) and circularly polarized luminescence(CPL) spectra. These chiroptical properties serve as direct indicators of the chiral supramolecular structure and hold promise for applications in sensing, molecular recognition, asymmetric synthesis, and material science. This review focuses on research published in the last five years, highlighting instances where assembled structures aggregated by small organic molecular modules demonstrate in-situ chiroptical changes through external condition control. It categorizes and discusses different modes of regulation, aiming to offer insights and guidelines for exploring dynamic changes in assembly processes and designing in-situ adjustable structures of assembly modules.

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Towards robustness and generalization of point cloud representation:A geometry coding method and a large-scale object-level dataset

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Computational Visual Media 2024年第1期10卷 27-43页

作者： Mingye Xu zhipeng Zhou Yali Wang Yu Qiao Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518000China University of Chinese Academy of Sciences Beijing065001China Shanghai AI Laboratory Shanghai200001China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen518000China Alibaba DAMO Academy Hangzhou242332China

Robustness and generalization are two challenging problems for learning point cloud representation.To tackle these problems,we first design a novel geometry coding model,which can effectively use an invariant eigengraph to group points with similar geometric information,even when such points are far from each other.We also introduce a large-scale point cloud dataset,PCNet184.It consists of 184 categories and 51,915 synthetic objects,which brings new challenges for point cloud classification,and provides a new benchmark to assess point cloud cross-domain generalization.Finally,we perform extensive experiments on point cloud classification,using ModelNet40,ScanObjectNN,and our PCNet184,and segmentation,using ShapeNetPart and S3DIS.Our method achieves comparable performance to state-of-the-art methods on these datasets,for both supervised and unsupervised learning.Code and our dataset are available at https://***/MingyeXu/PCNet184.

关键词： geometry coding self-supervised learning point cloud classification segmentation 3D analysis

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