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Traffic-Aware Fuzzy Classification Model to Perform IoT Data Traffic Sourcing with the Edge Computing

Computers, Materials & Continua 2024年第2期78卷 2309-2335页

作者： Huixiang xu College of Information Engineering Zhengzhou University of TechnologyZhengzhou450044China

The Internet of Things(IoT)has revolutionized how we interact with and gather data from our surrounding environment.IoT devices with various sensors and actuators generate vast amounts of data that can be harnessed to derive valuable insights.The rapid proliferation of Internet of Things(IoT)devices has ushered in an era of unprecedented data generation and connectivity.These IoT devices,equipped with many sensors and actuators,continuously produce vast volumes of data.However,the conventional approach of transmitting all this data to centralized cloud infrastructures for processing and analysis poses significant challenges.However,transmitting all this data to a centralized cloud infrastructure for processing and analysis can be inefficient and impractical due to bandwidth limitations,network latency,and scalability issues.This paper proposed a Self-Learning Internet Traffic Fuzzy Classifier(SLItFC)for traffic data analysis.The proposed techniques effectively utilize clustering and classification procedures to improve classification accuracy in analyzing network traffic data.SLItFC addresses the intricate task of efficiently managing and analyzing IoT data traffic at the edge.It employs a sophisticated combination of fuzzy clustering and self-learning techniques,allowing it to adapt and improve its classification accuracy over time.This adaptability is a crucial feature,given the dynamic nature of IoT environments where data patterns and traffic characteristics can evolve rapidly.With the implementation of the fuzzy classifier,the accuracy of the clustering process is improvised with the reduction of the computational time.SLItFC can reduce computational time while maintaining high classification accuracy.This efficiency is paramount in edge computing,where resource constraints demand streamlined data processing.Additionally,SLItFC’s performance advantages make it a compelling choice for organizations seeking to harness the potential of IoT data for real-time insights and decision-making.With the Self-Learning p

关键词： Internet of Things(IoT) edge computing traffic data self-learning fuzzy-learning

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A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction

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Machine Intelligence Research 2024年第1期21卷 153-168页

作者： Zefa Hu Ziyi Ni Jing Shi Shuang xu Bo xu School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Institute of Automation Chinese Academy of SciencesBeijing 100190China

This paper focuses on term-status pair extraction from medical dialogues(MD-TSPE),which is essential in diagnosis dia-logue systems and the automatic scribe of electronic medical records(EMRs).In the past few years,works on MD-TSPE have attracted increasing research attention,especially after the remarkable progress made by generative methods.However,these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge,which demands a deeper un-derstanding to model the relationship between terms and infer the status of each term.This paper presents a knowledge-enhanced two-stage generative framework(KTGF)to address the above challenges.Using task-specific prompts,we employ a single model to com-plete the MD-TSPE through two phases in a unified generative form:We generate all terms the first and then generate the status of each generated term.In this way,the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase,and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status generation.Furthermore,our proposed special status"not mentioned"makes more terms available and en-riches the training data in the second phase,which is critical in the low-resource setting.The experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-re-sourcesettings.

关键词： Medical dialogue understanding information extraction text generation knowledge-enhanced prompt low-resource setting dataaugmentation

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ARPES investigation of the electronic structure and its evolution in magnetic topological insulator MnBi2+2nTe4+3n family

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National Science Review 2024年第2期11卷 81-93页

作者： Runzhe xu Lixuan xu Zhongkai Liu Lexian Yang Yulin Chen State Key Laboratory of Low Dimensional Quantum Physics Department of PhysicsTsinghua University School of Physical Science and Technology Shanghai Tech University and CAS-Shanghai Science Research Center Shanghai Tech Laboratory for Topological Physics Frontier Science Center for Quantum Information Collaborative Innovation Center of Quantum Matter Department of Physics Clarendon LaboratoryUniversity of Oxford

In the past 5 years,there has been significant research interest in the intrinsic magnetic topological insulator family compounds MnBi2+2nTe4+3n（where n=0,1,2…）.In particular,exfoliated thin films of MnBi2Te4have led to numerous experimental breakthroughs,such as the quantum anomalous Hall effect,axion insulator phase and high-Chern number quantum Hall effect without Landau levels.However,despite extensive efforts,the energy gap of the topological surface states due to exchange magnetic coupling,which is a key feature of the characteristic band structure of the system,remains experimentally elusive.The electronic structure measured by using angle-resolved photoemission （ARPES） shows significant deviation from ab initio prediction and scanning tunneling spectroscopy measurements,making it challenging to understand the transport results based on the electronic structure.This paper reviews the measurements of the band structure of MnBi2+2nTe4+3nmagnetic topological insulators using ARPES,focusing on the evolution of their electronic structures with temperature,surface and bulk doping and film thickness.The aim of the review is to construct a unified picture of the electronic structure of MnBi2+2nTe4+3ncompounds and explore possible control of their topological properties.

关键词： magnetic topological insulator MnBi2Te4 electronic structure angle-resolved photoemission spectroscopy

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Coupling effect on the thermal hazard assessment of hazardous chemical materials via calorimetric technologies and simulation approaches

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Defence Technology（防务技术） 2024年第2期32卷 644-654页

作者： Yabei xu Jiankun Shao Wei Wang Shengliang xu Dongping Chen State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing 100081China Science and Technology on Aerospace Chemical Power Laboratory Hubei Institute of Aerospace ChemotechnologyXiangyang 441003China

The coupling effect of heat absorption and release exists in the thermal decomposition of a few chemical materials.However,the impact of the above coupling on thermal hazard assessment is not considered in the literature studies.In this work,nitroguanidine(NQ)and 1,3,5-trinitro-1,3,5-triazine(RDX)are selected as representative materials to explore the influence of the coupling effect on the thermal hazard assessment of chemical materials.The linear heating experiments of NQ and RDX are carried out by a microcalorimeter and synchronous thermal analyser.The thermal decomposition curves are decoupled by advanced thermokinetics software.The thermal decomposition and kinetic parameters before and after decoupling are calculated.The results of TG experiment show that both NQ and RDX began to lose mass during the endothermic stage.The endothermic melting and exothermic decomposition of NQ and RDX are coupled within this stage.The coupling effect has different degrees of influence on its initial decomposition temperature and safety parameters.Compared with the parameters in the coupling state,the initial decomposition temperature and adiabatic induction period after decoupling decrease.The self-accelerating decomposition temperature increases,and internal thermal runaway time decreases.In the thermal hazard assessment of chemical materials with coupling effects,the calculated parameters after decoupling should be taken as an important safety index。

关键词： Calorimetric technologies Kinetics Thermal hazard Phase transformation Thermal decomposition

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Tunable quantum anomalous Hall effects in ferromagnetic van der Waals heterostructures

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National Science Review 2024年第3期11卷 100-107页

作者： Feng xue Yusheng Hou Zhe Wang Zhiming xu Ke He Ruqian Wu Yong xu Wenhui Duan Beijing Academy of Quantum Information Sciences State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices Center for Neutron Science and Technology School of Physics Sun Yat-sen University State Key Laboratory of Surface Physics Key Laboratory of Computational Physical Sciences and Department of PhysicsFudan University Frontier Science Center for Quantum Information Department of Physics and Astronomy University of California-Irvine Tencent Quantum Laboratory Tencent Technology(Shenzhen)Co.Ltd RIKEN Center for Emergent Matter Science(CEMS) Institute for Advanced Study Tsinghua University

The quantum anomalous Hall effect（QAHE） has unique advantages in topotronic applications, but it is still challenging to realize the QAHE with tunable magnetic and topological properties for building functional devices. Through systematic first-principles calculations, we predict that the in-plane magnetization induced QAHE with Chern numbers C = ±1 and the out-of-plane magnetization induced QAHE with high Chern numbers C = ±3 can be realized in a single material candidate, which is composed of van der Waals（vdW）coupled Bi and MnBi2Te4monolayers. The switching between different phases of QAHE can be controlled in multiple ways, such as applying strain or（weak） magnetic field or twisting the vdW materials. The prediction of an experimentally available material system hosting robust, highly tunable QAHE will stimulate great research interest in the field. Our work opens a new avenue for the realization of tunable QAHE and provides a practical material platform for the development of topological electronics.

关键词： quantum anomalous Hall effect topological quantum phase transition van der Waals heterostructures tunable Chern number high Chern number

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Gluing Affine Vortices

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Acta Mathematica Sinica,English Series 2024年第1期40卷 250-312页

作者： Guang Bo xu Department of Mathematics Rutgers UniversityHill Center-Busch Campus 110 Frelinghuysen RoadPiscatawayNJ 08854-8019USA

We provide an analytical construction of the gluing map for stable affine vortices over the upper half plane with the Lagrangian boundary condition.This result is a necessary ingredient in studies of the relation betw... 详细信息

关键词： Affine vortices gauged linear sigma model adiabatic limit symplectic reduction

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Image Recognition Model of Fraudulent Websites Based on Image Leader Decision and Inception-V3 Transfer Learning

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China Communications 2024年第1期21卷 215-227页

作者： Shengli Zhou Cheng xu Rui xu Weijie Ding Chao Chen Xiaoyang xu Information Department of Zhejiang Police College Hangzhou 310053China Hangzhou Dianzi University Hangzhou 310018China Big Data Laboratory of Zhejiang Police College Hangzhou 310053China Hangzhou Public Security Bureau Hangzhou 310002China

The fraudulent website image is a vital information carrier for telecom fraud.The efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent websites.Current research on image recognition of fraudulent websites is mainly carried out at the level of image feature extraction and similarity study,which have such disadvantages as difficulty in obtaining image data,insufficient image analysis,and single identification types.This study develops a model based on the entropy method for image leader decision and Inception-v3 transfer learning to address these disadvantages.The data processing part of the model uses a breadth search crawler to capture the image data.Then,the information in the images is evaluated with the entropy method,image weights are assigned,and the image leader is selected.In model training and prediction,the transfer learning of the Inception-v3 model is introduced into image recognition of fraudulent websites.Using selected image leaders to train the model,multiple types of fraudulent websites are identified with high accuracy.The experiment proves that this model has a superior accuracy in recognizing images on fraudulent websites compared to other current models.

关键词： fraudulent website image leaders telecom fraud transfer learning

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Translation machinery: the basis of translational control

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Journal of Genetics and Genomics 2024年第4期51卷 367-378页

作者： Shu Yuan Guilong Zhou Guoyong xu State Key Laboratory of Hybrid Rice Institute for Advanced Studies(IAS)Wuhan UniversityWuhanHubei 430072China Hubei Hongshan Laboratory WuhanHubei 430070China

Messenger RNA(mRNA)translation consists of initiation,elongation,termination,and ribosome recycling,carried out by the translation machinery,primarily including tRNAs,ribosomes,and translation factors(TrFs).Translational regulators transduce signals of growth and development,as well as biotic and abiotic stresses,to the translation machinery,where global or selective translational control occurs to modulate mRNA translation efficiency(TrE).As the basis of translational control,the translation machinery directly determines the quality and quantity of newly synthesized peptides and,ultimately,the cellular adaption.Thus,regulating the availability of diverse machinery components is reviewed as the central strategy of translational control.We provide classical signaling pathways(e.g.,integrated stress responses)and cellular behaviors(e.g.,liquideliquid phase separation)to exemplify this strategy within different physiological contexts,particularly during hostemicrobe interactions.With new technologies developed,further understanding this strategy will speed up translational medicine and translational agriculture.

关键词： Translational control Ribosome tRNA Translation machinery uORF Phase separation Immune response

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The pathogenic mechanism of TAR DNA-binding protein 43(TDP-43)in amyotrophic lateral sclerosis

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Neural Regeneration Research 2024年第4期19卷 800-806页

作者： Xinxin Wang Yushu Hu Renshi xu Medical College of Nanchang University Department of Neurology Jiangxi Provincial People's HospitalThe First Affiliated Hospital of Nanchang Medical CollegeThe Clinical College of Nanchang Medical College

The onset of amyotrophic lateral sclerosis is usually characterized by focal death of both upper and/or lower motor neurons occurring in the motor cortex,basal ganglia,brainstem,and spinal cord,and commonly involves the muscles of the upper and/or lower extremities,and the muscles of the bulbar and/or respiratory regions.However,as the disease progresses,it affects the adjacent body regions,leading to generalized muscle weakness,occasionally along with memory,cognitive,behavioral,and language impairments;respiratory dysfunction occurs at the final stage of the disease.The disease has a complicated pathophysiology and currently,only riluzole,edaravone,and phenylbutyrate/taurursodiol are licensed to treat amyotrophic lateral sclerosis in many industrialized countries.The TAR DNA-binding protein 43 inclusions are observed in 97%of those diagnosed with amyotrophic lateral sclerosis.This review provides a preliminary overview of the potential effects of TAR DNAbinding protein 43 in the pathogenesis of amyotrophic lateral sclerosis,including the abnormalities in nucleoplasmic transport,RNA function,post-translational modification,liquid-liquid phase separation,stress granules,mitochondrial dysfunction,oxidative stress,axonal transport,protein quality control system,and non-cellular autonomous functions(e.g.,glial cell functions and prion-like propagation).

关键词： amyotrophic lateral sclerosis axonal transport liquid-liquid phase separation noncellular autonomous functions oxidative stress pathogenesis post-translational modification protein quality control system stress granules TAR DNA-binding protein 43(TDP-43)

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Discovery of Partial Differential Equations from Highly Noisy and Sparse Data with Physics-Informed Information Criterion

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Research 2024年第1期2023卷 247-259页

作者： Hao xu Junsheng Zeng Dongxiao Zhang BIC-ESAT EREand SKLTCSCollege of EngineeringPeking UniversityBeijing 100871P.R.China Institute of Applied Physics and Computational Mathematics Beijing 100088P.R.China Eastern Institute for Advanced Study Eastern Institute of TechnologyNingbo 315200ZhejiangP.R.China National Center for Applied Mathematics Shenzhen(NCAMS) Southern University of Science and TechnologyShenzhen 518055GuangdongP.R.China Department of Mathematics and Theories Peng Cheng LaboratoryShenzhen 518000GuangdongP.R.China

Data-driven discovery of partial differential equations(PDEs)has recently made tremendous progress,and many canonical PDEs have been discovered successfully for proof of concept.However,determining the most proper PDE without prior references remains challenging in terms of practical applications.In this work,a physics-informed information criterion(PIC)is proposed to measure the parsimony and precision of the discovered PDE synthetically.The proposed PIC achieves satisfactory robustness to highly noisy and sparse data on 7 canonical PDEs from different physical scenes,which confirms its ability to handle difficult situations.The PIC is also employed to discover unrevealed macroscale governing equations from microscopic simulation data in an actual physical scene.The results show that the discovered macroscale PDE is precise and parsimonious and satisfies underlying symmetries,which facilitates understanding and simulation of the physical process.The proposition of the PIC enables practical applications of PDE discovery in discovering unrevealed governing equations in broader physical scenes.

关键词： process canonical proof

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