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Subway Embedded Track Geometric Irregularity Safety Limits

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 322-331页

作者： yuxiang zhang Jian Han Huilai Song Yu Liu School of Economics and Management Southwest Jiaotong UniversityChengdu 610031China School of Mechanical Engineering Southwest Jiaotong UniversityChengdu 610031China School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China

A coupling dynamic model of a subway train and an embedded track is established to study the safety limits of track *** simulated vehicle system was a 74-degrees of freedom multi-rigid body model,and the rail was a Timoshenko *** slab was a three-dimensional solid finite element *** sensitive wavelength irregularity was first studied,and then the safety limit of the sensitive wavelength was *** wheel-rail lateral force exhibited a substantial effect on the track alignment and gauge irregularity safety *** wheel-rail vertical force and the rate of wheel load reduction significantly affected the height and cross-level irregularity safety *** results demonstrate that the safety limits of the alignment,gauge,height,and cross-level embedded track geometric irregularity are 5.3 mm,[−10.5,8]mm,5.6 mm,and 6 mm,respectively.

关键词： Embedded track Irregularity Sensitive wavelength Safety limit

Implementation Framework and Validation of Cluster-Nuclei Based Channel Model Using Environmental Mapping for 6G Communication Systems

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China Communications 2022年第4期19卷 1-13页

作者： Li Yu yuxiang zhang Jianhua zhang Zhiqiang Yuan State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel modeling. Considering channel model is prerequisite for system design and performance evaluation of 6 G technologies, we face a challenging task: how to accurately and efficiently model 6 G channel for various scenarios? This paper tries to answer it. Firstly, the features of cluster-nuclei(CN) and principle of cluster-nuclei based channel model(CNCM) are introduced. Then, a novel modeling framework is proposed to implement CNCM,which consists four steps: propagation environment reconstruction, cluster-nuclei identification, multipath parameters generation, and channel coefficients generation. Three-dimensional environment with material information is utilized to map CN with scatterers in the propagation pathway. CN are identified by geometrical and electric field calculation based on environmental mapping, and multipath components within CN are calculated by statistical characteristics of angle, power and delay domains. Finally, we present a three-level verification structure to investigate the accuracy and complexity of channel modeling comprehensively. Simulation results reveal that CNCM can perform higher accuracy than geometrybased stochastic model while lower complexity compared with ray-tracing model for practical propagation environment.

关键词： channel model 6G cluster-nuclei environmental mapping scatterer ray-tracing geometrybased stochastic model

Prior-guided GAN-based interactive airplane engine damage image augmentation method

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Chinese Journal of Aeronautics 2022年第10期35卷 222-232页

作者： Rui HUANG Bokun DUAN yuxiang zhang Wei FAN School of Computer Science and Technology Civil Aviation University of ChinaTianjin 300300China

Deep learning-based methods have achieved remarkable success in object detection,but this success requires the availability of a large number of training *** sufficient training images is difficult in detecting damages of airplane *** augmenting images by rotation,flipping,and random cropping cannot further improve the generalization ability of existing deep *** propose an interactive augmentation method for airplane engine damage images using a prior-guided GAN to augment training *** method can generate many types of damages on arbitrary image regions according to the strokes of *** proposed model consists of a prior network and a *** Prior network generates a shape prior vector,which is used to encode the information of user *** GAN takes the shape prior vector and random noise vectors to generate candidate *** damages are pasted on the given positions of background images with an improved Poisson *** compare the proposed method with traditional data augmentation methods by training airplane engine damage detectors with state-ofthe-art object detectors,namely,Mask R-CNN,SSD,and YOLO *** results show that training with images generated by our proposed data augmentation method achieves a better detection performance than that by traditional data augmentation methods.

关键词： Airplane engine Damage detection Data augmentation GAN Interactive

Incremental learning of the triangular membership functions based on single-pass FCM and CHC genetic model

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High Technology Letters 2017年第1期23卷 7-15页

作者：霍纬纲 Qu Feng zhang yuxiang Department of Computer Science and Technology Civil Aviation University of ChinaTianjin 300300P.R.China

In order to improve the efficiency of learning the triangular membership functions( TMFs) for mining fuzzy association rule( FAR) in dynamic database,a single-pass fuzzy c means( SPFCM)algorithm is combined with the real-coded CHC genetic model to incrementally learn the TMFs. The cluster centers resulting from SPFCM are regarded as the midpoint of TMFs. The population of CHC is generated randomly according to the cluster center and constraint conditions among TMFs. Then a new population for incremental learning is composed of the excellent chromosomes stored in the first genetic process and the chromosomes generated based on the cluster center adjusted by SPFCM. The experiments on real datasets show that the number of generations converging to the solution of the proposed approach is less than that of the existing batch learning approach. The quality of TMFs generated by the approach is comparable to that of the batch learning approach. Compared with the existing incremental learning strategy,the proposed approach is superior in terms of the quality of TMFs and time cost.

关键词： incremental learning triangular membership function ( TMFs) fuzzy associationrule (FAR) real-coded CHC

Latest progress for 3GPP ISAC channel modeling standardization

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Science China(Information Sciences) 2024年第11期67卷 357-358页

作者： yuxiang zhang Jianhua zhang Yuanpeng PEI Yameng LIU Tao JIANG State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Future Research Laboratory China Mobile Research Institute

Integrated sensing and communication(ISAC) is regarded as a promising technology for sixth-generation(6G) *** channel modeling is essential for designing and evaluating the performance of ISAC systems. In December 2023, the 3rd Generation Partnership Project(3GPP)established a new industry specification group dedicated to ISAC. The group's objective is to research ISAC channel modeling, laying the technical foundations for 6G standardization. Compared to the traditional 5G communication channel, 6G ISAC channel requires accurate modeling of new properties.

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Geological,physical,and chemical characteristics of seafloor hydrothermal vent fields

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Journal of Oceanology and Limnology 2020年第4期38卷 985-1007页

作者： ZENG Zhigang CHEN Zuxing zhang yuxiang LI Xiaohui Seafloor Hydrothermal Activity Laboratory CAS Key Laboratory of Marine Geology and EnvironmentInstitute of OceanologyChinese Academy of SciencesQingdao 266071China Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and TechnologyQingdao 266061China University of Chinese Academy of Sciences Beijing 100049China Center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China

Seafloor hydrothermal vent fields(SHVFs) are located in the mid-ocean ridge(MOR),backarc basin(BAB),island arc and hot-spot environments and hosted mainly by ultramafic,mafic,felsic rocks,and *** hydrothermal vent fluids of SHVFs have low oxygen,abnormal pH and temperature,numerous toxic compounds,and inorganic energy sources,such as sulfuric compounds,methane,and *** geological,physical,and chemical characteristics of SHVFs provide important clues to understanding the formation and evolution of seafloor hydrothermal systems,leading to the determination of metal sources and the reconstruction of the physicochemical conditions of *** the past two decades,we studied the geological settings,volcanic rocks,and hydrothermal products of SHVFs and drawn new conclusions in these areas,including:1) the hydrothermal plumes in the Okinawa Trough are affected by the Kuroshio current;2) S and Pb in the hydrothermal sulfides from MOR are mainly derived from their host igneous rocks;3) Re and Os of vent fluids are more likely to be incorporated into Fe-and Fe-Cu sulfide mineral facies,and Os is enriched under low-temperature(<200℃) hydrothermal conditions in global SHVFs;4) compared with low-temperature hydrothermal sulfides,sulfates,and opal minerals,high-temperature hydrothermal sulfides maintain the helium(He) isotopic composition of the primary vent fluid;5) relatively low temperature(<116℃),oxygenated,and acidic environment conditions are favorable for forming a native sulfur chimney,and a "glue pudding" growth model can be used to understand the origin of native sulfur balls in the Kueishantao hydrothermal field;and 6) boron isotope from hydrothermal plumes and fluids can be used to describe their diffusive *** monitoring and understanding of the physical structure,chemical composition,geological processes,and diverse organism of subseafloor hydrothermal systems will be a future hot spot and frontier of submarine hydrothermal geol

关键词： vent fields hydrothermal products volcanic rocks vent organisms seafloor hydrothermal systems

Mastering lanthanide energy states for next-gen photonic innovation

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Science China Chemistry 2023年第9期66卷 2460-2479页

作者： Yuyang Gu Chang Gu yuxiang zhang Zhen Mu Xiaogang Liu Department of Chemistry National University of SingaporeSingapore 117543Singapore Institute of Materials Research and Engineering Agency for ScienceTechnology and ResearchSingapore 138634Singapore

Lanthanide-based photonic materials have been extensively explored for use in laser crystals,lighting,fiber-optic communications,bioimaging,diagnostics,and many other *** recent years,they have enabled numerous breakthroughs in areas such as single-particle spectroscopy,super-resolution imaging,micro-lasing,lifetime multiplexing,and ***,we summarize recent advances in lanthanide photonic materials from an energy state perspective,focusing on the interplay between energy state manipulation and advanced photonic *** then discuss the challenges and prospects for controlling energy states at the single-particle *** wish to highlight the importance of quantifying and understanding the energy states of lanthanides for future innovations.

关键词： lanthanide nanomaterials super-resolution lifetime lasing

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Environment Information-Based Channel Prediction Method Assisted by Graph Neural Network

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China Communications 2022年第11期19卷 1-15页

作者： Yutong Sun Jianhua zhang yuxiang zhang Li Yu Qixing Wang Guangyi Liu State Key Lab of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Future Research Laboratory China Mobile Research InstituteBeijing 100053China

Recently,whether the channel prediction can be achieved in diverse communication scenarios by directly utilizing the environment information gained lots of attention due to the environment impacting the propagation characteristics of the wireless *** paper presents an environment information-based channel prediction(EICP)method for connecting the environment with the channel assisted by the graph neural networks(GNN).Firstly,the effective scatterers(ESs)producing paths and the primary scatterers(PSs)generating single propagation paths are detected by building the scatterercentered communication environment graphs(SCCEGs),which can simultaneously preserve the structure information and highlight the pending *** GNN-based classification model is implemented to distinguish ESs and PSs from other ***,large-scale parameters(LSP)and small-scale parameters(SSP)are predicted by employing the GNNs with multi-target architecture and the graphs of detected ESs and *** results show that the average normalized mean squared error(NMSE)of LSP and SSP predictions are 0.12 and 0.008,which outperforms the methods of linear data learning.

关键词： channel prediction propagation environment graph scatterer detection GNN

The Way to Apply Machine Learning to IoT Driven Wireless Network from Channel Perspective

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China Communications 2019年第1期16卷 148-164页

作者： Wei Li Jianhua zhang Xiaochuan Ma yuxiang zhang Hua Huang Yongmei Cheng Northwestern Polytechnical University State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communications Beijing University of Posts and Telecommunications Huawei Technologies Co. Ltd.

Internet of Things(IoT) is one of the targeted application scenarios of fifth generation(5 G) wireless *** brings a large amount of data transported on the *** those data,machine learning(ML) algorithms can be naturally utilized to make network efficiently and ***,how to fully apply ML to IoT driven wireless network is still *** fundamental reason is that wireless communication pursuits the high capacity and quality facing the challenges from the varying and fading wireless *** in this paper,we explore feasible combination for ML and IoT driven wireless network from wireless channel ***,a three-level structure of wireless channel fading features is defined in order to classify the versatile propagation *** three-layer structure includes scenario,meter and wavelength *** on this structure,there are different tasks like service prediction and pushing,self-organization networking,self adapting largescale fading modeling and so on,which can be abstracted into problems like regression,classification,clustering,***,we introduce corresponding ML methods to different levelsfrom channel perspective,which makes their interdisciplinary research promisingly.

关键词： 5G Internet of Things machine learning wireless channel