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SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1717-1719页

作者： Jiufang Chen ye yuan xin luo the College of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065 the Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China the College of Computer and Information Science Southwest UniversityChongqing 400715China IEEE

Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.

关键词： representation preserving undirected

Dynamic motion of quadrupedal robots on challenging terrain:a kinodynamic optimization approach

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Frontiers of Mechanical Engineering 2024年第3期19卷 23-40页

作者： Qi LI Lei DIng xin luo Engineering Research Center of Hubei Province for Clothing Information Wuhan 430200China School of Computer Science and Artificial Intelligence Wuhan Textile UniversityWuhan 430200China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China

The dynamic motion of quadrupedal robots on challenging terrain generally requires elaborate spatial–temporal kinodynamic motion planning and accurate control at higher refresh rate in comparison with regular ***,conventional quadrupedal robots usually generate relatively coarse planning and employ motion replanning or reactive strategies to handle terrain *** resultant complex and computation-intensive controller may lead to nonoptimal motions or the breaking of locomotion *** this paper,a kinodynamic optimization approach is *** generate long-horizon optimal predictions of the kinematic and dynamic behavior of the quadruped robot on challenging terrain,we formulate motion planning as an optimization problem;jointly treat the foot’s locations,contact forces,and torso motions as decision variables;combine smooth motion and minimal energy consumption as the objective function;and explicitly represent feasible foothold region and friction constraints based on terrain *** track the generated motions accurately and stably,we employ a whole-body controller to compute reference position and velocity commands,which are fed forward to joint controllers of the robot’s *** verify the effectiveness of the developed approach through simulation and on a physical quadruped robot *** show that the quadruped robot can successfully traverse a 30°slope and 43% of nominal leg length high step while maintaining the rhythm of dynamic trot gait.

关键词： quadrupedal robot kinodynamic planning nonlinear optimization challenging terrain whole-body control

Microstructure evolution of Ti_(48)Zr_(27)Cu_(6)Nb_(5)Be_(14)amorphous alloy after semi-solid isothermal treatment

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China Foundry 2024年第3期21卷 287-294页

作者： xin-hua Huang Jing-wen Pu y.ng-xin luo yue-jun Ouy.ng School of Material Electricity and Intelligent ManufacturingHuaihua UniversityHuaihua 330031HunanChina Hunan Renewable Aluminum Innovation Research Center Huaihua UniversityHuaihua 330031HunanChina

The as-cast amorphous Ti_(48)Zr_(27)Cu_(6)Nb_(5)Be_(14)composites,comprising in situ formedβ-Ti ductile crystalline precipitates,were prepared by water cooled copper mold suction ***,the semi-solid composites were obtained after the as-cast composites were treated by semi-solid isothermal *** microstructure evolution and kinetics of the composites were *** show that the microstructures of both the as-cast and semi-solid composites comprise ofβ-Ti crystal phases and amorphous matrix *** and after treatment,the crystals evolve from fine granular or fine dendritic crystals to coarse *** the treatment temperature increasing or the time prolonging,the average crystal size gradually increases and the surface morphology of the crystals gradually becomes *** study.ng the microstructural evolution and dynamics during the isothermal treatment process,it is found that the final morphology ofβ-Ti crystals is influenced by the isothermal treatment temperature and time(t),and theβ-Ti evolution rate increases with an increase in treatment *** addition,a linear relationship was observed between the size of cubicβ-Ti crystals(D^(3))and t;the growth kinetics factor K is 3.8μm^(3)·s^(-1).As the K value closes to 4μm^(3)·s^(-1),it is inferred the morphology evolution ofβ-Ti crystals is a coarsening behavior controlled by the diffusion of solute elements.

关键词： Ti_(48)Zr_(27)Cu_(6)Nb_(5)Be_(14) amorphous matrix composites semi-solid as-cast microstructure

Quick Weighing of Passing Vehicles Using the Transfer-Learning-Enhanced Convolutional Neural Network

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2507-2524页

作者： Wangchen yan Jinbao y.ng xin luo College of Civil Engineering Xiangtan UniversityXiangtan411105China Energy&Environmental Engineering Department China CEC Engineering CorporationChangsha410114China

Transfer learning could reduce the time and resources required by the training of new models and be therefore important for generalized applications of the trainedmachine learning *** this study,a transfer learningenhanced convolutional neural network(CNN)was proposed to identify the gross weight and the axle weight of moving vehicles on the *** proposed transfer learning-enhanced CNN model was expected to weigh different bridges based on a small amount of training datasets and provide high identification *** of all,a CNN algorithm for bridge weigh-in-motion(B-WIM)technology was proposed to identify the axle weight and the gross weight of the typical two-axle,three-axle,and five-axle vehicles as they crossed the bridge with different loading routes and ***,the pre-trained CNN model was transferred by fine-tuning to weigh themoving vehicle on another ***,the identification accuracy and the amount of training data required were compared between the two CNN *** showed that the pre-trained CNN model using transfer learning for B-WIM technology could be successfully used for the identification of the axle weight and the gross weight for moving vehicles on another bridge while reducing the training data by 63%.Moreover,the recognition accuracy of the pre-trained CNN model using transfer learning was comparable to that of the original model,showing its promising potentials in the actual applications.

关键词： Bridge weigh-in-motion transfer learning convolutional neural network

Long-term Evolution of Solar Activity and Prediction of the Following Solar Cycles

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Research in Astronomy and Astrophysics 2024年第3期24卷 194-204页

作者： Pei-xin luo Bao-Lin Tan National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 100049China

Solar activities have a great impact on modern high-tech systems,such as human aerospace activities,satellite communication and navigation,deep space exploration,and related scientific ***,study.ng the long-term evolution trend of solar activity and accurately predicting the future solar cycles are highly *** on the wavelet transform and empirical function fitting of the longest recorded data of the annual average relative sunspot number(ASN)series of 323 yr to date,this work decisively verifies the existence of the solar century cycles and confirms that its length is about 104.0 yr,and the magnitude has a slightly increasing trend on the timescale of several hundred *** on this long-term evolutionary trend,we predict solar cycles 25 and26 by using phase similar prediction *** for solar cycle 25,its maximum ASN will be about146.7±33.40,obviously stronger than solar cycle *** peak year will occur approximately in 2024,and the period will be about 11±1 *** for solar cycle 26,it will start around 2030,and reach its maximum between2035 and 2036,with maximum ASN of about 133.0±3.200,and period of about 10 yr.

关键词： Sun activity-Sun evolution-(Sun) sunspots-methods data analysis

Generalized Embedding Machines for Recommender Systems

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Machine Intelligence Research 2024年第3期21卷 571-584页

作者： Enneng y.ng xin xin Li Shen yudong luo Guibing Guo Software College Northeastern UniversityShenyang110000China School of Computer Science and Technology Shandong UniversityQingdao266000China JD Explore Academy JD Explore AcademyBeijing100000China

Factorization machine (FM) is an effective model for feature-based recommendation that utilizes inner products to capture second-order feature interactions. However, one of the major drawbacks of FM is that it cannot capture complex high-order interaction signals. A common solution is to change the interaction function, such as stacking deep neural networks on the top level of FM. In this work, we propose an alternative approach to model high-order interaction signals at the embedding level, namely generalized embedding machine (GEM). The embedding used in GEM encodes not only the information from the feature itself but also the information from other correlated features. Under such a situation, the embedding becomes high-order. Then we can incorporate GEM with FM and even its advanced variants to perform feature interactions. More specifically, in this paper, we utilize graph convolution networks (GCN) to generate high-order embeddings. We integrate GEM with several FM-based models and conduct extensive experiments on two real-world datasets. The results demonstrate significant improvement of GEM over the corresponding baselines.

关键词： Feature interactions high-order interaction factorization machine(FM) recommender system graph neural network(GNN)

A Novel Tensor Decomposition-Based Efficient Detector for Low-Altitude Aerial Objects With Knowledge Distillation Scheme

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 487-501页

作者： Nianyin Zeng xinyu Li Peishu Wu Han Li xin luo Department of Instrumental and Electrical Engineering Xiamen UniversityXiamen 361005China IEEE College of Computer and Information Science Southwest UniversityChongqing 400715China

Unmanned aerial vehicles(UAVs) have gained significant attention in practical applications, especially the low-altitude aerial(LAA) object detection imposes stringent requirements on recognition accuracy and computational resources. In this paper, the LAA images-oriented tensor decomposition and knowledge distillation-based network(TDKD-Net) is proposed,where the TT-format TD(tensor decomposition) and equalweighted response-based KD(knowledge distillation) methods are designed to minimize redundant parameters while ensuring comparable performance. Moreover, some robust network structures are developed, including the small object detection head and the dual-domain attention mechanism, which enable the model to leverage the learned knowledge from small-scale targets and selectively focus on salient features. Considering the imbalance of bounding box regression samples and the inaccuracy of regression geometric factors, the focal and efficient IoU(intersection of union) loss with optimal transport assignment(F-EIoU-OTA)mechanism is proposed to improve the detection accuracy. The proposed TDKD-Net is comprehensively evaluated through extensive experiments, and the results have demonstrated the effectiveness and superiority of the developed methods in comparison to other advanced detection algorithms, which also present high generalization and strong robustness. As a resource-efficient precise network, the complex detection of small and occluded LAA objects is also well addressed by TDKD-Net, which provides useful insights on handling imbalanced issues and realizing domain adaptation.

关键词： Attention mechanism knowledge distillation(KD) object detection tensor decomposition(TD) unmanned aerial vehicles(UAVs)

Jurassic integrative stratigraphy,biotas,and paleogeographical evolution of the Qinghai-Tibetan Plateau and its surrounding areas

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Science China Earth Sciences 2024年第4期67卷 1195-1228页

作者： Jianguo LI xin RAO Lin MU Xiaohui CUI xin LI Hui luo Peixue LIU Center for Excellence in Life and Paleoenvironment Nanjing Institute of Geology and PalaeontologyChinese Academy of SciencesNanjing 210008China Nanjing College University of Chinese Academy of SciencesNanjing 211135China

The Qinghai-Tibetan Plateau experienced a unique geological evolution during the Jurassic,driven by the termination of the Palaeotethys and the reduction of the *** Indian Plate separated from the northern margin of Gondwana and drifted northward from the Southern *** that the timing of strata serves as the basis for reconstructing geological history,the present work aimed to develop a new multiple stratigraphic and chronologic framework for the Jurassic strata of the Qinghai-Tibetan Plateau region via a synthesis of the material on lithostratigraphy,palaeontology,iso-radiometric dating,magnetostratigraphy,and other techniques with an emphasis on recent progress and *** new framework included the Jurassic System from the four major subdivisions of the plateau:the Baryan Har,Qiangtang,Lhasa-Gandise,and Southern Xizang(Himalaya).Ultimately,a more complete,refined biostratigraphic sequence was proposed,comprising the most common fossils in the plateau and those that are stratigraphically significant for the Jurassic stratigraphy,including ammonites,bivalves,brachiopods,foraminifera,radiolarians,and dinoflagellate cysts for the marine strata,and pollen and spores,and charophytes for the terrestrial *** biostratigraphic framework was correlated with the Jurassic international standard zonation of the Geological Time Scale 2020 via standard or representative species or genera of *** on this framework,we constructed a lateral correlation of the Jurassic strata between different basins of the *** palaeontologic correlation in the present work shows that the Lhasa-Gandise Block had a closer relationship with the Qiangtang Block than with the Southern Xizang Himalaya during the Jurassic ***,the Lhasa-Gandise Block and Qiangtang Block shared similar marine fauna features of the north marginal East *** contrasts the opinion suggesting that the yarlung Zangbo Tethys was a small back-arc basin.A c

关键词： Biostratigraphy Chronostratigraphy Correlation yarlung Zangbo suture Bangong Co-Nujiang suture Tethys

Superexchange and charge transfer in the nickelate superconductor La3Ni2O7 under pressure

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Science China(Physics,Mechanics & Astronomy) 2024年第11期Mechanics & Astronomy) .卷 5-12页

作者： Wéi Wú Zhihui luo Dao-xin yao Meng Wang Center for Neutron Science and Technology Guangdong Provincial Key Laboratory of Magnetoelectric Physics and DevicesSchool of Physics Sun Yat-sen University

Recently, a bulk nickelate superconductor La3Ni2O7is discovered at pressures with a remarkable high transition temperature Tc～ 80 K. Here, we study a Hubbard model with tight-binding parameters derived from ab initio calculations of La3Ni2O7,by employ.ng large scale determinant quantum Monte Carlo and cellular dynamical mean-field theory. Our result suggests that the superexchange couplings in this system are comparable to that of cuprates. The system is a charge transfer insulator as the hole concentration becomes four per site at large Hubbard U. Upon hole doping, two low-energy spin-singlet bands emerge in the system exhibiting distinct correlation properties: while the one composed of the out-of-plane Ni-d3z2-r2and O-pzorbitals demonstrates strong antiferromagnetic correlations and narrow effective bandwidth, the in-plane singlet band consisting of the Ni-dx2-y2and O-px/pyorbitals is in general more itinerant. Over a broad range of hole doping, the doped holes occupy primarily the dx2-y2and px/pyorbitals, whereas the d3z2-r2and pzorbitals retain underdoped. We propose an effective t-J model to capture the relevant physics and discuss the implications of our result for comprehending the La3Ni2O7superconductivity.

关键词： superconductivity nickelate superconductors Hubbard model superexchange charge transfer insulator quantum Monte Carlo