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29th International Conference on Computational Linguistics, COLING 2022

作者： Wang, Mengru Zheng, Jianming Cai, Fei Shao, Taihua Chen, Honghui Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology China

Few-shot relation extraction aims to identify the relation type between entities in a given text in the low-resource scenario. Albeit much progress, existing meta-learning methods still fall into prediction confusions owing to the limited inference ability over shallow text features. To relieve these confusions, this paper proposes a discriminative rule-based knowledge (DRK) method. Specifically, DRK adopts a logic-aware inference module to ease the word-overlap confusion, which introduces a logic rule to constrain the inference process, thereby avoiding the adverse effect of shallow text features. Also, DRK employs a discrimination finding module to alleviate the entity-type confusion, which explores distinguishable text features via a hierarchical contrastive learning. We conduct extensive experiments on four types of meta tasks and the results show promising improvements from DRK (6.0% accuracy gains on average). Besides, error analyses reveal the word-overlap and entity-type errors are the main courses of mispredictions in few-shot relation extraction. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Extraction

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Building an autonomous driving platform based on ROS and its safety analysis 9

Building an autonomous driving platform based on ROS and its...

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9th IEEE International Conference on Data science in Cyberspace, DSC 2024

作者： Wei, Zelin Chen, Qiwei Weng, Rui National University of Defense Technology National Key Laboratory of Information Systems Engineering Changsha China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China

ISBN: (纸本)9798350391367

In the new wave of technological development, autonomous driving technologies have become the top priority of the innovation of future transportation. Although many technologies are involved in autonomous driving, it is an autonomous mobile robot in essence, mainly including three parts: perception, positioning, and decision-making. Ensuring its security is one key challenge to realize its widespread applications. Therefore, it is necessary to systematically consider security issues of autonomous driving from the sensor level, the autonomous driving system level, and the underlying communication protocol level. In this thesis, we built an automatic driving platform on the ROS system based on the existing hardware infrastructure - - SiLaR, a landrover of the Simplexity Lab. Furthermore, we analyzed security issues of each module of SiLaR. Especially in the process of map construction, due to the limitation of the working principle of LiDAR, some specular reflective materials in the operating environment will interfere with the construction. We also used the sensor cross fusion to calibrate the environmental information through the depth camera during the composition process to ensure the accuracy of map construction. © 2024 IEEE.

关键词： autonomous driving ROS security SLAM

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Parallelism or Fairness? How to Be Friendly for SSDs in Cloud Environments

Parallelism or Fairness? How to Be Friendly for SSDs in Clou...

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2024 IEEE International Conference on Cluster Computing, CLUSTER 2024

作者： Zhou, Yang Wang, Fang Shi, Zhan Feng, Dan Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350358711

Modern SSDs achieve low latency and high throughput by utilizing multiple levels of SSD parallelism. Fairness is also a critical design consideration in cloud environments and has inspired great interest in recent years to study it. However, we find that excessive striving for SSD parallelism can inadvertently harm the SSD fairness due to the striped data layout. We observe from our experimental analysis that some common access patterns in cloud loads (e.g., high-intensity I/O) are not addressed by SSD parallelism, which can affect both SSD parallelism and fairness. In this paper, we analyze two address mapping policies with orthogonal characteristics from SSD parallelism and fairness perspectives. Based on extensive experiments and observations, we schedule a hybrid address mapping policy to achieve fairness of SSDs in cloud environments by distinguishing different I/O access modes and cold/hot data, while ensuring SSD performance. Experimental results on the latest block-level I/O traces show that our approach significantly improves performance and fairness by up to 77.3% and 62.8%, respectively, over the previous schemes with negligible cost. Meanwhile, it can also reduce the write amplification by 23.5% to 33.5%. © 2024 IEEE.

关键词： Cloud platforms

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Hierarchical microstructure enables high strength and good ductility in as-cast Fe_(27)Ni_(35)Cr_(18.25)Al_(13.75)Co_(2)Ti_(2)Mo_(2) high-entropy alloy

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Journal of Materials science & technology 2024年第12期179卷 9-21页

作者： Jiacheng Niu Zhiqiang Fu Weiping Chen Tiwen Lu Liangyan Hao Wei Xiong Haiming Wen Guangdong Key Laboratory for Advanced Metallic Materials Processing South China University of TechnologyGuangzhou 510640China National Engineering Research Center of Near-net-shape Forming for Metallic Materials South China University of TechnologyGuangzhou 510640China Key Laboratory of Pressure Systems and Safety Ministry of EducationEast China University of Science and TechnologyShanghai 200237China Physical Metallurgy and Materials Design Laboratory Department of Mechanical Engineering and Materials ScienceUniversity of PittsburghPittsburghPA15261United States of America Department of Materials Science and Engineering Missouri University of Science and TechnologyRollaMissouri 65409United States of America

As-cast alloys often require complex thermomechanical processing to obtain a hierarchical structure to achieve a good combination of strength and *** in this work,a novel hierarchical Fe_(27)Ni_(35)Cr_(18.25)Al_(13.75)Co_(2)Ti_(2)Mo_(2) high-entropy alloy(HEA)with ultra-high tensile strength and excellent ductility was fabricated by direct *** as-cast alloy exhibits hierarchical structure with an ul-trafine lamellar microstructure(ULM),ultrafine rhombus microstructure(URM),ultrafine vermicular mi-crostructure(UVM),nanosized precipitates and spinodal decomposition(SP)that develops during casting and *** incompatibility of face-centered cubic(FCC)and body-centered cubic(BCC)phases in the deformation process leads to heterogeneous deformation-induced(HDI)hardening,which brings the alloy a tensile yield strength(YS)of~1056 MPa,an ultimate tensile strength(UTS)of~1526 MPa and a total elongation(El)of~15.6%.Additionally,the numerous interfaces generated by the hierarchical structure absorb the energy during deformation,effectively retarding the dislocation motion and causing strong work-hardening.

关键词： Direct casting High-entropy alloy Hierarchical microstructure Mechanical properties

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Rydberg-Induced Topological Solitons in Three-Dimensional Rotation Spin–Orbit-Coupled Bose–Einstein Condensates

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Chinese Physics Letters 2024年第9期41卷 9-14页

作者： Yang Wang Jinlong Cui Hongkai Zhang Yuan Zhao Siliu Xu Qin Zhou Key Laboratory of Optoelectronic Sensing and Intelligent Control Hubei University of Science and TechnologyXianning 437100China School of Electronic and Information Engineering Hubei University of Science and TechnologyXianning 437100China School of Biomedical Engineering and Imaging Xianning Medical CollegeHubei University of Science and TechnologyXianning 437100China Research Center of Nonlinear Science School of Mathematics and Physical SciencesWuhan Textile UniversityWuhan 430200China

We present a novel approach for generating stable three-dimensional(3D)spatiotemporal solitons(SSs)within a rotating Bose–Einstein condensate,incorporating spin–orbit coupling(SOC),a weakly anharmonic potential and cold Rydberg *** intricate system facilitates the emergence of quasi-stable 3D SSs with topological charges|m|≤3 in two spinor components,potentially exhibiting diverse spatial *** findings reveal that the Rydberg long-range interaction,spin–orbit coupling,and rotational angular frequency exert significant influence on the domains of existence and stability of these ***,the Rydberg interaction contributes to a reduction in the norm of topological solitons,while the SOC plays a key role in stabilizing the SSs with finite topological *** research of SSs exhibits potential applications in precision measurement,quantum information processing,and other advanced technologies.

关键词： Rydberg topological Einstein

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Co-Attentive Graph Learning for Session-based Recommendation 5

Co-Attentive Graph Learning for Session-based Recommendation

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5th International Conference on Data science and information technology, DSIT 2022

作者： Cai, Fei Pan, Zhiqiang National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory China

ISBN: (数字)9781665498685

ISBN: (纸本)9781665498685

The goal of session-based recommendation is to predict user's action at the next timestamp by modeling his recent limited behaviors. Existing methods mainly concentrate on the sequential signal or pairwise transition relation between items using recurrent neural networks (RNN) or graph neural networks (GNN). However, the sequential methods fail to consider the transition relation between items while the GNN-based models face a serious over-smoothing problem. Thus, we propose a Co-Attentive Graph Learning (CAGL) method for session-based recommendation, which introduces a co-attention network to prevent over-smoothing, thus learning accurate representations for items. Extensive experiments are conducted on two public datasets, i.e., Diginetica and Gowalla. The results show that CAGL can beat the state-of-the-art baselines in terms of Recall and MRR. © 2022 IEEE.

关键词： Graph neural networks

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HfAlO-based ferroelectric memristors for artificial synaptic plasticity

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Frontiers of physics 2023年第6期18卷 163-171页

作者： Jie Yang Zixuan Jian Zhongrong Wang Jianhui Zhao Zhenyu Zhou Yong Sun Mengmeng Hao Linxia Wang Pan Liu Jingjuan Wang Yifei Pei Zhen Zhao Wei Wang Xiaobing Yan Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province College of Electron and Information EngineeringHebei UniversityBaoding 071002China Laboratory of Solid State Optoelectronics Information Technology Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China Department of Materials Science and Engineering National University of Singapore Singapore 117576Singapore

Memristors have received much attention for their ability to achieve multi-level storage and synaptic ***,the main factor that hinders the application of memristors to simulate neural synapses is the instability of the formation and breakage of conductive filaments inside traditional memristors,which makes it difficult to simulate the function of biological synapses in ***,the resistance change of ferroelectric memristors relies on the polarization inversion of the ferroelectric thin film,thus avoiding the above *** this study,a Pd/HfAlO/LSMO/STO/Si ferroelectric memristor is proposed,which can achieve resistive switching properties through the combined action of ferroelectricity and oxygen *** I−V curves show that the device has good stability and *** addition,the effect of pulse sequence modulation on the conductance was investigated,and the biological synaptic function and learning behavior were simulated *** results of the above studies provide a basis for the development of ferroelectric memristors with neurosynaptic-like behaviors.

关键词： memristor ferroelectric domain polarization resistance regulation artificial synapse

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Molecular-level proton acceptor boosts oxygen evolution catalysis to enable efficient industrial-scale water splitting

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Green Energy & Environment 2024年第2期9卷 344-355页

作者： Yaobin Wang Qian Lu Xinlei Ge Feng Li Le Chen Zhihui Zhang Zhengping Fu Yalin Lu Yang Song Yunfei Bu Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control(AEMPC)UNIST-NUIST Energy and Environment Jointed Lab(UNNU)School of Environmental Science and TechnologyNanjing University of Information Science and Technology(NUIST)219 NingliuNanjing210044China Laboratory of Advanced Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative MaterialsFudan University220 HandanShanghai200433China Jiangsu Key Laboratory of Advanced Materials and Technology School of Petrochemical EngineeringChangzhou University1 GehuChangzhou213164China Anhui Laboratory of Advanced Photon Science and Technology University of Science and Technology of China(USTC)96 JinzhaiHefeiAnhui 230026China School of Chemistry and Chemical Engineering Nanjing University of Science and Technology200 Xiaolingwei210094China

Industrial water splitting has long been suppressed by the sluggish kinetics of the oxygen evolution reaction(OER),which requires a catalyst to be ***,we propose a molecular-level proton acceptor strategy to produce an efficient OER catalyst that can boost industrial-scale water ***-level phosphate(-PO_(4))group is introduced to modify the surface of PrBa_(0.5)Ca_(0.5)Co_(2)O_(5)+δ(PBCC).The achieved catalyst(PO_(4)-PBCC)exhibits significantly enhanced catalytic performance in alkaline *** on the X-ray absorption spectroscopy results and density functional theory(DFT)calculations,the PO_(4)on the surface,which is regarded as the Lewis base,is the key factor to overcome the kinetic limitation of the proton transfer process during the *** use of the catalyst in a membrane electrode assembly(MEA)is further evaluated for industrial-scale water splitting,and it only needs a low voltage of 1.66 V to achieve a large current density of 1 A cm^(-2).This work provides a new molecular-level strategy to develop highly efficient OER electrocatalysts for industrial applications.

关键词： Oxygen evolution reaction Nanofiber Water splitting Proton acceptor Perovskite

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Distinct MLT asymmetry of auroral kilometric radiation observed by the FAST satellite

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Earth and Planetary Physics 2025年第1期9卷 188-193页

作者： JiaWen Tang Sai Zhang FuLiang Xiao HongMing Yang Si Liu YiHua He Chang Yang YuYue Jin ZhouKun Deng Ping Li Archie James Johnston School of Physics and Electronic Sciences Changsha University of Science and TechnologyChangsha 410114China Hunan Province Higher Education Key Laboratory of Modeling and Monitoring on the Near-Earth Electromagnetic Environments Changsha University of Science and TechnologyChangsha 410114China School of Electrical and Information Engineering Changsha University of Science and TechnologyChangsha 410114China

Auroral Kilometric Radiation (AKR) is a common radio emission,which can contribute to the magnetosphere-ionosphereatmosphere co u *** emissions have been observed in all magnetic planet magnetospheres of the solar *** this study,using observations from the FAST satellite from 30 August 1996 to 9 September 2001,the distribution of AKR in altitude=500-4500 km and invariant latitude (|ILAT|)=60°-80°has been analyzed.63045 AKR samples have been identified with~48%(52%) samples on the dayside (nightside).Of considerable interest,there is a distinct MLT asymmetry with the high occurrence rate in MLT=05-08 and 18-22(02-05 and 12-17) in the northern (southern) *** distinct MLT asymmetry is associated with the direction of Bxof the interplaneta ry magnetic *** addition,the occurrence rate on the nightside clearly increases as the AE^(*) index *** study further enriches the information and understanding of AKR in the magnetosphere as well as other similar radio emissions.

关键词： asymmetry auroral kilometric radiation interplanetary magnetic field

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Seasonal Forest Disaster Prediction using Machine Learning Models 5

Seasonal Forest Disaster Prediction using Machine Learning M...

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5th IEEE International Conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Niranjan, J. Krishnamoorthy, N. Vinothkumar, V. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Tamil Nadu Vellore India

ISBN: (数字)9798350379884

ISBN: (纸本)9798350379884

The forests are natural barriers that help prevent natural disasters such as heavy rainfall, heavy winds, etc. Because these disasters affect the forest, they make way for more disasters in surrounding areas including other forests, affecting animals, cities, and villages, especially tribal populations. This project aims to find solutions by analyzing the forest and its historical data including disaster incidents. The Seasonal Forest Disaster Analysis project harnesses advanced Machine Learning to investigate and mitigate the impact of forest disasters comprehensively. In essence, the Seasonal Forest Disaster Analysis project stands as a testament to the potential of cutting-edge technology and collaborative efforts in tackling some of the most pressing challenges facing our natural world. The Seasonal Forest Disaster Analysis project is a comprehensive endeavor that harnesses advanced Machine Learning & Deep Learning techniques to deeply investigate and mitigate the impact of forest disasters. Three models like CNN with Grad-CAM, ResNet and XceptionNet were proposed, out of which CNN with Grad-CAM produces an Accuracy of 94 %. By integrating a diverse array of datasets, including satellite imagery, climate data, and historical records, the project is geared towards effectively identifying, categorizing, and predicting a spectrum of seasonal forest disasters, including but not limited to wildfires, droughts, and floods. This integration enables the creation of a sophisticated framework that not only examines past occurrences but also foresees potential future hazards through predictive modelling. © 2024 IEEE.

关键词： Drought

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