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31st International Conference on Computational Linguistics, COLING 2025

作者： Cao, Jincheng Li, Bobo Liu, Jiang Ji, Donghong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University Wuhan China

ISBN: (纸本)9798891761964

Entity and relation extraction is a conventional task in the field of information extraction. Existing work primarily focuses on detecting specific relations between entities, often constrained to particular fields and lacking general applicability. In response, we propose a novel task: nominal compound relation extraction (NCRE), which concentrates on abstract and broadly applicable relation extraction between noun phrases. This task diverges significantly from traditional entity and relation extraction in two key respects. Firstly, our task involves general nominal compounds rather than named entities, which are longer and encompass a broader scope, presenting significant challenges for extraction. Secondly, relation extraction in NCRE demands an in-depth understanding of context to detect abstract relations. We manually annotate a high-quality Chinese dataset for the NCRE task and develop a model incorporating the rotary position-enhanced word pair (RoWP) detection schema. Experimental results demonstrate the efficiency of our RoWP model over previous baselines, while the suboptimal F1 scores indicate that NCRE remains a challenging task. Our code and data are available at https://***/yeecjc/NCRE. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Parallel finite element computation of incompressible magnetohydrodynamics based on three iterations

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Applied Mathematics and Mechanics(English Edition) 2022年第1期43卷 141-154页

作者： Qili TANG Yunqing HUANG Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationSchool of Mathematics and Computational ScienceXiangtan UniversityXiangtanHunan Province411105China

Based on local algorithms,some parallel finite element(FE)iterative methods for stationary incompressible magnetohydrodynamics(MHD)are *** approaches are on account of two-grid skill include two major phases:find the FE solution by solving the nonlinear system on a globally coarse mesh to seize the low frequency component of the solution,and then locally solve linearized residual subproblems by one of three iterations(Stokes-type,Newton,and Oseen-type)on subdomains with fine grid in parallel to approximate the high frequency *** error estimates with regard to two mesh sizes and iterative steps of the proposed algorithms are *** numerical examples are implemented to verify the algorithm.

关键词： local and parallel algorithm finite element(FE)method iteration stationary incompressible magnetohydrodynamics(MHD)

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Hyperspectral anomaly detection via memory‐augmented autoencoders

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1274-1287页

作者： Zhe Zhao Bangyong Sun Faculty of Printing Packaging Engineering and Digital Media TechnologyXi'an University of TechnologyXi'anChina Norwegian Colour and Visual Computing Laboratory Norwegian University of Science and TechnologyGjovikNorway

Recently,the autoencoder(AE)based method plays a critical role in the hyperspectral anomaly detection ***,due to the strong generalised capacity of AE,the abnormal samples are usually reconstructed well along with the normal background ***,in order to separate anomalies from the background by calculating reconstruction errors,it can be greatly beneficial to reduce the AE capability for abnormal sample reconstruction while maintaining the background reconstruction performance.A memory‐augmented autoencoder for hyperspectral anomaly detection(MAENet)is proposed to address this challenging ***,the proposed MAENet mainly consists of an encoder,a memory module,and a ***,the encoder transforms the original hyperspectral data into the low‐dimensional latent ***,the latent representation is utilised to retrieve the most relevant matrix items in the memory matrix,and the retrieved matrix items will be used to replace the latent representation from the ***,the decoder is used to reconstruct the input hyperspectral data using the retrieved memory *** this strategy,the background can still be reconstructed well while the abnormal samples *** conducted on five real hyperspectral anomaly data sets demonstrate the superiority of the proposed method.

关键词： anomaly detection hyperspectral images memory autoencoder

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Strengthening-softening transition and maximum strength in Schwarz nanocrystals

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Nano Materials science 2024年第3期6卷 320-328页

作者： Hanzheng Xing Jiaxi Jiang Yujia Wang Yongpan Zeng Xiaoyan Li Center for Advanced Mechanics and Materials Applied Mechanics LaboratoryDepartment of Engineering MechanicsTsinghua UniversityBeijing100084China Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)Singapore138632Singapore

Recently,a Schwarz crystal structure with curved grain boundaries(GBs)constrained by twin-boundary(TB)networks was discovered in nanocrystalline Cu through experiments and atomistic *** Cu with nanosized Schwarz crystals exhibited high strength and excellent thermal ***,the grainsize effect and associated deformation mechanisms of Schwarz nanocrystals remain ***,we performed large-scale atomistic simulations to investigate the deformation behaviors and grain-size effect of nanocrystalline Cu with Schwarz *** simulations showed that similar to regular nanocrystals,Schwarz nanocrystals exhibit a strengthening-softening transition with decreasing grain *** critical grain size in Schwarz nanocrystals is smaller than that in regular nanocrystals,leading to a maximum strength higher than that of regular *** simulations revealed that the softening in Schwarz nanocrystals mainly originates from TB migration(or detwinning)and annihilation of GBs,rather than GB-mediated processes(including GB migration,sliding and diffusion)dominating the softening in regular *** analyses of simulation data further showed that compared with those in regular nanocrystals,the GB-mediated processes in Schwarz nanocrystals are suppressed,which is related to the low volume fraction of amorphous-like GBs and constraints of TB *** smaller critical grain size arises from the suppression of GB-mediated processes.

关键词： Schwarz nanocrystal Curved grain boundary Atomistic simulation Grain size effect Maximum strength

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Advanced 3D-printed antibacterial nano 58S bioglass/AgNPs/CeO2-based scaffolds for bone tissue engineering

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Ceramics International 2025年第15期51卷 20939-20953页

作者： Singh, Indrajeet Kong, Ing Viswakarma, Ashok Balani, Kantesh Advanced Polymer and Composite Materials Laboratory Department of Engineering School of Computing Engineering and Mathematical Sciences La Trobe University BendigoVIC3550 Australia Department of Materials Science and Engineering Indian Institute of Technology Kanpur208016 India Department of Mechanical Engineering Indian Institute of Technology Kanpur208016 India

58S bioglass (BG) has been considered an effective bioceramic in bone tissue engineering due to its good osteoinductive and osteoconductive properties;however, its poor antibacterial and printing properties remain a challenge in the development of ideal patient-specific, fully interconnected, bone-like scaffolds. To address this issue, this study presents novel 3D-printed BG/AgNPs/CeO2 (BGAC3D) composite scaffolds. These scaffolds exhibit a fully interconnected pore network (≈99 %) with a porosity of ≈64 % and optimally designed pore and strut sizes of 404 ± 15 μm and 394 ± 30 μm, respectively, making them suitable for bone healing applications. Adding AgNPs and ceria nanoparticles significantly increased the shear-thinning properties of Pluronic F-127/BG/AgNPs/CeO2-based ink, as compared to Pluronic F-127/BG-based ink. As a result, BGAC3D scaffold showed improved dimensional accuracy during printing relative to pristine BG. Nanoindentation studies revealed substantial increase in the mechanical properties of BGAC3D scaffolds, with elastic modulus, hardness, and compressive strength showing enhancement of 76 % (57.9 ± 8 GPa), 24 % (3.1 ± 1 GPa), and 275 % (1.5 ± 0.4 MPa), respectively. The antibacterial properties of BGAC3D scaffolds were investigated using disc diffusion and bacterial adhesion assays, which demonstrated an exceptional bactericidal efficacy of 99.3 % against Escherichia coli (E. coli) and 99.4 % against Staphylococcus aureus (S. aureus) compared to pristine BG. The cytocompatibility of the scaffolds was assessed using resazurin assays with mouse BMSCs and MTT assays with mouse fibroblasts, revealing enhanced cell viability for the BGAC3D composition compared to BG. Additionally, both BG and BGAC3D composites showed similar apatite mineralization on their surfaces, as observed under a scanning electron microscope. These findings indicate that BGAC3D scaffolds possess the necessary mechanical, antibacterial, and cytocompatibility properties, making th

关键词： Escherichia coli

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A HIGH ORDER SCHEME FOR FRACTIONAL DIFFERENTIAL EQUATIONS WITH THE CAPUTO-HADAMARD DERIVATIVE

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Journal of Computational Mathematics 2025年第3期43卷 615-640页

作者： Xingyang Ye Junying Cao Chuanju Xu School of Science Jimei UniversityXiamen 361021China School of Data Science and Information Engineering Guizhou Minzu UniversityGuiyang 550025China School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High Performance Scientific Computing Xiamen UniversityXiamen 361005China

In this paper,we consider numerical solutions of the fractional diffusion equation with theαorder time fractional derivative defined in the Caputo-Hadamard sense.A high order time-stepping scheme is constructed,analyzed,and numerically *** contribution of the paper is twofold:1)regularity of the solution to the underlying equation is investigated,2)a rigorous stability and convergence analysis for the proposed scheme is performed,which shows that the proposed scheme is 3+αorder *** numerical examples are provided to verify the theoretical statement.

关键词： Caputo-Hadamard derivative Fractional differential equations High order scheme Stability and convergence analysis

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Partial label learning via label-specific features enhancement and semi-disambiguation

Partial label learning via label-specific features enhanceme...

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2024 International Conference on Automation Control, Algorithm, and Intelligent Bionics, ACAIB 2024

作者： Hu, Jinhua Chai, Jing Sun, Xianran School of information Science and Engineering Yunnan University Kunming650504 China Yunnan Key Laboratory of Intelligent Systems and Computing China

ISBN: (纸本)9781510682597

Partial Label Learning (PLL) represents a common multi-class weakly supervised learning challenge, where each instance is linked with a set of possible labels, only one of which is the ground-truth label, and it remains unknown during the training. A common strategy for solving this multi-class problems is to decompose it into a series of binary classification problems based on certain coding rules (e.g., OvO, ECOC), and then process each binary classification problem separately using the original features. To address the deficiency of discriminative information in the original features, a feature enhancement mechanism is proposed to introduce label-specific features to improve the discriminative performance of features. Firstly, label-specific features are generated for each decomposed binary classification problem, and then fused with the original features. The fused features are used to design corresponding binary classifiers. Additionally, due to the presence of a large number of false positive labels in the training examples, a semi-disambiguation strategy can be employed to remove some false positive labels, thereby "slimming down" the candidate label set as a preprocessing step to reduce its ambiguity. The proposed partial label learning algorithm based on features enhancement and semi-disambiguation proves its effectiveness on synthetic and real-world data sets through extensive experiments. © 2024 SPIE.

关键词： Contrastive Learning

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Non-Destructive Judgment of Watermelon Ripeness Based on Multi-Feature Fusion of Image 20

Non-Destructive Judgment of Watermelon Ripeness Based on Mul...

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20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2024

作者： Shi, Hongbao Liu, Jun Huang, Yimei Li, Jinping School of Information Science and Engineering University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan China

ISBN: (纸本)9798350356328

The nondestructive judgment of watermelon ripeness is a key issue in everyday life. Whether watermelons are ripe or not affects the interests of watermelon farmers and consumers. So far, acoustic, electrical, machine vision and other methods have been applied to the nondestructive judgment of agricultural product ripeness, but the equipment used in the lab, such as spectrometers and laser Doppler vibrometers, is expensive, difficult to carry, and has limited practical value in daily life. Based on practical experience, the ripeness of watermelons can be judged by observing specific physical characteristics, such as the rind's glossiness, texture, fuzz on the fruit stalk and navel. In this study, images of the watermelon's texture, fuzz and navel were captured using a smartphone. We utilized ResN et with an embedded Coordinate Attention mechanism and Swin-Transformer networks to independently analyze the ripeness of each feature. Then we combined the output prediction scores using post-fusion technology, with the highest weighted prediction score judging the final ripeness assessment. Our method achieved a 90.2% accuracy rate on the test set. The experiments demonstrate that a deep learning model utilizing multi-feature fusion of image data can reliably and accurately identify watermelon ripeness, even under varying image conditions. © 2024 IEEE.

关键词： Laser Doppler velocimeters

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Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information 30

Enhancing Cross-Document Event Coreference Resolution by Dis...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Gao, Qiang Li, Bobo Meng, Zixiang Li, Yunlong Zhou, Jun Li, Fei Teng, Chong Ji, Donghong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University China

ISBN: (纸本)9782493814104

Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such as location, time, agent, and patient), lacking the ability to utilize document-level information. As a result, they struggle to capture long-distance dependencies. This shortcoming leads to their underwhelming performance in determining coreference for the events where their argument information relies on long-distance dependencies. In light of these limitations, we propose the construction of document-level Rhetorical Structure Theory (RST) trees and cross-document Lexical Chains to model the structural and semantic information of documents. Subsequently, cross-document heterogeneous graphs are constructed and GAT is utilized to learn the representations of events. Finally, a pair scorer calculates the similarity between each pair of events and co-referred events can be recognized using standard clustering algorithm. Additionally, as the existing cross-document event coreference datasets are limited to English, we have developed a large-scale Chinese cross-document event coreference dataset to fill this gap, which comprises 53,066 event mentions and 4,476 clusters. After applying our model on the English and Chinese datasets respectively, it outperforms all baselines by large margins. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Clustering algorithms

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MUTS-Based Cooperative Target Stalking for A Multi-USV System

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1582-1592页

作者： Chengcheng Wang Yulong Wang Qing-Long Han Yunkai Wu Shanghai Key Laboratory of Power Station Automation Technology and the School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia College of Automation Jiangsu University of Science and TechnologyZhenjiang 212100China

This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)*** on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalking(MUTS)algorithm is ***,a V-type probabilistic data extraction method is proposed for the first time to overcome shortcomings of the MADDPG *** advantages of the proposed method are twofold:1)it can reduce the amount of data and shorten training time;2)it can filter out more important data in the experience buffer for ***,in order to avoid the collisions of USVs during the stalking process,an action constraint method called Safe DDPG is ***,the MUTS algorithm and some existing algorithms are compared in cooperative target stalking *** order to demonstrate the effectiveness of the proposed MUTS algorithm in stalking tasks,mission operating scenarios and reward functions are well designed in this *** proposed MUTS algorithm can help the multi-USV system avoid internal collisions during the mission ***,compared with some existing algorithms,the newly proposed one can provide a higher convergence speed and a narrower convergence domain.

关键词： Cooperative target stalking improved deep reinforcement learning multi-unmanned surface vehicle(multi-USV)systems V-type probabilistic data extraction

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