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24th International Conference on Web Information Systems engineering, WISE 2023

作者： Yang, Xiaoying Li, Lijie Xu, Gang Song, Ming Zhang, Feng College of Computer Science Inner Mongolia University Hohhot010021 China Inner Mongolia A.R. Key Laboratory of Data Mining and Knowledge Engineering Inner Mongolia University Hohhot010021 China School of Computer and Information Technology Shanxi University Taiyuan030000 China

ISBN: (纸本)9789819972531

Link prediction is a crucial issue in opportunistic networks routing research. Static link prediction methods ignore the historical information of network evolution, which affects the prediction accuracy. In this paper, we propose a link prediction method (HS-LSTM) that combines hybrid similarity metrics and the E-LSTM-D model. The approach extracts structural features using hybrid similarity metrics, constructs a structural feature matrix, and applies the E-LSTM-D model to extract temporal features and predict the links that have not yet appeared in the network. Our experiments on three real datasets of opportunistic networks (Infocom5, MIT, and Haggle) shows that our proposed method outperforms the baseline method in terms of prediction accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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Interface-induced polymerization strategy for constructing titanium dioxide embedded carbon porous framework with enhanced chemical immobilization towards lithium polysulfides

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Nano Research 2024年第3期17卷 1473-1481页

作者： Yue Ouyang Xiaoxiao Li Jiexin Zhu Wei Zong Yuhang Dai Xuan Gao Wei Zhang Shengyuan Yang Roohollah Bagherzadeh Feili Lai Yue-E Miao Tianxi Liu State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua University2999 North Renmin RoadShanghai 201620China The Key Laboratory of Synthetic and Biological Colloids Ministry of EducationSchool of Chemical and Material EngineeringJiangnan UniversityWuxi 214122China Advanced Fibrous Materials LAB Institute for Advanced Textile Materials and Technologies(ATMT)School of Advanced Materials and ProcessesAmirkabir University of TechnologyTehran 15914Iran Christopher Ingold Laboratory Department of ChemistryUniversity College London20 Gordon StreetLondon WC1H 0AJUK Department of Chemistry KU LeuvenCelestijnenlaan 200FLeuven 3001Belgium

The shuttle effect induced by soluble lithium polysulfides(LiPSs)is known as one of the crucial issues that limit the practical applications of lithium-sulfur(Li-S)***,a titanium dioxide nanoparticle embedded in nitrogen-doped porous carbon nanofiber(TiO_(2)@NCNF)composite is constructed via an interface-induced polymerization strategy to serve as an ideal sulfur *** the protection of the nanofiber walls,the uniformly dispersed TiO_(2) nanocrystalline can act as capturing centers to constantly immobilize LiPSs towards durable sulfur ***,the mesoporous microstructure in the fibrous framework endows the TiO_(2)@NCNF host with strong physical reservation for sulfur and LiPSs,sufficient pathways for electron/ion transfer,and excellent endurance for volume *** expected,the sulfur-loaded TiO_(2)@NCNF composite electrode presents a fabulous rate performance and long cycle lifespan(capacity fading rate of 0.062%per cycle over 500 cycles)at 2.0 ***,the assembled Li-S batteries harvest superb areal capacity and cycling stability even under high sulfur loading and lean electrolyte conditions.

关键词： interface-induced polymerization electrospun porous nanofibers lithium-sulfur(Li-S)batteries high sulfur loading lithium polysulfides(LiPSs)immobilization

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Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need 38

Unlearnable 3D Point Clouds: Class-wise Transformation Is Al...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Wang, Xianlong Li, Minghui Liu, Wei Zhang, Hangtao Hu, Shengshan Zhang, Yechao Zhou, Ziqi Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity information, unauthorized usage of this new type data has also become a serious concern. To address this, we propose the first integral unlearnable framework for 3D point clouds including two processes: (i) we propose an unlearnable data protection scheme, involving a class-wise setting established by a category-adaptive allocation strategy and multi-transformations assigned to samples;(ii) we propose a data restoration scheme that utilizes class-wise inverse matrix transformation, thus enabling authorized-only training for unlearnable data. This restoration process is a practical issue overlooked in most existing unlearnable literature, i.e., even authorized users struggle to gain knowledge from 3D unlearnable data. Both theoretical and empirical results (including 6 datasets, 16 models, and 2 tasks) demonstrate the effectiveness of our proposed unlearnable framework. Our code is available at https://***/CGCL-codes/UnlearnablePC. © 2024 Neural information processing systems foundation. All rights reserved.

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A High-Quality and Efficient Bus-Aware Global Router

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Chinese Journal of Electronics 2025年第2期34卷 444-456页

作者： Liu Genggeng Wei Ling Yu Yantao Xu Ning College of Computer and Data Science Fuzhou University Fuzhou 350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou 350108 China School of Information Engineering Wuhan University of Technology Wuhan 430070 China

As advanced technology nodes enter the nanometer era, the complexity of integrated circuit design is increasing, and the proportion of bus in the net is also increasing. The bus routing has become a key factor affecting the performance of the chip. In addition, the existing research does not distinguish between bus and non-bus in the complete global routing process, which directly leads to the expansion of bus deviation and the degradation of chip performance. In order to solve these problems, we propose a high-quality and efficient bus-aware global router, which includes the following key strategies: By introducing the routing density graph, we propose a routing model that can simultaneously consider the routability of non-bus and the deviation value of bus;A dynamic routing resource adjustment algorithm is proposed to optimize the bus deviation and wirelength simultaneously, which can effectively reduce the bus deviation;We propose a layer assignment algorithm consider deviation to significantly reduce the bus deviation of the 3D routing solution;And a depth-first search (DFS)-based algorithm is proposed to obtain multiple routing solutions, from which the routing result with the lowest deviation is selected. Experimental results show that the proposed algorithms can effectively reduce bus deviation compared with the existing algorithms, so as to obtain high-quality 2D and 3D routing solutions considering bus deviation.

关键词： Global routing Layer assignment Bus deviation Physical design Bus routing

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AF-YOLO:A Road Scene Object Detection Algorithm Fused with Mixed-domain Attention

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第2期8卷 347-363页

作者： Liao, Lyuchao Chen, Ruixiang Shi, Jinjin Zheng, Qi Xiong, Rong Zeng, Jiemao Fujian Provincial Universities Key Laboratory of Industrial Control and Data Analysis Fujian Provincial Universities Engineering Research Center for Intelligent Driving Technology Fujian University of Technology Fuzhou350118 China Fujian Provincial Universities Engineering Research Center for Intelligent Driving Technology Fujian University of Technology Fuzhou350118 China

Object identification is a significant computer vision issue with a growing number of applications in the area of autonomous driving. In order to solve the problem of difficult detection of small objects and dense objects in the target detection algorithm in the autonomous driving scenarios,we propose an object detection method with a hybrid domain attention mechanism. In the model, the Neck network is integrated with a parallel mixed-domain attention mechanism to increase the usable features in the feature map from both channel and spatial aspects. Then, we improve the Spatial Pyramid Pooling (SPP) module with dilated convolutions to limit the loss of important information in the feature map after max pooling, which further optimizes the detector performance. Finally, a fusion approach is proposed to improve the detection layer and enhance the capability of detecting tiny objects. Extensive experiments on the BDD100k dataset show that the proposed model outperforms the state-of-the-art YOLOv5s model with an average accuracy increase of 6.22%(mAP @0.5). © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Convolution

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Distribution and ecological risks of microplastics in a tropical tourism island area in Hainan,china

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Journal of Oceanology and Limnology 2025年第2期43卷 433-445页

作者： Weijie BIAN Rui SUN Yurui LI Shuguo LÜ Dongwei YANG Hongbo LI Yingxu ZENG Min LIU Yazhou Bay Innovation Institute/Key Laboratory for Coastal Marine Eco-environment Process and Carbon Sink of Hainan Province/Modern Marine Ranching Engineering Research Center of Hainan/College of Ecology and Environment Hainan Tropical Ocean UniversitySanya 572022China Hainan Academy of Environmental Science Haikou 571126China Key Laboratory of Island Tourism Resource Data Mining and Monitoring Ministry of Culture and TourismHainan Tropical Ocean UniversitySanya 572022China National Marine Environmental Monitoring Center Dalian 116023China

Microplastics are a widely distributed pollutant that threatens the growth and health of marine *** to the mainland,island ecosystems with unique characteristics are fragile and sensitive to natural and human *** investigated the characteristics and ecological risks of microplastics in the soils of Wuzhizhou Island,Hainan,china,and its surrounding nearshore sediments affected by human *** show that the microplastic abundance in soil was 1116.67 items/kg;the particles were fragmented in size of less than 2 mm,the main polymer types were polypropylene(PP),polyethylene(PE),and polybutylene(PB),in transparent,gray,green,or *** microplastic abundances in nearshore sediments of Wuzhizhou Island and the surrounding Haitang Bay were 274.67 and 755.17 items/kg,respectively;the particles were mainly fibrous,less than 1 mm in size,the main polymer types were rayon and polyethylene terephthalate(PET),mostly *** abundance of microplastics showed a decreasing trend from shore to *** in the supratidal and intertidal zones differed in mainly the abundance and *** microplastics in land soil were from tourism activities and infrastructure while the those in nearshore sediments came from not only tourism but also domestic sewage and fishing *** ecological risk of microplastics in the terrestrial soils of Wuzhizhou Island was higher than that in its surrounding nearshore *** findings help to gain a deeper understanding of microplastic pollution in the island subjected to intensive human activities,and provide a scientific basis for subsequent in-situ toxicology research on microplastics and plastic pollution control.

关键词： microplastic occurrence characteristic ecological risk tropical tourism island

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An Improved Semantic Place Retrieval Method by Learning-based Clustering 7

An Improved Semantic Place Retrieval Method by Learning-base...

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7th International Conference on data Science and Information Technology, DSIT 2024

作者： Lu, Jiamin Liu, Jiahao Fan, Zhendong Zhou, Zhenyu Kong, Xu Feng, Jun Hohai University Key Laboratory of Water Big Data Technology Ministry of Water Resources Nanjing China Hohai University College of Computer and Software Nanjing China PowerChina Huadong Engineering Corporation Limited Hangzhou China

ISBN: (纸本)9798350384093

Traditional sorting-based semantic place retrieval methods may face the problem of a large retrieval space. An improved method is proposed in this paper, based on Learning-based Clustering. It has three components: encoding, clustering and retrieval. Specifically, we craft a spatial entity encoder that integrates both spatial and semantic dimensions to embed spatial entities. Then, we utilize a cascaded Siamese network architecture for deep clustering, thereby minimizing the retrieval space for downstream tasks. Finally, we employ the SSPR method to assess the impact of our approach on retrieval efficiency. © 2024 IEEE.

关键词： Content based retrieval

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An improved branching algorithm for the proper interval edge deletion problem

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Frontiers of Computer Science 2022年第2期16卷 178-180页

作者： Wenjun LI Xiaojing TANG Yongjie YANG School of Computer and Communication Engineering Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on TransportationChangsha University of Science and TechnologyChangsha 410015China School of Computer Science and Engineering Central South UniversityChangsha 410083China

1 Introduction For a graph class G,the G-EDGE DELETION problem is to determine whether a given graph can be transformed into a graph in G by deleting at most k *** G-EDGE DELETION problem for a large body of graph cla... 详细信息

关键词： branching problem transformed

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Advances and prospects in SAR microwave vision three-dimensional imaging

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National Science Open 2024年第5期3卷 53-83页

作者： Xiaolan Qiu Zekun Jiao Zhe Zhang Qiancheng Yan Chibiao Ding National Key Laboratory of Microwave Imaging Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100190China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100094China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou 215123China

Synthetic Aperture Radar three-dimensional(3D)imaging enables the acquisition of more comprehensive information,making it a recent hotspot in radar *** 3D imaging methods have evolved from 2D and interferometric imaging,combining elevation aperture extension with signal processing *** such as long acquisition or complex system from its imaging mechanism restrict its *** recent years,rapid development of artificial intelligence has led to a swift advancement in radar,injecting new vitality into SAR 3D *** microwave vision 3D imaging theory,which is built upon advanced technologies,has emerged as a new interdisciplinary field for radar *** paper reviews SAR 3D imaging’s history and present situation,and introduces SAR microwave *** establish a theoretical framework covering representation models,computational models,processing paradigms and evaluation ***,our research progress in this area is discussed,along with future prospects for SAR microwave vision 3D imaging.

关键词： SAR microwave vision 3D imaging visual semantics scattering mechanism

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Unveiling Vulnerability of Self-Attention 30

Unveiling Vulnerability of Self-Attention

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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： Liong, Khai Jiet Wu, Hongqiu Zhao, Hai Xiaoshan, Li Minjie, Bian Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Technology Innovation Department Shanghai Data Group Co. Ltd. China Shanghai Data Group Co. Ltd. China

ISBN: (纸本)9782493814104

Pre-trained language models (PLMs) are shown to be vulnerable to minor word changes, which poses a big threat to real-world systems. While previous studies directly focus on manipulating word inputs, they are limited by their means of generating adversarial samples, lacking generalization to versatile real-world attack. This paper studies the basic structure of transformer-based PLMs, the self-attention (SA) mechanism. (1) We propose a powerful perturbation technique HackAttend, which perturbs the attention scores within the SA matrices via meticulously crafted attention masks. We show that state-of-the-art PLMs fall into heavy vulnerability that minor attention perturbations (1%) can produce a very high attack success rate (98%). Our paper expands the conventional text attack of word perturbations to more general structural perturbations. (2) We introduce S-Attend, a novel smoothing technique that effectively makes SA robust via structural perturbations. We empirically demonstrate that this simple yet effective technique achieves robust performance on par with adversarial training when facing various text attackers. Code is publicly available at ***/liongkj/HackAttend. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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