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Edge-Enabled Metaverse:The Convergence of Metaverseand Mobile Edge Computing

Tsinghua science and technology 2024年第3期29卷 795-805页

作者： Nyothiri Aung Sahraoui Dhelim Liming Chen Huansheng Ning Luigi Atzori Tahar Kechadi Information Engineering College Xinjiang Institute of EngineeringUrumqi 830023Chinaand also with School of Computer ScienceUniversity College DublinDublinD04 V1W8Ireland School of Computing Ulster UniversityBelfastBT151EDUK School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Department of Electrical and Electronic Engineering University of CagliariSardinia 09124Italy School of Computer Science University College DublinDublinD04 V1W8Ireland

Metaverse is a virtual environment where users are represented by their avatars to navigate a virtual world having strong links with its physical *** state-of-the-art Metaverse architectures rely on a cloud-based approach for avatar physics emulation and graphics rendering *** current centralized architecture of such systems is unfavorable as it suffers from several drawbacks caused by the long latency of cloud access,such as low-quality *** this end,we propose a Fog-Edge hybrid computing architecture for Metaverse applications that leverage an edge-enabled distributed computing *** applications leverage edge devices’computing power to perform the required computations for heavy tasks,such as collision detection in the virtual universe and high-computational 3D physics in virtual *** computational costs of a Metaverse entity,such as collision detection or physics emulation,are performed at the device of the associated physical *** validate the effectiveness of the proposed architecture,we simulate a distributed social Metaverse *** simulation results show that the proposed architecture can reduce the latency by 50%when compared with cloud-based Metaverse applications.

关键词： industrial Metaverse edge computing Blockchain virtual environment task offloading fog computing

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Unpaired remote sensing image super-resolution with content-preserving weak supervision neural network

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science China(Information sciences) 2023年第1期66卷 324-325页

作者： Jie WU Runmin CONG Leyuan FANG Chunle GUO Bob ZHANG Pedram GHAMISI College of Electrical and Information Engineering Hunan University Institute of Information Science Beijing Jiaotong University College of Computer Science Nankai University Department of Computer and Information Science University of Macau Helmholtz-Zentrum Dresden-Rossendorf Helmholtz Institute Freiberg for Resource Technology Institute of Advanced Research in Artificial Intelligence (IARAI)

Dear editor,Image super-resolution(SR) uses image processing methods to increase the resolution of the image without increasing any hardware cost. Remote sensing images with high spatial resolution contain rich imagery information, which can be utilized for object detection, building segmentation, building extraction, change detection, and so on.

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Deep Learning-Based Event Prediction for Text Analysis 14

Deep Learning-Based Event Prediction for Text Analysis

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14th International Conference on Information and Communication technology Convergence, ICTC 2023

作者： Waseem, Muhammad Umer, Qasim Lee, Choonhwa Chung, Sungwook Latif, Zohaib Beijing Institute of Technology School of Computer Science and Technology Beijing China Hanyang University Department of Computer Science Seoul Korea Republic of Changwon University Department of Computer Engineering Changwon Korea Republic of Nazarbayev University Department of Computer Science Astana Kazakhstan

ISBN: (纸本)9798350313277

This paper addresses automatic event prediction from unstructured text, specifically event chains. While current approaches employ LSTM for encoding full chains, learning long-range narrative orders, or learning partial orders and long-range narrative orders, none of them consider writer sentiment. To address this, we propose a deep learning-based approach that incorporates writer sentiment. We pre-process the text, extract events, compute sentiment scores using SentiWordNet, convert events to digital vectors, and feed them along with sentiment scores into a deep learning-based classifier. This classifier uses hidden states for event pair modeling, with each pair having its associated sentiment. Evaluation results show that our approach significantly surpasses state-of-the-art methods with 29.2% accuracy. © 2023 IEEE.

关键词： Deep Learning Event Prediction Sentiment

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An Improved Semi-Supervised Learning-Based U-Net for Underwater Image Enhancement 5

An Improved Semi-Supervised Learning-Based U-Net for Underwa...

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5th International Seminar on Artificial Intelligence, Networking and Information technology, AINIT 2024

作者： Han, Jiqun Liu, Xinyu Tan, Dongxu Zhu, Jiehui School of Computer Science and Engineering Northeastern University Shenyang China Guangdong Institute of Intelligent Unmanned System Technology Research and Development Department Guangzhou China

ISBN: (纸本)9798350385557

The attenuation and scattering of light in underwater environments often lead to degradation issues such as image blurring, color cast, and low contrast. Due to the lack of high-quality paired datasets, the performance of deep learning-based methods is limited. To address these challenges, we propose an improved U-Net architecture based on semi-supervised learning for underwater image enhancement. First, a multi-scale input-level fusion module is proposed to allow our network to fully exploit global spatial information from input images, natural light fields, and depth maps. Second, a multi-branch hybrid convolutional attention residual block is designed to improve the network's feature extraction capability and focus on important spatial and channel information in underwater images. Finally, a semi-supervised learning approach is used to fully exploit unpaired datasets, improving the generalization ability of the network model. Through qualitative and quantitative analysis, the proposed network achieves satisfactory image enhancement results in various underwater scenarios. © 2024 IEEE.

关键词： Image enhancement

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SciMRC: Multi-perspective Scientific Machine Reading Comprehension 30

SciMRC: Multi-perspective Scientific Machine Reading Compreh...

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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： Zhang, Xiao Zheng, Heqi Nie, Yuxiang Huang, Heyan Mao, Xian-Ling School of Computer Science and Technology Beijing Institute of Technology China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China Southeast Academy of Information Technology Beijing Institute of Technology China State Grid Smart Grid Research Institute Co. Ltd. China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9782493814104

Scientific Machine Reading Comprehension (SMRC) aims to facilitate the understanding of scientific texts through human-machine interactions. While existing dataset has significantly contributed to this field, it predominantly focus on single-perspective question-answer pairs, thereby overlooking the inherent variation in comprehension levels among different readers. To address this limitation, we introduce a novel multi-perspective scientific machine reading comprehension dataset, SciMRC, which incorporates perspectives from beginners, students, and experts. Our dataset comprises 741 scientific papers and 6,057 question-answer pairs, with 3,306, 1,800, and 951 pairs corresponding to beginners, students, and experts respectively. Extensive experiments conducted on SciMRC using pre-trained models underscore the importance of considering diverse perspectives in SMRC and highlight the challenging nature of our scientific machine comprehension tasks. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Natural language processing systems

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LEGF-DST:LLMs-Enhanced Graph-Fusion Dual-Stream Transformer for Fine-Grained Chinese Malicious SMS Detection

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computers, Materials & Continua 2025年第2期82卷 1901-1924页

作者： Xin Tong Jingya Wang Ying Yang Tian Peng Hanming Zhai Guangming Ling School of Information and Cybersecurity People’s Public Security University of ChinaBeijing100038China Cyber Investigation Technology Research and Development Center The Third Research Institute of the Ministry of Public SecurityShanghai201204China Department of Cybersecurity Defense Beijing Police CollegeBeijing102202China School of Computer Science Henan Institute of EngineeringZhengzhou451191China

With the widespread use of SMS(Short Message Service),the proliferation of malicious SMS has emerged as a pressing societal *** deep learning-based text classifiers offer promise,they often exhibit suboptimal performance in fine-grained detection tasks,primarily due to imbalanced datasets and insufficient model representation *** address this challenge,this paper proposes an LLMs-enhanced graph fusion dual-stream Transformer model for fine-grained Chinese malicious SMS *** the data processing stage,Large Language Models(LLMs)are employed for data augmentation,mitigating dataset *** the data input stage,both word-level and character-level features are utilized as model inputs,enhancing the richness of features and preventing information loss.A dual-stream Transformer serves as the backbone network in the learning representation stage,complemented by a graph-based feature fusion *** the output stage,both supervised classification cross-entropy loss and supervised contrastive learning loss are used as multi-task optimization objectives,further enhancing the model’s feature *** results demonstrate that the proposed method significantly outperforms baselines on a publicly available Chinese malicious SMS dataset.

关键词： Transformers malicious SMS multi-task learning large language models

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Grinding preparation of 2D/2D g-C3N4/BiOCl with oxygen vacancy heterostructure for improved visible-light-driven photocatalysis

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Carbon Research 2024年第1期3卷 1-12页

作者： Hou, Jianhua Wang, Haoyi Qin, Rongrong Zhang, Qikai Wu, Di Hou, Zhenhua Yang, Wei Hussain, Asif Tahir, Muhammad Yin, Weiqin Zhang, Yongcai Wang, Xiaozhi College of Environmental Science and Engineering Yangzhou University Yangzhou225000 China Beijing Xinfeng Aerospace Equipment Co. Ltd Beijing100854 China Jiangxi Xinda Hangke New Materials Technology Co. Ltd Nanchang330096 China Beijing System Design Institute of Electro-Mechanic Engineering Beijing100005 China Department of Physics Division of Science & Technology University of Education Lahore Pakistan School of Chemistry and Chemical Engineering Yangzhou University Yangzhou225009 China

A novel 2D/2D g-C3N4/BiOCl (CN/BOC) heterojunction photocatalyst was synthesized by grinding appropriate amounts of CN, Bi(NO3)3·5H2O, glacial acetic acid and KCl at room temperature. The porous CN nanosheets not only facilitate the in situ nucleation and growth of BOC to form thin nanosheets and constitute an intimate contact interface, but also introduce more oxygen vacancies (OVs) in the grinding process. The 2D/2D CN/BOC heterojunction had a good interface and generates a built-in electric field, which can improve the separation of e− and h+. The synergistic effect of the heterostructure and OVs made the photocatalyst have significantly better performance than CN and BOC alone under visible light. The most efficient CN/BOC-5 could achieve a tetracycline (TC) degradation rate of 89.8% within 2 h, which was 1.9 and 1.2 times faster than CN and BOC, respectively. It catalyzed the reduction of CO2 to CO at a rate of 2.00 μ mol h−1 g−1, 1.1 and 3.2 times faster than CN and BOC, respectively. The mechanism for the photocatalysis of CN/BOC-5 was revealed. It was confirmed that the efficiency of photo-induced carrier separation and visible-light photo-absorption were both considerably increased by the synergistic interaction between OVs and 2D/2D heterojunction. This research may open up new possibilities for the logical design of efficient photocatalysts through combining 2D/2D heterojunctions with OVs for environmental remediation. Graphical Abstract: [Figure not available: see fulltext.] © 2024, The Author(s).

关键词： Nanosheets

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Perimeter-Search-Based Semi-Join Query Optimization Algorithm in Data-Sharing Environment

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Chinese Journal of Electronics 2023年第4期18卷 593-598页

作者： Xiaoqing Wang Youyuan Fang Yanxing Zheng Jianjian Zong Tianyang Gu Department of Computer Science and Technology Tsinghua University Beijing China Beijing Institute of System Engineering Beijing China

The problem of SQO (Semi-join query optimization) in data-sharing environment is addressed and a Perimeter-search-based semi-join query optimization algorithm (PSSJA) is presented. The algorithm can determine optimal sequence of semi-join operations, minimize the data transmission cost, saves storage space, and reduce the search complexity in a costeffective manner. Experiment shows the efficiency of our algorithm.

关键词： Costs Query processing Soft sensors Distributed databases Aerospace electronics Complexity theory Data communication

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Physics-based fuid simulation in computer graphics: Survey, research trends, and challenges

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Computational Visual Media 2024年第5期10卷 803-858页

作者： Xiaokun Wang Yanrui Xu Sinuo Liu Bo Ren Jiri Kosinka Alexandru C.Telea Jiamin Wang Chongming Song Jian Chang Chenfeng Li Jian Jun Zhang Xiaojuan Ban Beijing Advanced Innovation Center for Materials Genome Engineering and School of Intelligence Science and Technologyand Shunde Innovation School University of Science and Technology BeijingBeijing 100083China National Center for Computer Animation Faculty of Media and CommunicationBournemouth UniversityPoole BH125BBUK. Bernoulli Institute University of GroningenGroningen 9700 AKthe Netherlands School of Computer Science Peking UniversityBeijing 100871China. TMCC College of Computer ScienceNankai UniversityTianjin 300350China Department of Information and Computing Sciences Utrecht UniversityUtrecht 3584 CCthe Netherlands. Zienkiewicz Institute for Modelling Data and AISwansea UniversitySwansea SA18ENUK. Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China.

Physics-based fluid simulation has played an increasingly important role in the computer graphics *** methods in this area have greatly improved the generation of complex visual effects and its computational *** techniques have emerged to deal with complex boundaries,multiphase fluids,gas-liquid interfaces,and fine *** parallel use of machine learning,image processing,and fluid control technologies has brought many interesting and novel research *** this survey,we provide an introduction to theoretical concepts underpinning physics-based fuid simulation and their practical implementation,with the aim for it to serve as a guide for both newcomers and seasoned researchers to explore the field of physics-based fuid simulation,with a focus on developments in the last *** by the distribution of recent publications in the field,we structure our survey to cover physical background;discretization approaches;computational methods that address scalability;fuid interactions with other materials and interfaces;and methods for expressive aspects of surface detail and *** a practical perspective,we give an overview of existing implementations available for the above methods.

关键词： computer graphics physical simulation fluid simulation fluid coupling

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Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

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Chinese Journal of Aeronautics 2024年第2期37卷 431-445页

作者： Hao LU Lan GAO Yunda YAN Mingzhe HOU Chenliang WANG Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Science and Technology Hangzhou Normal UniversityHangzhou 311121China Department of Computer Science University College LondonLondon WC1E 6BTUnited Kingdom Center for Control Theory and Guidance Technology Harbin Institute of TechnologyHarbin 150001China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight *** cope with various wind conditions,this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the *** the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint,a scaling mechanism is introduced to tune the proportions of the compensation and nominal ***,an optimization problem is formulated to pursue a maximum wind compensation in strong winds,which can be solved analytically to yield two scaling factors.A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector ***-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises,achieves promising accuracy in normal winds,and mitigates the deviation from a desired path in wild winds.

关键词： Path following Guiding vector field Wind disturbance Disturbance rejection Fixed wings

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