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npj Natural Hazards 2025年第1期2卷 1-9页

作者： Pinglang Kou Xu Dong Yuxiang Tao Ruikun Chen Zhengwu Yuan Ying Xia Qiang Xu Ali P. Yunus Rui Liu Qin Ji Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Key Laboratory of Tourism Multisource Data Perception and Decision Ministry of Culture and Tourism (TMDPD MCT) Chongqing University of Posts and Telecommunications Chongqing 400065 China State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of Technology Chengdu Sichuan 610059 China Department of Earth and Environmental Sciences Indian Institute of Science Education and Research Mohali Sahibzada Ajit Singh Nagar Punjab 140 306 India Chongqing Key Laboratory of GIS Application School of Geography and Tourism Chongqing Normal University Chongqing 401331 China

Climate change intensifies urban flood hazards, yet existing research often overlooks the complex dynamic relationships between surface deformation, soil properties, and flooding. This study uses the 2024 Guilin flood event as a case study, integrating SBAS-InSAR, DInSAR techniques, and various machine learning methods to explore the complex interactions between surface deformation, soil characteristics, and flooding. The results show that the flood caused significant water expansion, with ground subsidence mainly concentrated in the southern and eastern parts of Guilin, highly coinciding with the severely flooded areas. The flood-inundated areas exhibited opposite deformation trends before and after the flood, shifting from subsidence to uplift, while road subsidence also showed a dynamic process. Different machine learning methods showed varying performance in predicting surface deformation, with the ERT model performing relatively well. Soil thickness was positively correlated with surface subsidence within a certain range, and this relationship exhibited noticeable nonlinear characteristics post-flood. The findings of this study have important practical implications for urban flood mitigation, aiding urban planners in more accurately identifying flood-prone areas, especially those experiencing subsidence.

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The unintended consequences of retail investor attention: the case of the long-term use of short-term debt

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Finance research Letters 2025年 82卷

作者： Cai Liu Xiaoxiao He Faculty of Finance City University of Macau 402 Stanley Ho Building Avenida Padre Tomás Pereira Taipa Macao China School of Finance Southwestern University of Finance and Economics China Engineering Research Center of Intelligent Finance Ministry of Education China Big Data Laboratory on Financial Security and Behavior SWUFE (Laboratory of Philosophy and Social Sciences Ministry of Education) 555 Liutai Avenue Wenjiang District Chengdu Sichuan 611130 China

We explore the impact of retail investor attention (RIA) on the maturity mismatch between firms’ investment and financing. We document a positive and robust association between RIA and the long-term use of short-term debt (LUSD) of listed Chinese firms. The incremental impact of RIA is more pronounced for firms in more competitive industries, firms with high managerial myopia, and firms with low refinancing risk. Collectively, our findings suggest that RIA encourages managerial opportunistic behavior.

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Smart surgical telementoring system with patch-to-pixel point tracking method

EngMedicine

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EngMedicine 2025年第1期2卷

作者： Yanwei Qu Ling Li Tongtong Li Jieyu Zheng Wentao Tang Xiaojian Li School of Management Hefei University of Technology Hefei 230009 Anhui China Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance Ministry of Education Hefei 230009 Anhui China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei 230009 Anhui China Hefei Haochuan Information Technology Co. Ltd Hefei 230088 Anhui China Ministry of Education Engineering Research Center for Intelligent Decision-Making Information System Technologies Hefei 230009 Anhui China

The utilization of surgical telementoring has become increasingly prevalent in enhancing the surgical standards of grassroots hospitals in contemporary times. In the traditional framework of surgical telementoring, remote doctors guide grassroots doctors via video and audio communication, which may encounter obstacles such as inadequate information transfer and challenges in accurately pinpointing the surgical site and path. To mitigate these issues, this study introduces an intelligent surgical telementoring system based on edge computing. This system enables the transmission of points marked by remote doctors to grassroots doctors, updating these points’ coordinates in real-time on the local endoscopic video. In this system, a novel method named P2PTracking (Patch-to-Pixel Point Tracking) is implemented. This process begins with the tracking of a square patch surrounding the point marked by the remote doctor using SiameseFC. Following this, feature matching is performed on the tracked patch in the current frame and the square patch in the labelled frame or template frame. The affine transformation is then calculated based on the feature matching results. Lastly, the point tracking result is derived using the computed affine transformation. Experimental results indicate that the proposed system has a transmission speed of 1.99M/s and a transmission latency of 171 ms when transmitting video at a resolution of 1920 × 1080px, while the proposed method can achieve an accuracy of 96.6 % when the pixel error is 4. The code and data are available at https://***/hfut66/*** .

关键词： Surgical telementoring Patch tracking Point tracking Feature matching Template update mechanism

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Erratum to “Event-triggering-based H∞ load frequency control for multi-area cyber–physical power system under DoS attacks” [Franklin Open Volume 3, June 2023, 100012]

Franklin Open

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Franklin Open 2024年 9卷

作者： Xingyue Liu Kaibo Shi Kun Zhou Shiping Wen Yiqian Tang Lin Tang School of Electronic Information and Electrical Engineering Chengdu University Chengdu 610106 PR China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang University Hangzhou 310018 PR China Engineering Research Center of Power Quality of Ministry of Education Anhui University Hefei 230601 PR China Institute of Electronic and Information Engineering of University of Electronic Science and Technology of China in Guangdong 523808 PR China Australian AI Institute Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW 2007 Australia

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Time-aware bike flow prediction framework with dynamic edge fusion and memory integration

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Knowledge-Based systems 2025年 322卷

作者： M.Rajeh, Taha Li, Tianrui Luo, Zhpeng Javed, Muhammad Hafeez Alhaek, Fares School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China Engineering Research Center of Sustainable Urban Intelligent Transportation Ministry of Education Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Manufacturing Industry Chains Collaboration and Information Support Technology Key Laboratory of Sichuan Province Southwest Jiaotong University Chengdu611756 China Stirling College Chengdu University Chengdu610106 China Computing Science Faculty of Natural Sciences University of Stirling StirlingFK9 4LA United Kingdom

Bike-Sharing systems (BSSs) have become a popular solution to urban sustainability concerns, providing affordable and environmentally friendly transportation. However, modeling and predicting shared-bike flow patterns are essential for developing intelligent transportation systems and facilitating city management. Despite the existence of several inflow and outflow prediction models, certain unresolved issues remain, including the inability to differentiate and capture heterogeneous dynamic relationships within daily flows, and the suboptimal utilization of historical flow data for forecasting. To address these limitations, we propose MVRC (Multi-View Relational Framework based on Clustering), a novel deep-learning framework for precise inflow and outflow prediction. The MVRC framework models three types of heterogeneous dynamic flow relationships during different periods of the day. Initially, we introduce a novel clustering method to group nearby stations exhibiting similar patterns, followed by creating a dynamic memory module to store and update edge attributes based on the time of day. Furthermore, the dynamic edge fusion mechanism effectively integrates heterogeneous, time-evolving flow features, capturing their varying impacts. To further enhance the model's capabilities, an offline component that leverages historical data is incorporated, improving performance during testing. Extensive experiments conducted on real datasets from New York City and Washington, D.C., demonstrate the superior prediction efficiency and framework effectiveness of the MVRC framework compared to existing state-of-the-art techniques. These results highlight the practicality and efficacy of MVRC in terms of prediction accuracy and stability. © 2025

关键词： Urban transportation

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Waterline mapping of inland great lake with subpixel accuracy from GF-3 SAR images 6

Waterline mapping of inland great lake with subpixel accurac...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Li, Ning Niu, Shilin Wang, Robert Wu, Lin Guo, Zhengwei College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Kaifeng475004 China Department of Space Microwave Remote Sensing System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728129129

High-accuracy waterline mapping with Synthetic Aperture Radar (SAR) images is a challenging task because of the inhomogeneities of SAR imagery caused by the speckle noise and complex terrain. This paper presents a novel method for waterline mapping with subpixel accuracy. The proposed method mainly consists of three steps. Firstly, an improved Non-Local filter is adapted to suppress the speckle noise. Secondly, a Fuzzy C-Means (FCM) clustering algorithm is used to extract the pixel-level waterline. Thirdly, along the pixel-level waterline, a novel subpixel-scale waterline extraction method based on bicubic convolution and Geometric Active Contour (GAC) model is presented to further improve the accuracy of the waterline. Without loss of generality, the Danjiangkou reservoir (DJKR), which is the largest artificial freshwater lake in Asia, is selected as a study case. SAR images from Chinese GaoFen-3 (GF-3) satellite working on different modes are processed to demonstrate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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Modeling method for the coupling relations of microgrid cyber-physical systems driven by hybrid spatiotemporal events

arXiv

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arXiv 2021年

作者： Bo, Xiaoyong Chen, Xiaoyu Li, Huashun Dong, Yunchang Qu, Zhaoyang Wang, Lei Li, Yang School of Electrical Engineering Northeast Electric Power University Jilin132012 China Electrical and Information Engineering College Jilin Agricultural Science and Technology University Jilin132101 China Jilin Engineering Technology Research Center of Intelligent Electric Power Big Data Processing Jilin132012 China State Grid Jilin Electric Power Co. Ltd. Baishan Power Supply Company Baishan134300 China State Grid Jilin Electric Power Co. Ltd. Jilin Power Supply Company Jilin132011 China

The essence of the microgrid cyber-physical system (CPS) lies in the cyclical conversion of information flow and energy flow. Most of the existing coupling models are modeled with static networks and interface structures, in which the closed-loop data flow characteristic is not fully considered. It is difficult for these models to accurately describe spatiotemporal deduction processes, such as microgrid CPS attack identification, risk propagation, safety assessment, defense control, and cascading failure. To address this problem, a modeling method for the coupling relations of microgrid CPS driven by hybrid spatiotemporal events is proposed in the present work. First, according to the topological correlation and coupling logic of the microgrid CPS, the cyclical conversion mechanism of information flow and energy flow is analyzed, and a microgrid CPS architecture with multi-agents as the core is constructed. Next, the spatiotemporal evolution characteristic of the CPS is described by hybrid automata, and the task coordination mechanism of the multi-agent CPS terminal is designed. On this basis, a discrete-continuous correlation and terminal structure characteristic representation method of the CPS based on heterogeneous multi-groups are then proposed. Finally, four spatiotemporal events, namely state perception, network communication, intelligent decision-making, and action control, are defined. Considering the constraints of the temporal conversion of information flow and energy flow, a microgrid CPS coupling model is established, the effectiveness of which is verified by simulating false data injection attack (FDIA) scenarios. © 2021, CC BY-NC-ND.

关键词： Multi agent systems

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An auto code generator for stencil on SW26010 21

An auto code generator for stencil on SW26010

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and systems, HPCC/SmartCity/DSS 2019

作者： Zhu, Xiaomin Zeng, Yunhui Wei, Yanjie Feng, Shengzhong Liu, Weiguo Balaji, Pavan Joint Engineering Research Center Health Big Data Intelligent Analysis Technology Center for High Performance Computing Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shandong Computer Science Center National SuperComputer Center in Jinan Jinan China Sclool of Software Shandong University Jinan China Argonne National Laboratory United States

ISBN: (纸本)9781728120584

Stencil is a basic building block widely used in many HPC areas and applications. It generally dominates the time cost and is critical to the overall performance. Given that heterogeneous many-core is frequently adopted to build super computers, porting and optimizing stencil codes on modern accelerator-based architectures is important. Porting is non-trivial, and optimization is more difficult as it requires better understanding of the underlying architecture. As a result, auto tuning targeting on accelerators such as GPU becomes a hot research topic. In this paper, we focus on tuning stencil automatically on SW26010, which is a heterogeneous many-core CPU equipped in Sunway TaihuLight SuperComputer, and mainly work on 2D stencil variants code in ROMS (Regional Ocean Modeling system). The code generator can generate codes running on slave cores for 50+ different FORTRAN stencil-alike loops in ROMS in seconds, and optimization methods are integrated into the generator as well. The performance is better than the directive based method (OpenACC) and the hand-drafted code by a junior programmer, and it is comparable compared with the code written by a senior programmer with several years of programming experience. © 2019 IEEE.

关键词： Supercomputers

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An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems

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Scientific Reports 2025年第1期15卷 1-17页

作者： Sasikumar, A. Ravi, Logesh Devarajan, Malathi Almazyad, Abdulaziz S. De, Shuvodeep Xiong, Guojiang Mousavirad, Seyed Jalaleddin Mohamed, Ali Wagdy Department of Data Science and Business Systems Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India Centre for Advanced Data Science Tamil Nadu Chennai 600127 India School of Electronics Engineering Vellore Institute of Technology Tamil Nadu Chennai 600127 India School of Computer Science and Engineering Vellore Institute of Technology Chennai 600127 India Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia Virginia Tech Blacksburg United States Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical Engineering Guizhou University Guiyang 550025 China Department of Computer and Electrical Engineering Mid Sweden University Sundsvall Sweden Operations Research Department Faculty of Graduate Studies for Statistical Research Cairo University Giza 12613 Egypt Applied Science Research Center Applied Science Private University Amman 11931 Jordan Centre for Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India

The past ten years have seen notable research activity and significant advancements in multiuser multiple-input multiple-output (MU-MIMO) antennas. An MU-MIMO antenna system must accommodate many subscribers without additional bandwidth or energy. User scheduling becomes a critical strategy to take advantage of multiuser heterogeneity and acquire maximum gain in systems where the total number of recipients exceeds the number of transmitting antennas. Due to their high computational cost, many user selection methods currently in use, such as greedy algorithms and exhaustive search are unsuitable for MU-MIMO systems. A suitable scheduling mechanism is essential for the various users in an MU-MIMO system to utilise bandwidth and enhance the system’s total rate effectively. In this article, we proposed a user and antenna scheduling with a population-based meta-heuristic approach, namely the binary salp swarm algorithm (binary SSA), to increase the system sum rate with low computing complexity. We specifically used a population-based meta-heuristics optimisation technique to simulate the user scheduling problem in MU-MIMO systems, characterising complicated issues with binary decisions. Additionally, binary SSA significantly outperforms existing population-based models, such as the binary bat algorithm (binary BA), PSO, SSA, FPA and binary flower pollination algorithm (binary FPA), regarding system throughput/sum rate. The proposed binary SSA technique also effectively achieves a system sum rate compared to a random search scheme and other existing suboptimal scheduling methods. Compared to binary BA and binary FPA approaches, the binary SSA has a higher convergence rate and superior searching capabilities. The simulation outcomes show the proposed binary SSA-based scheduling scheme delivers noticeable performance benefits. © The Author(s) 2025.

关键词： Antenna Binary salp swarm algorithm Metaheuristics optimization Multiuser MIMO User scheduling

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Convergence Analysis of a Fast Non-negative Latent Factor Model

Convergence Analysis of a Fast Non-negative Latent Factor Mo...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yue Zhou Zhigang Liu Xiaojiang Yu Yajuan Wu Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China Computer School of China West Normal University Nanchong Sichuan China

A fast non-negative latent factor (FNLF) model adopts a single latent factor-dependent, non-negative, multiplicative and momentum-incorporated update (SLF-NM 2 U) algorithm, which can ensure fast convergence on a high-dimensional and sparse (HiDS) matrix according to empirical studies in prior researches. However, it is crucial to investigate the theoretical proof regarding the reason why incorporation of a generalized momentum method into an SLF-NM 2 U algorithm can ensure the fast convergence of an FNLF model, which has not been addressed in previous work. Therefore, this paper aims to unveil how a generalized momentum method improves the convergence rate of an FNLF model in the discrete time case by combining physical analysis. The FNLF model is superior to the NLF model in terms of the convergence rate and the prediction accuracy of missing data. This conclusion is obtained by empirically research on the HiDS matrix in industrial applications, which also provides empirical basis for theoretical proof.

关键词： Convergence Analytical models Sparse matrices data models Computational modeling Acceleration Friction

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