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Short-Term Rolling Prediction of Tropical Cyclone Intensity Based on Multi-Task Learning with Fusion of Deviation-Angle Variance and Satellite Imagery

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Advances in Atmospheric sciences 2025年第1期42卷 111-128页

作者： Wei TIAN Ping SONG Yuanyuan CHEN Yonghong ZHANG Liguang WU Haikun ZHAO Kenny Thiam Choy LIM KAM SIAN Chunyi XIANG School of Software Nanjing University of Information Science and TechnologyNanjing 210044China School of Computer Nanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China Fudan University Shanghai 200433China Pacific Typhoon Research Center Nanjing University of Information Science and TechnologyNanjing 210044China Wuxi University Wuxi 214100China National Meteorological Center Beijing 100081China

Tropical cyclones(TCs)are one of the most serious types of natural disasters,and accurate TC activity predictions are key to disaster prevention and ***,TC track predictions have made significant progress,but the ability to predict their intensity is obviously lagging *** present,research on TC intensity prediction takes atmospheric reanalysis data as the research object and mines the relationship between TC-related environmental factors and intensity through deep ***,reanalysis data are non-real-time in nature,which does not meet the requirements for operational forecasting ***,a TC intensity prediction model named TC-Rolling is proposed,which can simultaneously extract the degree of symmetry for strong TC convective cloud and convection intensity,and fuse the deviation-angle variance with satellite images to construct the correlation between TC convection structure and *** TCs'complex dynamic processes,a convolutional neural network(CNN)is used to learn their temporal and spatial *** real-time intensity estimation,multi-task learning acts as an implicit time-series *** model is designed with a rolling strategy that aims to moderate the long-term dependent decay problem and improve accuracy for short-term intensity *** multiple tasks are correlated,the loss function of 12 h and 24 h are *** testing on a sample of TCs in the Northwest Pacific,with a 4.48 kt root-mean-square error(RMSE)of 6 h intensity prediction,5.78 kt for 12 h,and 13.94 kt for 24 h,TC records from official agencies are used to assess the validity of TC-Rolling.

关键词： tropical cyclone intensity structure rolling prediction multi-task

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A survey on cross-user federated recommendation

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science China(Information sciences) 2025年第4期68卷 7-32页

作者： Enyue YANG Yudi XIONG Wei YUAN Weike PAN Qiang YANG Zhong MING College of Computer Science and Software Engineering Shenzhen University School of Electrical Engineering and Computer Science The University of Queensland WeBank AI Lab WeBank Department of Computer Science and Engineering Hong Kong University of Science and Technology College of Big Data and Internet Shenzhen Technology University Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)

Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distributed paradigm to address these concerns by enabling privacy-preserving recommendations directly on user devices. In this survey, we review and categorize current progress in CUFR, focusing on four key aspects: privacy, security, accuracy, and efficiency. Firstly,we conduct an in-depth privacy analysis, discuss various cases of privacy leakage, and then review recent methods for privacy protection. Secondly, we analyze security concerns and review recent methods for untargeted and targeted *** untargeted attack methods, we categorize them into data poisoning attack methods and parameter poisoning attack methods. For targeted attack methods, we categorize them into user-based methods and item-based methods. Thirdly,we provide an overview of the federated variants of some representative methods, and then review the recent methods for improving accuracy from two categories: data heterogeneity and high-order information. Fourthly, we review recent methods for improving training efficiency from two categories: client sampling and model compression. Finally, we conclude this survey and explore some potential future research topics in CUFR.

关键词： cross-user federated recommendation federated recommendation federated learning recommender systems user privacy

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An Improved Hybrid Deep Learning Approach for Security Requirements Classification

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computers, Materials & Continua 2025年第3期82卷 4041-4067页

作者： Shoaib Hassan QianmuLi Muhammad Zubair Rakan AAlsowail Muhammad Umair School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing210094China Faculty of Information Technology and Computer Science University of Central PunjabLahore5400Pakistan Computer Skills Self-Development Skills DevelopmentDeanship of Common First YearKing Saud UniversityRiyadh11362Saudia Arabia

As the trend to use the latestmachine learning models to automate requirements engineering processes continues,security requirements classification is tuning into the most researched field in the software engineering *** literature studies have proposed numerousmodels for the classification of security ***,adopting those models is constrained due to the lack of essential datasets permitting the repetition and generalization of studies employing more advanced machine learning ***,most of the researchers focus only on the classification of requirements with security *** did not consider other nonfunctional requirements(NFR)directly or indirectly related to *** has been identified as a significant research gap in security requirements *** major objective of this study is to propose a security requirements classification model that categorizes security and other relevant security *** use PROMISE_exp and DOSSPRE,the two most commonly used datasets in the software engineering *** proposed methodology consists of two *** the first step,we analyze all the nonfunctional requirements and their relation with security *** found 10 NFRs that have a strong relationship with security *** the second step,we categorize those NFRs in the security requirements *** proposedmethodology is a hybridmodel based on the ConvolutionalNeural Network(CNN)and Extreme Gradient Boosting(XGBoost)***,we evaluate the model by updating the requirement type column with a binary classification column in the dataset to classify the requirements into security and non-security *** performance is evaluated using four metrics:recall,precision,accuracy,and F1 Score with 20 and 28 epochs number and batch size of 32 for PROMISE_exp and DOSSPRE datasets and achieved 87.3%and 85.3%accuracy,*** proposed study shows an enhancement in metrics

关键词： Requirements engineering security requirements deep learning CNN XGBoost classification

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Burst traffic demand based adaptive network planning and optimization approach for 5G/6G network

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IEEE Communications Letters 2025年第5期29卷 883-887页

作者： Guo, Yiyun Xie, Yaqin Changwang School of Honors Nanjing University of Information Science and Technology Nanjing China School of Electronics and Information Engineering Nanjing University of Information Science and Technology Nanjing China

To support the long-term stable communication demand along with burst traffic demands in 5G/6G smart environments, a new hybrid deployment strategy for fixed base stations (BSs) and unmanned aerial vehicles (UAVs) is proposed. Firstly, a cell integration strategy based on user distribution is proposed, which addresses the issues of high algorithm complexity and poor stability associated with existing hybrid macro/micro BS deployments. Secondly, to tackle the problem of large-scale burst traffic demand that cannot be solely covered by fixed BSs, UAVs are deployed according to user traffic demand, thereby effectively enhancing network coverage and minimizing unnecessary overheads. Simulation results reveal that our approach enhances coverage by 38.45%, reduces algorithm complexity by 31.22%, and decreases UAV deployment costs by 8.9% compared to the traditional method, while ensuring over 98% coverage of burst traffic demand. Furthermore, it confirms that our method fulfills the requirements of mobile user scenarios. © 1997-2012 IEEE.

关键词： 5G mobile communication systems

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Boosting the performance of β-Ga2O3/Sn-Ga2O3 n-N homojunction deep ultraviolet photodetector via interfacial Fermi-level reversal

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science China Technological sciences 2025年第5期68卷 286-293页

作者： Muzi LI Zhaoying XI Min LI Maolin ZHANG Shan LI Xueqiang JI Zhang ZHANG Lili YANG Weihua TANG Innovation Center of Gallium Oxide Semiconductor (IC-GAO) College of Integrated Circuit Science and EngineeringNanjing University of Posts and Telecommunications School of Materials Science and Engineering Nanjing University of Science and Technology

Apart from the inherent material characteristics, the regulation of device performance is also inseparable from the interface states for photodetector（PD） devices. In this paper, a β-Ga2O3/Sn-Ga2O3film was prepared by a facile-plasma enhanced chemical vapor deposition technology to explore the impact of n-N homogeneous interface design on the performance of PD. Thanks to the formation of a depletion layer on the Sn-Ga2O3side at the homogeneous interface, a self-powered supply with an open-circuit voltage of ～100 mV is successfully achieved. Moreover, a peculiar phenomenon that the rectification direction of the β-Ga2O3/Sn-Ga2O3n-N homojunction device can be controlled by light irradiation is also worthy of attention, which should be fundamentally attributed to the reversal of Fermi-levels controlled by light irradiation. In this case,the photo-to-dark current ratio can reach up to 1.19 × 10～5 under the voltage of 5 V. To a certain extent, this work implies the potential application prospects of the homogeneous structural interface design through same-type doped concentrations difference on the high-performance PDs.

关键词： deep-ultraviolet photodetector β-Ga2O3/Sn-Ga2O3 n-N homojunction interface design Fermi-level reversal self-powered

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Zinc-based fiber-shaped rechargeable batteries:Insights into structures,electrodes,and electrolytes

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Nano Research 2025年第1期18卷 278-293页

作者： Xuan Zhang Hongcheng Zhang Mengxiang Chen Jingqi Lu Evgeny Zhuravlev Jing Jiang Pin Liu Shengyang Dong Du Yuan Guoyin Zhu Lianbo Ma Yizhou Zhang Institute of Advanced Materials and Flexible Electronics(IAMFE) School of Chemistry and Materials ScienceNanjing University of Information Science and TechnologyNanjing 210044China School of Materials Science and Engineering Anhui University of TechnologyMaanshan 243002China College of Materials Science and Engineering Changsha University of Science and TechnologyChangsha 410004China

The rapid evolution of flexible wearable electronics has spurred a growing demand for energy storage devices,characterized by low-cost manufacturing processes,high safety standards,exceptional electrochemical performance and robust mechanical *** novel flexible devices,fiber-shaped batteries(FSBs)have emerged as prominent solutions exceptionally suited to future applications,owing to their unique one-dimensional(1D)architecture,remarkable flexibility,potential for miniaturization,adaptability to deformation and compatibility with the conventional textile *** the forefront research on fiber-shaped batteries,zincbased FSBs(ZFSBs)have garnered significant attentions,featured by the promising electrochemical properties of metallic *** enthusiasm is driven by the impressive capacity of Zn(820 mAh·g^(-1))and its low redox potential(Zn/Zn^(2+):-0.76 V *** hydrogen electrode).This review aims to consolidate recent achievements in the structural design,fabrication processes and electrode materials of flexible ***,we highlight three representative structural configurations:parallel type,twisted type and coaxial *** also place special emphasis on electrode modifications and electrolyte ***,we delve into the promising development opportunities and anticipate future challenges associated with ZFSBs,emphasizing their potential roles in powering the next generation of wearable electronics.

关键词： zinc-based batteries fiber-shape parallel type twisted type coaxial type

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Double-Click: dual-click iteration and dual-branch networks for interactive segmentation 16

Double-Click: dual-click iteration and dual-branch networks ...

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2024 16th International Conference on Graphics and Image Processing, ICGIP 2024

作者： Jiang, Mingcheng Wang, Di Ren, Benzhe School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

ISBN: (数字)9781510688780

ISBN: (纸本)9781510688773

The main aim of Interactive image segmentation is to accurately segment regions of interest by utilizing simple user-provided interactive information. Currently, the most popular training approach involves using the previous segmentation result as supplementary information for the next segmentation process to establish a connection between the two interactions. This iterative training method transfers all the information carried by interactions to the global level, without considering its impact at the local level. This will affect the final segmentation results and the training efficiency. To address this problem, we propose an iterative training strategy called Double-Click to involve cropping the image based on the newly added clicks and then separately feeding the cropped image and the newly added clicks into a smaller branch network to obtain predictions for the local region. Subsequently, the locally segmented result is fused with the previous segmentation result to achieve the final outcome. Then, the refined segmentation results are used to guide the next segmentation, ensuring that more precise results guide subsequent segmentations while maintaining the guidance information of the clicks on the global image. Our training strategy improves the training effectiveness by handling two clicks in an iterative process. The accuracy of the segmentation is ensured through both local and global predictions. Additionally, we designed a dual-branch network to accommodate our proposed training strategy. The effectiveness of this strategy has been tested on four validated on four benchmarks, namely GrabCut, Berkeley, SBD, and DAVIS. Experimental results demonstrate that the Double-Click method achieves better performance with fewer interactions compared to previous methods. © 2025 SPIE.

关键词： Semantic Segmentation

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A novel large kernel two-branch semantic segmentation network 24

A novel large kernel two-branch semantic segmentation networ...

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4th International Conference on Signal Processing and Communication technology, SPCT 2024

作者： Zhang, Xinrui Fu, Peng School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing China

ISBN: (纸本)9798400710636

For semantic branching in a two-branch network structure, it is crucial to quickly improve the feeling field, in addition, the feature fusion interaction of two-branching needs to take into account the structural and multi-scale information fusion of features under different feeling fields. In this paper, in order to cope with this challenge, we propose to accumulate the receptive field in dense convolution using separable large kernel convolution through an adaptive semantic extraction module, and design a selectable large kernel attention module for the problem of mismatch of receptive field of feature information. Finally, this paper designs a multiscale feature extraction module that fuses local and global information, and uses large kernel dense separable convolution in the module with the ability to extract high-dimensional semantics serially and capture multiscale in parallel. © 2024 Copyright held by the owner/author(s).

关键词： Semantic Segmentation

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A Review on Air-Ground Coordination in Mobile Edge Computing:Key Technologies,Applications and Future Directions

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1359-1386页

作者： Siqi Li Guoqiang Liu Li Li Zhongyuan Zhang Wenhao Fei Haolong Xiang School of Art Nanjing University of Information Science and TechnologyNanjing 210044China School of Software Nanjing University of Information Science and TechnologyNanjing 210044China College of Computer Science and Technology China University of Petroleum(East China)Qingdao 266555China School of Math and Applied Mathematics Nanjing University of Information Science and TechnologyNanjing 210044China

In recent years,Mobile Edge Computing(MEC)has received extensive research attention due to its characteristics,such as real-time data processing and flexible application ***,traditional MEC server deployment relies on the terrestrial Base Stations(BSs),resulting in high deployment costs and limited coverage *** response to these challenges,air-ground coordination has emerged,which effectively combines the advantages of edge computing and Unmanned Aerial Vehicles(UAVs),providing an effective architecture for edge *** utilizing the flexibility of UAVs and empowering them into edge nodes with computing resources,the coverage range of MEC can be expanded,thereby reducing the reliance of edge devices on terrestrial ***,leveraging terrestrial BSs as supplements to the computing power compensates for relatively limited computational capabilities of *** extensive studies have been conducted on air-ground coordination,there are few related summaries of application technologies and ***,the key technologies of air-ground coordination and applications are comprehensively reviewed in this ***,to provide guidance for interested researchers,the development trends and potential applications of air-ground coordination are explored.

关键词： air-ground coordination air-ground control air-ground perception emergency management resource management

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SAF-SFT-SRAF-Based Signal Coherent Integration Method for High-Speed Target Detecting in Airborne Radar

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Progress in Electromagnetics Research C 2025年 154卷 183-190页

作者： Xu, Wenwen Wang, Yuhang Huang, Jidan Wang, Hao Cao, Jianyin School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China

In radar target detection, long-term coherent integration (LTCI) is widely employed to improve the signal-to-noise ratio (SNR) and enhance the detection capability for weak and small targets. Meanwhile, the airborne radar, with advantages of wide-area surveillance, high sensitivity, and strong maneuver ability, demonstrates significant superiority in detecting high-speed targets. However, during the flight of the airborne radar platform, motion errors and the relative motion of high-speed targets can cause significant range migration (RM) and Doppler frequency migration (DFM), degrading coherent integration performance. To this end, this paper proposes a coherent integration method for high-speed target in airborne radar based on the symmetric autocorrelation function, scaled Fourier transform, and sequence reversing autocorrelation function (SAF-SFT-SRAF). Detailed comparisons between SAF-SFT-SRAF and several typical methods demonstrate that the proposed method effectively balances computational complexity and detection performance. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Aircraft detection

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