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International Conference on Image, Vision and Intelligent Systems, ICIVIS 2023

作者： Fang, Jiuchuan Zhao, Hui Zheng, Mingwen Wang, Zijian Niu, Sijie Gao, Xizhan Shandong Provincial Key Laboratory of Network Based Intelligent Computing School of Information Science and Engineering University of Jinan Jinan250022 China School of Mathematics and Statistics Shandong University of Technology Zibo255000 China

ISBN: (纸本)9789819708543

The increasing popularity of the internet and mobile devices, cloud storage has emerged as a popular storage method. However, because data carries a lot of information, untrustworthy servers can access users’ private information. This paper introduces an approach based on adaptive block compressed sensing and hash retrieval. The objective of this paper is to reduce the storage space required by encryption algorithms while simultaneously improving interaction efficiency. Firstly, compress images using block compressed sensing, and use BCS-SPL algorithm to reconstruct. And curves are fitted based on the gradient features and root mean square values of the blocks. Then, the sub-rates are allocated based on the gradient characteristics of the image using a fitting curve, and then the image is compressed. Next, encrypt the image and save it. The features of the queried image are used for retrieval, the results are decrypted, and then reconstructed. Finally, through a series of security analyses, the method is effective. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cloud storage

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Text information Mining in Cyberspace: An information Extraction Method Based on T5 and keyBERT 9

Text Information Mining in Cyberspace: An Information Extrac...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Liu, Kuan Li, Yumei Qi, Yuanhua Qi, Ning Zhai, Mengran Qilu University of Technology Shandong Academy of Sciences Information Research Institute Shandong Academy of Sciences Jinan China Qilu University of Technology Shandong Academy of Sciences Shandong Institute of Economy and Informatization Development Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China Qilu University of Technology Shandong Academy of Sciences Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China SHANDONG SCICOM Information and Economy Research Institute Co. Ltd Jinan China Shandong Institute of Economy and Informatization Development Jinan China

ISBN: (纸本)9798350391367

With the development of the digital economy and the advent of the big data era, the rapid growth of textual information in cyberspace has placed higher demands on information processing technology. This paper proposes an information extraction technique based on the Text-to-Text Transfer Transformer, known as T5, and keyBERT models, aiming to efficiently distill the key content from textual information in cyberspace. This method combines automatic summarization and keyword extraction to form information briefs. The experiments selected representative policy documents related to data elements as input data and employed information entropy and ROUGE scores as metrics to evaluate the automatic summarization model. The results were compared with the outputs of similar models. Experimental results indicate that the T5 model outperforms other models in terms of summarization effectiveness, and the proposed information extraction method shows significant advantages in readability and processing efficiency, demonstrating practical application value. © 2024 IEEE.

关键词： Spatio-temporal data

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Optimal Controller Design for Non-Affine Nonlinear power Systems with Static Var Compensators for Hybrid UAVs

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Tsinghua Science and Technology 2022年第1期27卷 196-206页

作者： Yanchu Li Qingqing Ding Shufang Li Stanimir Valtchev Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networkand School of Information&Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua UniversityBeijing 100084China the Nova School of Science and Technology(FCT/UNL) Caparica 2829-516LisbonPortugal Technical University of Sofia(TUS) Sofia 2125Bulgaria

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator(SVC)or State Var System(SVS)for hybrid Unmanned Aerial Vehicles(UAVs).The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its *** the inverse system method and the Linear Quadratic Regulation(LQR),an optimized SVC controller is *** simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

关键词： Static Var Compensator(SVC) Unmanned Aerial Vehicles(UAV) power system non-affine nonlinear control inverse system method Linear Quadratic Regulation(LQR)

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Community Evolution Tracking Based on Core Node Extension and Edge Variation Discerning 17th

Community Evolution Tracking Based on Core Node Extension a...

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17th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2022

作者： Zhuang, Qifeng Yu, Zhiyong Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350108 China Key Laboratory of Spatial Data Mining and Information Sharing Ministry of Education Fuzhou350108 China

ISBN: (纸本)9789819923557

Communities exist anywhere in various complex networks, and community evolution tracking is one of the most well-liked areas of inquiry in the study of dynamic complex networks. Community evolution tracking has many applications in daily life, such as predicting social network behaviors or analyzing the spread of infectious illnesses. However, the majority of existing evolution tracking algorithms obtain community detection results before matching the community in tracking evolution events, making it difficult to trace the whole evolution of communities because of community matching errors. In addition, the majority of evolution tracking algorithms do not adequately account for the potential scenarios in community evolution, resulting in erroneous detection of evolution events. In this research, a community evolution tracking algorithm based on edge variation discerning and core node extension is proposed. First, we detect communities based on the core node extension strategy, which avoids the problem of community matching errors. Second, we track community evolution based on the edge variation discerning strategy, which fully considers various situations that may occur during the community evolution process. According to the outputs of our experiments, our system can effectively track the evolution of communities in synthetic dynamic networks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Complex networks

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IGED:Towards Intelligent DDoS Detection Model Using Improved Generalized Entropy and DNN

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Computers, Materials & Continua 2024年第8期80卷 1851-1866页

作者： Yanhua Liu Yuting Han HuiChen Baokang Zhao XiaofengWang Ximeng Liu College of Computer and Data Science Fuzhou UniversityFuzhou350108China Engineering Research Center of Big Data Intelligence Ministry of EducationFuzhou350108China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhou350108China College of Computer National University of Defense TechnologyChangsha410073China

As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly *** propose an intelligent detection model named IGED by using improved generalized entropy and deep neural network(DNN).The initial detection is based on improved generalized entropy to filter out as much normal traffic as possible,thereby reducing data *** the fine detection is based on DNN to perform precise DDoS detection on the filtered suspicious traffic,enhancing the neural network’s generalization *** results show that the proposed method can efficiently distinguish normal traffic from DDoS *** with the benchmark methods,our method reaches 99.9%on low-rate DDoS(LDDoS),flooded DDoS and CICDDoS2019 datasets in terms of both accuracy and efficiency in identifying attack flows while reducing the time by 17%,31%and 8%.

关键词： DDoS real-time improved generalized entropy DNN

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A Generative Prediction Model Based on TimeVAE and Crossformer for Predicting Multichannel Data of Transformer Bushing

A Generative Prediction Model Based on TimeVAE and Crossform...

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2024 China Automation Congress, CAC 2024

作者： Huang, Xiangjie Lang, Xun Li, Peng Guo, Tao Yu, Li Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China Honghe Power Supply Bureau Yunnan Power Grid Corporation Honghe Yunnan China

ISBN: (纸本)9798350368604

Transformer bushings play a crucial role in power systems. Despite their importance, there has been limited research specifically on the state prediction of transformer bushings. Moreover, currently available models only predict univariate data of bushings without considering the physical connection to other relevant data, which would give rise to a compromised prediction. To achieve a more accurate joint prediction of three critical transformer states: dielectric loss, end shield current, and equivalent capacitance, this work builds upon the state-of-the-art predictive network Crossformer. In addition to Crossformer, a data generation model named TimeVAE is introduced to enlarge the scale of the training dataset. This combination enabled us to achieve accurate multivariate predictions for transformer bushings. To evaluate the effectiveness of the proposed predictor, we conducted comparative experiments with attention-based frameworks (Autoformer, Pyraformer, Informer, Reformer, Transformer), which are considered efficient for multivariable prediction tasks. The results show that our proposed model outperforms these models in four key metrics: mean square error, mean absolute error, root mean squared error, and coefficient of determination. © 2024 IEEE.

关键词： Prediction models

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Risk Analysis of Integrated Terminal in Micro-Grid 24

Risk Analysis of Integrated Terminal in Micro-Grid

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5th International Conference on Computer information and Big Data Applications, CIBDA 2024

作者： Wang, Yunfan Xi, Zesheng Lv, Zhuo Chang, Hao Zhang, Bo Chen, Cen He, Chuan State Grid Smart Grid Research Institute co. Ltd. State Grid Key Laboratory of Information & Network Nanjing210000 China State Grid Smart Grid Research Institute co. Ltd. State Grid Key Laboratory of Information & Network Nanjing China State Grid Henan Electric Power Research Institute Zhengzhou450000 China

ISBN: (纸本)9798400718106

pThe integrated terminal provides the bi-directional communication between master station in power grid and the edge-side equipment in micro-grid. Thus, it is vital to guarantee the safety of the integrated terminal. This paper firstly investigates the micro-grid scenario to analysis the potential vulnerabilities of the integrated terminal. Then, a penetration test is implemented to clarify these vulnerabilities and evaluating the severity of these vulnerabilities. Finally, this paper offers some state-of-art protection techniques to enhance the safety of the micro-grid. © 2024 ACM.

关键词： Risk analysis

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ASPCD-UNet: An Improved network for Change Detection

ASPCD-UNet: An Improved Network for Change Detection

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International Conference on Image, Vision and Intelligent Systems, ICIVIS 2023

作者： Wang, Kangyi Han, Tianhao Dong, Jiwen Fu, Hanghang Niu, Sijie School of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan250022 China Shandong Hongye Information Technology Co. Ltd. Jinan250013 China

ISBN: (纸本)9789819708543

Change detection (CD) is used to identify the required significant changes between two-phase images. High-resolution remote sensing image CD plays an important role in land and resources planning, military strategy research, geological exploration research, natural disaster prediction and other fields. Given two identical registration photographs taken at various times, lighting or seasonal changes are frequently present, as well as other issues such significant changes in the image of the real thing. Despite these issues, the real object's small size and its boundary changes are still a concern. Therefore, we propose a Siam network based on UNet to solve some subtle problems in CD for edge information and small object detection. The original convolutional module in our UNet network is improved into an optimization module in the form of jumper connections, a pyramidal pool module is added at the bottom of the encoder to better extract global information, and these changes together create an improved ASPCD-UNet network model. The model training is based on cross-entropy loss function, with a variety of optimization strategies to achieve end-to-end ground object change information extraction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Change detection

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Low-Cost Beam Steering that Covers the Entire Azimuthal Plane powered by Amplitude-Only Synthesis of a Quintuple-Dipole Source

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Electromagnetic Science 2023年第3期1卷 100-113页

作者： Da Yi Zhiyang Qi Mingchun Tang Dajiang Li Yilin Lang Xingchang Wei The Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education College of Microelectronics and Communication EngineeringChongqing UniversityChongqing 400044China Chongqing Key Laboratory of Space Information Network and Intelligent Information Fusion Chongqing UniversityChongqing 400044China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China

A new amplitude-only synthesis approach in quintuple electric dipoles(EDs)is proposed to enable the regulation of power flow in the azimuthal *** regulation methodology is investigated analytically with double ED,triple ED and quintuple ED ***,when the phase difference between the EDs switches,the double ED model,acting as a reconfigurable source,can work in two modes with different power flow directions,i.e.,unidirectional mode and bidirectional ***,from the triple ED model,it is verified that the power flow in the two working modes can be regulated to the desired direction in the azimuthal plane with high precision by controlling the feeding amplitudes of the ***,a quintuple ED model is developed to enhance the symmetry and consistency of the power flow regulation in the ***,a prototype of the azimuthal beam steering system,including digitally controlled radio-frequency(RF)frontend tuning circuits,optimized practical feeding elements,and an end-fire radiator,is designed,fabricated and *** unidirectional and bidirectional modes are observed,and satisfactory single-beam and dual-beam steering performance in the azimuthal plane is *** most phased arrays that realize beam steering by configuring phases,the beam steering of the proposed reconfigurable source in each mode can be arbitrarily synthesized only by the amplitudes of the quintuple feeding elements,which provides a new route for realizing low-cost and multifunctional beam-steering systems.

关键词： Electric dipole Reconfigurable devices Amplitude-only synthesis Beam steering

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Neural network-Based Safety Optimization Control for Constrained Discrete-Time Systems 49

Neural Network-Based Safety Optimization Control for Constra...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wang, Xueli Zhao, Shangwei Yang, Ming Wu, Xiaoming Wang, Xin Xu, Shuo Hu, Xu Qilu University of Technology Key Laboratory of Computing Power Network and Information Security Shandong Computer Science Center Jinan China Shanghai Jiao Tong University Department of Automation Shanghai China Public Security Bureau of Jinan Jinan China

ISBN: (纸本)9798350331820

This paper proposes a constraint-aware safety control approach via adaptive dynamic programming (ADP) to address the control optimization issues for discrete-time systems subjected to state constraints. First, the constrained control framework is established via the primal-dual approach with the modified Lagrangian based on the relaxed barrier function. Herein, the Lagrangian multiplier is designed to achieve the trade-off between optimization performance and state constraints. In addition, the sub optimality of the dual method is built by proving that the dual gap can be arbitrarily small. And the value iteration algorithm is utilized to implement the constraint-aware ADP controller. Furthermore, the weight estimation error is proved to be bounded when the learning rate satisfies a given sufficient condition. Finally, numerical simulation proves the effectiveness and superiority of the proposed method. © 2023 IEEE.

关键词： Iterative methods

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