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arXiv 2024年

作者： Hu, Jinhui Chen, Guo Li, Huaqing Cheng, Huqiang Guo, Xiaoyu Huang, Tingwen School of Automation Central South University Changsha410083 China Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Key Laboratory of Dependable Services Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing400044 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518055 China

Privacy leakage and Byzantine failures are two adverse factors to the intelligent decision-making process of multiagent systems (MASs). Considering an unsafe MAS with these two issues, this paper targets the resolution of a class of nonconvex optimization problems under the Polyak-Lojasiewicz (P-L) condition. To address this problem, we first identify and construct the unsafe MAS model. Under this kind of unfavorable MASs, we mask the local gradients with Gaussian noises and adopt a resilient aggregation method self-centered clipping (SCC) to design a differentially private (DP) decentralized Byzantine-resilient algorithm, namely DP-SCC-PL, which simultaneously achieves differential privacy and Byzantine resilience. The convergence analysis of DP-SCC-PL is challenging since the convergence error can be contributed jointly by privacy-preserving and Byzantine-resilient mechanisms, as well as the nonconvex relaxation, which is addressed via seeking the contraction relationships among the disagreement measure of reliable agents before and after SCC aggregation, together with the optimal gap. Theoretical results reveal that DP-SCC-PL achieves consensus among all reliable agents and sublinear (inexact) convergence with well-designed step-sizes. It has also been proved that if there are no privacy issues and Byzantine agents, then the asymptotic exact convergence can be recovered. Numerical experiments verify the utility, resilience, and differential privacy of DP-SCC-PL by tackling a nonconvex optimization problem satisfying the P-L condition under various Byzantine attacks. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

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Blockchain-Based Homomorphic Transaction Framework for Enhanced Consumer Security and Business Scalability

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IEEE Transactions on Consumer Electronics 2024年

作者： Guo, Tao Shang, Fengjun Dai, Xiangguang Liu, Qilie Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing400065 China Key Laboratory of Big Data Intelligent Computing Chongqing400065 China Chongqing Three Gorges University Key Lab. of Intelligent Info. Proc. and Contr. of Chongqing Munic. Institutions of Higher Education Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology School of Three Gorges Artificial Intelligence Chongqing400044 China Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China

Energy trading in distributed microgrids represents an effective means of enhancing the utilization of renewable energy. However, the aggregation of large-scale consumption data may encounter business scalability issues and potential privacy exposure concerns, necessitating the development of novel secure and scalable frameworks for integrating consumption demands between prosumer and microgrid entities. we research focuses on providing a user-friendly transaction model for consumers and microgrid operators. Firstly, a privacy aggregation scheme for user resource requests is designed to ensure the security and decentralization of user data. In addition, the model employs a bidirectional heterogeneous resource allocation mechanism to support the optimal allocation of multiple resources, such as renewable energy, power assets, energy storage devices, and carbon credits, among different microgrids. Finally, a microgrid transaction prototype has been constructed on the Truffle development framework. In this context, smart contracts has been designed to ensure that the transactions are carried out automatically. Experimental results indicate that the scheme provides enhanced security for multi-resource trading in a cluster context relative to existing methodologies. The number of transactions increases linearly with the resource overhead, resulting in more efficient utilization of energy trading. Furthermore, the framework's scalability has been demonstrated through both temporal and spatial considerations. © 1975-2011 IEEE.

关键词： Decentralized finance

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Vehicle tracking by detection in UAV aerial video

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Science China(Information Sciences) 2019年第2期62卷 192-194页

作者： Shaohua LIU Suqin WANG Wenhao SHI Haibo LIU Zhaoxin LI Tianlu MAO School of Electronic Engineering University of Beijing Posts and Telecommunications Institute of Electronic and Information Engineering in Guangdong University of Electronic Science and Technology of China School of Control and Computer Engineering North China Electric Power University Beijing Key Lab of Mobile Computing and Pervasive Device Institute of Computing TechnologyChinese Academy of Sciences

With the maturity and popularity of UAV (unmanned aerial vehicle) technology [1–3], UAV video is becoming an effective supplement to the fixed monitoring video [4, 5]. In the aspect of traffic information acquisition, the advantages of UAV are obvious. UAV can fly not only between the buildings, but also on the freeway, and even into the tunnel, showing the unique flexibility and maneuverability. UAV can control its hovering position artificially and has a high angle shot to get more comprehensive and clearer video *** some emergent situation, such as evacuation caused by typhoons and earthquakes, there are lots of countryside areas without fixed road monitoring cameras. UAV is undoubtedly the best choice to

关键词： UAV Vehicle tracking by detection in UAV aerial video

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A Gray-Box Approach for Curriculum Learning 6th

A Gray-Box Approach for Curriculum Learning

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6th World Congress on Global Optimization, WCGO 2019

作者： Foglino, Francesco Leonetti, Matteo Sagratella, Simone Seccia, Ruggiero School of Computing University of Leeds Leeds United Kingdom Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Via Ariosto 25 Roma00185 Italy

ISBN: (纸本)9783030218027

Curriculum learning is often employed in deep reinforcement learning to let the agent progress more quickly towards better behaviors. Numerical methods for curriculum learning in the literature provides only initial heuristic solutions, with little to no guarantee on their quality. We define a new gray-box function that, including a suitable scheduling problem, can be effectively used to reformulate the curriculum learning problem. We propose different efficient numerical methods to address this gray-box reformulation. Preliminary numerical results on a benchmark task in the curriculum learning literature show the viability of the proposed approach. © 2020, Springer Nature Switzerland AG.

关键词： Reinforcement learning

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Automated Door to Prevent COVID-19 using Fuzzy Logic

Automated Door to Prevent COVID-19 using Fuzzy Logic

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International Conference on Electrical, Communication, and Computer engineering (ICECCE)

作者： Salah-Ud-Din Khokhar Rana Sohaib Abdul Muneeb Irfana Bibi Muhammad Yasir Noor Muhammad Imran School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan P.R.China Department of Computer Science G.C. University Lahore Lahore Pakistan Department of Computer Science Faculty of Computing and Information Technology University of Punjab Lahore Pakistan Department of Electronics G.C. University Lahore Lahore Pakistan

Due to the vagueness and uncertainties due to the coronavirus, it is crucial to implement the standard operating procedures (SOPs) issued by the World Health Organization and the authorities. Therefore an effective control system is required that minimizes the vagueness and uncertainties of people who are on the front line during the period of this pandemic checking the entering persons in an indoor area where it is necessary to maintain a distance of six feet from one another to avoid the spread of coronavirus. In this research work, a robust and efficient system has been proposed that takes protective mask and feverishness values as input and applies them using the fuzzy logic algorithm. If these input values are according to the rules defined in the system, then the door will open as an output. Otherwise, the door will not open. It is, finally, analyzing the output values. This fuzzy model had been implemented using a microcontroller. The genuine difference in the duty cycle of the microcontroller’s output pulse was measured using a 100 MHz digital oscilloscope. Our proposed system was compared with different systems reported in the literature. This work reduces the human effort as well as the negligence of people and builds up the management system without the labor in a mint.

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Intellectual lidar-based object classification for V2V communication technology implementation 22

Intellectual lidar-based object classification for V2V commu...

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Proceedings of the 6th International Conference on Future Networks & Distributed Systems

作者： Ansaf Abdulnagimov Ekaterina Lopukhova Gleb Alektorov Nail Klyavlin Department of Automated Control Systems Ufa University of Science and Technology Russian Federation Department of Telecommunication Systems Ufa University of Science and Technology Russian Federation Department of Computational Mathematics and Engineering Cybernetics Ufa University of Science and Technology Russian Federation Department of High Performance Computing Systems and Technology Ufa University of Science and Technology Russian Federation

ISBN: (纸本)9781450399050

The deep learning techniques have been shown to make a traffic objects classification system for V2V communications to ensure traffic safety and traffic flow prediction. The robust classifier on the base of MLP and PointNet are explored to recognize the traffic objects from lidar point clouds. The features of a lidar sensor, the lidar point cloud coordinate system and its complex properties for creation a smart traffic object detection and recognition model are described. The best configuration of PointNet architecture with hyperparameters are shown, which is more efficient and robust with respect to input perturbation and corruption of lidar point clouds.

关键词： PointNet

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Few-Shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and Knowledge Distillation

Few-Shot Class-Incremental Semantic Segmentation via Pseudo-...

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Information Science, Parallel and Distributed Systems (ISPDS), International Conference on

作者： Chengjia Jiang Tao Wang Sien Li Jinyang Wang Shirui Wang Antonios Antoniou Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China The Key Laboratory of Cognitive Computing and Intelligent Information Processing Fujian Education Institutions Wuyi University Wuyishan China College of Computer and Data Science Fuzhou University Fuzhou China Department of Computer Science and Engineering European University Cyprus Nicosia Cyprus

We address the problem of learning new classes for semantic segmentation models from few examples, which is challenging because of the following two reasons. Firstly, it is difficult to learn from limited novel data to capture the underlying class distribution. Secondly, it is challenging to retain knowledge for existing classes and to avoid catastrophic forgetting. For learning from limited data, we propose a pseudo-labeling strategy to augment the few-shot training annotations in order to learn novel classes more effectively. Given only one or a few images labeled with the novel classes and a much larger set of unlabeled images, we transfer the knowledge from labeled images to unlabeled images with a coarse-to-fine pseudo-labeling approach in two steps. Specifically, we first match each labeled image to its nearest neighbors in the unlabeled image set at the scene level, in order to obtain images with a similar scene layout. This is followed by obtaining pseudo-labels within this neighborhood by applying classifiers learned on the few-shot annotations. In addition, we use knowledge distillation on both labeled and unlabeled data to retain knowledge on existing classes. We integrate the above steps into a single convolutional neural network with a unified learning objective. Extensive experiments on the Cityscapes and KITTI datasets validate the efficacy of the proposed approach in the self-driving domain. Code is available from https://***/ChasonJiang/FSCILSS.

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Fast Coding Mode Prediction for Intra Prediction in VVC SCC

Fast Coding Mode Prediction for Intra Prediction in VVC SCC

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IEEE International Conference on Image Processing

作者： Dayong Wang Junyi Yu Xin Lu Frederic Dufaux Hongwei Guo Hui Guo Ce Zhu Chongqing Key Laboratory on Big Data for Bio Intelligence Chongqing University of Posts and Telecommunications Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Faculty of Computing Engineering and Media (CEM) De Montfort University Université Paris-Saclay CNRS CentraleSupélec Laboratoire des signaux et systèmes School of Engineering Honghe University Mengzi Yunnan China University of Electronic Science and Technology of China

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Currently, screen content video applications are increasingly widespread in our daily lives. The latest Screen Content Coding (SCC) standard, known as Versatile Video Coding (VVC) SCC, employs screen content Coding Modes (CMs) selection. While VVC SCC achieves high coding efficiency, its coding complexity poses a significant obstacle to the further widespread adoption of screen content video. Hence, it is crucial to enhance the coding speed of VVC SCC. In this paper, we propose a fast mode and splitting decision for Intra prediction in VVC SCC. Specifically, we initially exploit deep learning techniques to predict content types for all CUs. Subsequently, we examine CM distributions of different content types to predict candidate CMs for CUs. We then introduce early skip and early terminate CM decisions for different content types of CUs to further eliminate unlikely CMs. Finally, we develop Block-based Differential Pulse-Code Modulation (BDPCM) early termination to improve coding speed. Experimental results demonstrate that the proposed algorithm can improve coding speed by $34.95 \%$ on average while maintaining almost the same coding efficiency.

关键词： Video coding Deep learning Image coding Modulation Prediction algorithms Complexity theory Copper

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A Commitment and Ring Signature based Scheme for Amount and Identity Privacy Protection in Blockchain

A Commitment and Ring Signature based Scheme for Amount and ...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Shiyong Huang Haocong Li Ruoting Xiong Wei Ren Jie He Yi Ren School of Computer Science China University of Geosciences Wuhan China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University China School of Computer Science Beijing Jiaotong University Beijing China School of Computing Science University of East Anglia Norwich UK Beijing Key Laboratory of Urban Spatial Information Engineering Beijing China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Blockchain has been envisioned as an anonymous cryptocurrency framework and can be applied in various applications such as e-payment, share economics, and distributed ledger. Although an account is anonymous, privacy in terms of consumption behaviors still imposes leakage risks. For example, an adversary may infer the consumption capability related to an account further by analyzing the history of consumption records. It is thus of critical importance to design a solution to preserve the anonymity of both transaction amount and transaction peer’s identity, which is changeable because the amount must be still authenticated in anonymity. In this paper, we propose a scheme by using Pedersen commitment to anonymize the transaction amount, and together using ring signature to conceal the transaction peer’s identity while maintaining authentication. Especially, we further improve the security of anonymous authentication enabled by ring signature by introducing accountability, which can defend against double-spending attacks by penalization and empower auditability. The extensive performance and security analysis justify the applicability of the proposed scheme.

关键词： Economics Privacy Distributed ledger Authentication Blockchains Information filtering Security

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No 8-Instant ZTD (Zhang Time Discretization) Formula with Quintic Precision or Higher as Proved

No 8-Instant ZTD (Zhang Time Discretization) Formula with Qu...

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2021 China Automation Congress, CAC 2021

作者： Zhang, Yunong Zheng, Kangze Guo, Jinjin School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Research Institute of Sun Yat-sen University in Shenzhen Shenzhen518057 China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou510006 China

ISBN: (纸本)9781665426473

Since 2014, Zhang time discretization (ZTD, also termed Zhang et al. discretization) formulas have been put forward as a new method for time discretization by Zhang et al. Originally, ZTD formulas were used to obtain discrete Zhang neural network (ZNN) model from continuous ZNN one. ZTD formulas were also used later to discretize other continuous-time systems. So far, ZTD formulas with various number of instants have been proposed and applied, and the highest precisions of the 2-instant ZTD formula to 7-instant ZTD formulas have been discovered. Instinctively, we want to find out the highest precision of 8-instant ZTD formulas. During our investigation, we ascertain that any convergent 8-instant ZTD formula cannot possess quintic precision or higher. Combined with previous work, we conclude that any 8-instant ZTD formula converges with a truncation error in proportion to the 4-th power of the sampling interval or greater. The conclusion is proved in our paper. © 2021 IEEE

关键词： Continuous time systems

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