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8th International Conference on Data Science in Cyberspace, DSC 2023

作者： Zhang, Min Ye, Qing Deng, Kaihuan Naval University of Engineering Department of Information Security Wuhan China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798350331035

The real-time map plays a vital role in the Internet of Vehicles (IoV) navigation. Compared with the existing map review, the real-time map review method is based on crowdsensing enabling faster data updates and shortening the map period from map collection to service. However, the crowdsensing method requires frequent interaction between the vehicle and nearby devices or servers, increasing the risk of user privacy leakage. How to ensure the privacy of users is a challenge in the real-time map review. Starting from the typical architecture of IoV and combining the core idea of zero-trust 'never trust, continuous verification', IoV-ZT conceptual model architecture is designed. This paper proposes a based on linkable ring signature map review scheme for zero-trust autonomous vehicles (LRSMR). In the LRSMR, a linkable ring signature based on the SM2 digital signature algorithm is used to protect user identity privacy and ensures while ensuring signature linkability by hiding the identity of the actual signer in the ring. Through the requirement for user credit, the reliability of the review data is improved. At the same time, the distribution of rewards increases users' motivation. At last, the security analysis indicates that the LRSMR satisfies correctness, unforgeability, unconditional anonymity, linkability and nonslanderability. The simulation results illustrate that the LRSMR is efficient in terms of communication overhead and computation cost. © 2023 IEEE.

关键词： Internet of vehicles Linkable ring signature Map review Zero-trust environment

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CYBER-PHYSICAL SYSTEM IMPLEMENTATION FOR THE AR-ASSISTED AIT OF AEROSPACE COMPONENTS 34th

CYBER-PHYSICAL SYSTEM IMPLEMENTATION FOR THE AR-ASSISTED AIT...

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34th Congress of the International Council of the Aeronautical Sciences, ICAS 2024

作者： Pesce, J. Carini, A. Marinacci, M. Boscia, M. Marzioli, P. Pasquali, M. Eugeni, M. Mecella, M. Piergentili, P. Gaudenzi, P. Department of Mechanical and Aerospace Engineering Sapienza University of Rome Via Eudossiana 18 Rome00184 Italy Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy

Industry 4.0 technologies are profoundly transforming the assembly, integration, and testing (AIT) processes of aerospace components, with augmented reality (AR) and cyber-physical systems (CPS) at the forefront of this evolution, marking a significant shift in traditional methodologies. This research explores the integration of CPS into the AIT processes of aerospace components, leveraging AR as a powerful tool to enhance efficiency, precision, and safety. To do so, the case of an aerospace system that showcases the practical implementation of the proposed CPS and AR framework in aerospace AIT is presented. Results show how the developed CPS can provide valuable assistance to the AIT operator, constituting a promising option to achieve significant improvements in assembly accuracy and overall process efficiency. The research also explores the implications of the proposed framework on the testing phase of aerospace components resorting to the CPS capability to facilitate real-time monitoring of performance metrics, ensuring the accomplishment of stringent quality standards. © 2024, International Council of the Aeronautical Sciences. All rights reserved.

关键词： Smart manufacturing

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T-S fuzzy model-based fault tolerant tracking controller design of a quadrotor: A fuzzy lyapunov functional approach

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Journal of Institute of control, Robotics and Systems 2021年第2期27卷 154-160页

作者： An, Ji Ho Han, Tae Joon Kim, Han Sol Department of Control and Automation Engineering Korea Maritime and Ocean University Korea Republic of

This paper proposes a fault tolerant tracking controller design method for a quadrotor based on the T-S (Takagi-Sugeno) fuzzy model. First, the nonlinear dynamics of the quadrotor is represented as a T-S fuzzy model, and its tracking error dynamics is obtained to design the tracking controller. The fault matrix is employed to express the actuator fault, and the upper and lower bounds of each element of the fault matrix are assumed to be known. The conservativeness of a stabilization condition is reduced by using the fuzzy Lyapunov function. Also, the tracking controller design condition is derived in terms of LMIs (Linear Matrix Inequalities). Finally, a simulation example is considered to validate the tracking performance of the proposed method. © ICROS 2021.

关键词： Linear matrix inequalities

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ONE-PIXEL SHORTCUT: ON THE LEARNING PREFERENCE OF DEEP NEURAL NETWORKS 11

ONE-PIXEL SHORTCUT: ON THE LEARNING PREFERENCE OF DEEP NEURA...

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11th International Conference on Learning Representations, ICLR 2023

作者： Wu, Shutong Chen, Sizhe Xie, Cihang Huang, Xiaolin Department of Automation Shanghai Jiao Tong University China Computer Science and Engineering University of California Santa Cruz United States

Unlearnable examples (ULEs) aim to protect data from unauthorized usage for training DNNs. Existing work adds ∞-bounded perturbations to the original sample so that the trained model generalizes poorly. Such perturbations, however, are easy to eliminate by adversarial training and data augmentations. In this paper, we resolve this problem from a novel perspective by perturbing only one pixel in each image. Interestingly, such a small modification could effectively degrade model accuracy to almost an untrained counterpart. Moreover, our produced One-Pixel Shortcut (OPS) could not be erased by adversarial training and strong augmentations. To generate OPS, we perturb in-class images at the same position to the same target value that could mostly and stably deviate from all the original images. Since such generation is only based on images, OPS needs significantly less computational cost than the previous methods using DNN generators. Based on OPS, we introduce an unlearnable dataset called CIFAR-10-S, which is indistinguishable from CIFAR-10 by humans but induces the trained model to extremely low accuracy. Even under adversarial training, a ResNet-18 trained on CIFAR-10-S has only 10.61% accuracy, compared to 83.02% by the existing error-minimizing method. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Pixels

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Fractional-order binary bat algorithm for feature selection on high-dimensional microarray data

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Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7453-7467页

作者： Esfandiari, Ahmad Farivar, Faezeh Khaloozadeh, Hamid Department of Computer and Mechatronics Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Systems and Control Faculty of Electrical Engineering K. N. Toosi University of Technology Seyed-Khandan Shariati Ave. Tehran16317-14191 Iran

High-dimensional microarray data suffer from the confounding effects of irrelevant, redundant and noisy genes on the scalability and efficiency of classification algorithms. In order for an effective dimensionality reduction and the selection of informative genes, this paper introduces a novel approach using fractional calculus concepts. This study proposes a modified version of binary the bat algorithm named fractional-order binary bat algorithm (FBBA) able to control the convergence process using more historical memory of bat behaviors. The gene selection technique contains a two-stage hybrid filter/wrapper method which employs a new correlation-based feature clustering (CFC) algorithm in the filter stage and the FBBA in the wrapper stage. The CFC-FBBA is evaluated on ten microarray gene expression datasets by employing the support vector machine classifier with a k-fold Monte Carlo cross validation data partitioning model. Furthermore, the results show that the CFC-FBBA, while minimizing the size of the gene subset, achieves the highest classification accuracy in most cases compared to several state-of-art hybrid techniques. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Classification (of information)

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Machine Learning-Based Calibration Approaches for Single-Beam and Multiple-Beam Distance Sensors

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IEEE Sensors Journal 2024年第1期24卷 975-983页

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Biernacki, Piotr Ziebinski, Adam National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and Informatics Devices Gliwice44-100 Poland Silesian University of Technology Department of Distributed Systems and Informatic Devices Gliwice44-100 Poland

Sensors are the foundation to facilitate smart cities, smart grids, and smart transportation, and distance sensors are especially important for sensing the environment and gathering information. Researchers have developed various methods to calibrate distance sensors;however, they mainly focus on using external information for calibration, which is inefficient and computationally expensive. To alleviate the above problems, we propose machine learning (ML)-based calibration approaches for distance sensors. We develop two calibration mechanisms, where the naive mechanism directly predicts the true distance, while the residual mechanism predicts the residual for calibration. The conventional ML regression algorithms are then adopted to predict the true distance or calibration residual. Experimental results show that the designed residual calibration mechanism outperforms the naive mechanism by reducing the root mean square error (RMSE) by 92.2% and mean absolute error (MAE) by 93.3% in the fitting task. In prediction, the proposed 2-D-residual mechanism achieves an improvement of 78.6% and 65.7% compared to the state-of-the-art method. The experimental results show the effectiveness and generalization of the proposed ML-based calibration method, especially for the 2-D mechanism, which achieves the highest robustness in all fitting and prediction tasks. © 2001-2012 IEEE.

关键词： Calibration

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Intelligent Execution of computer Vision Tasks in Delay-Constrained UAV-Aided Networks

Intelligent Execution of Computer Vision Tasks in Delay-Cons...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Varshney, Nancy Puligheddu, Corrado Chiasserini, Carla Fabiana Casetti, Claudio De, Swades Indian Institute of Technology Department of Electrical Engineering Delhi India Department of Electronics and Telecommunications Politecnico di Torino Italy Department of Control and Computer Engineering Politecnico di Torino Italy

ISBN: (纸本)9798350370218

Autonomous unmanned aerial vehicles (UAVs) are crucial in critical target tracking and disaster management services. However, challenges arise due to limited channel capacity causing large transmission delays and constraints imposed by UAV batteries when running computationally intensive object detection and tracking algorithms. To address this, we propose in-telligent offloading computer vision tasks to a high-computational edge server at millimeter wave (mmWave) frequency. Transmission at mmWave needs large transmission power and is susceptible to blockages that necessitate considering the link quality in the offloading policy. Additionally, the timely processing of frames containing objects of interest is essential for context-based UAV operations to achieve a low frame drop rate. In this work, we present a delayed-reward reinforcement learning framework to determine the offloading policy of computer vision tasks in a delay-constrained environment. This approach considers the importance of the content within frames, which is unknown to the UAV. The objective is to jointly reduce UAV energy consumption and frame drop rates, leveraging statistical information of both the channel and the frame semantics. Through extensive simulations, we demonstrate by considering statistical information of the communication channel and frame semantics, we achieve approximately 45% energy savings compared to the UAV's energy consumption when processing all frames locally and maintaining the drop rate of delay-constrained frames below 5%. © 2023 IEEE.

关键词： Communication channel delay frame semantics offloading unmanned aerial vehicle (UAV)

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Tensorized Timeline Alignment for Neural Dynamical Systems in Irregularly Sampled Time Series Prediction 42

Tensorized Timeline Alignment for Neural Dynamical Systems i...

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42nd Chinese control Conference, CCC 2023

作者： Qin, Linxiao Sun, Tao Zhang, Shuo Sun, Xi-Ming School of Control Science and Engineering Dalian University of Technology Dalian116024 China Tsinghua University Department of Automation Beijing100084 China

ISBN: (纸本)9789887581543

For many real-world scenarios, time series prediction needs to be performed on irregularly sampled data. Neural ordinary differential equations have successfully introduced neural dynamical system (NDS) methods into such tasks. However, these models suffer from a large computational cost, and cannot effectively utilize the temporal information in mini-batches, due to mismatched timestamps of samples. In this work, a unified architecture for NDS is developed, with two novel implementations on discrete input sequences (named TDINDS) and continuous sequences (named TCINDS). The reuse of network modules effectively reduces the scale of parameters and time consumption, while maintaining accuracy. In addition, a tensorized timeline alignment method is proposed, which preserves the temporal information of each training sample via reversible mappings, improving prediction performance and reducing time complexity by at least one order of magnitude. Experiments are conducted on the GoogleStock dataset, where we evaluate model accuracy and computational cost by predicting irregular future sequences. The model robustness is tested using incomplete inputs. The results demonstrate the superior performance of TDINDS and TCINDS, with mean square error reduced by 44% and 50% respectively. Robustness evaluation shows that tensorized timeline alignment is also a key factor to enhance irregular time series prediction ability. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Ordinary differential equations

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A Fault-Tolerant Task Allocation Framework for Overactuated Multi-Robot Systems 9

A Fault-Tolerant Task Allocation Framework for Overactuated ...

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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Govoni, Lorenzo Cristofaro, Andrea Sapienza University of Rome Department of Computer Control and Management Engineering Via Ariosto 25 Rome00185 Italy

ISBN: (纸本)9798350311402

Given a system of overactuated heterogeneous robots executing several tasks, we propose an algorithm that simultaneously assigns the tasks considering the different nature of the robots, and allocates the control while satisfying the limitations on the actuators. The efficiency of the proposed method has been tested in terms of robustness with respect to faults by means of numerical simulations, analysing different scenarios. © 2023 IEEE.

关键词： Multipurpose robots

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Pager Explosion:Cybersecurity Insights and Afterthoughts

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2359-2362页

作者： Chuan Sheng Wanlun Ma Qing-Long Han Wei Zhou Xiaogang Zhu Sheng Wen Yang Xiang Fei-Yue Wang Swinburne University of Technology Hawthorn VIC 3122Australia IEEE the School of Computer and Mathematical Sciences the University of AdelaideAdelaideSouth Australia 5005Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

PAGER EXPLOSION:THE *** 2024 Lebanon pager explosions represent one of the most unexpected and devastating technological incidents in recent *** September 17 and 18,2024,thousands of pagers and walkie-talkies exploded simultaneously across Lebanon and parts of Syria,resulting in 42 deaths and more than 3500 *** handheld communication devices,previously regarded as secure and low-profile,were rigged with concealed explosives and remotely triggered by attackers.

关键词： injuries thoughts explosion

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