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30th International Conference on electrical engineering, ICEE 2022

作者： Ghanbari, Sara Ashtyani, Zahra Parvin Masouleh, Mehdi Tale University of Tehran School of Electrical and Computer Engineering Human and Robot Interaction Laboratory Tehran Iran

ISBN: (纸本)9781665480871

The main objective of a hand-geometry-based user identification model consists in designing a method that could be implemented with a satisfactory trade-off between cost, accuracy, and ease of utilizing. In this paper, an efficient, peg-free hand geometry-based approach for user identification is presented, which can be easily implemented with low-cost pieces of equipment and results up to a 98.7% accuracy in user identification. Three different feature-based methods, namely, circular representation, FPL, and FPLKW, are designed and examined. In order to extract required landmarks to the end of generating intended features, the so-called Media-Pipe is used. The first method is the circular representation, in which the radius ratio of the circles formed by the three middle finger straps is taken as model features. The second method extracts fingers length and phalanges length of each finger and uses their ratio as features, which is called Finger Phalanges Length (FPL) method. The third method extracts Fingers Length and Phalanges Length of each finger and Knuckles Width, abbreviated as (FPLKW), and uses their ratios for extracting features. Two datasets are collected, one for examining the efficiency of the proposed methods and finding the promising one, and the second one for validating the performance of the selected method. The first dataset contains images of the back-side of both hands in spread fingers mode and picked altogether fingers mode, taken from 21 individuals on a black background. The second dataset contains images of 100 individual hands in the front-side of both hands and the back-side of both hands in spread fingers mode. Different classifications are used to obtain maximum accuracy, including SVM SVC, SVM NuSVC, the decision tree classifier, the extra tree classifier, the random forest classifier, and one hidden layer MLP. Obtained results reveal that the extra tree classifier leads to better performance with respect to the methods mentioned abov

关键词： Biometrics

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EVADE: Targeted Adversarial False Data Injection Attacks for State Estimation in Smart Grid

IEEE Transactions on Sustainable Computing

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IEEE Transactions on Sustainable Computing 2024年第3期10卷 534-546页

作者： Tian, Jiwei Shen, Chao Wang, Buhong Ren, Chao Xia, Xiaofang Dong, Runze Cheng, Tianhao Ministry of Education Key Laboratory for Intelligent Networks and Network Security School of Cyber Science and Engineering Xi'an Jiaotong University Xi'an China Air Traffic Control and Navigation College Air Force Engineering University Xi'an China Information and Navigation College Air Force Engineering University Xi'an China School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Computer Science and Technology Xidian University Xi'an China

Although conventional false data injection attacks can circumvent the detection of bad data detection (BDD) in sustainable power grid cyber physical systems, they are easily detected by well-trained deep learning-based detectors. Still, state estimation models with deep leaning-based detectors are not secure due to the vulnerabilities and fragility of deep learning models. Using the related laws of conventional false data injection attacks and adversarial sample attacks, this paper proposes the targEted adVersarial fAlse Data injEction (EVADE) strategy to explore targeted adversarial false data injection attacks for state estimation in Smart Grid. The proposed EVADE attack strategy selects key state variables based on adversarial saliency maps to improve the attack efficiency and perturbs as few state variables as possible to reduce the attack cost. In this way, the EVADE attack strategy can bypass the detection of BDD and neural attack detection (NAD) methods (that is, maintaining deep stealthy) with a high success rate and achieve the attack target simultaneously. Experimental results demonstrate the effectiveness of the proposed strategy, posing serious and pressing concerns for sustainable cyber physical power system security. © 2016 IEEE.

关键词： Cyber attacks

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A genetic programming approach with adaptive region detection to skin cancer image classification

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Journal of Automation and Intelligence 2024年第4期3卷 240-249页

作者： Kunjie Yu Jintao Lian Ying Bi Jing Liang Bing Xue Mengjie Zhang School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China State Key Laboratory of Intelligent Agricultural Power Equipment Luoyang471000China Longmen Laboratory Luoyang471000China School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang453000China School of Engineering and Computer Science&Centre for Data Science and Artificial Intelligence Victoria University of WellingtonWellington6201New Zealand

Dermatologists typically require extensive experience to accurately classify skin *** recent years,the development of computer vision and machine learning has provided new methods for assisted *** skin cancer image classification methods have certain limitations,such as poor interpretability,the requirement of domain knowledge for feature extraction,and the neglect of lesion area information in skin *** paper proposes a new genetic programming(GP)approach to automatically learn global and/or local features from skin images for *** achieve this,a new function set and a new terminal set have been *** proposed GP method can automatically and flexibly extract effective local/global features from different types of input images,thus providing a comprehensive description of skin images.A new region detection function has been developed to select the lesion areas from skin images for feature *** performance of this approach is evaluated on three skin cancer image classification tasks,and compared with three GP methods and six non-GP *** experimental results show that the new approach achieves significantly better or similar performance in most *** analysis validates the effectiveness of our parameter settings,visualizes the multiple region detection functions used in the individual evolved by the proposed approach,and demonstrates its good convergence ability.

关键词： Genetic programming Skin cancer image classification Region detection Feature extraction

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Physical conversion and superposition of optical skyrmion topologies

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Photonics Research 2023年第12期11卷 2042-2053页

作者： HOUAN TENG JINZHAN ZHONG JIAN CHEN XINRUI LEI QIWEN ZHAN School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Zhangjiang Laboratory Shanghai 201204China

Optical skyrmions are quasiparticles with nontrivial topological textures that have significant potential in optical information processing,transmission,and ***,we theoretically and experimentally achieve the conversion of optical skyrmions among Néel,Bloch,intermediate skyrmions,and bimerons by polarization devices,where the fusion and annihilation of optical skyrmions are demonstrated *** analyzing the polarization pattern in Poincarébeams,we reveal the skyrmion topology dependence on the device,which provides a pathway for the study of skyrmion interactions.A vectorial optical field generator is implemented to realize the conversion and superposition experimentally,and the results are in good agreement with the theoretical *** results enhance our comprehension of optical topological quasiparticles,which could have a significant impact on the transfer,storage,and communication of optical information.

关键词： Poincaré superposition topological

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Improving Motor Imagery Classification in BCI systems Using EMD and Multi-Layer CNNs 14

Improving Motor Imagery Classification in BCI Systems Using ...

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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Arghand, Reza Chaibakhsh, Ali Radman, Moein University of Guilan Intelligent Systems and Advanced Control Lab Faculty of Mechanical Engineering Rasht Guilan41996-13776 Iran University of Essex Brain-Computer Interfacing and Neural Engineering Laboratory School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom

ISBN: (纸本)9798331511272

Brain-computer Interface (BCI) systems are relatively new technologies that could play a significant role in aiding the recovery of impaired activities resulting from neuromuscular disabilities in affected individuals. Accurate recognition and classification of motor imagery in BCI systems present a challenge, leading to extensive research in recent years aimed at improving the accuracy of these systems. In this study, a combination of the Empirical Mode Decomposition (EMD) method and a multi-layer Convolutional Neural Network (CNN) is employed. Initially, the signal is decomposed into Intrinsic Mode Functions (IMFs) using EMD, and all IMFs across all trials are analyzed to select the best ones, which are then fed into the CNN as inputs. Additionally, the study incorporates the fusion of three CNN networks, each corresponding to a different IMF. The features extracted from these networks are combined and used to train an SVM classifier. The proposed method achieved an accuracy of 86.1% on the BCI-2a 2008 dataset, outperforming other state-of-the-art approaches. ©2024 IEEE.

关键词： Brain computer interface

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Analysis and Control for Synchronization of Coupled Reaction-Diffusion Neural Networks with Multistate Couplings Subject to Recoverable Attacks 13

Analysis and Control for Synchronization of Coupled Reaction...

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13th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2023

作者： Zhao, Xin-Yu Ren, Shun-Yan Wang, Jin-Liang School of Computer Science and Technology Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tianjin300387 China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan611731 China

ISBN: (纸本)9798350315196

This paper addresses the synchronization for coupled reaction-diffusion neural networks (CRNNs) with multi-state couplings suffering attacks. By utilizing the Kronecker product, a network synchronization criterion is formulated. Moreover, since networks suffering attacks may not be synchronized in some circumstances, a simple controller is also developed. Finally, the effectiveness of the devised control schemes is verified through a numerical example. © 2023 IEEE.

关键词： Synchronization

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Supremal and Robust Control against Actuator Jamming Attacks in Cyber-Physical systems

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第9期9卷 1-13页

作者： Duo, Wenli Wang, Shouguang Zhou, MengChu You, Dan Wisniewski, Remigiusz Bazydlo, Grzegorz Albeshri, Aiiad Institute of Systems Engineering Macau University of Science and Technology Macau China School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Department of Computer Science King Abdulaziz University Jeddah Saudi Arabia

Cyber-physical systems, such as unmanned aerial vehicles and connected and autonomous vehicles, are vulnerable to cyber attacks, which can cause significant damage to society. This paper examines the attack issue in cyber-physical systems within the framework of discrete event systems. Specifically, we consider a scenario where a malicious intruder injects a jamming signal into an actuator channel. It disrupts the transmission of control commands and prevents an actuator from receiving them. This is termed an actuator jamming attack. In the paper, we first analyze the closed-loop system behavior under such an attack. An attack structure is constructed to illustrate how an intruder exploits a jamming attack to drive a system into unsafe states. Then, we study the supervisory control problem for a system exposed to such an attack. The problem is reduced to a basic supervisory control one in discrete event systems by introducing the concept of dynamically controllable language. A solution to this problem is explored, where we establish an existence condition for a supremal and robust supervisor that is capable of defending against actuator jamming attacks, and design an algorithm to derive it. Finally, the effectiveness of our method is illustrated by an intelligent automated guided vehicle system. IEEE

关键词： Discrete event simulation

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Synergy of Deep Learning and Artificial Potential Field Methods for Robot Path Planning in the Presence of Static and Dynamic Obstacles 30

Synergy of Deep Learning and Artificial Potential Field Meth...

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30th International Conference on electrical engineering, ICEE 2022

作者： Basiri, Mohammad Amin Chehelgami, Shirin Ashtari, Erfan Masouleh, Mehdi Tale Kalhor, Ahmad University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9781665480871

In a fast-changing world we are in today, unmanned vehicles are displacing old, obsolete and frustrating tasks. Since unmanned vehicles are intended to work in an environment without any conduction, finding a collision-free path of movement is of paramount importance and a definite asset in practice. The objective of a global path planner consists in generating an optimized path without considering unknown obstacles. In contrast, a local path planner properly avoids the unknown obstacles while getting close to the goal. This results in an inefficient movement, particularly in complex circumstances. In this paper, a complete global and local path planning method is proposed for avoiding both static and dynamic obstacles. The proposed method benefits the advantages of both approaches while covering each other's weaknesses. First, a method for generating numerous obstacle-free paths from random pairs of start and goal points is introduced. Next, a novel deep-learning approach is proposed in order to train the robot in an environment free of moving obstacles. After extracting the desired via points, an efficient Artificial Potential Field (APF) approach for attaining the local path planning is introduced with the aim of avoiding dynamic obstacles while the robot travels through the aforementioned via points. The proposed method can be well extended to different platforms such as mobile robots, arm robots, quadrotors, etc;in this paper, both local and global path planning methods are implemented on a simulated quadrotor to examine the robot's performance for both approaches. Furthermore, it has been revealed that implementing both approaches should be implemented seamlessly in order to attain a complete efficient path planning with the presence of both static and dynamic obstacles. Finally, both local and global path planning methods are implemented on a detailed simulated quadrotor to evaluate the robot's performance for the aforementioned approaches. © 2022 IEEE.

关键词： Motion planning

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Spatiotemporal optical vortex wavepackets with phase singularities embedded in multiple domains[Invited]

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Chinese Optics Letters 2023年第8期21卷 6-11页

作者：顾亮亮曹前詹其文 School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Zhangjiang Laboratory Shanghai 201204China

Spatiotemporal optical vortex(STOV)wavepacket carrying transverse photonic orbital angular momentum(OAM)has been extensively studied in the past few *** this Letter,we propose and study a novel STOV wavepacket with multiple phase singularities embedded in different space–time domains using analytical and numerical *** tuning different parameters used for designing the wavepacket,it is possible to engineer both the magnitude and orientation of the photonic OAM in space–*** vectorially controllable OAM will pave new avenues and facilitate applications such as novel optical communication,studying complicated quantum systems,and spin-and-OAM interactions.

关键词： spatiotemporal optical vortices photonic orbital angular momentum ultrafast optics

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Determination of electrical Discharge Characteristics in Soil through Impulse Voltage and Current Measurements

Determination of Electrical Discharge Characteristics in Soi...

引用

2022 IEEE International Conference on High Voltage engineering and Applications, ICHVE 2022

作者： Datsios, Z.G. Mikropoulos, P.N. Vasileiou, M.G. School of Electrical & Computer Engineering Aristotle University of Thessaloniki High Voltage Laboratory Thessaloniki Greece

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407502

Soil ionization is important for several engineering applications since when occurring dominates the impulse behavior of grounding systems. Thus, knowledge on electrical discharge characteristics developing in soil is essential;their accurate determination is performed experimentally due to the complex physical mechanisms involved and the widely varying soil properties and conditions. This work introduces a methodology for processing and analyzing the associated measured impulse voltage and current waveforms. Time instants related to soil ionization phenomena are identified along with current, voltage and impedance values. Characteristic curves are constructed in order to evaluate the dynamics of soil ionization growth. The recorded impulse waveforms are processed automatically using a code written in MATLAB software. Preliminary results for a wet sandy soil are presented and discussed. © 2022 IEEE.

关键词： Soils

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