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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Abdulwahid, Ali Hadi Karetla, Girija Rani Ganesh, K.V.B. Kumar, A Suresh Radha, K. Shivakumar, K. Southern Technical University Engineering Technical College Control and Automation Engineering Department Basra Iraq Western Sydney University School of Computer Data and Mathematical Sciences Australia Koneru Lakshmaiah Education Foundation KL Business School Guntur Andhra Pradesh India Graphic Era Deemed to Be University Department of CSE India St. Martin's Engineering College Dept. of IT Secunderabad Telangana India SR University School of Computer Science and Artificial Intelligence Warangal Telangana India

ISBN: (纸本)9798350399264

An electroencephalogram that was captured with electrodes placed can easily get contaminated with a variety of artifacts. Here is a comparative of various electroencephalogram (EEG) de-noising techniques. Three alternative techniques are used to eliminate five different kinds of noise, and also the outcomes are evaluated. These three methods are just the Least Mean Square (LMS) technique, the Connected Neural Network, and also the Recursive Least-square (RLS) adaptable algorithm (FCNN). Period charts of the actual EEG signal, the noise EEG signal, and thus the predicted EEG signal are used to display the results. RRMSE and signal-to-noise ratio were utilized to compare the effectiveness of the 3 de-noising strategies in this study. Investigating the model parameters in this case, we discover the FCNN forecasts a better outcome compared to the other two methods. © 2023 IEEE.

关键词： Electroencephalography

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Temporal-Aware Lightweight Visual Tracking Method for Dynamic Traffic Scenes

Temporal-Aware Lightweight Visual Tracking Method for Dynami...

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

作者： Xuming Cen Nan Hu Haozhe Wang Shiyi Liu School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China Department of Computer Science Faculty of Environment Science and Economy University of Exeter Exeter UK

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

In traffic-based tracking scenes, acknowledging category diversity and visual field motion is pivotal. This leads tracking models to prioritize multi-category feature learning, motion analysis, and extended time series modeling rather than singularly focusing on attribute acquisition and background modeling. With this goal in mind, we construct a tracking model by integrating re-identification branches into a lightweight detection model. Simultaneously, we establish an inter-frame spatio-temporal attention mechanism using the Feature Transfer Module. This mechanism aligns the current frame features with the corresponding local features of the previous frame, which can bolster feature representation and downstream task performance. Experimental results on the traffic dataset validate the efficacy of the proposed approach in addressing challenges such as occlusion and deformation within traffic scenes. The proposed method attains a significant 31.5 MOTA and 35.7 AP on the BDD100K dataset with random data selection.

关键词： Representation learning Analytical models Visualization Privacy Target tracking Time series analysis Security

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Sharing the control of Robot Swarms Among Multiple Human Operators: A User Study

Sharing the Control of Robot Swarms Among Multiple Human Ope...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Genki Miyauchi Yuri K. Lopes Roderich Groß Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom Department of Computer Science Santa Catarina State University Joinville Brazil

Simultaneously controlling multiple robot swarms is challenging for a single human operator. When involving multiple operators, however, they can each focus on controlling a specific robot swarm, which helps distribute the cognitive workload. They could also exchange some robots with each other in response to the requirements of the tasks they discover. This paper investigates the ability of multiple operators to dynamically share the control of robot swarms and the effects of different communication types on performance and human factors. A total of 52 participants completed an experiment in which they were randomly paired to form a team. In a $2\times 2$ mixed factorial study, participants were split into two groups by communication type (direct vs. indirect). Both groups experienced different robot-sharing conditions (robot-sharing vs. no-robot-sharing). Results show that although the ability to share robots did not necessarily increase task scores, it allowed the operators to switch between working independently and collaboratively, reduced the total energy consumed by the swarm, and was considered useful by the participants.

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Innate Cyber-Immunity and Acquired Cyber-Immunity across Multi-Area Power Systems

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IEEE Transactions on Power Systems 2025年

作者： Hou, Jiazuo Song, Yue Hou, Yunhe Peng, Jimmy Chih-Hsien National University of Singapore Department of Electrical and Computer Engineering Singapore Tongji University Department of Control Science and Engineering National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology Shanghai201804 China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong University of Hong Kong Shenzhen Institute of Research and Innovation Shenzhen518057 China

Organisms have evolved innate and acquired immune systems to defend against pathogens like coronaviruses. Similarly, power networks, threatened by cyber-attacks, desire cyber-immunity. Inspired by the immunology research, this study develops a cyber-immune strategy-characterizing innate cyber-immunity and establishing acquired cyber-immunity-for any selected portion of a power network (termed as power subnetwork) against stealthy false data injection (FDI) cyberattacks. Therein, without extrinsic protection and information asymmetry, this paper for the first time confirms the existence and provides closed-form conditions for power subnetworks that are innately immune to FDI cyber-attacks despite all measurements being compromised. Single-leader-multi-follower bi-level optimization models are then developed to strategically allocate measurement protection, leading to the acquired cyber-immunity, whose conditions for existence and the least cost are explicitly formulated. More importantly, a bi-directional cyber-immunity propagation mechanism is presented to provide the optimal spatial allocation of defense resources across adjacent subnetworks. It also explicitly determines the temporal allocation sequence, revealing its sequential and cumulative impacts on establishing cyber-immunity. This is achieved by designing recursive traversal algorithms, one of which is modelled as a post-order depth-first-search problem of a multi-fork tree. The proposed subnetwork-specific cyber-immune strategy is verified in a modified Australian National Electricity Market. © 1969-2012 IEEE.

关键词： Phishing

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A Distributed Optimization Algorithm Considering Inequality Constraints and its Application in Economic Dispatch Problem

A Distributed Optimization Algorithm Considering Inequality ...

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IEEE International Conference on Power and Energy Applications (ICPEA)

作者： Baitong Chen Jianhua Yang Wei Lu Witold Pedrycz Changhai Sun School of Control Science and Engineering Dalian University of Technology Dalian Liaoning China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada School of Electrical Engineering Dalian University of Technology Dalian Liaoning China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

The economic dispatch problem (EDP) is crucial in optimizing and controlling power systems. As modern power system become more complex, traditional centralized communication methods are becoming less reliable. Therefore, distributed optimization method that relie on communication between neighboring nodes without the need for a central node are proposed. Existing distributed optimization methods for economic dispatch problems mainly focus on equality constraints like supply-demand balance, while problems with global inequality constraints are rarely studied. To address this gap, we propose a distributed optimization algorithm based on the primal-dual method and gradient tracking technique that can handle both global equality and inequality constraints. We thoroughly analyze its convergence and successfully apply it to the EDP with emission constraints to demonstrate its effectiveness.

关键词： Economics Optimization methods Numerical simulation control systems Power system reliability Numerical models Communication networks Reliability Distributed algorithms Convergence

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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Performance Analysis of Distributed Filtering under Mismatched Noise Covariances

arXiv

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arXiv 2024年

作者： Lyu, Xiaoxu Wen, Guanghui Shi, Ling Duan, Peihu Duan, Zhisheng The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The Laboratory of Security Operation and Control for Intelligent Autonomous Systems Department of Systems Science School of Mathematics Southeast University Nanjing211189 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

This paper systematically investigates the performance of consensus-based distributed filtering under mismatched noise covariances. First, we introduce three performance evaluation indices for such filtering problems, namely the standard performance evaluation index, the nominal performance evaluation index, and the estimation error covariance. We derive difference expressions among these indices and establish one-step relations among them under various mismatched noise covariance scenarios. We particularly reveal the effect of the consensus fusion on these relations. Furthermore, the recursive relations are introduced by extending the results of the one-step relations. Subsequently, we demonstrate the convergence of these indices under the collective observability condition, and show this convergence condition of the nominal performance evaluation index can guarantee the convergence of the estimation error covariance. Additionally, we prove that the estimation error covariance of the consensus-based distributed filter under mismatched noise covariances can be bounded by the Frobenius norms of the noise covariance deviations and the trace of the nominal performance evaluation index. Finally, the effectiveness of the theoretical results is verified by numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Wiener filtering

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Competitive Perimeter Defense of Conical Environments

Competitive Perimeter Defense of Conical Environments

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IEEE Conference on Decision and control

作者： Shivam Bajaj Eric Torng Shaunak D. Bopardikar Alexander Von Moll Isaac Weintraub Eloy Garcia David W. Casbeer Department of Electrical and Computer Engineering Michigan State University Department of Computer Science and Engineering Michigan State University Control Science Center Air Force Research Laboratory

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We consider a perimeter defense problem in a planar conical environment in which a single vehicle, having a finite capture radius, aims to defend a concentric perimeter from mobile intruders. The intruders are arbitrarily released at the circumference of the environment and they move radially toward the perimeter with fixed speed. We present a competitive analysis approach to this problem by measuring the performance of multiple online algorithms for the vehicle against arbitrary inputs, relative to an optimal offline algorithm that has information about entire input instance in advance. In particular, we establish two necessary conditions on the parameter space to guarantee (i) finite competitiveness of any algorithm and (ii) a competitive ratio of at least 2 for any algorithm. We then design and analyze three online algorithms and characterize parameter regimes in which they have finite competitive ratios. Specifically, our first two algorithms are provably 1, and 2-competitive, respectively, whereas our third algorithm exhibits different competitive ratios in different regimes of problem parameters. Finally, we provide a numerical plot in the parameter space to reveal additional insights into the relative performance of our algorithms.

关键词： Atmospheric measurements Aerospace electronics Particle measurements

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DexRepNet: Learning Dexterous Robotic Grasping Network with Geometric and Spatial Hand-Object Representations

arXiv

引用

arXiv 2023年

作者： Liu, Qingtao Cui, Yu Ye, Qi Sun, Zhengnan Li, Haoming Li, Gaofeng Shao, Lin Chen, Jiming College of Control Science and Engineering Zhejiang University Hangzhou310027 China Department of Computer Science National University of Singapore 15 Computing Dr 117418 Singapore

Robotic dexterous grasping is a challenging problem due to the high degree of freedom (DoF) and complex contacts of multi-fingered robotic hands. Existing deep reinforcement learning (DRL) based methods leverage human demonstrations to reduce sample complexity due to the high dimensional action space with dexterous grasping. However, less attention has been paid to hand-object interaction representations for high-level generalization. In this paper, we propose a novel geometric and spatial hand-object interaction representation, named DexRep, to capture object surface features and the spatial relations between hands and objects during grasping. DexRep comprises Occupancy Feature for rough shapes within sensing range by moving hands, Surface Feature for changing hand-object surface distances, and Local-Geo Feature for local geometric surface features most related to potential contacts. Based on the new representation, we propose a dexterous deep reinforcement learning method DexRepNet to learn a generalizable grasping policy. Experimental results show that our method outperforms baselines using existing representations for robotic grasping dramatically both in grasp success rate and convergence speed. It achieves a 93% grasping success rate on seen objects and higher than 80% grasping success rates on diverse objects of unseen categories in both simulation and real-world ex eriments © 2023, CC BY-NC-ND.

关键词： Reinforcement learning

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FPGA Implementation of SIMON-128 Cryptographic Algorithm Using Artix-7 14

FPGA Implementation of SIMON-128 Cryptographic Algorithm Usi...

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14th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2022

作者： Ghayoula, Ridha Fattahi, Jaouhar Smida, Amor El Gmati, Issam Pricop, Emil Ziadia, Marwa Laval University Department of Electrical and Computer Engineering Quebec Canada Laval University Department of Computer Science and Software Engineering Quebec Canada Majmaah University Department of Medical Equipment Technology Majmaah Saudi Arabia College of Engineering Al Gunfudha Umm Al Qura University Umm Al Qura Saudi Arabia Petroleum-Gas University of Ploiesti Automatic Control Computers and Electronics Department Ploiesti Romania

ISBN: (数字)9781665495356

ISBN: (纸本)9781665495356

FPGA is a hardware architecture based on a matrix of programmable and configurable logic circuits thanks to which a large number of functionalities inside the device can be modified using a hardware description language. These functionalities must often be secured especially when the context is sensitive (military, banking, medical, legal, etc.). In this paper, we put forward an efficient implementation of SIMON's block cipher algorithm using Xilinx Vivado 2018.2. The proposed design is analyzed through simulation on Xilinx Artix-7. A prototype of our design is implemented using the xc7a35tcsg324-1 FPGA chip. Performance and results are discussed. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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