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1st IEEE International Conference on Data Intelligence and Innovative Application, DIIA 2024

作者： Wu, Man Wang, Gaocai Zhang, Wei Wen, Lili Qu, Hui School of Electrical Engineering Guangxi University Nanning China School of Computer and Electronic Information Guangxi University Nanning China Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Guangxi Key Laboratory of Intelligent Control and Operation and Maintenance of Power Equipment Nanning China Research Center for Carbon Sink and Low-Carbon Engineering The Beibu Gulf of Guangxi Guangxi Academy of Sciences Nanning China National Marine Data and Information Service Tianjin China

ISBN: (纸本)9798331504434

The examination of power systems plays a pivotal role in averting power interruptions while safeguarding grid integrity as well as fostering economic resilience. Within imagery from these inspections lie diminutive target entities alongside multiscale complexities;challenges arise in distinguishing foreground from background amidst uneven sample distributions. To fortify our model's capacity for discerning intricate targets amid mitigating background noise disruptions along with environmental fluctuations necessitates amalgamating multilevel multidimensional image features. Henceforth emerges our introduction of BiFPN (Bidirectional Feature Pyramid Network) module coupled with our proposition of YOLOvlO object detection network featuring bidirectional feature fusion. Within this framework's architecture lies an integration of BiFPN replacing Concat for streamlined multiscale feature fusion efficiency;further complemented by a novel Focal-EloU loss function aimed at harmonizing contributions from high- versus low-quality samples towards enhancing model efficacy across imbalanced datasets. Experimental evaluations conducted on power system inspection datasets demonstrate superior detection capabilities exhibited by our proposed network compared against incumbent models as well as mainstream object detection networks-thus advancing secure intelligent scrutiny over power lines. © 2024 IEEE.

关键词： Object detection

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Best Practices for a Handwritten Text Recognition System

arXiv

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arXiv 2024年

作者： Retsinas, George Sfikas, Giorgos Gatos, Basilis Nikou, Christophoros School of Electrical and Computer Engineering National Technical University of Athens Greece Computational Intelligence Laboratory Institute of Informatics and Telecommunications National Center for Scientific Research "Demokritos" Greece Department of Computer Science and Engineering University of Ioannina Greece Department of Surveying and Geoinformatics Engineering University of West Attica Greece

Handwritten text recognition has been developed rapidly in the recent years, following the rise of deep learning and its applications. Though deep learning methods provide notable boost in performance concerning text recognition, non-trivial deviation in performance can be detected even when small pre-processing or architectural/optimization elements are changed. This work follows a "best practice" rationale;highlight simple yet effective empirical practices that can further help training and provide well-performing handwritten text recognition systems. Specifically, we considered three basic aspects of a deep HTR system and we proposed simple yet effective solutions: 1) retain the aspect ratio of the images in the preprocessing step, 2) use max-pooling for converting the 3D feature map of CNN output into a sequence of features and 3) assist the training procedure via an additional CTC loss which acts as a shortcut on the max-pooled sequential features. Using these proposed simple modifications, one can attain close to state-of-the-art results, while considering a basic convolutional-recurrent (CNN+LSTM) architecture, for both IAM and RIMES datasets. Code is available at https://***/georgeretsi/HTR-best-practices/. © 2024, CC BY.

关键词： Convolution

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Reinforcement Learning-Enhanced Active Disturbance Rejection control for Mobile Robot Trajectory Tracking

Reinforcement Learning-Enhanced Active Disturbance Rejection...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： H. Usama M. Nasir R. Fareh J. Ghommam S. Khadraoui M. Bettayeb Research Institute of Sciences and Engineering University of Sharjah Sharjah UAE Department of Electrical Engineering University of Sharjah Sharjah UAE Department of Electrical and Computer Engineering Sultan Qaboos University Oman Control and Energy Management Laboratory (CEM Lab) Ecole National d'Ingenieur de Sfax Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

In recent years, the application of robotics has significantly advanced many fields, providing robust performance and efficiency in complex tasks without the need for human intervention. Robot control is a key area of robotics that has received a lot of interest and technological development. Active Disturbance Rejection controllers (ADRCs) are widely adopted due to several features, including their ability to maintain robust performance and effectively reject disturbances. The manual tuning of controller parameters is time-consuming and highlights the need for automation. This paper presents an innovative approach to tune the parameters of ADRC using Reinforcement Learning (RL) based on Deep Deterministic Policy Gradient (DDPG) for a Differential Drive Mobile Robot (DDMR). The RL agent learns the ideal parameters of the ADRC through real-time, iterative interactions with the simulated environment, improving ADRC's performance without manual tuning. Simulation results demonstrate the effectiveness of the proposed idea in improving the trajectory tracking performance. Combining RL and ADRC provides a promising automated controller tuning solution, opening the door to more intelligent and adaptive robotic systems. 10.0pt.

关键词： Robust control Trajectory tracking Simulation Reinforcement learning Manuals Scattering parameters Mobile robots Artificial intelligence State estimation Tuning

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On the Outage of Far-Reach Communications via RIS-Empowered Satellites

On the Outage of Far-Reach Communications via RIS-Empowered ...

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IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： Fan Wang Ruihong Jiang Yuan Liu Tingnan Bao Mugen Peng State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Zhejiang Laboratory Research Center for Space Computing System Hangzhou China School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada

ISBN: (数字)9798350362312

ISBN: (纸本)9798350362329

The rising demand for reliable, high-bandwidth satellite communications in far-reach areas drives the integration of low earth orbit (LEO) satellites into future 6G networks. In this paper, we investigate the deployment of reconfigurable intelligent surface (RIS) technology and rate splitting multiple access (RSMA) within LEO satellite systems to improve communication quality and system capacity. We derive closed-form expressions for outage probability (OP) and reliable throughput that validate the theoretical advantages of these technologies under various signal-to-noise ratio conditions. Numerical results demonstrate that, compared with traditional space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) approaches, our RSMA and RIS-integrated framework significantly can reduce OP and enhance reliable throughput with an appropriate power-splitting factor, showcasing its superiority in RIS-enabled satellite communication scenarios.

关键词： NOMA Satellites Closed-form solutions computer network reliability Low earth orbit satellites Reconfigurable intelligent surfaces Reliability theory Throughput Multiaccess communication Satellite communications

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Task Offloading and Primary Node Selection in Blockchain, Digital Twin, and MEC Enabled Internet of Vehicles 100

Task Offloading and Primary Node Selection in Blockchain, Di...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Du, Jianbo Fang, Huifang Li, Shulei Du, Pengfei Kong, Ziwen Kang, Jiawen Niyato, Dusit Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security School of Communications and Information Engineering Xi'an China Xidian University School of Communications Engineering Xi'an710071 China Tianyuan Ruixin Communication Technology Co. LTD. Xi'an710071 China Xihua University Engineering Research Center of Intelligent Airground Integrated Vehicle and Traffic Control Ministry of Education Chengdu610039 China Guangdong University of Technology School of Automation China Nanyang Technological University School of Computer Science and Engineering Singapore

ISBN: (纸本)9798331517786

In this paper, we investigate the safe task offloading and primary node selection in blockchain, digital twin (DT) and Multi-access Edge Computing (MEC) enabled Internet of Vehicles (IoV). Edge servers centers provide computing power for task processing for Mobile Vehicles (MVs), while blockchain can provide security guarantees for MVs during task offloading. Based on the above system, we propose a joint optimization scheme for vehicle task offloading decision and the Practical Byzantine Fault Tolerance (PBFT) consensus process. Due to the large number of optimization variables and constraints, the problem becomes more complex. Traditional convex optimization and dynamic programming methods are difficult to effectively solve this problem. To address this issue, we propose a deep reinforcement learning based algorithm that utilizes Proximal Policy Optimization (PPO). The experimental results show that the algorithm proposed in this paper outperforms the benchmark algorithm in terms of convergence and other aspects. © 2024 IEEE.

关键词： Dynamic programming

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Stability Analysis and Performance Evaluation of Delayed Bilateral Telerobotic Systems over a Lossy Communication Channel

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Journal of Systems Science & Complexity 2021年第1期34卷 157-179页

作者： BAKHSHI Ali ALFI Alireza TALEBI Heidar Ali SOURATGAR Amir Aboulfazl YOUSEFI Mahdi Faculty of Electrical and Robotic Engineering Shahrood University of TechnologyShahrood 36199-95161Iran Power Plants Control Systems Technology Development Plan Department of monitoring and ControlNiroo Research InstituteTehran 14665-517Iran Real-Time and Robotics system Laboratory Faculty of Electrical EngineeringAmirkabir University of TechnologyHafez AvenueTehran 15914Iran Electrical and Computer Engineering Department The University of British Columbia2385East MallVan couverBC V6T 1Z4Canada

The focus of this paper is to address a novel control technique for stability and transparency analysis of bilateral telerobotic systems in the presence of data loss and time delay in the communication channel. Different control strategies have been reported to compensate the effects of time delay in the communication channel;however, most of them result in poor performance under data loss. First, a model for data loss is proposed using a finite series representation of a set of periodic continuous *** improve the performance and data reconstruction, a holder circuits is also introduced. The passivity of the overall system is provided via the wave variable technique based on the proposed model for the data loss. The stability analysis of the system is then derived using the Lyapunov theorem under the time delay and the data loss. Finally, experimental results are given to illustrate the capability of the proposed control technique.

关键词： Lossy channel passivity stability telerobotic transparency

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Robotic Teleoperation control Using PSO-Tuned Fractional Order Active Disturbance Rejection

Robotic Teleoperation Control Using PSO-Tuned Fractional Ord...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Omar Gad R. Fareh J. Ghommam M. Nasir S. Khadraoui M. Bettayeb Dept. of Electrical Engineering University of Sharjah UAE Research Inst. of Sciences and Engineering University of Sharjah UAE Dept. of Electrical and Computer Engineering Sultan Qaboos University Oman Control and Energy Management Laboratory (CEM Lab) Ecole National d'Ingenieur de Sfax Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Bilateral teleoperation systems have become essential for enabling precise remote manipulation in fields such as robotic surgery and hazardous material handling. However, these systems face significant challenges, including time delays, environmental uncertainties, and nonlinear dynamics, which can affect their stability and performance. This research aims to investigate the application of Active Disturbance Rejection control (ADRC) to address these challenges. ADRC is chosen for its real-time estimation and compensation for disturbances, even with limited knowledge of the system model. Additionally, the study incorporates enhancements such as Fractional-Order control and optimization techniques, including Particle Swarm Optimization (PSO), for parameter tuning. A simulation study is conducted to assess the performance of the proposed controller in tracking control of bilateral teleoperation systems with 3-DOF and 4-DOF manipulators. Results illustrate the superiority of the fractional order ADRC in disturbance rejection and trajectory tracking compared to linear ADRC, making it a promising solution for teleoperation applications.

关键词： Robust control Uncertainty Trajectory tracking Simulation 3-DOF Surgery Manipulators Stability analysis Particle swarm optimization Tuning

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Stable control and Disturbance Rejection Strategy for Planar 2R Underactuated Robot via Intelligent Algorithm 48

Stable Control and Disturbance Rejection Strategy for Planar...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Huang, Zixin Wan, Xiao Zhou, Yaosheng Wang, Lejun Wang, Liheng School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Institute of Technology School of Electrical and Information Engineering Wuhan China Wuhan Institute of Technology School of Innovation and Entrepreneurship Wuhan China Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Stable control and active disturbance rejection strategy is proposed for planar 2R underactuated robot via intelligent algorithm in this paper. At first, we build the dynamic model and describe the control characteristic. After that, we design PD controller for the active link. According to the underactuated constraint, we then optimize the parameters of controller by using the differential evolution algorithm (DEA), so that we can ensure the target states of all links could eventually be reached at the identical time. And the simulation results indicate the strategy is effective. © 2022 IEEE.

关键词： Disturbance rejection

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Full-Duplex Communication for ISAC: Joint Beamforming and Power Optimization

Full-Duplex Communication for ISAC: Joint Beamforming and Po...

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作者： He, Zhenyao Xu, Wei Shen, Hong Ng, Derrick Wing Kwan Eldar, Yonina C. You, Xiaohu Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China The University of New South Wales School of Electrical Engineering and Telecommunications SydneyNSW2052 Australia Weizmann Institute of Science Faculty of Mathematics and Computer Science Rehovot7610001 Israel

Beamforming design has been widely investigated for integrated sensing and communication (ISAC) systems with full-duplex (FD) sensing and half-duplex (HD) communication, where the base station (BS) transmits and receives radar sensing signals simultaneously while the integrated communication operates in either downlink or uplink. To achieve higher spectral efficiency, in this paper, we extend existing ISAC beamforming design to a general case by considering the FD capability for both radar and communication. Specifically, we consider an FD ISAC system, where the BS performs target detection and communicates with multiple downlink users and uplink users reusing the same time and frequency resources. We jointly optimize the downlink dual-functional transmit signal and the uplink receive beamformers at the BS and the transmit power at the uplink users. The problems are formulated under two criteria: power consumption minimization and sum rate maximization. The downlink and uplink transmissions are tightly coupled due to both the desired target echo and the undesired interference received at the BS, making the problems challenging. To handle these issues in both cases, we first determine the optimal receive beamformers in closed forms with respect to the BS transmit beamforming and the user transmit power. Subsequently, we invoke these results to obtain equivalent optimization problems and propose iterative algorithms to solve them. In addition, we consider a special case under the power minimization criterion and propose an alternative low complexity design. Numerical results demonstrate that the optimized FD communication-based ISAC brings tremendous improvements in terms of both power efficiency and spectral efficiency compared to the conventional ISAC with HD communication. © 1983-2012 IEEE.

关键词： Signal to noise ratio

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When Sign Language Meets Semantic Communications 35

When Sign Language Meets Semantic Communications

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Kouvakis, Vasileios Trevlakis, Stylianos E. Boulogeorgos, Alexandros-Apostolos A. Tsiftsis, Theodoros Singh, Keshav Qi, Nan InnoCube P.C. Department of Research and Development 17th Noemvriou 79 Thessaloniki55535 Greece University of Western Macedonia Department of Electrical and Computer Engineering Kozani50100 Greece University of Thessaly Department of Informatics & Telecommunications Lamia35100 Greece Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Nanjing210016 China

ISBN: (纸本)9798350362244

This paper presents an American sign language (ASL) semantic communications scheme. The scheme consists of a semantic encoder that leverages a convolutional neural network to effectively utilize the ASL alphabet. The encoded information is transmitted with the 24-QAM quadrature amplitude modulation (QAM). Additionally, this paper introduces a dataset that involves the overlaying of red-green-blue landmarks and key-points onto the acquired images, thereby augmenting the depiction of hand posture. The quantification of the proposed system's training, testing, and communication performance is accomplished through numerical results, which serve to emphasize the attainable benefits and stimulate meaningful discussions. © 2024 IEEE.

关键词： Quadrature amplitude modulation

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