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Modeling and Channel Estimation for Piezo-Acoustic Backscatter Assisted Underwater Acoustic Communications

China Communications 2022年第11期19卷 297-307页

作者： Junliang Lin Gongpu Wang Zijian Zheng Ruyi Ye Ruisi He Bo Ai School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100091China School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100091China China National Institute of Standardization Beijing 100088China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100091China

Relying on direct and converse piezoelectric effects,piezo-acoustic backscatter(PAB)technology reflects ambient acoustic signals to enable underwater backscatter communications at near-zero power,which was first realized through a *** this paper,we propose a mathematical model of the PAB assisted underwater acoustic(UWA)communication,and address the sparse channel estimation ***,we present a five-stage backscatter process to derive the backscatter coefficient,and propose the channel model for the shallow-water ***,we formulate the shallow-water acoustic channel estimation problem as a sparse vector recovery one according to the compressed sensing theory,and leverage the orthogonal matching pursuit(OMP)algorithm to obtain the channel ***,simulation results are provided to corroborate our proposed studies.

关键词： channel estimation compressed sensing piezo-acoustic backscatter underwater acoustic communications

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Data Preprocessing with IRM for skill extraction using NMF 26

Data Preprocessing with IRM for skill extraction using NMF

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Oeda, Shinichi Iizumi, Shunsuke Department of Information and Computer Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Chiba Kisarazu Japan Advanced Course of Control and Information Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Chiba Kisarazu Japan

To provide examinees with appropriate question items, identifying and evaluating users' latent and acquired skills is important in e-learning systems. These latent skills are defined in terms of a Q-matrix. Constructing Q-matrices manually is relatively labor-intensive, because doing so requires expert insight as well as verbal examination to identify which skills students have mastered. Methods to extract a Q-matrix from examination results automatically using nonnegative matrix factorization (NMF) have been explored, and improved methods such as online NMF have been proposed, which extracts an immutable Q-matrix from time-series data. In this study, we propose a data preprocessing method to improve the accuracy of NMF using a co-clustering method called an infinite relational model (IRM). We also describe experiments conducted using synthetic data, in which learners'skills and the bias in the number of their responses were evaluated, and show that the results demonstrate the efficacy of the proposed approach. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022)

关键词： Non-negative matrix factorization

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QoI-Aware Configuration Adaptation and Heterogeneous Resource Allocation for Edge Video Analytics

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IEEE Internet of Things Journal 2025年第12期12卷 19215-19230页

作者： He, Zixuan Sun, Yanjing Zhang, Beibei Dong, Kaiwen Wang, Bowen Xu, Hongli China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China China University of Mining and Technology IoT Perception Mine Research Center Xuzhou221116 China School of Information and Control Engineering China University of Science and Technology of China School of Computer Science and Technology Anhui Hefei230027 China University of Science and Technology of China Suzhou Institute for Advanced Research Jiangsu Suzhou215123 China

Edge video analytics enables agile responses of machine-centric applications by streaming videos from end devices to edge servers (ESs) for resource-intensive Deep Neural Network (DNN) inference. Quality of Inference (QoI), reflected by end-to-end analytics delay and inference accuracy, is crucial for the high-quality real-time decision-making. Due to the limited ES resources and dynamic network conditions, video configuration adaptation and fine-grained resource allocation are necessary to enhance the QoI of video streams, which involves a delicate balance between delay and accuracy. In this paper, we propose an edge-enabled multi-video analytics framework, in which performing DNN inference relies on heterogeneous resources, including CPU, GPU, and memory. Considering the different impacts of heterogeneous resources on QoI and double-queue backlogs, we formulate the joint video configuration adaptation, CPU-GPU resource allocation, and batch size selection (JCCGB) problem based on semi-Markov Decision Process to maximize the long-term average QoI. Then, Lyapunov optimization is applied to transform the original problem into one that minimizes the Lyapunov drift-plus-penalty upper bound, thereby ensuring the stability of both the transmission and computation queues. To tackle the potential multimodality of the optimal configuration adaptation and resource allocation policy, we propose the diffusion deep reinforcement learning based JCCGB (DD-JCCGB) scheme. This approach effectively enhances the policy performance and accelerates the training process. Experiments driven by real-world network traces demonstrate that the DD-JCCGB algorithm improves the long-term average QoI and outperforms baseline schemes. © 2025 IEEE.

关键词： Markov processes

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Experimental study on the deformation and failure mechanism of overburden rock during coal mining using a comprehensive intelligent sensing method

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第5期14卷 1626-1641页

作者： Gang Cheng Wentao Xu Bin Shi Jinghong Wu Binyang Sun Honghu Zhu School of Computer Science North China Institute of Science and TechnologyBeijing101601China School of Earth Sciences and Engineering Nanjing UniversityNanjing210023China State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of TechnologyChengdu610059China School of Civil Engineering Suzhou University of Science and TechnologySuzhou215009China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and TechnologyHuainan232001China

Understanding the spatiotemporal evolution of overburden deformation during coal mining is still a challenge in engineering practice due to the limitation of monitoring techniques. Taking the Yangliu Coal Mine as an example, a similarity model test was designed and conducted to investigate the deformation and failure mechanism of overlying rocks in this study. Distributed fiber optic sensing(DFOS), highdensity electrical resistivity tomography(HD-ERT) and close-range photogrammetry(CRP) technologies were used in the test for comprehensive analyses. The combined use of the three methods facilitates the investigation of the spatiotemporal evolution characteristics of overburden deformation, showing that the mining-induced deformation of overburden strata was a dynamic evolution process. This process was accompanied by the formation, propagation, closure and redevelopment of separation ***, the key rock stratum with high strength and high-quality lithology played a crucial role in the whole process of overburden deformation. There were generally three failure modes of overburden rock layers, including bending and tension, overall shearing, and shearing and sliding. Shear failure often leads to overburden falling off in blocks, which poses a serious threat to mining safety. Therefore, realtime and accurate monitoring of overburden deformation is of great significance for the safe mining of underground coal seams.

关键词： Similarity model Distributed fiber optic sensing(DFOS) Overburden deformation Failure mechanism Coal seam mining

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The effect of PV modules on temperature conditions of nearby power cables

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Frontiers in Energy Research 2025年 13卷

作者： Czapp, Stanislaw Szultka, Seweryn Tomaszewski, Adam Khan, Laiq Faculty of Electrical and Control Engineering Gdansk University of Technology Gdansk Poland Institute of Fluid-Flow Machinery Polish Academy of Sciences Gdansk Poland Department of Electrical and Computer Engineering COMSATS University Islamabad Pakistan

The highest permissible load of power cables (ampacity) depends strongly on the ambient temperature, which in the case of cables surrounded by free air is generally assumed to be 25°C. Considering the installation of photovoltaic (PV) modules, the thermal conditions for the cables connected to these modules may be very unfavorable. The cables are laid under the module and the space underneath it is heated by this module. The aim of the paper is to present a numerical model of an example PV module mounted on the roof of a building, as well as the results of numerical calculations of the temperature around the module. Based on the numerical model of the PV system and advanced calculations it is possible to introduce a correction factor to determine the ampacity of the power cables located in the vicinity of the PV module. The authors’ research allows for the correct determination of the cable ampacity, avoiding its overheating and preventing the risk of fire. Copyright © 2025 Czapp, Szultka, Tomaszewski and Khan.

关键词： ampacity energy photovoltaic source power cable power system thermal effect

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Improvement of the Predictive control Method for the High-Level controller 17

Improvement of the Predictive Control Method for the High-Le...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer Engineering, TCSET 2024

作者： Budashko, Vitalii Sandler, Albert Glazeva, Oksana Educational and Scientific Institute of Automation and Electrical Engineering National University 'Odessa Maritime Academy' NUOMA Odesa Ukraine National University 'Odessa Maritime Academy' NUOMA Department of the theory of automatic control and computer technology Odesa Ukraine National University 'Odessa Maritime Academy' NUOMA Department of electrical engineering and electronics Odesa Ukraine

ISBN: (纸本)9798331520564

Automation of ship maneuvering in limited sailing conditions usually requires 100% redundancy of thrusters (THRs) of various modifications and their locations in accordance with the matrix. The hierarchy of the motion control system is branched by levels using high-level motion controllers and THRs control distribution algorithms, which allows for a modular design with software, where the high-level controller (HLC) can be designed without comprehensive information about the thruster motors, and the input signal branching and speed limits are handled by the motion controller. But, for certain THRs configurations, this branching leads to the decrease in control efficiency due to the limitation of data on the physical characteristics of the ships and the operation of the motion controller. This research examines different approaches to improving control efficiency using methods of nonlinear predictive control models as a basis for developing motion controllers with decision optimization based on relevant constraints. The implemented branched system is the result of solving two simple problems of ship's motion, which highlight the related problems. The use of different approaches to eliminate the identified shortcomings made it possible to develop the nonlinear controller that combines the motion controller with distributed control of the THRs and ensuring the certain level of system reliability. The modularity of the control system is provided by the expansion of the closed system, which made it possible to achieve an increase in efficiency during the combined mode of operation. The obtained solution of nonlinear control with time-varying constraints made it possible to increase the accuracy of the control with a decrease in the duration of the pause in response to the change of the disturbance within 10% © 2024 IEEE.

关键词： Predictive control systems

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Design and Implementation of Indoor Visual Autonomous Navigation System for Quadrotor UAV Based on Binocular Camera and IMU

Design and Implementation of Indoor Visual Autonomous Naviga...

引用

computer Science, Electronic Information Engineering and Intelligent control technology (CEI), IEEE International Conference on

作者： Jiaze Tang Tianxing Guo Liudan Junbao Li Jinwei Sun Wenbin Huang Qisong Wang Electrical Measurement technology and Intelligent Control Institute School of Instrumention Science and Engineering Harbin Institute of Technology Harbin China Schools of electronics and information Engineering Harbin Institute of Technology Harbin China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (数字)9798350372052

ISBN: (纸本)9798350372069

Addressing the challenge of unmanned aerial vehicles (UAVs) navigating indoors without satellite positioning, this study introduces a novel method combining binocular camera and inertial measurement unit (IMU) data. This approach overcomes the structural differences between visual and inertial information, integrating them effectively for enhanced indoor autonomous navigation. The research presents a gradient-free path planning framework, pivotal for enhancing the UAV's ability to execute efficient and stable flight in intricate indoor settings. The cornerstone of this system is an advanced path planning algorithm, adept at swiftly identifying optimal routes and adapting to environmental shifts. The system's efficacy was rigorously evaluated through simulations and real-world tests, confirming its precision in positioning and path planning without reliance on satellite data. The findings demonstrate the system's capacity for precise localization and effective route determination, utilizing an integration of visual and inertial inputs. This research significantly contributes to the autonomous flight capabilities of UAVs, offering a valuable reference for future UAV autonomous navigation systems. By delving into visual-inertial fusion navigation technology, the study paves the way for expanded indoor UAV applications.

关键词： Visualization Satellites Measurement units Inertial navigation Autonomous aerial vehicles Satellite navigation systems Path planning

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Research on Data Communication Monitoring System of Master and Slave Equipment in Avionics System Based on 1553B Bus 2

Research on Data Communication Monitoring System of Master a...

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2nd International Conference on Networking Systems of AI, INSAI 2022

作者： Zhu, Zhitian Fu, Yanfang Lu, Chengtao Qiao, Yongxing Cai, Zhipeng School of Weapon Science and Technological Xi'an Technological University Xi'an China School of Computer Science and Engineering Xi'an Technological University Xi'an China North-Automatic Control Technology Institute Taiyuan China

ISBN: (纸本)9781665491785

When the terminal sub-device sends data to the main device of the peer avionics system, it faces the related problems of data loss, blurred transmission, and format parsing errors. In response to these problems, this paper combs the basic concept and basic topology structure of the airborne bus 1553B applied to the master-slave equipment of the avionics system, analyzes the application method of the 1553B bus in the avionics system for high-efficiency and high-precision data transmission, and proposes an industrial control system. The scheme of optimizing data transmission between master and slave devices through 1553B bus access to the avionics system provides a new research idea for the development of data communication between master and slave devices in the real avionics system. The data communication monitoring system of the master-slave equipment of the electrical system will avoid risks for future real scenarios in terms of data analysis, data flow, and whether the transmission and reception are successful on the ground. © 2022 IEEE.

关键词： Data communication systems

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Risk-Averse Learning with Delayed feedback

arXiv

引用

arXiv 2024年

作者： Wang, Siyi Wang, Zifan Johansson, Karl H. Hirche, Sandra Department of Electrical and Computer Engineering Technical University of Munich Munich80333 Germany Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden

In real-world scenarios, the impacts of decisions may not manifest immediately. Taking these delays into account facilitates accurate assessment and management of risk in real-world environments, thereby ensuring the efficacy of strategies. In this paper, we investigate risk-averse learning using Conditional Value at Risk (CVaR) as risk measure, while incorporating delayed feedback with unknown but bounded delays. We develop two risk-averse learning algorithms that rely on one-point and two-point zeroth-order optimization approaches, respectively. The regret achieved by the algorithms is analyzed in terms of the cumulative delay and the number of total samplings. The results suggest that the two-point risk-averse learning achieves a smaller regret bound than the one-point algorithm. Furthermore, the one-point risk-averse learning algorithm attains sublinear regret under certain delay conditions, and the two-point risk-averse learning algorithm achieves sublinear regret with minimal restrictions on the delay. We provide numerical experiments on a dynamic pricing problem to demonstrate the performance of the proposed algorithms. © 2024, CC0.

关键词： Adversarial machine learning

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Reinforcement Learning-Based Fault-Tolerant control of Uncertain Strict-Feedback Nonlinear Systems With Intermittent Actuator Faults

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IEEE Transactions on Neural Networks and Learning Systems 2025年第6期36卷 10464-10478页

作者： Qinmin Yang Huaying Li Zhengwei Ruan Bo Fan Shuzhi Sam Ge State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Hangzhou Huawei Communication Technology Company Ltd. Hangzhou China School of Automation Science and Engineering Xi’an Jiaotong University Xi’an China Department of Electrical and Computer Engineering Institute for Functional Intelligent Materials National University of Singapore Queenstown Singapore

In this work, a novel reinforcement learning-based adaptive fault-tolerant control (FTC) scheme with actuator redundancy is presented for a nonlinear strict-feedback system with nonlinear dynamics and uncertainties. A learning-based switching function technique is established to steer different groups of actuators automatically and successively to mitigate the impact of faulty actuators by observing a switching performance index. The optimal tracking control problem (OTCP) of strict-feedback nonlinear systems is transformed into an equivalent optimal regulation problem of each affine subsystem via adaptive feedforward controllers. Subsequently, the designed objective functions associated with Hamilton–Jacobi–Bellman (HJB) estimate errors caused by neural network (NN) approximations can be minimized by the reinforcement learning algorithm without value or policy iterations. It is proved that the tracking objective can be achieved and all signals in the closed-loop system can be guaranteed to be bounded, as long as the minimum time interval between two successive failures is bounded. Theoretical results are verified by simulations.

关键词： Actuators Switches Fault tolerant systems control systems Optimal control Redundancy Nonlinear dynamical systems Adaptive control Regulation Industrial control

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