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

作者： Dai, Pham Duc Viet, Nguyen Hoang Thuyloi University Department of Control Engineering and Automation Hanoi Viet Nam

ISBN: (数字)9781665495356

ISBN: (纸本)9781665495356

Water loss occurring in water distribution systems (WDSs) can be reduced by regulating operations of Pressure Reducing Valves (PRVs) installed in WDSs. This practical problem can be casted into a nonlinear program (NLP). The quality control of WDSs depends on how fast the solution of the NLP is deduced. It is due to the fact that solving such the optimization normally requires a large computation time, the fully accurate solution of the NLP is thus not suitable for real time control. In this paper, we applied the sensitivity-based method for deriving the real time pressure settings for PRVs, which is appropriate for real time control of the WDS. One benchmark WDS is taken for optimal pressure control to demonstrate the efficacy of the sensitivity-based method. The results have shown that the real time solution by the sensitivity-based method while requiring a negligible time computation have acceptable accuracy. © 2022 IEEE.

关键词： Water distribution systems

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Drone-Based Predictive Structure Analysis: A Review

Drone-Based Predictive Structure Analysis: A Review

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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Patil, Trushant Nandan, Durgesh Sharma, Kanhaiya Parashar, Deepak Department of Robotics and Automation Pune India Department of Electronics and Telecommunication Engg. Pune India Department of Computer Science & Engineering Pune India Faculty of Engineering Pune India

ISBN: (纸本)9798350329186

Drone-based predictive structure analysis is a rapidly growing field that has the potential to revolutionize infrastructure and building inspection. In this review of the research, we give a general overview of how drones could increase the effectiveness and precision of structural analysis, particularly for keeping an eye on difficult-to-reach locations. The usage of drones for 3D mapping, inspection, and monitoring of diverse constructions, such as concrete buildings, bridges, tunnels, and dams. The investigations show that drone-based inspection can produce 3D models and high-resolution photos, allowing for remote monitoring and the early identification of possible problems. The findings show that drones may greatly boost infrastructure management's safety and effectiveness, making them an important tool for predictive structural research. © 2023 IEEE.

关键词： Drones

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Circularity Reinforcement of Critical Raw Materials in Europe: A Case of Niobium

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Circular Economy and Sustainability 2024年第4期4卷 2449-2472页

作者： von Rennenberg, Theresa Yu, Yifei Fraccascia, Luca Yazan, Devrim Murat Department of Industrial Engineering and Business Information Systems University of Twente Drienerlolaan 5 Enschede 7522 NB Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy

Critical Raw Materials attract increasing attention due to their depleting reserves and low recyclability. Niobium, one of the most rare and vital elements, is primarily found in Brazil. This research explores the potential impact of Circular Economy (CE) strategies on mitigating niobium's criticality within Europe. First, a niobium supply chain is designed and analysed by Enterprise Input–Output modelling. Second, the supply risk is calculated based on the criticality matrix proposed by the European Commission under three scenarios associated with resources, technologies, and policies. The results show that urban mining is a potential solution to reduce niobium’s criticality and mitigate its environmental impacts. A higher recycling input rate and/or a mix of recycling and substitution strategies is necessary to offset niobium’s criticality. Aligned with the CE action plan, the research offers a scientific foundation to strategically prevent the risk of niobium supply shortages. © The Author(s) 2024.

关键词： Circular economy Critical raw materials Enterprise input–output Niobium supply chain Scenario analysis

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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 2024年第9期9卷 5435-5447页

作者： Duo, Wenli Wang, Shouguang Zhou, MengChu You, Dan Winiewski, Remigiusz Bazydlo, Grzegorz Albeshri, Aiiad Macau University of Science and Technology Institute of Systems Engineering 999078 China Zhejiang Gongshang University School of Information and Electronic Engineering Hangzhou310018 China New Jersey Institute of Technology Helen and John C. Hartmann Department of Electrical and Computer Engineering NewarkNJ07102 United States University of Zielona Góra Institute of Control and Computation Engineering Zielona Góra65-516 Poland King Abdulaziz University Department of Computer Science Jeddah21481 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. © 2016 IEEE.

关键词： Discrete event simulation

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A Day-Ahead Market Clearing Model Under System Inertia Constraints 16

A Day-Ahead Market Clearing Model Under System Inertia Const...

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16th IEEE PES Asia-Pacific Power and Energy engineering Conference, APPEEC 2024

作者： Ma, Yuting Jin, Jiangliang Hao, Liangliang Huang, Qisheng Shen, Liye College of Information Scienc and Technology Donghua University Shanghai China Shandong University Department of Control Science and Engineering Shandong China School of Mechanical Engineering and Automation Harbin Institute of Technology Shanghai China

ISBN: (纸本)9798350386127

We study the market clearing model for electric energy, inertia, and reserve in the day-ahead market, with a particular focus on the virtual inertia provided by wind units. In this paper, we consider synchronous inertia and virtual inertia as sources of system inertia. We incorporate system inertia constraints into the unit commitment (UC) and the economic dispatch (ED) models, and assign economic value to virtual inertia, so as to incentivize wind power to provide virtual inertia. Numerical results demonstrate that the proposed model enhances the participation of wind power units, increases the wind utilization rate and reduces the total costs. © 2024 IEEE.

关键词： Wind power

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Formation control and Sub-Swarm Generation of Multirotor UAVs

Formation Control and Sub-Swarm Generation of Multirotor UAV...

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2023 International Conference on Robotics and automation in Industry, ICRAI 2023

作者： Shahzad, Muhammad Muzamal Asad, Muhammad Haroon Haris, Muhammad Munawar, Hammad Yousaf, Muhammad Haroon University of Engineering and Technology Taxila Swarm Robotics Lab National Center of Robotics and Automation Taxila Pakistan University of Engineering and Technology Taxila Computer Engineering Department Taxila Pakistan

ISBN: (纸本)9781665464727

The research field of collective behaviors takes inspiration from natural self-organizing systems like honeybees, fish schools, social insects, bird flocks, and other social animals. These behaviors can be transformed into robots by replicating the same set of rules as found in the natural swarms. The deployment of aerial swarm robotics has become significant due to their multiple applications in surveillance, agriculture, and military. These applications lead to the development of aerial swarm robotic platforms to solve real-world problems. For example, a swarm of low-tech, cost-effective small UAVs can engage a high-tech target effectively. Similarly, a swarm of UAVs can perform surveillance and rescue missions in disastrous areas and build an emergency communication network through multiple UAV swarms. The critical part of swarm technology is multiple swarm intelligence algorithms that have been proposed and tested by various simulation platforms such as V-rep, Gazebo and MATLAB. Very few of them have been deployed on hardware to solve real scenarios that include formation control, navigation, pattern formation, and a few sub-swarm generation algorithms. Team connectivity is one of the essential aspects of a swarm network that emerges the collective intelligence of the group and ensures the readiness of the algorithm to deploy and solve real-world problems. Many researchers proposed the team connectivity algorithms in a single swarm network but still left the connectivity gap between the sub-swarms during a mission. This research work contributes toward designing a swarm intelligence algorithm to improve the connectivity techniques and team connectivity between the swarm agents and the sub-swarm groups. © 2023 IEEE.

关键词： Antennas

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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

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Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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Modeling of Improved Solar Energy Installation for Efficient Power Systems 14

Modeling of Improved Solar Energy Installation for Efficient...

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14th International Conference on Advanced computer Information Technologies, ACIT 2024

作者： Satsyk, Viktor Reshetylo, Oleksandr Markina, Lyudmila Khrystynets, Nataliia Bahniuk, Nataliia Melnychuk, Yuliia Lutsk National Technical University Automation and Computer-Integrated Technologies Department Lutsk Ukraine Lutsk National Technical University Department of Automation and Computer-Integrated Technologies Lutsk Ukraine Lutsk National Technical University Computer Engineering and Cyber Security Department Lutsk Ukraine Lutsk National Technical University Department of Computer Engineering and Cyber Security Lutsk Ukraine Lutsk National Technical University Department of Digital Educational Technologies Lutsk Ukraine

ISBN: (纸本)9798350350036

in the article we develop modeling and creating a prototype of improved solar power plant for economical power supply systems for consumers which require simple autonomous inexpensive practical energy solutions. On the basis of Arduino Uno microcontroller board, a software-hardware complex for controlling the angle of the solar panel has been developed, which allows to follow the position of sun and automatically turn the solar panel in its direction. With aid of developed Android application on a smartphone screen, it is possible to monitor the amount of voltage produced by the solar panel at current time moment, and to analyze the dynamics of its change over time and, accordingly, to plan effective use the generated energy. © 2024 IEEE.

关键词： Hybrid power

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A Three-Dimensional Force Estimation Method for the Cable-Driven Soft Robot Based on Monocular Images

A Three-Dimensional Force Estimation Method for the Cable-Dr...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Zhu, Xiaohan Bu, Ran Li, Zhen Xu, Fan Wang, Hesheng School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Automation China Artificial Intelligence Research Institute School of Information and Control Engineering China University of Mining and Technology China

ISBN: (纸本)9781665481090

Soft manipulators are known for their superiority in coping with high-safety-demanding interaction tasks, e.g., robot-assisted surgeries, elderly caring, etc. Yet the challenges residing in real-time contact feedback have hindered further applications in precise manipulation. This paper proposes an end-to-end network to estimate the 3D contact force of the soft robot, with the aim of enhancing its capabilities in interactive tasks. The presented method features directly utilizing monocular images fused with multidimensional actuation information as the network inputs. This approach simplifies the preprocessing of raw data compared to related studies that utilize 3D shape information for network inputs, consequently reducing configuration reconstruction errors. The unified feature representation module is devised to elevate low-dimensional features from the system's actuation signals to the same level as image features, facilitating smoother integration of multimodal information. The proposed method has been experimentally validated in the soft robot testbed, achieving satisfying accuracy in 3D force estimation (with a mean relative error of 0.84% compared to the best-reported result of 2.2% in the related works). © 2024 IEEE.

关键词： Robotic surgery

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Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

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computer Systems Science & engineering 2023年第5期45卷 1469-1482页

作者： Doaa Sami Khafaga Amel Ali Alhussan Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mohamed Saber El-Sayed M.El-kenawy Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electronics and Communications Engineering Department Faculty of EngineeringDelta University for Science and TechnologyMansouraEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Arrhythmia has been classified using a variety of *** of the dynamic nature of electrocardiogram(ECG)data,traditional handcrafted approaches are difficult to execute,making the machine learning(ML)solutions more *** with cardiac arrhythmias can benefit from competent monitoring to save their *** arrhythmia classification and prediction have greatly improved in recent *** are a category of conditions in which the heart's electrical activity is abnormally rapid or *** year,it is one of the main reasons of mortality for both men and women,*** the classification of arrhythmias,this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors(KNN)*** proposed method makes advantage of the UCI repository,which has a 279-attribute high-dimensional cardiac arrhythmia *** proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s *** purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia *** method of comprehensive arrhythmia classification outperforms earlier methods presented in the *** achieved classification accuracy using the proposed approach is 99.8%.

关键词： Feature selection electrocardiogram metaheuristics dipper throated algorithm

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