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5th International Conference on System Reliability and Safety engineering, SRSE 2023

作者： Liu, Weiming Chen, Cen Wang, Zhifei Zhang, Xiaosheng Zhai, Guofu Zheng, Wei Engineering & Automation Harbin Institute of Technology Department of Electrical Harbin China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9798350305944

The energy meter is a widely used digital-analog electronic system. However, metering accuracy is inevitably influenced by factors such as ambient temperature, load current, and component tolerance. This paper introduces a method utilizing digital twin models to analyze the consistency of metering accuracy in a new single-phase smart meter prototype. An electro-thermal coupling model incorporating a temperature compensation algorithm is established, and the metering accuracy is solved using a surrogate model. By employing the Monte Carlo method, a batch of product samples is generated to determine the impact of varying ambient temperature and load current conditions on the metering accuracy's consistency within the maximum operating range. The results of this study provides a valuable foundation for robust design and reliability optimization of the energy meter. © 2023 IEEE.

关键词： Smart meters

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Elimination of Digital Delay Effect on Rotor Position for Two-Step Finite control Set MPCC Used in PMSMs 49

Elimination of Digital Delay Effect on Rotor Position for Tw...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Liu, Jinglin Gong, Chao Ge, Lefei School of Automation Northwestern Polytechnical University Xi'an China University of Alberta Department of Electrical and Computer Engineering Edmonton Canada

ISBN: (纸本)9798350331820

This paper proposes a novel concept to eliminate the digital delay effect on rotor position for the traditional two-step finite control set model predictive current control (FCS-MPCC) method used in the PMSMs. Specifically, that the digital delay affects the position, and further the prediction accuracy is discussed firstly, posing the necessity of compensating the position used for control. Then, a speed-prediction-based linear compensation method which takes the speed shift trend into account is proposed to eliminate the digital delay impact on position, which is conducive to the control performance. Finally, simulation is conducted on a three-phase PMSM to validate the proposed strategy in comparison with the traditional two-step FCS-MPCC. © 2023 IEEE.

关键词： Model predictive control

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Intelligent On-Line System for Monitoring Technical Condition of High-Voltage Cable Couplings

Intelligent On-Line System for Monitoring Technical Conditio...

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2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Gasiyarov, Vadim R. Voronin, Stanislav V. Radionov, Andrey A. Lyubimov, Ivan V. Evdokimov, Sergey A. Khramshin, Vadim R. Moscow Polytechnic University Department of Automation and Control Moscow Russia South Ural State University Department of Mechatronics and Automation Chelyabinsk Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (纸本)9798350395044

The article provides the characteristics of the end cable couplings of the closed switchgear 110 kV at the electric steelmaking workshop of the metallurgical plant. The functions of the continuous technical condition monitoring system are substantiated, including continuous temperature monitoring and on-line registration of partial discharges in the insulation. The first function provides monitoring of the operational load, and the second has the maximum sensitivity for diagnosing defect propagation. A functional diagram of the developed intelligent on-line system for monitoring technical condition with digital signal transmission is provided. The choice of sensors and processor unit is justified. The authors consider the temperature control system of high-voltage equipment 'WDM-T', including a wireless sensor and an information receiver. The results of monitoring the thermal regime are provided, the advantages of partial discharge analysis are pointed out. The temperature trends of the end couplings included in the cable line phases are considered. The system is implemented on the closed switchgear 110 kV end couplings, its long-term operation has confirmed the effectiveness of technical condition monitoring. The developed system may be a component of an on-line cyberphysical system for monitoring the condition of high-voltage equipment in the electric steelmaking workshop. © 2024 IEEE.

关键词： Electric lines

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Short-Term Traffic Flow Prediction of Highway Tunnels Based on SSA and Improved TSK Fuzzy System

Short-Term Traffic Flow Prediction of Highway Tunnels Based ...

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2023 China automation Congress, CAC 2023

作者： Huang, Zhijing Chen, Kang Xu, Zhezhuang Zeng, Qinbo Xu, Zhibin College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350303759

Aiming at the problem that the traffic flow has an low prediction accuracy due to varying randomness and high nonlinearity, an improved TSK fuzzy neural network prediction model by singular spectrum analysis is ***, the original traffic flow time series can be decomposed into several subseries by singular spectrum analysis (SSA). Then, the Takagi-Sugeno-Kang (TSK) fuzzy system was trained using simulated annealing genetic algorithm (SAGA) and minibatch gradient descent method (MBGD) combined with three techniques (RDA) of regularization, DropRule and *** prediction model of TSK fuzzy neural network is established to predict each subseries independently, and the forecasted traffic flow is obtained by superimposing the prediction results of each subseries. Finally, the traffic flow dataset of expressway tunnels in a city is used to verify the effectiveness of the model. Experimental results can show high traffic flow prediction accuracy of the model, and the model can accurately predict multiple different highway tunnels. © 2023 IEEE.

关键词： Forecasting

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Facial Expression Recognition Model Depending on Optimized Support Vector Machine

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computers, Materials & Continua 2023年第7期76卷 499-515页

作者： Amel Ali Alhussan Fatma M.Talaat El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Mona Alnaggar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Machine Learning&Information Retrieval Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Robotics and Intelligent Machines Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt

In computer vision,emotion recognition using facial expression images is considered an important research *** learning advances in recent years have aided in attaining improved results in this *** to recent studies,multiple facial expressions may be included in facial photographs representing a particular type of *** is feasible and useful to convert face photos into collections of visual words and carry out global expression *** main contribution of this paper is to propose a facial expression recognitionmodel(FERM)depending on an optimized Support Vector Machine(SVM).To test the performance of the proposed model(FERM),AffectNet is *** uses 1250 emotion-related keywords in six different languages to search three major search engines and get over 1,000,000 facial photos *** FERM is composed of three main phases:(i)the Data preparation phase,(ii)Applying grid search for optimization,and(iii)the categorization *** discriminant analysis(LDA)is used to categorize the data into eight labels(neutral,happy,sad,surprised,fear,disgust,angry,and contempt).Due to using LDA,the performance of categorization via SVM has been obviously *** search is used to find the optimal values for hyperparameters of SVM(C and gamma).The proposed optimized SVM algorithm has achieved an accuracy of 99%and a 98%F1 score.

关键词： Facial expression recognition machine learning linear dis-criminant analysis(LDA) support vector machine(SVM) grid search

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Automatic generation of repair suggestions for overall I&C architecture represented with an ontology 28

Automatic generation of repair suggestions for overall I&C a...

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Ovsiannikova, Polina Pakonen, Antti Vyatkin, Valeriy VTT Technical Research Centre of Finland Ltd. Espoo Finland Aalto University Department of Electrical Engineering and Automation Espoo Finland Luleiå Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden

ISBN: (纸本)9798350339918

We present an approach for suggesting possible fixes to an overall I&C nuclear architecture during its design phase. Despite the I&C architecture, in our case, being represented with an ontology, we do not aim to change the properties of an ontology per se. Instead, we focus on the subset of ABox triples that do not contain terminological elements in either subject, predicate, or object parts. Such a subset we call the design artifacts. When the ontology is filled with the design artifacts, the analyst runs the check of non-functional requirements using SPARQL queries. The requirements associated with the queries that returned results do not hold. The goal of the current work is to provide support for the next stage when the analyst has to change the design artifacts so that the queries no longer return results. Our method is based on representing the results of queries as graphs, intersecting them, and finding the minimal changes that prevent the results from being mapped on their (or other) queries. © 2023 IEEE.

关键词： Ontology

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Multi-party secure communication using blockchain over 5G

Multi-party secure communication using blockchain over 5G

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Archana, K. Kareem, Z.H. Al-Farhani, Liwa H. Bagyalakshmi, K. Jenvi, Ignatia K. Majella Kumar, Ashok Department of Computer Engineering Pimpri Chinchwad College of Engineering and Research Maharashtra Pune India Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq System Analysis Control and Information Processing dep Academy of Engineering RUDN University Moscow Russia Sri Ranganathar Institute of Engineering and Technology Coimbatore India Mathematics Department Saveetha School of Engineering SIMATS Saveetha Nagar Chennai India Department of Computer Science Banasthali Vidyapith Rajasthan Banasthali India

ISBN: (纸本)9781032669663

One of the most critical problems facing the blockchain technology industry right now is how to protect the privacy of users’ data on the blockchain in a way that is both effective and cheap. Based on the Pedersen commitment and the Schnorr protocol, this study comes up with a secure multi-party computing protocol (BPLSM). By making the structure of the protocol and doing formal proof calculations, it has been shown that the protocol can be used in the blockchain network to combine private messages for efficient signing while keeping people’s identities secret. Furthermore, by looking at the nature and security of the protocol, it is also possible to find that the BPLSM protocol on the blockchain has a low cost of computing and a high level of information secrecy. Furthermore, it was found that the BPLSM protocol takes less time to check than the current mainstream BLS signature in a simple multi-party transaction with a fixed number of participants. © 2024 The Author(s).

关键词： Blockchain

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SpikeNAS-Bench: Benchmarking NAS Algorithms for Spiking Neural Network Architecture

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第6期6卷 1614-1625页

作者： Sun, Genchen Liu, Zhengkun Gan, Lin Su, Hang Li, Ting Zhao, Wenfeng Sun, Biao Tianjin University School of Electrical and Information Engineering Tianjin300072 China Northwestern Polytechnical University School of Automation Xi'an710072 China Politecnico di Milano Department of Electronics Information and Bioengineering Milan20133 Italy Chinese Academy of Medical Science Institute of Biomedical Engineering Pecking Union Medical College Tianjin300020 China Binghamton University Department of Electrical and Computer Engineering State University of New York BinghamtonNY United States

In recent years, Neural Architecture Search (NAS) has marked significant advancements, yet its efficacy is marred by the dependence on substantial computational resources. To mitigate this, the development of NAS benchmarks has emerged, offering datasets that enumerate all potential network architectures and their performances within a predefined search space. Nonetheless, these benchmarks predominantly focus on convolutional architectures, which are criticized for their limited interpretability and suboptimal hardware efficiency. Recognizing the untapped potential of Spiking Neural Networks (SNNs) - often hailed as the third generation of neural networks for their biological realism and computational thrift - this study introduces SpikeNAS-Bench. As a pioneering benchmark for SNN, SpikeNAS-Bench utilizes a cell-based search space, integrating leaky integrate-and-fire (LIF) neurons with variable thresholds as candidate operations. It encompasses 15,625 candidate architectures, rigorously evaluated on CIFAR10, CIFAR100 and Tiny-ImageNet datasets. This paper delves into the architectural nuances of SpikeNAS-Bench, leveraging various criteria to underscore the benchmark's utility and presenting insights that could steer future NAS algorithm designs. Moreover, we assess the benchmark's consistency through three distinct proxy types: zero-cost-based, early-stop-based, and predictor-based proxies. Additionally, the paper benchmarks seven contemporary NAS algorithms to attest to SpikeNAS-Bench's broad applicability. We commit to providing training logs, diagnostic data for all candidate architectures, and the promise to release all code and datasets post-acceptance, aiming to catalyze further exploration and innovation within the SNN domain. SpikeNAS-Bench is open source at https://***/XXX (hidden for double anonymous review). © 2020 IEEE.

关键词： HTTP

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Exploring Innovations in Autonomous Robotics and Mechatronics: Application in Manufacturing and Healthcare 5

Exploring Innovations in Autonomous Robotics and Mechatronic...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Shalini, T.Grace Ganeshabu, L. Chemudugunta, Priyanka Yamsani, Nagendar Kumar, Ch.Ashok Athiraja, A. School of Computing Department of Computational Intelligence Chengalpattu Tamil Nadu Kattankulathur India Rajalakshmi Engineering College Department of Robotics and Automation Thandalam Mevalurkuppam Rajalakshmi Nagar Tamil Nadu Chennai India Karpaga Vinayaga College of Engineering and Technology Department of Robotics and Automation Tamil Nadu Chengalpattu India Sr University Department of School of Computer Science and Artificial Engineering Warangal India Malla Reddy Engineering College Department of Mechanical Engineering Main Campus Hyderabad Telangana Maisammaguda India Telangana Secunderabad India

ISBN: (纸本)9798331504403

Autonomous robotics and mechatronics have drastically changed the manufacturing and healthcare sectors by increasing productivity, precision, and flexibility. This work addresses the pressing need for new methods to advance these sectors by merging intelligent algorithms with autonomous systems. A hybrid strategy was employed, combining Deep Reinforcement Learning (DRL) and Adaptive control Systems (ACS), to develop and optimize robotic operations. Extensive studies were conducted to assess the success of this strategy, which demonstrated a 25% reduction in operating expenses and a 30% increase in production efficiency in manufacturing settings. The method produced a precision rate of about 99% in the healthcare industry, which is significantly better than the 93% average of current systems. It also reduced patient recovery times by an estimated 20%. These results highlight the improved performance and promise of ACS with DRL combination in autonomous robotics, which may have revolutionary implications for the manufacturing and healthcare industries. The success, highlighted by economic and medical benefits, demonstrates the efficacy of our methodology and provides a strong platform for future developments in autonomous robotics and mechatronics. © 2024 IEEE.

关键词： Deep reinforcement learning

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Passive Attack Detection for a Class of Stealthy Intermittent Integrity Attacks

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 898-915页

作者： Kangkang Zhang Christodoulos Keliris Thomas Parisini Bin Jiang Marios M.Polycarpou Department of Electrical and Electronic Engineering Imperial College LondonLondon SW72AZUKand also with the KIOS Research and Innovation Center of ExcellenceUniversity of CyprusNicosia 1678Cyprus KIOS Research and Innovation Center of Excellence and the Department of Electrical and Computer Engineering University of CyprusNicosia 1678Cyprus Department of Electrical and Electronic Engineering Imperial College LondonLondon SW72AZUK Department of Engineering and Architecture University of TriesteTrieste 34127Italy KIOS Research and Innovation Center of Excellence University of CyprusNicosia 1678Cyprus College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

This paper proposes a passive methodology for detecting a class of stealthy intermittent integrity attacks in cyberphysical systems subject to process disturbances and measurement noise.A stealthy intermittent integrity attack strategy is first proposed by modifying a zero-dynamics attack *** stealthiness of the generated attacks is rigorously investigated under the condition that the adversary does not know precisely the system state *** order to help detect such attacks,a backward-in-time detection residual is proposed based on an equivalent quantity of the system state change,due to the attack,at a time prior to the attack occurrence time.A key characteristic of this residual is that its magnitude increases every time a new attack *** estimate this unknown residual,an optimal fixed-point smoother is proposed by minimizing a piece-wise linear quadratic cost function with a set of specifically designed weighting *** smoother design guarantees robustness with respect to process disturbances and measurement noise,and is also able to maintain sensitivity as time progresses to intermittent integrity attack by resetting the covariance matrix based on the weighting *** adaptive threshold is designed based on the estimated backward-in-time residual,and the attack detectability analysis is rigorously investigated to characterize quantitatively the class of attacks that can be detected by the proposed ***,a simulation example is used to demonstrate the effectiveness of the developed methodology.

关键词： Backward-in-time equivalent quantity fixed-point smoother intermittent integrity attacks

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