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Ontology-Based Semantic Reasoning for Multi-Source Heterogeneous Industrial Devices Using OPC UA

IEEE Internet of Things Journal 2025年

作者： Bi, Jing Wu, Rina Yuan, Haitao Wang, Ziqi Zhang, Jia Zhou, MengChu Beijing University of Technology College of Computer Science Beijing100124 China Beihang University School of Automation Science and Electrical Engineering Beijing China Southern Methodist University Department of Computer Science Lyle School of Engineering DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

The advent of smart manufacturing in Industry 4.0 signifies the era of connections. As a communication protocol, Object linking and embedding for Process Control Unified Architecture (OPC UA) can address most semantic heterogeneity issues. However, its semantics are not formally defined at the application layer. To address the information silo problem caused by semantic heterogeneity, an integration framework named Querying of Ontology Mapping-based OPC UA (QOMOU) is proposed. QOMOU extracts information models of OPC UA servers into resource description framework triples and utilizes web ontology language for semantic enrichment and inference. Then, an Event Class Semantic Similarity Calculation (ECSSC) method is proposed for device type identification, enabling the classification of semantically heterogeneous OPC UA devices. The effectiveness of ECSSC is validated through queries with the RDF query language (SPARQL) protocol in Apache Jena. Experimental results demonstrate that ECSSC improves the accuracy of device identification by approximately 7% compared to benchmark device identification models. Specifically, compared with graph embedding-based methods, QOMOU’s query performance is approximately 13% higher, and its query efficiency is 5% higher on average compared to both structured query and extensible markup languages. Moreover, by employing a keyword-matching algorithm, the query accuracy of the existing heterogeneous data integration scheme is improved by 4% on average. This enhancement can boost the operational efficiency of Internet of Things systems based on the OPC UA architecture. © 2014 IEEE.

关键词： Structured Query Language

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Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target segmentation

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Frontiers of Information Technology & Electronic engineering 2022年第4期23卷 571-586页

作者： Xiao YANG Chun YIN Sara DADRAS Guangyu LEI Xutong TAN Gen QIU School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu611731China Electrical and Computer Engineering Department Utah State UniversityLoganUT84321USA

To detect spacecraft damage caused by hypervelocity impact,we propose an advanced spacecraft defect extraction algorithm based on infrared imaging *** Gaussian mixture model(GMM)is used to classify the temperature change characteristics in the sampled data of the infrared video stream and reconstruct the image to obtain the infrared reconstructed image(IRRI)reflecting the defect *** designed segmentation objective function is used to ensure the effectiveness of image segmentation results for noise removal and detail preservation,while taking into account the complexity of IRRI(that is,the required trade-offs are different).A multi-objective optimization algorithm is introduced to achieve balance between detail preservation and noise removal,and a multi-objective evolutionary algorithm based on decomposition(MOEA/D)is used for optimization to ensure damage segmentation *** results verify the effectiveness of the proposed algorithm.

关键词： Hypervelocity impact damage Defect detection Gaussian mixture model Image segmentation

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A Review of Smart Materials for the Boost of Soft Actuators,Soft Sensors,and Robotics Applications

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Chinese Journal of Mechanical engineering 2022年第2期35卷 12-27页

作者： Yufei Hao Shixin Zhang Bin Fang Fuchun Sun Huaping Liu Haiyuan Li School of mechanical engineering University of Science and Technology BeijingBeijing 100083China School of Engineering and Technology China University of Geosciences(Beijing)Beijing 100083China Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and TechnologyTsinghua UniversityBeijing 100084China School of Automation Beijing University of Posts and TelecommunicationsBeijing 100876China

With the advance of smart material science,robotics is evolving from rigid robots to soft *** to rigid robots,soft robots can safely interact with the environment,easily navigate in unstructured fields,and be minimized to operate in narrow spaces,owning to the new actuation and sensing technologies developed by the smart *** the review,different actuation and sensing technologies based on different smart materials are analyzed and *** to the driving or feedback signals,actuators are categorized into electrically responsive actuators,thermally responsive actuators,magnetically responsive actuators,and photoresponsive actuators;sensors are categorized into resistive sensors,capacitive sensors,magnetic sensors,and optical waveguide *** introducing the principle and several robotic prototypes of some typical materials in each category of the actuators and *** advantages and disadvantages of the actuators and sensors are compared based on the categories,and their potential applications in robotics are also presented.

关键词： Smart material Soft robot Actuator Sensor

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Advances in cost-effective integrated spectrometers

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Light(Science & Applications) 2022年第7期11卷 1379-1396页

作者： Ang Li Chunhui Yao Junfei Xia Huijie Wang Qixiang Cheng Richard Penty Yeshaiahu Fainman Shilong Pan Key Laboratory of Radar Imaging and Microwave Photonics Ministry of EducationNanjing University of Aeronautics and AstronauticsNanjing 210016China Litin Technology XuzhouJiangsuChina Department of Engineering University of Cambridge9 JJ Thomson AvenueCambridge CB30FAUK Colllege of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Department of Electrical and Computer Engineering University of California at San DiegoLa JollaCAUSA

The proliferation of Internet-of-Things has promoted a wide variety of emerging applications that require compact,lightweight,and low-cost optical *** substantial progresses have been made in the miniaturization of spectrometers,most of them are with a major focus on the technical side but tend to feature a lower technology readiness level for *** importantly,in spite of the advancement in miniaturized spectrometers,their performance and the metrics of real-life applications have seldomly been connected but are highly *** review paper shows the market trend for chip-scale spectrometers and analyzes the key metrics that are required to adopt miniaturized spectrometers in real-life *** progress addressing the challenges of miniaturization of spectrometers is summarized,paying a special attention to the CMOS-compatible fabrication platform that shows a clear pathway to massive *** for ways forward are also presented.

关键词： cost summarized spite

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Towards Understanding the Benefit of Multitask Representation Learning in Decision Process

arXiv

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arXiv 2025年

作者： Lu, Rui Yue, Yang Zhao, Andrew Du, Simon S. Huang, Gao Department of Automation Tsinghua University China Paul G. Allen School of Computer Science and Engineering University of Washington United States

Multitask Representation Learning (MRL) has emerged as a prevalent technique to improve sample efficiency in Reinforcement Learning (RL). Empirical studies have found that training agents on multiple tasks simultaneously within online and transfer learning environments can greatly improve efficiency. Despite its popularity, a comprehensive theoretical framework that elucidates its operational efficacy remains incomplete. Prior analyses have predominantly assumed that agents either possess a pre-known representation function or utilize functions from a linear class, where both are impractical. The complexity of real-world applications typically requires the use of sophisticated, non-linear functions such as neural networks as representation function, which are not pre-existing but must be learned. Our work tries to fill the gap by extending the analysis to unknown non-linear representations, giving a comprehensive analysis for its mechanism in online and transfer learning setting. We consider the setting that an agent simultaneously playing M contextual bandits (or MDPs), developing a shared representation function from a non-linear function class Φ using our novel Generalized Functional Upper Confidence Bound algorithm (GFUCB). We formally prove that this approach yields a regret upper bound that outperforms the lower bound associated with learning M separate tasks, marking the first demonstration of MRL’s efficacy in a general function class. This framework also explains the contribution of representations to transfer learning when faced with new, yet related tasks, and identifies key conditions for successful transfer. Empirical experiments further corroborate our theoretical findings. Copyright © 2025, The Authors. All rights reserved.

关键词： Federated learning

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Data Driven Level Set Fuzzy Modeling for Cryptocurrencies Price Forecasting 14th

Data Driven Level Set Fuzzy Modeling for Cryptocurrencies Pr...

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14th International Joint Conference on Computational Intelligence, IJCCI 2022

作者： Maciel, Leandro Ballini, Rosangela Gomide, Fernando Department of Business Administration Faculty of Economics Business and Accounting University of Sao Paulo Sao Paulo Brazil Department of Economic Theory Institute of Economics University of Campinas Sao Paulo Brazil Department of Computer Engineering and Automation School of Electrical and Computer Engineering University of Campinas Sao Paulo Brazil

ISBN: (纸本)9789897586118

The paper develops a data-driven fuzzy modeling procedure based on level set to forecast cryptocurrencies prices. Data-driven level set is a novel fuzzy modeling method that differs from linguistic and functional fuzzy models in how the fuzzy rules are built and processed. The level set-based model outputs the weighted average of output functions associated with the fuzzy rules. Output functions map the activation levels of the fuzzy rules directly in the model outputs. Computational experiments are done to evaluate the level set method to forecast the closing prices of Bitcoin, Ethereum, Litecoin and Ripple. Comparisons are made with ARIMA, ETS, MLP and naïve random walk. The results suggest that the random walk outperforms most methods addressed in this paper, but it is surpassed by the level set model for Ethereum. When performance is measured by the direction of price change, the level set-based fuzzy modeling performs best amongst the remaining methods. Copyright © 2022 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Forecasting

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Mathematical Model for Increasing Accuracy when Measuring Linear Quantities in Conditions of External Mechanical Impacts 33

Mathematical Model for Increasing Accuracy when Measuring Li...

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33rd International Scientific Symposium Metrology and Metrology Assurance, MMA 2023

作者： Dichev, Dimitar Zhelezarov, Iliya Diakov, Dimitar Dicheva, Ralitza Kupriyanov, Oleksandr Malakov, Ivo Anastasov, Kalin Valkov, Stefan Petrov, Nikolay Technical University of Gabrovo Department of Machine and Precision Engineering Gabrovo Bulgaria Technical University of Sofia Department of Precision Engineering and Measurement Instruments Sofia Bulgaria Ukrainian Engineering Pedagogics Academy Department of Information Computer Technologies and Mathematics Kharkiv Ukraine Technical University of Sofia Department of Automation of Discrete Production Engineering Sofia Bulgaria Technical University of Gabrovo Department of Mechanical Engineering Technology and Machine Tools Gabrovo Bulgaria Technical University of Gabrovo Department of Mathematics Informatics and Natural Sciences Gabrovo Bulgaria

ISBN: (纸本)9798350338102

A new method of error correction of coordinate measuring and technological systems is presented in the article. The method is based on the basic assumptions of the Kalman filter and is aimed at removing errors whose sources have both dynamic and static origins. This universality of the method is provided by a new methodology for defining the model error variance, based on a measurement-computational platform whose input vector is formed by data from a three-axis MEMS accelerometer. © 2023 IEEE.

关键词： Kalman filters

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Divide, Conquer, and Coalesce: Meta Parallel Graph Neural Network for IoT Intrusion Detection at Scale 24

Divide, Conquer, and Coalesce: Meta Parallel Graph Neural Ne...

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33rd ACM Web Conference, WWW 2024

作者： Ding, Hua Chen, Lixing Li, Shenghong Bai, Yang Zhou, Pan Qu, Zhe School of Cyber Science and Engineering Shanghai Jiao Tong University Shanghai China Institute of Cyber Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan China School of Computer Science and Engineering Central South University Hunan Changsha China

ISBN: (纸本)9798400701719

This paper proposes Meta Parallel Graph Neural Network (MPGNN) to establish a scalable Network Intrusion Detection System (NIDS) for large-scale Internet of Things (IoT) networks. MPGNN leverages a meta-learning framework to optimize the parallelism of GNN-based NIDS. The core of MPGNN is a coalition formation policy that generates meta-knowledge for partitioning a massive graph into multiple coalitions/subgraphs in a way that maximizes the performance and efficiency of parallel coalitional NIDSs. We propose an offline reinforcement learning algorithm, called Graph-Embedded Adversarially Trained Actor-Critic (G-ATAC), to learn a coalition formation policy that jointly optimizes intrusion detection accuracy, communication overheads, and computational complexities of coalitional NIDSs. In particular, G-ATAC learns to capture the temporal dependencies of network states and coalition formation decisions over offline data, eliminating the need for expensive online interactions with large IoT networks. Given generated coalitions, MPGNN employs E-GraphSAGE to establish coalitional NIDSs which then collaborate via ensemble prediction to accomplish intrusion detection for the entire network. We evaluate MPGNN on two real-world datasets. The experimental results demonstrate the superiority of our method with substantial improvements in F1 score, surpassing the state-of-the-art methods by 0.38 and 0.29 for the respective datasets. Compared to the centralized NIDS, MPGNN reduces the training time of NIDS by 41.63% and 22.11%, while maintaining an intrusion detection performance comparable to centralized NIDS. © 2024 ACM.

关键词： Reinforcement learning

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To Test or Not: Incentivizing Individuals in a Population to Achieve Socially Optimal Testing in Epidemics

To Test or Not: Incentivizing Individuals in a Population to...

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IEEE International Conference on automation Science and engineering (CASE)

作者： Amal Roy Chandramani Singh Y Narahari Department of Computer Science and Automation Indian Institute of Science Bangalore India Department of Electronic Systems Engineering Indian Institute of Science Bangalore India

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

With multiple waves of epidemics devastating the global population and the possibility of future waves looming large, testing has moved to the centre-stage of epidemic management. In this study, we explore how offering incentives for testing during epidemics can encourage people to test themselves responsibly, without having to resort to strict penalties for noncompliance. We use a scientific approach to examine how adjusting testing costs can influence people’s behavior during outbreaks. We compare two scenarios: one where testing decisions are centrally managed for maximum social benefit, and another where individuals make their own testing choices. For achieving computational tractability in analyzing a large population, we use the mean field approach. By combining ideas from optimal control theory and mean field game theory, we investigate how policymakers can use subsidies to motivate people to test more responsibly during epidemics. This research offers valuable insights for policymakers on the quantum of subsidies needed to encourage desirable testing behavior of rational individuals in a population.

关键词： Epidemics Costs computer aided software engineering automation Optimal control Game theory Testing

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Parameters Design of a Digital VSG Control Strategy for Grid-Forming DG Systems Applications

Parameters Design of a Digital VSG Control Strategy for Grid...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Thiago F. Do Nascimento Andres O. Salazar Department of Computer Engineering and Automation Federal University of Rio Grande do Norte Natal Brazil

This paper presents a controller design procedure for a digital virtual synchronous generator (VSG) strategy applied to grid-forming distributed generation (DG) systems. The main contribution of the design methodology is to support researchers who are implementing DG systems with VSG-based power flow control strategies in a digital environment. For this purpose, an impedance model describes the DG power flow dynamic characteristics. Then, the digital VSG controllers parameters design uses the root-locus method (RLM) to achieve the desired dynamic performance. A case study demonstrates the effectiveness of the DG system with a VSG control strategy designed based on the proposed design method. Furthermore, the results evaluate the VSG controller's dynamic performance under the system's equivalent impedance variations.

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