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Development of 5G Cyber-Physical Production System

International Journal of Networked and Distributed Computing 2023年第1期11卷 9-19页

作者： Huang, Hsuan-Chao Tsai, Chun-Hsien Lin, Hsiung-Cheng Department of Computer Science and Information Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan PhD program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan Department of Electronic Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan

The cyber-physical production system (CPPS) was developed for the interconnection between operational technology (OT) and information and communication technology (ICT) among the machines and decentralized production control. However, OT and ICT are now getting more complex in the modern industry. To enhance industrial management and production process, the CPPS based on the 5G architecture under production environments can provide a more comprehensive solution in the context of Industry 4.0. For this purpose, a 5G CPPS model to improve the interoperability of CPPS in ICT and OT is proposed to build a virtualized Industry 4.0 asset management shell system. First, real-time task artifacts and 5G communication modules are bound in a certain form of virtualization. Second, task artifacts are released to the production line in a real-time scheduling. Third, an order is placed on a production line and split into multiple tasks for production process. Single-machine single-workpiece and multi-machine and multi-workpiece processing cases are used for testing in the production line. Experimental results show that the proposed 5G CPPS can efficiently achieve multi-machine work piece processing. © 2022, The Author(s).

关键词： 5G Cyber-physical production system (CPPS) Digital twin (DT) Industry 4.0 information technology Operational technology

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Prediction-Based Thunderstorm Path Recovery Method Using CNN-BiLSTM

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Intelligent Automation & Soft Computing 2023年第8期37卷 1637-1654页

作者： Xu Yang Ling Zhuang Yuqiang Sun Wenjie Zhang School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing210044China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2R3Canada CCCC Highway Consultants Co. Ltd.Beijing100101China School of Geographical Sciences Nanjing University of Information Science and TechnologyNanjing210044China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing100101China

The loss of three-dimensional atmospheric electric field(3DAEF)data has a negative impact on thunderstorm *** paper proposes a method for thunderstorm point charge path *** on the relation-ship between a point charge and 3DAEF,we derive corresponding localization formulae by establishing a point charge localization ***,point charge movement paths are obtained after fitting time series localization ***,AEF data losses make it difficult to fit and visualize ***,using available AEF data without loss as input,we design a hybrid model combining the convolutional neural network(CNN)and bi-directional long short-term memory(BiLSTM)to predict and recover the lost *** paths are not present during sunny weather,we propose an extreme gradient boosting(XGBoost)model combined with a stacked autoencoder(SAE)to further determine the weather conditions of the recovered ***,historical AEF data of known weathers are input into SAE-XGBoost to obtain the distribution of predicted values(PVs).With threshold adjustments to reduce the negative effects of invalid PVs on SAE-XGBoost,PV intervals corresponding to different weathers are *** recovered AEF is then input into the fixed SAE-XGBoost *** paths need to be fitted is determined by the interval to which the output PV *** results confirm that the proposed method can effectively recover point charge paths,with a maximum path deviation of approximately 0.018 km and a determination coefficient of 94.17%.This method provides a valid reference for visual thunderstorm monitoring.

关键词： Thunderstorm point charge atmospheric electric field(AEF) recovery

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Creating a Surround View Algorithm with Implementation on a Real Embedded ADAS Platform 32

Creating a Surround View Algorithm with Implementation on a ...

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32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Marinic, Ivan Vranjes, Mario Grbic, Ratko Herceg, Marijan TTTech Auto d.o.o. Cara Hadrijana 10b Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Kneza Trpimira 2B Osijek Croatia

ISBN: (纸本)9789532901382

computer Vision (CV) has seen significant advances, and autonomous driving technologies have been transforming the automotive industry in recent years. Autonomous vehicles require robust CV algorithms, while Advanced Driver Assistance Systems (ADAS) help the driver when driving and increase traffic safety. In this paper, the algorithm for generating a Surround View (SV) of the vehicle is proposed and implemented on a real embedded ADAS platform to test its performance in real hardware scenarios. The algorithm implements geometric operations like image distortion correction, perspective transformation, and image stitching to create a comprehensive and connected surround view. The subjective image quality evaluation results showed that the proposed algorithm achieves a fairly high quality of the final top-view image. The experiments also show that its operating speed when running on a real ADAS platform is suitable for cases when the vehicle speed is not high, such as when parking. © 2024 University of Split, FESB.

关键词： Automotive industry

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Unmanned Aerial Vehicle Mapping of River Flow for Water Resources Management 1

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Peko, Marina Crnjac Milić, Dominika Vidaković, Ivan Faculty of Electrical Engineering Computer Science and Information Technology Osijek Kneza Trpimira 2B Osijek31000 Croatia AIR-RMLD d.o.o. Jarunska ulica 19 Zagreb10000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

Unmanned aerial vehicle surveying of the riverbed enables detailed mapping of the river flow, which is useful for various purposes such as flood management, ecosystem monitoring and geological processes. Unmanned aerial vehicles are used to collect data on water height, flow velocity and bed shape, creating precise maps of river systems. This process can be fast, efficient and safe for operators, and is therefore increasingly used in scientific research and water resource management. Riverbed surveying can be done with a LiDAR (Light Detection and Ranging/Laser scanning) camera which collects visual data on the condition of the riverbed, such as changes in shape, erosion and sedimentation. LiDAR cameras, also known as side-scan sonar, use sound signals to collect data on the depth and shape of the riverbed and create a precise 3D map of the riverbed. This process enables a detailed analysis of the river system and is useful for water resource management and environmental protection. The paper will give an overview of the methods and technologies that are currently relevant for the implementation of such recordings. Also, future work will be presented, as well as the advantages and challenges of such a project from an economic and technological point of view. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mapping

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Decentralized Federated Graph Learning with Lightweight Zero Trust Architecture for Next-Generation Networking Security

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IEEE Journal on Selected Areas in Communications 2025年第6期43卷 1908-1922页

作者： Zhou, Xiaokang Liang, Wei Wang, Kevin I-Kai Yada, Katsutoshi Yang, Laurence T. Ma, Jianhua Jin, Qun Kansai University Faculty of Business Data Science Osaka565-0823 Japan RIKEN Center for Advanced Intelligence Project RIKEN Tokyo103-0027 Japan Hunan University of Technology and Business School of Computer Science Changsha410205 China Xiangjiang Laboratory Changsha410205 China The University of Auckland Department of Electrical Computer and Software Engineering Auckland1010 New Zealand St. Francis Xavier University Department of Computer Science AntigonishNSB2G 2W5 Canada Hosei University Faculty of Computer and Information Sciences Chiyoda-ku102-8160 Japan Waseda University Faculty of Human Sciences Tokorozawa359-1192 Japan

The rapid development and usage of digital technologies in modern intelligent systems and applications bring critical challenges on data security and privacy. It is essential to allow cross-organizational data sharing to achieve smart service provisioning, while preventing unauthorized access and data leak to ensure end users' efficient and secure collaborations. Federated Learning (FL) offers a promising pathway to enable innovative collaboration across multiple organizations. However, more stringent security policies are needed to ensure authenticity of participating entities, safeguard data during communication, and prevent malicious activities. In this paper, we propose a Decentralized Federated Graph Learning (FGL) with Lightweight Zero Trust Architecture (ZTA) model, named DFGL-LZTA, to provide context-aware security with dynamic defense policy update, while maintaining computational and communication efficiency in resource-constrained environments, for highly distributed and heterogeneous systems in next-generation networking. Specifically, with a re-designed lightweight ZTA, which leverages adaptive privacy preservation and reputation-based aggregation together to tackle multi-level security threats (e.g., data-level, model-level, and identity-level attacks), a Proximal Policy Optimization (PPO) based Deep Reinforcement Learning (DRL) agent is introduced to enable the real-time and adaptive security policy update and optimization based on contextual features. A hierarchical Graph Attention Network (GAT) mechanism is then improved and applied to facilitate the dynamic subgraph learning in local training with a layer-wise architecture, while a so-called sparse global aggregation scheme is developed to balance the communication efficiency and model robustness in a P2P manner. Experiments and evaluations conducted based on two open-source datasets and one synthetic dataset demonstrate the usefulness of our proposed model in terms of training performance, computa

关键词： Federated learning

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Synchronous speed control for industrial production line based on BP neural network

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International Journal of Manufacturing technology and Management 2022年第2-4期36卷 127-140页

作者： Pan, Tianci Zhu, Changhong Department of Information Engineering Bowen College of Management Guilin University of Technology No. 317 Yanshan Street Guangxi Guilin541006 China School of Computer Science and Engineering Guilin University of Aerospace Technology No. 2 Jinji Road Guangxi Guilin541004 China

In order to overcome the problems of large speed control error and poor anti-interference effect existing in the traditional speed control methods, the paper proposes a speed synchronisation control method of industrial production line based on BP neural network. Firstly, the state of production equipment is adjusted through PLC operation instruction, and amplifier circuit is designed to reduce the influence of signal interference. Then the speed control parameters of the production line are adjusted by adaptive control method, and the parameters are fused by fuzzy control theory. Finally, the speed of the industrial production line is synchronously controlled by BP neural network. The experimental results show that the control error coefficient of this method is always lower than 9%, and the influence of step disturbance signal is low, indicating that this method has good application performance. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Speed control

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A Species-based Particle Swarm Optimization with Adaptive Population Size and Deactivation of Species for Dynamic Optimization Problems

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ACM Transactions on Evolutionary Learning and Optimization 2023年第4期3卷 1-25页

作者： Yazdani, Delaram Yazdani, Danial Yazdani, Donya Omidvar, Mohammad Nabi Gandomi, Amir H. Yao, Xin Department of Computer Engineering Mashhad Branch Azad University Mashhad*** Iran Faculty of Engineering & Information Technology University of Technology Sydney Ultimo2007 Australia AI Lab British Antarctic Survey CambridgeCB3 0ET United Kingdom School of Computing Leeds University Business School University of Leeds LeedsLS2 9JT United Kingdom Obuda University Budapest1034 Hungary Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China School of Computer Science University of Birmingham BirminghamB15 2TT United Kingdom

Population clustering methods, which consider the position and fitness of individuals to form sub-populations in multi-population algorithms, have shown high efficiency in tracking the moving global optimum in dynamic optimization problems. However, most of these methods use a fixed population size, making them inflexible and inefficient when the number of promising regions is unknown. The lack of a functional relationship between the population size and the number of promising regions significantly degrades performance and limits an algorithm’s agility to respond to dynamic changes. To address this issue, we propose a new species-based particle swarm optimization with adaptive population size and number of sub-populations for solving dynamic optimization problems. The proposed algorithm also benefits from a novel systematic adaptive deactivation component that, unlike the previous deactivation components, adapts the computational resource allocation to the sub-populations by considering various characteristics of both the problem and the sub-populations. We evaluate the performance of our proposed algorithm for the Generalized Moving Peaks Benchmark and compare the results with several peer approaches. The results indicate the superiority of the proposed method. © 2023 Copyright held by the owner/author(s).

关键词： Resource allocation

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Correction to: Improving time and energy efficiency in multi-UAV coverage operations by optimizing the UAVs’ initial positions (International Journal of Intelligent Robotics and Applications, (2024), 10.1007/s41315-024-00333-2)

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International Journal of Intelligent Robotics and Applications 2024年第1期9卷 365-373页

作者： Stefanopoulou, Aliki Raptis, Emmanuel K. Apostolidis, Savvas D. Gkelios, Socratis Kapoutsis, Athanasios Ch. Chatzichristofis, Savvas A. Vrochidis, Stefanos Kosmatopoulos, Elias B. Information Technologies Institute The Centre for Research & ampTechnology Hellas 6th km Harilaou - Thermis Thessaloniki57001 Greece Department of Electrical and Computer Engineering Democritus University of Thrace Kimmeria Campus Xanthi67100 Greece Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos 2 Danais Avenue PafosCY 8042 Cyprus

In the original publication, the author has found few errors in the figures 2, 4, 11 and 12 which significantly impact both the paper's quality and the reputation of the journal. These issues undermine the clarity of the methodology and the novelty of the research. 1. Each column represents a different case in the experiment, corresponding to the number of UAVs in both the obstacle-free and obstacle areas. However, in Fig. 2, the first row contains identical subfigures across all columns, while the subfigures in the remaining rows are identical to each other The incorrect Fig. 2 appears as below: (Figure presented.) However the corrected Fig. 2 should appear as below. (Figure presented.) 2. In Fig. 4, every row showcase the average QoF for the testing scenarios (obstacle-free and obstacle area). However the first row has the exact same figures with the second row. The incorrect Fig. 4 appears as below: (Figure presented.) However the corrected Fig. 4 should appear as below. (Figure presented.) 3. Figures 11 and 12 showcase the distribution of each Quality of Flight (QoF) metric value for every UAV in the conducted trials during the testing scenarios. However, Fig. 11 is the same with Fig. 12. The incorrect Figs. 11 and 12 appears as below: (Figure presented.) However the corrected Figs. 11 and 12 should appear as below. (Figure presented.) Distribution of each Quality of Flight metric value for every UAV in the conducted trials during the coverageof the obstacle-free area Distribution of each Quality of Flight metric value for every UAV in the conducted trials during the coverageof the obstacle area The original article has been corrected. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

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Eight-direction least-square phase unwrapping algorithm for optical three-dimensional measurement 3

Eight-direction least-square phase unwrapping algorithm for ...

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3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： He, Yantao Liu, Sijia Pan, Minling Wang, Rongfu Li, Xueri Zhang, Rong Department of Computer Science Guangdong University of Science and Technology No. 2 Songshan Lake Section 523668 China School of Mechanical Engineering Hunan University of Science and Technology Taoyuan Road 411201 China School of Electronics and Information Engineering Beibu Gulf University No. 12 Binhai Avenue 535011 China

ISBN: (纸本)9781510668522

The least-square method is widely used in the fast phase unwrapping of optical three-dimensional measurement due to its high-speed and comprehensive characteristics. In order to solve the problem of measurement error propagation in the phase unwrapping algorithm based on least-square method, an improved eight-direction least-square phase unwrapping algorithm is proposed in this paper. This algorithm not only researches the gradient difference between the target phase and its eight-neighbor phases, improving measurement accuracy and reducing measurement errors. The superiority and robustness of this algorithm have been demonstrated through simulation data and measurement of industrial bearing roller end faces © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Measurement errors

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Arrhythmia classification based on multi-feature multi-path parallel deep convolutional neural networks and improved focal loss

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Mathematical Biosciences and engineering 2024年第4期21卷 5521-5535页

作者： Ran, Zhongnan Jiang, Mingfeng Li, Yang Wang, Zhefeng Wu, Yongquan Ke, Wei Xia, Ling School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China School of Computer Science and Technology Zhejiang Sci-Tech University Hangzhou310018 China Department of Cardiology Beijing Anzhen Hospital Capital Medical University No. 2 Anzhen Road Chaoyang District Beijing100029 China School of Applied Sciences Macao Polytechnic Institute China Department of Biomedical Engineering Zhejiang University Hangzhou310027 China

Early diagnosis of abnormal electrocardiogram (ECG) signals can provide useful information for the prevention and detection of arrhythmia diseases. Due to the similarities in Normal beat (N) and Supraventricular Premature Beat (S) categories and imbalance of ECG categories, arrhythmia classification cannot achieve satisfactory classification results under the inter-patient assessment paradigm. In this paper, a multi-path parallel deep convolutional neural network was proposed for arrhythmia classification. Furthermore, a global average RR interval was introduced to address the issue of similarities between N vs. S categories, and a weighted loss function was developed to solve the imbalance problem using the dynamically adjusted weights based on the proportion of each class in the input batch. The MIT-BIH arrhythmia dataset was used to validate the classification performances of the proposed method. Experimental results under the intra-patient evaluation paradigm and inter-patient evaluation paradigm showed that the proposed method could achieve better classification results than other methods. Among them, the accuracy, average sensitivity, average precision, and average specificity under the intra-patient paradigm were 98.73%, 94.89%, 89.38%, and 98.24%, respectively. The accuracy, average sensitivity, average precision, and average specificity under the inter-patient paradigm were 91.22%, 89.91%, 68.23%, and 95.23%, respectively. © 2024 the Author(s).

关键词： Diseases

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