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Online Credibility Assessment of Equipment Digital Twin for Discrete Manufacturing

IEEE Transactions on Automation science and engineering 2025年 22卷 14763-14774页

作者： Lu, Han Zhang, Lin Deen, M. Jamal Wang, Kunyu Cheng, Hongbo Yang, Laurence T. Beihang University Hangzhou International Innovation Institute Zhejiang 311115 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China State Key Laboratory of Intelligent Manufacturing System Technology Beijing100854 China AI Atlas Inc Canada Zhengzhou University School of Computer and Artificial Intelligence School of Software Engineering Zhengzhou China St. Francis Xavier University Department of Computer Science Antigonish Canada

The equipment digital twins (EDTs) for discrete manufacturing should be calibrated quickly to avoid irreversible physical damage to the equipment caused by biased control commands. Therefore, an online credibility assessment method for EDTs is urgently needed. However, existing assessment approaches consume too much time, and thus could not reveal dynamic faults in time. In this paper, the dynamic relationship between online evolution and actual applications of EDTs is investigated. Then, two steps are proposed to accelerate the assessment process significantly. One involves pre-constructing a performance-deviation-agent (PDA), and the other involves dynamically fitting the application-time-window (ATW) probability distribution. The methodology is applicable to discrete manufacturing processes. The dynamic credibility of EDT evolution process can be updated after every iteration of the model evolution. Sorting manufacturing equipment was used as a case study to demonstrate the effectiveness of this method. The time consumption was reduced by 90% compared with traditional assessment methods in the case. © 2025 IEEE.

关键词： Fabrication

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Low Chirp Dual-Racetrack Modulator for PAM-4 Modulation with Low Driving Voltage

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Journal of Lightwave Technology 2025年第10期43卷 4840-4847页

作者： Yu, Fuhao Zeng, Zhaobang Tang, Kaifei Yang, Shichong Ji, Xiang Xin, Yu Gu, Tingyi Jiang, Wei Nanjing University Key Laboratory of Intelligent Optical Sensing and Manipulation Engineering Research Center for Precision Photonics Integration & System Applications Ministry of Education Nanjing210023 China Nanjing University National Laboratory of Solid-State Microstructures College of Engineering and Applied Sciences Institute of Optical Communication Engineering Nanjing210023 China Nanjing University of Information Science & Technology School of Physics and Optoelectronic Engineering Nanjing210044 China University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States

Micro-ring modulators with a small footprint and energy consumption have been explored for densely integrated high throughput optical interconnects. However, their strong dispersive response results in frequency chirp and pulse broadening, which limits their signal transmission distance. Here we explore the low chirp operation of a dual-racetrack modulator symmetrically coupled to a bus waveguide. With opposite index changes in the two resonators, the coherent couplings of two resonators' optical fields with the bus waveguide and their interference can cancel out the output phase variation due to a single resonator. This allows the push-pull operation to achieve a lower chirp compared to the single-drive operation. The advantage of lower chirp operation is experimentally verified through open eye diagram with 100 Gbps PAM-4 transmitted over 2 km single-mode fiber (SMF), with a peak-to-peak driving voltage of 1.6 V. © 1983-2012 IEEE.

关键词： Single mode fibers

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Chirp-free hundred-picosecond pulse fiber laser based on carbon nanotubes mode-locker

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Optics Express 2025年第7期33卷 14850-14857页

作者： Li, Weixi Jiang, Kailin Dai, Lilong Huang, Qianqian Zou, Meng Luo, Siyu Chen, Siyu Song, Yingxiong Liu, Yunqi Yan, Zhijun Mou, Chengbo Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai Institute for Advanced Communication and Data Science Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai200444 China School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access System Huazhong University of Science and Technology Wuhan430074 China

We demonstrate a narrow bandwidth passively erbium-doped mode-locked fiber laser based on single-wall carbon nanotubes (SWCNTs). The center wavelength is 1546.61 nm. The strong filtering effect and low saturable absorber (SA) modulation depth provide advantages for a long pulse duration of 323 ps. An overall spectral bandwidth of 1.3 GHz (0.01 nm) is measured by the optical heterodyne method, representing the narrowest spectral width based on SWCNT under a single filter structure. The obtained spectral width is very close to the transform-limited bandwidth of 8 pm, indicating that the pulse is chirp-free. Meanwhile, the generation of beat signals reveals the strong coherence between pulses. The repetition frequency of the laser is 7.8 MHz, and the number of longitudinal mode locks is only 166, which is the minimum number of longitudinal mode-locking in passively mode-locked laser based on material SA. At the same time, numerical simulations further support our experimental results and reveal the pulse evolution, providing evidence that SA and filter are the key factors in the generation of chirp-free long pulse. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Saturable absorbers

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Joint Sensing and Computation Incentive Mechanism for Mobile Crowdsensing Networks: A Multiagent Reinforcement Learning Approach

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IEEE Internet of Things Journal 2025年第9期12卷 13033-13046页

作者： Zhao, Nan Sun, Yiling Pei, Yiyang Niyato, Dusit Hubei University of Technology Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430061 China Singapore Institute of Technology Information and Communications Technology Cluster Tampines Singapore Nanyang Technological University School of Computer Science and Engineering Jurong West Singapore

Mobile crowdsensing (MCS) is a novel sensing paradigm by utilizing mobile users (MUs) to collect data from environment. Considering the finite sensing and computing resources of MUs, it is crucial to inspire MUs to take part in crowdsensing willingly. In this study, a multiagent-deep-reinforcement-learning (DRL)-based incentive mechanism is investigated to tackle the joint data sensing and computing issues. Specifically, due to the heterogeneity of sensing tasks, multiple MCS platforms (MCPs) motivate MUs to participate in different tasks. The interaction between MCPs and MUs is modeled as a multileader-multifollower Stackelberg game with Stackelberg equilibrium proved by derivation. Moreover, the Stackelberg game is transformed as a Markov decision process (MDP) to deal with a multiagent DRL method without any prior knowledge. Due to the continuous high-dimensional action space of multiple MCPs and MUs, a multiagent double actors deep deterministic policy gradient (MA-DADDPG) algorithm is proposed to obtain the optimal sensing data size, computing resource, and incentive payment policies. Extensive simulation results illustrate the effectiveness of the proposed crowdsensing incentive mechanism. © 2014 IEEE.

关键词： Deep reinforcement learning

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APLASE: Compression using Adaptive Piecewise Linear Approximation and Sparse Encoding

APLASE: Compression using Adaptive Piecewise Linear Approxim...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ravi Raj Saxena T.V. Prabhakar Joy Kuri Chandra R. Murthy Dept. of Electronic System Engineering Indian Institute of Science Bengaluru India Dept. of Electrical Communication Engineering Indian Institute of Science Bengaluru India

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This work focuses on compressing vast amounts of time series data from IoT sensors while achieving low reconstruction error, at a low compression ratio (ratio of output data size to input data size), for efficient storage and transmission. We investigate two lossy compression techniques: Adaptive Piecewise Linear Approximation (APLA) and Sparse Encoding (SE). APLA reduces data volume by leveraging the temporal correlation in time series data, while SE captures small, complex variations that APLA might miss. We identify a signal characteristic parameter, denoted by σ d , which is used to derive error bounds for SE using σ d , the dictionary used, and the input compression parameters. We also introduce APLASE, a novel compression technique that combines the two techniques by applying SE to the reconstruction error generated by APLA. We evaluate APLA, SE and APLASE using data from the NASA flight data recorder database consisting of recordings from 116 sensors. Our results show that APLASE consistently outperforms both APLA and SE individually, as well as the recent QoZ algorithm, particularly at lower compression ratios.

关键词： Measurement Dictionaries Time series analysis Piecewise linear approximation NASA Signal processing algorithms Encoding Sensors Speech processing Standards

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A Dynamic Workload Prediction and Distribution in Cloud Computing using Deep Reinforcement Learning and LSTM

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Journal of Harbin institute of Technology(New series) 2025年

作者： Nampally Vijay Kumar Satarupa Mohanty Prasant Kumar Pattnaik School of Computer Engineering KIIT Deemed to be University Department of Computer Science and Business System B V RAJU Institute of Technology

Maintaining high-quality service supply and sustainability in modern cloud computing is essential to ensuring optimal system performance and energy efficiency. A novel approach is introduced in this study to decrease a system.s overall delay and energy consumption by utilising a deep reinforcement learning(DRL)model to predict and allocate incoming workloads flexibly. The proposed methodology integrates workload prediction utilising long short-term memory(LSTM)networks with efficient load-balancing techniques led by deep Q-learning and Actor-Critic algorithms. By continuously analysing current and historical data,the model can efficiently allocate resources,prioritizing speed and energy preservation. The experimental findings demonstrate that our load balancing system,which utilises DRL,significantly reduces average response times and energy usage compared to traditional methods. This approach provides a scalable and adaptable strategy for enhancing cloud infrastructure performance. It consistently provides reliable and durable performance across a range of dynamic workloads.

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Micro-convex structure-assisted laser-induced backside dry etching for high-efficiency fabrication of micro-groove array on fused silica toward manipulation of wetting characteristics

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Journal of Manufacturing Processes 2025年 145卷 236-251页

作者： Huang, Hu An, Hong Qian, Yongfeng Zhang, Zhiyu Jiang, Minqiang Yan, Jiwang Key Laboratory of CNC Equipment Reliability Ministry of Education School of Mechanical and Aerospace Engineering Electron Microscopy Center Jilin University Changchun130022 China Key Laboratory of Optical System Advanced Manufacturing Technology Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun130033 China State Key Laboratory of Nonlinear Mechanics Institute of Mechanics Chinese Academy of Sciences Beijing100190 China School of Engineering Science University of Chinese Academy of Sciences Beijing101408 China Department of Mechanical Engineering Faculty of Science and Technology Keio University Yokohama223-8522 Japan

Fused silica has garnered significant attention in various industrial applications. The creation of surface micro/nanostructures on fused silica can impart specialized functional properties, such as extreme wettability, ultra-high transmittance, and excellent antimicrobial characteristics. Nonetheless, existing technologies for achieving surface micro/nanopatterning of fused silica, including wire electrical discharge machining, chemical etching, and electrochemical deposition, generally suffer from long processing cycles and high energy consumption, which are inconsistent with the development concept of the low-carbon economy. In this study, a novel approach termed micro-convex structure-assisted laser-induced backside dry etching (MCSALIBDE) is proposed for high-efficiency fabrication of micro-groove array on fused silica surfaces. The synergistic effect of enhanced heat conduction and plasma explosion in a confined space facilitates material ablation. The impact of processing parameters including scanning pitch and peak laser power intensity on the morphological and topographical features of the MCSALIBDE-processed fused silica surfaces is studied. Notably, the micro-groove structures with a depth-to-width ratio of 1.19 is fabricated. Furthermore, the wetting behaviors of the MCSALIBDE-processed fused silica surfaces before and after annealing treatment are studied. Experimental findings reveal that the MCSALIBDE-processed fused silica surfaces exhibit enhanced hydrophilicity compared to the untreated one. After annealing treatment, a transformation from hydrophilicity to superhydrophobicity is observed. The superhydrophobic surfaces produced under different laser parameters exhibit distinct adhesion and droplet bouncing behaviors. This work offers an in-depth understanding of the high-efficiency fabrication of micro/nanostructures on fused silica surfaces and as well the modulation of their wetting characteristics, heralding innovations in surface engineering fo

关键词： Wetting

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Compressed VGGNet for Automatic COVID-19 Disease Detection from CT Scan Images 8th

Compressed VGGNet for Automatic COVID-19 Disease Detection f...

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8th IFIP TC 12 International Conference on Computer, Communication and Signal Processing, ICCCSP 2024

作者： Vinothini, R. Niranjana, G. Dhamanti, Inge Lailiyah, Syifa’ul Yakub, Fitri Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur 603203 India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur 603203 India Department of Health Policy and Administration Faculty of Public Health Universitas Airlangga Surabaya Indonesia Faculty of Health Medicine and Life Sciences Universitas Airlangga East Java Indonesia Electronic System Engineering Department Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia

ISBN: (纸本)9783031736162

Millions of people across the globe were affected by this rapidly spreading disease by the year 2020. Contamination of the respiratory system results from contracting COVID-19. Nonetheless, establishing a conclusive diagnosis of COVID-19 may prove difficult due to the subtle differences it shares with conventional pneumonia and the complexities involved in identifying areas of infection. A growing number of approaches based on deep learning (DL) are being proposed for the automated detection of COVID-19 from CT scan images. By employing the data pretreatment methodology, unprocessed image data becomes prepared for further analysis. The proposed framework utilised transfer learning to construct VGGNet, which is capable of discerning the Covid-19 disease. The model was subsequently assessed in comparison to the most sophisticated models, VGG16 and VGG19, using the SARS-COV2 CT scan dataset. This dataset contains 1230 CT scans of non-infected images and 1252 CT scans of Covid-19-infected images. The model has achieved 99% accuracy, 98% precision, 97% recall, and 98% F1-score, among other performance metrics. © IFIP International Federation for Information Processing 2025.

关键词： COVID-19

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High-Misalignment Tolerance WPT system for UAV by Symmetric Rotating Magnetic Field

High-Misalignment Tolerance WPT System for UAV by Symmetric ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Fengshuo Yang Yu Lan Qingxuan Zhang Mingxing Xiong Jinhai Jiang Kai Song Xudong Wang Wanli Xu School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of System Engineering Academy of Military Science Beijing China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

This paper proposes an novel solenoid magnetic coupler for omnidirectional wireless charging of unmanned aerial vehicles (UAVs). The magnetic coupler features asymmetry compensation, a compact structure, high rotational and misalignment tolerance, and low magnetic leakage interference. The transmitting coils consist of three groups of solenoid coils, each comprising a large coil and a small coil connected in series. The small coil compensates for the uneven coupling caused by axial misalignment of the UAV. The excitation current phase difference of 120° in each transmitter coil group generates rotating magnetic field. The transmitting coils primarily produce horizontal magnetic fields with minimal vertical components, significantly reducing electromagnetic interference with UAV equipment. Two groups of receiving solenoid coils are conformally installed on the UAV landing gear. The topology, where each group of receiving coils is rectified and then connected in series, compensates for the uneven coupling caused by radial misalignment. Simulation results indicate that the system maintains a stable received power of 379W-477W under angular offsets of 0-360° and positional offsets of ±60mm, demonstrating excellent misalignment tolerance.

关键词： Coils Couplings Gears Simulation Inductive charging Couplers Autonomous aerial vehicles Topology Magnetic fields Solenoids

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Research on Entity Recognition Method for Quality Standards of Concrete Prefabricated Components 1

Research on Entity Recognition Method for Quality Standards ...

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1st International Conference on Intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Zhang, Tingshu Tu, Ming Wang, Gefan Chen, Bingyong Zhao, Yishi Shang, Jianga School of Computer Science China University of Geosciences Wuhang China Intelligent Construction System Research Institute China Construction Third Engineering Buerau Group Co.L Wuhang China Engineering Research Center of Natural Resource Information Management and Digital Twin Engineering Software Ministry of Education School of Computer Science China University of Geosciences Wuhang China

ISBN: (纸本)9781643685779

In recent years, the country has released a large number of standard documents related to prefabricated concrete components. Due to the dispersion and complexity of these standards, it is difficult for industry managers to implement them. Therefore, it is imperative to establish a knowledge graph in the field of quality standards for precast concrete components to achieve knowledge management. The construction of knowledge graph first requires named entity recognition, but due to the specificity of the construction industry, entity recognition of the text in this field still suffers from the problems of low recognition accuracy and high resource consumption. Aiming at the low recognition accuracy and high resource consumption in named entity recognition due to the specificity of the industry, this paper proposes a named entity recognition model ALBERT-BiLSTM-SA-CRF for the field of precast concrete component quality standard, which can capture the full text and local feature information more effectively through the combination of BiLSTM and self-attention mechanism, and accurately recognize entities in the standard. Meanwhile, using ALBERT as the word embedding layer can play the role of reducing resource consumption and improving processing efficiency. © 2025 The Authors.

关键词： Knowledge graph

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