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Phase unwrapping based on self-attention dense residual network

Optics and Laser technology 2025年 191卷

作者： Wang, Zhongyang Ma, Hongwei Chen, Yuan Wang, Quan College of Mechanical Engineering Xi'an University of Science and Technology Shaanxi Xi'an710054 China College of Sciences Xi'an University of Science and Technology Shaanxi Xi'an710054 China Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control Xi'an University of Science and Technology Shaanxi Xi'an710054 China

Phase unwrapping, a critical step in obtaining holographic information, plays a significant role in the field of digital holography, particularly in applications such as fringe projection for 3D imaging, synthetic aperture radar, and magnetic resonance imaging. Traditional phase unwrapping algorithms often suffer from error accumulation, high computational costs, and poor performance in low signal-to-noise ratio (SNR) environments. To address these issues, this paper proposes a novel deep learning framework, named as Self-Attention Dense Residual Network (SA-DRNet), for phase unwrapping. To obtain continuous phase, we initially employed a dense network for multiple extractions of phase features. However, to alleviate the phase discontinuities and phase jumps caused by gradient issues, we integrated residual connections within the dense network. Finally, we incorporated a self-attention module to enhance the global phase information restoration, including the background phase, thereby achieving high-precision phase acquisition. Additionally, we established an off-axis digital holographic optical system to capture the holograms of the USAF resolution test target and artificial ink dots. Finally, the robustness of the proposed algorithm under severe noise conditions was first verified through numerical simulations, followed by experimental validation of its effectiveness. © 2025 Elsevier Ltd

关键词： Holograms

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Asymptotic state estimation for linear systems with sensor and actuator faults

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science China(Information sciences) 2019年第11期62卷 106-120页

作者： Chun-Hua XIE Hui YANG Dianhui WANG Zhe LI School of Electrical and Automation Engineering East China Jiaotong University Key Laboratory of Advanced Control & Optimization of Jiangxi Province Department of Computer Science and Information Technology La Trobe University College of Electrical and Information Engineering Hunan University

This paper investigates the asymptotic state estimation problem for linear systems with sensor and actuator faults, where the faults are modeled via multiple modes. For the case of sensor faults, we first introduce a new notion of detectability, i.e., detectability of system against sensor faults. The notion helps to address the question of whether it is possible to asymptotically estimate the system state by using the control input and system output, irrespective of which mode the system is in and what values the fault signals are.A necessary and sufficient condition for the system to be detectable against sensor faults is given, and then two switched observers are proposed for asymptotic state estimation with the help of maximin strategy. For the system with ? fault modes, we provide the explicit form of the switched observer, which is based on a bank of ?(?+1)/2 Luenberger-like or sliding-mode observers. Furthermore, extensions to the case of sensor and actuator faults are further studied. Finally, a simulation example of a reduced-order aircraft system is provided to show the effectiveness of the proposed approaches.

关键词： asymptotic state estimation observer linear systems sensor faults actuator faults

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PenAAc-based interfacial passivation to reduce voltage loss and defect densities in lead-free perovskite solar cells

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Journal of Applied Physics 2025年第21期137卷

作者： Guo, Jun Liu, Yu Chen, Xinyao Cheng, Jin Zhao, Longjiang Li, Junming Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China Beijing Key Laboratory for Sensor School of Science Beijing Information Science and Technology University Beijing100101 China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100192 China College of Engineering Qufu Normal University Rizhao276826 China

Tin-based perovskites are considered a promising alternative to lead-based perovskites due to their low toxicity and suitable optical bandgap. However, the defects and voltage loss issues severely limit their device performance. In this study, an interfacial passivation strategy based on pentylammonium acetate (PenAAc) was proposed in tin-based perovskite solar cells. The PenAAc-modified layer can effectively improve the perovskite film morphology, crystallinity, and hydrophobicity. Meanwhile, the introduction of the PenAAc layer can significantly inhibit carrier complexation and reduce the hysteresis effect in solar cells. By systematically analyzing the charge transport and compounding mechanisms, the PenAAc layer enhances the built-in electric field, improves the carrier separation and the carrier extraction efficiency, and reduces the defect density in the perovskite layer. The optimal tin-based perovskite solar cell achieved a power conversion efficiency of 7.0%. Moreover, the PenAAc-modified device maintained above 89% of its initial efficiency even after 1200 h storage in a nitrogen-filled glovebox. © 2025 Author(s).

关键词： Defect density

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Anomalous large positive τ f of two K20 microwave dielectric ceramics LaMGa 11 O 19 (M = Mg, Zn) as temperature compensators

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Ceramics International 2025年

作者： Feilong Liu Junqi Chen Huaicheng Xiang Jie Li Yang Yang Ying Tang Liang Fang Guangxi Universities Key Laboratory of Non-ferrous Metal Oxide Electronic Functional Materials and Devices College of Materials Science and Engineering Guilin University of Technology Guilin 541004 China Guangxi Key Laboratory of Special Engineering Equipment and Control Guilin University of Aerospace Technology Guilin 541004 China College of Physics and Electronic Information Engineering Guilin University of Technology Guilin 541004 China

In this work, two novel hexagonal magnetoplumbite-type LaMGa 11 O 19 (M = Mg, Zn) ceramics were prepared and deeply investigated. XRD patterns, SAED and HRTEM images analysis results demonstrated that the LaMGa 11 O 19 (M = Mg, Zn) ceramics are formation of hexagonal magnetoplumbite structure with a space group of P 6 3 / mmc . Both ceramics exhibited relatively high density (>95 %) and large positive τ f (+145.1 and + 136.7 ppm/°C), combined with moderate ε r around 20 and reasonable Q × f values of 19,328 GHz and 22,197 GHz, which be used as a temperature compensator for LTCC applications. The intense rattling effect of La 3+ cations resulted in abnormally high dielectric constant with a large positive variation by a factor of over 0.70 from the theoretical values calculated using the Clausius-Mossotti formula according to each ion's polarizability, negative τ αm , and positive τ f values. The P–V–L chemical bond theory analysis and impedance spectroscopy showed that the large dielectric loss might result from the high ionicity of the La-O bond and conduction loss, thus leading to relatively low Q × f for the LaMGa 11 O 19 (M = Mg, Zn) ceramics.

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Maintenance Optimization for Combined Heat and Power Unit Based on Opportunistic Maintenance Strategy

Maintenance Optimization for Combined Heat and Power Unit Ba...

引用

2020 IEEE/IAS industrial and Commercial Power System Asia, I and CPS Asia 2020

作者： Zhang, Yumin Ji, Xingquan Yu, Yixiao Xu, Bo Han, Xueshan Zhang, Lin Shandong University of Science and Technology College of Electrical Engineering and Automation Qingdao China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Energy Research Institute Co. Beijing102209 China

ISBN: (纸本)9781728143033

Integrated energy system is composed of different multiple energy systems. When the combined heat and power (CHP) unit fails, more than one energy systems can be influenced. Therefore, it is very important to improve the reliability of CHP unit. In this paper, we propose a maintenance decision making model for CHP unit based on opportunistic maintenance strategy. Firstly, the expression of the availability of CHP unit considering opportunistic maintenance is derived. And then, in order to quantify the impact of different maintenance strategies on system operation, system operation risk is given taking electrical load loss and thermal load loss into account. Finally, maintenance decision making model of the CHP unit is established with maintenance constraints. Case studies show that the model can optimize maintenance strategies and improve the reliability of CHP unit and the overall system efficiency. © 2020 IEEE.

关键词： Decision making

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Spiking Neural Network for Intra-cortical Brain Signal Decoding

arXiv

引用

arXiv 2025年

作者： Yang, Song Fu, Haotian Zhang, Herui Zhang, Peng Li, Wei Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China Department of Biomedical Engineering College of Life Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Decoding brain signals accurately and efficiently is crucial for intra-cortical brain-computer interfaces. Traditional decoding approaches based on neural activity vector features suffer from low accuracy, whereas deep learning based approaches have high computational cost. To improve both the decoding accuracy and efficiency, this paper proposes a spiking neural network (SNN) for effective and energy-efficient intra-cortical brain signal decoding. We also propose a feature fusion approach, which integrates the manually extracted neural activity vector features with those extracted by a deep neural network, to further improve the decoding accuracy. Experiments in decoding motor-related intra-cortical brain signals of two rhesus macaques demonstrated that our SNN model achieved higher accuracy than traditional artificial neural networks;more importantly, it was tens or hundreds of times more efficient. The SNN model is very suitable for high precision and low power applications like intracortical brain-computer interfaces. © 2025, CC BY.

关键词： Deep neural networks

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Temperature prediction of generator carbon brush based on LSTM neural network

Temperature prediction of generator carbon brush based on LS...

引用

2021 China Automation Congress, CAC 2021

作者： Zhang, Qing Jiao, Tingyang Ma, Yinxing Zhang, Youmin Wu, Xiaohui Wu, Pengyue Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China The Faculty of Computing Science The University of Alberta EdmontonABT6G 2R3 Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi 'an University of Technology Xi'an710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University MontrealQCH3G 1M8 Canada Huaneng Weihai Power Generation Co. Ltd Weihai264200 China Xi 'an Thermal Power Research Institute Co. Ltd Xi'an710048 China

ISBN: (纸本)9781665426473

In order to improve the prediction accuracy of the carbon brush temperature trend of the generator, analyzing the operating state of the generator more accurately, and reduce other accidents like the unplanned outage caused by carbon brush failure of the generator in the power plant. A multi-step temperature prediction model based on the LSTM (Long Short-Term Memory) neural network is proposed. The data comes from real operating carbon brush temperature of Weihai Power Plant in ten days. Then the temperature prediction model is established to achieve an accurate prediction of the carbon brush temperature in the future day. The prediction error is stable within 0.4 °C. By comparing the predicted results of the BP model and Elman model, the error between the predicted results of each model and the actual temperature data is analyzed. By comparing the indicators and analyzing the actual curves, the results show that LSTM neural network has higher accuracy in predicting the temperature of generator carbon brush. This method is of reference significance for the accurate analysis of the operation state of the generator and the load analysis of the excitation system. © 2021 IEEE

关键词： Long short-term memory

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Corrigendum to "Multispectral analysis and molecular simulation of quinoa protein-tannic acid interactions: Conformational changes and functional properties" [Food Chem. 481 (2025) 143961] (Food Chemistry (2025) 481, (S0308814625012129), (10.1016/***.2025.143961))

引用

Food Chemistry 2025年 485卷 144571页

作者： Qu, Guangfan Yang, Feiyan Liu, Fei He, Xudong Sun, Shuguo National Engineering Laboratory for Deep Process of Rice and Byproducts Hunan Key Laboratory of Grain-oil Deep Process and Quality Control Hunan Key Laboratory of Forestry Edible Resources Safety and Processing College of Food Science and Engineering Central South University of Forestry and Technology Hunan Changsha410004 China

The authors regret, The SEM morphological structure images labeled 1:0.03 and 1:0.1 were mistakenly interchanged during the figure assembly process. While this error does not affect the scientific conclusions or data interpretation of the study. The authors would like to apologise for any inconvenience caused. © 2025 Elsevier Ltd

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A Parallel Framework for Scene Understanding

A Parallel Framework for Scene Understanding

引用

Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Wenwen Zhang Jiangong Wang Kunfeng Wang School of Software Engineering Xi'an Jiaotong University Xi'an China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China College of Information Science and Technology Beijing University of Chemical Technology Beijing China

Different related computer vision tasks make it possible to understand and analyze the scene totally. However, there is no useful framework combining different tasks for scene understanding. In this paper, we investigate the current state of scene understanding from different aspects relying on different computer vision tasks and propose an effective framework based on the theory of parallel vision to combine different tasks for scene understanding. With the maintained artificial scene throughout time from the proposed framework, we can understand the scene in an elegant way. To explain our proposed framework, a case study is given.

关键词： Computer vision Digital twin Conferences Task analysis

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Effects of field-aging on the impact of biochar on herbicide fate and microbial community structure in the soil environment

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Chemosphere 2024年 348卷 140682页

作者： Cheng, Hongguang Xing, Dan Twagirayezu, Gratien Lin, Shan Gu, Shangyi Tu, Chenglong Hill, Paul W. Chadwick, David R. Jones, Davey L. State Key Laboratory of Environmental Geochemistry Institute of Geochemistry Chinese Academy of Sciences Guizhou Guiyang550002 China School of Environment Natural Resources & Geography Bangor University Gwynedd BangorLL57 2UW United Kingdom Guizhou Academy of Agricultural Science Institute of Pepper Guiyang Guiyang550000 China Ministry of Agriculture College of Resources and Environment Huazhong Agricultural University Wuhan430070 China College of Resources and Environmental Engineering Guizhou University Guiyang550025 China Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University Gui'an New Region Guiyang550025 China SoilsWest Centre for Sustainable Farming Systems Food Futures Institute Murdoch University MurdochWA Australia

Biochar can enhance organic carbon storage and mitigate the adverse effects of pesticides in the soil. However, the mechanisms by which field-aging affects the impacts of biochar on herbicide behavior and the composition of microbial communities in the soil remain unclear. This study aimed to investigate the influences of aged and fresh biochar on herbicide behavior and microbial community structure in the soil. Herein, with 14C-labeled technology, aged treatment (soil amended with field-aged biochar), fresh treatment (soil amended with fresh biochar), and control (soil without biochar) were installed to evaluate their treatment capacities. The results showed that the average leaching out and mineralization of simazine in the aged treatment were significantly higher by 4.8% and 1.66% (P © 2023

关键词： Soils

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