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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Junfeng Li Xianglin Kong Fengjun Wang Zhuowei Miao Xiaoyi Wang Xiaopeng Shen Shengjun Zhang Lei Zhao School of Information and Control Engineering China University of Mining and Technology Xuzhou China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematical Beijing China School of Information Science and Engineering Southeast University Nanjing China Department of Electrical Engineering Polytechnique Montreal Montreal Quebec Canada School of Materials Science and Physics China University of Mining and Technology Xuzhou China

This paper presents a dual-frequency coding metasurface (CM) for vortex beam generation. The metasurface unit cell is realized with two symmetric metal layers separated by a dielectric substrate. Each metal layer consists of an outer square ring, a middle square ring, and an inner rhombus patch. Two out-of-phase transmitting states in two bands are achieved by rotating the inner rhombus patch by 90 °. Two 1 = + 2 vortex beams are then realized in two different bands by properly distributing the two states on the metasurface aperture. A metasurface with $30 \times 30$ elements is designed, simulated, and experimentally demonstrated. The experimental results agree well with the simulating ones, showing that the metasurface achieves a high transforming efficiency in both Ku (13.6-14.8GHz) band and Ka (26.7-27.7 GHz) band.

关键词： Wireless communication Electric potential Analytical models Computational modeling Dielectric substrates Metals Apertures

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Out-of-domain generalization for remaining useful life prediction of rotating machinery from a single source: An adversarial contrastive learning approach

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Mechanical Systems and Signal Processing 2025年 236卷

作者： Jie Shang Danyang Xu Pei Liang Chen Jiang Haobo Qiu Liang Gao State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science & Technology Wuhan 430074 PR China School of Mechanical Science and Engineering Huazhong University of Science & Technology Wuhan 430074 PR China National Center of Technology Innovation for Intelligent Design and Numerical Control Wuhan 430074 PR China

With the extensive sensor data provided by the Industrial Internet of Things, data-driven remaining useful life (RUL) prediction methods are crucial for enhancing equipment reliability in industrial environments. To enhance prediction accuracy under unknown operating conditions (OCs), domain adaptation and domain generalization-based RUL prediction methods have emerged. However, when only a single-source domain is available, the lack of sample diversity, coupled with significant and unpredictable domain shifts (DSs) between the source and unknown target domains, hinders the model’s ability to generalize effectively to the unknown target domain. To address these challenges, a novel RUL prediction method based on adversarial contrastive learning for single-source domain generalization (ACL-SDG) under unknown OCs is proposed. First, a semantic embedding-based multi-pseudo-domain generation (SE-MPDG) module is designed, which generates diverse and valid pseudo-domain samples, guided by the developed subdomain-level supervised contrastive learning loss, subdomain continuity manifold regularization, and semantic consistency constraints to improve the model’s out-of-domain generalization capability. Subsequently, a domain-invariant feature-guided RUL prediction (DIF-RP) module is proposed to alleviate DS. This module compels the feature extractor to mine domain-invariant degradation features across different domains, constrained by label-level supervised contrastive learning loss. Finally, adversarial training is conducted between the SE-MPDG and DIF-RP modules to further enhance the diversity of pseudo-domains while ensuring the cross-domain invariance of degradation features. Extensive experimental validation of single-source cross-domain RUL prediction for one practical dataset and two public datasets, under unknown OCs, demonstrates the efficacy and superiority of the proposed method.

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Evaluation and Uncertainty Analysis of Himawari-8 Hourly Aerosol Product Version 3.1 and its Influence on Surface Solar Radiation Before and During the COVID-19 Outbreak

SSRN

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SSRN 2023年

作者： Tang, Chenqian Shia, Chong Husi, Letu Ma, Run Yoshida, Mayumi Kikuchi, Maki Xu, Jian Li, Nan Zhao, Mengjie Chen, Liangfu Shi, Guangyu State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100101 China Nanjing University of Information Science & Technology Nanjing210044 China Remote Sensing Technology Center of Japan Tsukuba305-8505 Japan Japan Aerospace Exploration Agency Tsukuba305-8505 Japan National Space Science Center Chinese Academy of Sciences Beijing100190 China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology Nanjing210044 China Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing100101 China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China University of Chinese Academy of Sciences Beijing100049 China

The hourly Himawari-8 version 3.1 (V31) aerosol product has been released and incorporates an updated Level 2 algorithm that uses forecast data as an a priori estimate. However, there has not been a thorough evaluation of V31 data across a full-disk scan, and V31 has yet to be applied in the analysis of its influence on surface solar radiation (SSR). This study firstly investigates the accuracy of V31 aerosol products, which includes three categories of aerosol optical depth (AOD) (AODMean, AODPure, and AODMerged) as well as the corresponding Ångström exponent (AE), using ground-based measurements from the AERONET and SKYNET. Results indicate that V31 AOD products are more consistent with ground-based measurements compared to previous products (V30). The highest correlation and lowest error were seen in the AODMerged, with a correlation coefficient of 0.8335 and minimal root mean square error of 0.1919. In contrast, the AEMerged shows a larger discrepancy with measurements unlike the AEMean and AEPure. Error analysis reveals that V31 AODMerged has generally stable accuracy across various ground types and geometrical observation angles, however, there are higher uncertainties in areas with high aerosol loading, particularly for fine aerosols. The temporal analysis shows that V31 AODMerged performs better compared to V30, particularly in the afternoon. Finally, the impacts of aerosols on SSR based on the V31 AODMerged are investigated through the development of a sophisticated SSR estimation algorithm in the clear sky. Results demonstrate that the estimated SSR is significant consistency with those of well-known CERES products, with preservation of 20 times higher spatial resolution. The spatial analysis reveals a significant reduction of AOD in the North China Plain before and during the COVID-19 outbreak, resulting in an average 24.57 W m–2 variation of the surface shortwave radiative forcing in clear sky daytime. © 2023, The Authors. All rights reserved.

关键词： COVID-19

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Secure and Privacy-preserving Data-sharing Framework based on Blockchain technology for Al-Najaf/Iraq Oil Refinery 19

Secure and Privacy-preserving Data-sharing Framework based o...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Umran, Samir M. Lu, SongFeng Abduljabbar, Zaid Ameen Lu, Zhi Feng, Bingyan Zheng, Lu Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Iraqi Cement State Company Ministry of Industry and Minerals Baghdad10011 Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518057 China University of Basrah College of Education for Pure Sciences Iraq Al-Kunooze University College Technical Computer Engineering Department Basrah Iraq Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan430074 China Industrial Internet Research Institute Wuhan Huazhong Numerical Control Co. Ltd Wuhan430074 China South-Central University for Nationalities College of Computer Science Wuhan430074 China

ISBN: (纸本)9798350346558

The Industrial Internet of Things or Industry 4.0 efficiently enhances the manufacturing process in terms of raising productivity, system performance, cost reduction, and building large-scale systems. It enables the connection of numerous heterogeneous devices and sensors into the internet network through the utilization of revolutionary techniques that transfer the manufacturing paradigm to intelligent processes. The traditional industrial internet of things adopts centralized architectures and complex encryption algorithms that suffer from several cyber-security threats and lead to data leakage, privacy disclosure, and high computational and communicational costs. In our work, we proposed a decentralized, efficient, low-power, scalable, secure, privacy-preserving, and trusting architecture based on a private blockchain network/smart contract and interplanetary file system technology for the Al-NajafyIraq oil refinery factory. That enables autonomous working and provides a high level of security authentication and privacy preservation, P2P communication, remote access, immutability and information backtracking. Traditional blockchain technology has storage limitation issues, most recent works adopted external servers or the cloud for storage purposes. Our proposed scheme addresses the limitations of blockchain data storage by adopting an interplanetary file system (IPFS) network;provides an efficient data encryption mechanism at the perceptual layer by adopting a lightweight encryption algorithm, high-performance, and ultra-low-power consumption ARM Cortex-M microcontroller. In addition, our architecture succeeds in merging blockchain technology, IoTs, and an IPFS with the oil refinery as an industrial application area. Moreover, it provides an efficient framework that resists common cyber-security attacks and realizes cyber-security requirements represented by data availability, integrity, and confidentiality. © 2022 IEEE.

关键词： Digital storage

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A KDC-enhanced closest point method for thermal analysis on curved geometries using LS-GFDM

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Applied Mathematics Letters 2025年 171卷

作者： Tang, Zhuochao Gu, Jiming Chen, Bin Fu, Zhuojia School of Management Science and Engineering Anhui University of Technology Maanshan243002 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Maanshan243002 China Center for Numerical Simulation Software in Engineering and Sciences College of Mechanics and Engineering Science Hohai University Nanjing211100 China

This paper presents a Krylov-deferred correction (KDC)-enhanced closest point method (CPM) integrated with the least-squares generalized finite difference method (LS-GFDM) for thermal analysis on curved geometries. To overcome the inherent limitations of conventional single-step/multi-step temporal schemes in long-time simulations, we systematically unify three advanced components: (i) CPM's embedding strategy that transforms surface PDEs into extended problems over Cartesian grids, (ii) LS-GFDM's spatial discretization employing dual point sets to enhance applicability beyond conventional GFDM, and (iii) KDC's predictor–corrector framework that iteratively refines temporal solutions to achieve high-order accuracy. Building upon our previous work (Tang et al. 2025) where LS-GFDM was integrated with CPM using explicit Euler temporal schemes, this study constitutes a critical advancement by replacing low-order temporal discretization with the KDC methodology. numerical experiments demonstrate that our KDC-CPM-LSGFDM framework achieves superior numerical performance. © 2025 Elsevier Ltd

关键词： Least squares approximations

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The Maintenance Strategy for Serial Machines Considering Intermediate Buffer and Different Spare Parts Replenishment Methods

The Maintenance Strategy for Serial Machines Considering Int...

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2019计算智能、工程与信息技术世界大会

作者： Shuyuan Gan Xinzhou Zhang Lan Chen Department of Mechanical Engineering Jiangsu University Jiangsu Key Laboratory of Advanced Numerical Control Technology

This paper is devoted to the maintenance strategy of two deteriorating machines,taking into account different spare parts replenishment methods,two spare parts inventories,and buffer level *** minimal system cost is achieved by determining the initiating conditions of *** on machine age and buffer level,the maintenance policy is given with 9 control parameters corresponding to related *** to large complexity involved,the optimization is performed by a method combining Monte Carlo simulation and Genetic Algorithm.A numerical example is given to illustrate the proposed *** results show that the minimal cost seems stable with different production rates of the upstream ***,among two groups of maintenance conditions,higher machine age corresponds to lower buffer *** study firstly considers buffer and different spare replenishment methods together during the maintenance of serial *** proposed method can be theory basis for combined maintenance decisions.

关键词： Carlo Monte The Maintenance Strategy for Serial Machines Considering Intermediate Buffer and Different Spare Parts Replenishment Methods Buffer

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Condition-Based Maintenance Strategy for Stochastic Degradation Systems Considering Spare Parts

Condition-Based Maintenance Strategy for Stochastic Degradat...

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2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2019

作者： Ren, Nai-Fei Wang, Yu Gan, Shu-Yuan Jiangsu University School of Mechanical Engineering Zhen Jiang Jiangsu212013 China Jiangsu Key Laboratory of Advanced Numerical Control Technology Nanjing211167 China School of Mechanical Engineering Jiangsu University Zhen Jiang Jiangsu212013 China

ISBN: (纸本)9781728114279

Effective spare parts inventory management can not only ensure timely maintenance of equipment maintenance activities, but also reduce inventory capital occupation and improve the economic benefits of enterprises. In this paper, we present a condition-based maintenance strategy that considers spare parts issues for systems, with the goal of jointly optimizing conditional-based maintenance and spare parts management. Random systems are gradually degraded and continuously monitored. Spare parts supply using (S-1,S) type inventory strategy. According to the proposed strategy, the replacement of components is based on the actual degree of degradation, which is caused by the demand for spare parts. The Monte Carlo simulation method was used to simulate the proposed condition-based maintenance and spare parts replacement strategy. Therefore, the optimal solution is obtained by jointly optimizing the spare parts and condition-based maintenance of the components. Finally, a numerical example is delivered to show the proposed method. © 2019 IEEE.

关键词： Condition based maintenance

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Secure and Privacy-preserving Data-sharing Framework based on Blockchain technology for Al-Najaf/Iraq Oil Refinery

Secure and Privacy-preserving Data-sharing Framework based o...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Samir M. Umran SongFeng Lu Zaid Ameen Abduljabbar Zhi Lu Bingyan Feng Lu Zheng Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Ministry of Industry and Minerals Iraqi Cement State Company Baghdad Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China College of Education for Pure Sciences University of Basrah Technical Computer Engineering Department Al-Kunooze University College Basrah Iraq School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Huazhong Numerical Control Co. Ltd Industrial Internet Research Institute Wuhan China College of Computer Science South-Central University for Nationalities Wuhan China

The Industrial Internet of Things or Industry 4.0 efficiently enhances the manufacturing process in terms of raising productivity, system performance, cost reduction, and building large-scale systems. It enables the connection of numerous heterogeneous devices and sensors into the internet network through the utilization of revolutionary techniques that transfer the manufacturing paradigm to intelligent processes. The traditional industrial internet of things adopts centralized architectures and complex encryption algorithms that suffer from several cyber-security threats and lead to data leakage, privacy disclosure, and high computational and communicational costs. In our work, we proposed a decentralized, efficient, low-power, scalable, secure, privacy-preserving, and trusting architecture based on a private blockchain network/smart contract and interplanetary file system technology for the Al-NajafyIraq oil refinery factory. That enables autonomous working and provides a high level of security authentication and privacy preservation, P2P communication, remote access, immutability and information backtracking. Traditional blockchain technology has storage limitation issues, most recent works adopted external servers or the cloud for storage purposes. Our proposed scheme addresses the limitations of blockchain data storage by adopting an interplanetary file system (IPFS) network; provides an efficient data encryption mechanism at the perceptual layer by adopting a lightweight encryption algorithm, high-performance, and ultra-low-power consumption ARM Cortex-M microcontroller. In addition, our architecture succeeds in merging blockchain technology, IoTs, and an IPFS with the oil refinery as an industrial application area. Moreover, it provides an efficient framework that resists common cyber-security attacks and realizes cyber-security requirements represented by data availability, integrity, and confidentiality.

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Optimal interface surface determination for multi-axis freeform surface machining with both roughing and finishing

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Chinese Journal of Aeronautics 2018年第2期31卷 370-384页

作者： Lufeng CHEN Pengcheng HU Ming LUO Kai TANG Hong Kong University of Science and Technology Hong Kong China National Numerical Control System Engineering Research Center Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Contemporary Design and Integrated Manufacturing Technology Ministory of EducationNorthwestern Polytechnical University Xi'an 710072 China

In the current practice of multi-axis machining of freeform surfaces, the interface surface between the roughing and finishing process is simply an offset surface of the nominal surface. While there have already been attempts at minimizing the machining time by considering the kinematic capacities of the machine tool and/or the physical constraints such as the cutting force, they all target independently at either the finishing or the roughing process alone and are based on the simple premise of an offset interface surface. Conceivably, since the total machining time should count that of both roughing and finishing process and both of them crucially depend on the interface surface, it is natural to ask if, under the same kinematic capacities and the same physical constraints, there is a nontrivial interface surface whose corresponding total machining time will be the minimum among all the possible（infinite） choices of interface surfaces, and this is the motivation behind the work of this paper. Specifically, with respect to the specific type of iso-planar milling for both roughing and finishing, we present a practical algorithm for determining such an optimal interface surface for an arbitrary freeform surface. While the algorithm is proposed for iso-planar milling, it can be easily adapted to other types of milling strategy such as contour milling. Both computer simulation and physical cutting experiments of the proposed method have convincingly demonstrated its advantages over the traditional simple offset method.

关键词： Feed rate Finishing and roughing process Interface surface lso-planar tool path Physical constraints

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Research on interpolation of NURBS curve based on fractional power

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Journal of Physics: Conference Series 2020年第1期1633卷

作者： Hao Zhu Mulan Wang Baosheng Wang School of Communication Nanjing Institute of Technology Nanjing 211167 China Jiangsu Key Laboratory of Advanced Numerical Control Technology Nanjing 211167 China

According to the problem of discontinuous of jerk and low rate of federate change in S-shape federate control method, a jerk-limited federate control scheme which reduces the shock to machine tool in interpolating is presented. The constraints are analyzed from the angle of bow height error and acceleration. The simulation result shows that this method can improve the feed speed faster, realize the smooth transition of acceleration, and reduce NURBS Flexible impact on machine tool during curve interpolation.

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