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6th CAA International Conference on Vehicular control and Intelligence, CVCI 2022

作者： Cao, Entong Ding, Wenlong Duan, Bin Song, Jinqiu Zhan, Chenzhong Wan, Dongxiang Zhang, Chenghui School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9781665453745

ISBN: (纸本)9781665453745

Four-switch buck-boost converter (FSBB) has received extensive attention in the fields of power battery test and energy storage because of its bidirectional buck and boost capabilities, which are suitable for wide-range voltage changes. However, due to its complex mode detection and disturbance brought by mode transition, it faces great challenge of operating mode selection and also has difficulty in achieving smooth mode transition. In this paper, a mode selection and transition strategy based on predictive control strategy is proposed, and the traditional three modes of FSBB are expanded to four modes, which reduces the sudden change of duty cycle resulted from control dead zones. The predictive control method is used to select the best working mode and ensure smooth transition of working mode. The simulation results demonstrate that the proposed method can successfully accomplish the aforementioned functions and exhibit strong dynamic performance when the input voltage and output are almost equal. © 2022 IEEE.

关键词： Buck-Boost converter

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Slow Convergence of Interacting Kalman Filters in Word-of-Mouth Social Learning 60

Slow Convergence of Interacting Kalman Filters in Word-of-Mo...

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60th Annual Allerton Conference on Communication, control, and Computing, Allerton 2024

作者： Krishnamurthy, Vikram Rojas, Cristian R. School of Electrical and Computer Engineering Cornell University United States School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden

ISBN: (纸本)9798331541033

We consider word-of-mouth social learning involving m Kalman filter agents that operate sequentially. The first Kalman filter receives the raw observations, while each subsequent Kalman filter receives a noisy measurement of the conditional mean of the previous Kalman filter. The prior is updated by the m-th Kalman filter. When m=2, and the observations are noisy measurements of a Gaussian random variable, the covariance goes to zero as k-1/3 for 7kappa;observations, instead of O(k-1) in the standard Kalman filter. In this paper we prove that for m agents, the covariance decreases to zero as k-(2m-1), i.e, the learning slows down exponentially with the number of agents. We also show that by artificially weighing the prior at each time, the learning rate can be made optimal as k-1. The implication is that in word-of-mouth social learning, artificially re-weighing the prior can yield the optimal learning rate. © 2024 IEEE.

关键词： Kalman filters

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Mercury removal from flue gas using nitrate as an electron acceptor in a membrane biofilm reactor

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Frontiers of Environmental science & engineering 2022年第2期16卷 63-74页

作者： Zaishan Wei Meiru Tang Zhenshan Huang Huaiyong Jiao School of Environmental Science and Engineering Sun Yat-sen UniversityGuangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation TechnologyGuangzhou 510275China

Mercury(Hg^(0))is a hazardous air pollutant for its toxicity,and *** study reported that membrane biofilm reactor achieved mercury removal from flue gas using nitrate as the electron ***^(0) removal efficiency was up to 88.7%in 280 days of *** content in flue gas affected mercury redox reactions,mercury biooxidation and microbial *** biological mercury oxidation increased with the increase of oxygen concentration(2%‒17%),methylation of mercury reduced with the increase of oxygen *** dominant bacteria at oxygen concentration of 2%,6%,17%,21%were Halomonas,Anaerobacillus,Halomonas and Pseudomonas,*** addition of ferrous sulfide could immobilize Hg^(2+) effectively,and make both Hg^(2+) and MeHg transform into HgS-like substances,which could achieve the inhibition effect of methylation,and promote conversion of *** dominant bacteria changed from Halomonas to Planctopirus after FeS *** drives mercury oxidation through katE,katG,nar,nir,nor,and nos for Hg^(0) removal in flue gas.

关键词： Mercury removal Oxygen Ferrous sulfide Transformation of mercury Microbial community

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A Planar Quad-Band Bandpass Filter Employing Transmission Lines Loaded with Tri-Stepped Impedance Open-and Dual-Stepped Impedance Short-Ended Resonators

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Progress In Electromagnetics Research C 2024年 147卷 65-72页

作者： Arif, Kamran Phani Kumar, Kanaparthi V. Barik, Rusan Kumar Chakaravarthi, Geetha Department of Instrumentation and Control Engineering National Institute of Technology Tiruchirappalli Tamil Nadu Tiruchirappalli620015 India Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu 603203 India School of Microelectronics Southern University of Science and Technology Guangdong Shenzhen518055 China

A highly miniaturized bandpass filter with quad-band response is demonstrated in this article. The proposed quad-band bandpass filter has a novel topology comprising series quarter wavelength transmission lines loaded with tri-stepped impedance open-ended resonators and a dual-stepped impedance short-ended resonator. The proposed quad-band bandpass filter configuration is validated by theoretically verifying the transmission zeros and pole frequencies using even-odd mode analysis. A prototype operating at 0.475 GHz, 1.695 GHz, 3.48 GHz, and 4.53 GHz is designed, implemented, and experimented. The tested insertion losses at these center frequencies are 0.38 dB, 0.71 dB, 1.03 dB, and 1.22 dB, and the return loss is better than 10 dB in each passband. Each passband is isolated by a transmission zero with a rejection better than 40 dB. The proposed quad-band filter occupies a compact size of 0.146 × 0.087λ2g and is distinguished by its high compactness, wide bandwidth, multiple transmission zeros and poles, and high performance compared to benchmark designs making it more suitable for multi-band wireless applications. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Bandpass filters

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Quantum-Inspired Solvers on Mixed-Integer Linear Programming Problem 41

Quantum-Inspired Solvers on Mixed-Integer Linear Programming...

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第41届中国控制会议

作者： Hao Wang Yu Pan Wei Cui School of Automation Science and Engineering South China University of Technology College of Control Science and Engineering Zhejiang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Mixed-integer linear programming(MILP) plays a crucial role in artificial intelligence,biochemistry,finance,cryptography,*** popular for decades,the researches of MILP solvers are still limited by the resource consumption caused by complexity and failure of Moore's ***-inspired Ising machines,as a new computing paradigm,can be used to solve integer programming problems by reducing them into Ising ***,it is necessary to understand the technical evolution of quantum inspired solvers to break the *** this paper,the concept and traditional algorithms for MILP are ***,focused on Ising model,the principle and implementations of annealers and coherent Ising machines are ***,the paper discusses the challenges and opportunities of miniaturized solvers in the future.

关键词： Mixed-integer Linear Programming Solver Annealer Coherent Ising Machine

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Investigating the impacts of spatial-temporal variation features of air density on assessing wind power generation and its fluctuation in China

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science China(Technological sciences) 2023年第6期66卷 1797-1814页

作者： REN GuoRui WANG Wei WAN Jie HONG Feng YANG Ke YU DaRen School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001China Xi’an Thermal Power Research Institute Co. Ltd.Xi’an 710054China School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China

Air density plays an important role in assessing wind *** density significantly fluctuates both spatially and *** literature typically used standard air density or local annual average air density to assess wind *** present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in *** air density at 100 m height is accurately calculated by using air temperature,pressure,and *** spatial-temporal variation features of air density are firstly *** the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,***ρstoverestimates the annual wind energy production(AEP)in 93.6%of the study *** significantly affects AEP in central and southern China *** more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are ***ρsitesignificantly reduces the estimation error in *** AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in *** for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρ***ρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as *** impacts of air density on assessing wind resource are almost independent of the wind turbine types.

关键词： air density spatial-temporal variation power curve wind resource assessment fluctuation ERA-5

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Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning 41

Harnessing Neural Unit Dynamics for Effective and Scalable C...

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41st International Conference on Machine Learning, ICML 2024

作者： Li, Depeng Wang, Tianqi Chen, Junwei Dai, Wei Zeng, Zhigang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

Class-incremental learning (CIL) aims to train a model to learn new classes from non-stationary data streams without forgetting old ones. In this paper, we propose a new kind of connectionist model by tailoring neural unit dynamics that adapt the behavior of neural networks for CIL. In each training session, it introduces a supervisory mechanism to guide network expansion whose growth size is compactly commensurate with the intrinsic complexity of a newly arriving task. This constructs a near-minimal network while allowing the model to expand its capacity when cannot sufficiently hold new classes. At inference time, it automatically reactivates the required neural units to retrieve knowledge and leaves the remaining inactivated to prevent interference. We name our model AutoActivator, which is effective and scalable. To gain insights into the neural unit dynamics, we theoretically analyze the model's convergence property via a universal approximation theorem on learning sequential mappings, which is under-explored in the CIL community. Experiments show that our method achieves strong CIL performance in rehearsal-free and minimal-expansion settings with different backbones. Copyright 2024 by the author(s)

关键词： Adversarial machine learning

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Evidence of microstructural evolution linked to non-monotonic distribution of micromechanical properties induced by shot peening

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材料科学技术（英文版） 2025年第4期207卷 238-245页

作者： Guoxin Lu Qiang Wang Bonnie Attard Huhu Su Shijian Zheng Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials Ministry of EducationSchool of Materials Science and EngineeringShandong UniversityJinan250061China Aviation Key Laboratory of Science and Technology on Advanced Corrosion and Protection for Aviation Material AECC Beijing Institute of Aeronautical MaterialsBeijing100095China Department of Metallurgy and Materials Engineering University of MaltaMSD2080Malta Tianjin Key Laboratory of Materials Laminating Fabrication and Interface Control Technology School of Materials Science and EngineeringHebei University of TechnologyTianjin300130China

The residual stress field induced by surface strengthening processes such as mechanical shot peening and other forms of plastic deformation does not generally exhibit a simple"monotonic"distribution *** researchers have analyzed this fact from a mechanical perspective based on Hertz ***,the micro/nano-scale microstructural changes corresponding to the distribution of residual stress fields still appear to be *** this study,we focused on a widely used material in aviation manufacturing,namely nickel-based superalloy GH4169,as our experimental *** subjected GH4169 alloy to me-chanical strengthening treatment using a shot peening intensity of 0.25 mmA,followed by quantitative testing of micromechanical performance indicators such as microhardness and residual *** thor-oughly investigate the relationship between micromechanical properties and microstructure changes,we utilized transmission electron microscopy(TEM)to observe and analyze shot-peened materials at differ-ent *** findings revealed that the most severe microstructural distortion induced by mechanical shot peening in GH4169 alloy was likely to occur within a depth range of 25 to 75 *** observation aligns with the actual phenomenon that the maximum microhardness and maximum residual compres-sive stress did not manifest on the outermost surface of the *** presenting a detailed analysis of deformation defects such as dislocations,stacking faults,and twinning in different depths of mechan-ically strengthened layers,our study contributes to a deeper understanding and practical application of post-processing technologies based on plastic deformation.

关键词： Mechanical shot peening Surface strengthening Residual stress Microstructure

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Improvements to YOLOv4 for Steel Surface Defect Detection 5

Improvements to YOLOv4 for Steel Surface Defect Detection

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5th International Conference on Intelligent Autonomous Systems, ICoIAS 2022

作者： Cheng, Yi Wang, Siqing School of Control Science and Engineering Tiangong University Tianjin China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

The effective detection of surface defects in steel is a key concern for steel producers. Conventional target detection algorithms are unable to effectively detect defective targets. Using the advantages of deep learning in feature learning, a surface defect detection algorithm with improved YOLOv4 is proposed to address the problem of poor detection accuracy caused by a variety of steel surface defects and the presence of a large number of small areas and blurred edge damage. Firstly, TBConv (Tied Block Convolution) was introduced to improve the standard convolutional layer in the backbone feature extraction network CSPDarknet to enhance its feature learning capability for different types of surface defects. Secondly, the ECA(Efficient Channel Attention) attention mechanism is introduced in the detection layer to increase the weight of useful features while suppressing the weight of invalid features to improve the ability to fuse shallow and deep information. A cascading bottleneck residual structure is added after the SPP feature pyramid module, with the output of the previous stage being used as the input to the next stage in a sequential training process to enhance the target feature representation. The experimental results show that the improved YOLOv4 algorithm has 6.2% higher accuracy and 27.46% smaller model size compared to the original algorithm, and the algorithm has improved the detection rate of small area defects and can effectively detect surface defect targets. © 2022 IEEE.

关键词： Surface defects

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Audio-Visual Event and Sound Source Localization Based on Spatial-Channel Feature Fusion 7

Audio-Visual Event and Sound Source Localization Based on Sp...

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7th International Conference on Signal and Image Processing, ICSIP 2022

作者： Zheng, Xiaolong Wei, Ying Shandong University School of Control Science and Engineering Jinan China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

In this paper we refer to scenes where visual and sound streams co-occur in video clips as audio-visual events (AVEs), and mainly focus on supervised and weakly supervised audio-visual event localization of unconstrained video clips and sound source localization in audio-visual events. Besides the commonly used spatial attention to learn the weight coefficients of the whole image, the channel attention to learn the weight coefficients of different feature channels is introduced. Key information of audio and video is fused in both spatial and channel domain. And then the fused features from the spatial attention part and channel attention part are further fused as the input of the Bi-LSTM for recognition. We conducted experiments on the public data set AVE, and compared with the previous methods, our method achieved new accuracy in both supervised and weakly supervised audio-visual event positioning, thus verifying the effectiveness of our method. © 2022 IEEE.

关键词： Long short-term memory

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