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Impacts of meteorology and precursor emission change on O_(3) variation in Tianjin, China from 2015 to 2021

Journal of Environmental sciences 2023年第4期126卷 506-516页

作者： Jing Ding Qili Dai Wenyan Fan Miaomiao Lu Yufen Zhang Suqin Han Yinchang Feng Tianjin Environmental Meteorological Center Qi xiangtai roadTianjin 300074China State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control College of Environmental Science and EngineeringNankai UniversityTianjin 300350China CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research Tianjin 300074China

Deterioration of surface ozone (O_(3)) pollution in Northern China over the past few years received much *** many cities,it is still under debate whether the trend of surface O_(3)variation is driven by meteorology or the change in precursors *** this work,a time series decomposition method (Seasonal-Trend decomposition procedure based on Loess (STL)) and random forest (RF) algorithm were utilized to quantify the meteorological impacts on the recorded O_(3)trend and identify the key meteorological factors affecting O_(3)pollution in Tianjin,the biggest coastal port city in Northern *** “removing” the meteorological fluctuations from the observed O_(3)time series,we found that variation of O_(3)in Tianjin was largely driven by the changes in precursors *** meteorology was unfavorable for O_(3)pollution in period of 2015-2016,and turned out to be favorable during ***,meteorology contributed 9.3μg/m^(3)O_(3)(13%) in 2019,together with the increase in precursors emissions,making 2019 to be the worst year of O_(3)pollution since *** then,the favorable effects of meteorology on O_(3)pollution tended to be *** was the most important factor affecting O_(3)level,followed by air humidity in O_(3)pollution *** the midday of summer days,O_(3)pollution frequently exceeded the standard level (>160μg/m^(3)) at a combined condition with relative humidity in 40%-50%and temperature>31℃.Both the temperature and the dryness of the atmosphere need to be subtly considered for summer O_(3)forecasting.

关键词： Ozone Meteorological conditions Time series decomposition Random forest Meteorological adjustment

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A Nonlinear Coupling-Based Motion Trajectory Planning Method for Double-Pendulum Rotary Crane Subject to State Constraints

A Nonlinear Coupling-Based Motion Trajectory Planning Method...

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International Conference on Applied Nonlinear Dynamics, Vibration and control, ICANDVC 2021

作者： Li, Gang Ma, Xin Li, Zhi Li, Yibin Center for Robotics School of Control Science and Engineering Shandong University Jinan250061 China

ISBN: (纸本)9789811659119

Fast and accurate positioning while suppressing swing is pivotal to efficient and safe operation for the rotary cranes. The problem becomes more complicated when a double-pendulum effect exists for some certain payloads. This paper proposes a nonlinear coupling-based motion trajectory planning method for double-pendulum rotary crane subject to state constraints. The proposed control method consists of two parts: a positioning reference component and a swing-eliminating component. The positioning reference angular acceleration trajectory is derived from a trapezoid-like function with suitable duration, which considers state constraints. The swing-eliminating angular acceleration trajectory is designed based on the nonlinear coupling relationship among the boom luffing motion, the hook swing and the payload swing. State constraints can be guaranteed by adjusting angular acceleration (deceleration) change duration, hold duration and constant velocity duration. The Lyapunov technique and LaSalle’s invariance theorem are used for stability analysis. Simulation results verify the control performance of the proposed nonlinear coupling-based motion trajectory planning method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trajectories

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Molecular behavior and interactions with microbes during anaerobic degradation of bio-derived DOM in waste leachate

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Journal of Environmental sciences 2023年第4期126卷 174-183页

作者： Junjie Qiu Tianqi Li Fan Lü Yulong Huang Chao Li Hua Zhang Liming Shao Pinjing He Institute of Waste Treatment and Reclamation Tongji UniversityShanghai 200092China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China Shanghai Engineering Research Center of Multi-source Solid Wastes Co-Processing and Energy Utilization Shanghai 200092China

It is the key to control bio-derived dissolved organic matters (DOM) in order to reduce the effluent concentration of wastewater treatment, especially for waste leachate with high organic contaminants. In the present study, the anaerobic degradation of aerobically stabilized DOM was investigated with DOM substrate isolated through electrodialysis. The degradation of bio-derived DOM was confirmed by reduction of 15%of total organic carbon in 100 *** characterized the molecular behavior of bio-derived DOM by coupling molecular and biological information analysis. Venn based Sankey diagram of mass features showed the transformation of bio-derived DOM mass features. Occurrence frequency analysis divided mass features into six categories so as to distinguish the fates of intermediate metabolites and persistent compounds. Reactivity continuum model and machine learning technologies realized the semi-quantitative determination on the kinetics of DOM mass features in the form of pseudo-first order, and confirmed the reduction of inert mass features. Furthermore, network analysis statistically establish relationship between DOM mass features and microbes to identify the active microbes that are able to utilize bio-derived DOM. This work confirmed the biological technology is still effective in controlling recalcitrant bio-derived DOM during wastewater treatment.

关键词： Soluble microbial products Data mining Machine learning Solid waste Orbitrap

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Domain Adversarial Enhanced Multi-Channel Graph Networks for Aeroengine Gas Path Fault Diagnosis 49

Domain Adversarial Enhanced Multi-Channel Graph Networks for...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Xu, Changyi Gui, Xuecheng Huo, Mingxiao School of Control Science and Engineering Dalian University of Technology Dalian China Research Institute of Robotics Uc Berkeley Berkeley United States

ISBN: (纸本)9798350331820

The gas path system is an important part of aero-engine, and its fault will bring terrible suffering, therefore the research on fault diagnosis method of the gas path has always been a concern. However, the existing diagnosis methods have the problems of low diagnostic accuracy and poor adaptability to performance degradation. This paper proposes the domain adversarial enhanced multi-channel graph networks to improve the above shortages. In this method, the spatiotemporal series is embedded by multi-head attention enhanced temporal and spatial graph networks, combining domain adversarial training supplemented by spectral norm regularization. On the one hand, this solution can fully mine the spatiotemporal relationship of multivariate sequences in aeroengine gas path, on the other hand, it can improve the difference in data distribution and model generalization. According to the comparison experiment, the proposed model performs better fault feature extraction ability and domain transfer ability, which demonstrates its potential application in gas path fault diagnosis. © 2023 IEEE.

关键词： Failure analysis

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research on Gesture Recognition of Surface EMG Based on Machine Learning 16th

Research on Gesture Recognition of Surface EMG Based on Mach...

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16th Chinese Conference on Biometric Recognition, CCBR 2022

作者： Liu, Linjie Zhang, Na Li, Ke Center for Intelligent Medical Engineering School of Control Science and Engineering Shandong University Jinan250000 China

ISBN: (纸本)9783031202322

Gesture recognition pertains to recognizing meaningful expressions of motion by human, it is utmost important in medical rehabilitation, robot control as well as prosthesis design. Compared with gesture recognition based on machine vision, the gesture recognition based on wearable device, especially wearable surface electromyogram (sEMG) signal acquisition equipment, has more important theoretical and practical application prospects. However, there are still many urgent problems in sEMG signals, involving the signal acquisition and recognition accuracy of multi-channel sEMG signals, to be solved. For these problems, we designed a wearable sEMG armband with convenient acquisition and high precision to record sEMG signals and then done the gesture recognition based on deep learning method. Firstly, sEMG signals are classified, denoised and extracted features, and then extended data by sliding window. Then, Convolutional Neural Networks (CNN) and Multilayer Perceptron (MLP) were constructed to classify the 9 predefined gestures. The result showed that both methods achieve high offline recognition rate. The average gesture recognition accuracy of CNN is 99.47%;The average gesture recognition accuracy of MLP is 98.42%. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multilayer neural networks

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Modeling and analysis of the influence of air gap structure size on the churning loss in wet-type permanent magnet synchronous motors

Modeling and analysis of the influence of air gap structure ...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Cheng, Yunkai Li, Shuanglu Lin, Jionghui Liu, Zhicheng Jiang, Chaofan Zhang, Xinbin Yu, Tian Tianmushan Laboratory Hangzhou China Shanghai Aerospace Control Technology Research Institute Shanghai China Science and Technology on Aircraft Control Laboratory Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China Ningbo Institute of Technology Beihang University Ningbo China

Wet-type permanent magnet synchronous motors (WTPMSM) are extensively utilized to meet the power density requirements of electro-hydrostatic actuators (EHA), which are widely used in modern aircraft control systems. These motors are valued for their superior thermal performance and compact design. However, WTPMSM face a key challenge in the form of oil churning loss, especially within narrow air gaps. This churning loss can significantly impact the motor's performance and efficiency. In this paper, an analytical model has been established and computational fluid dynamics (CFD) has been employed to simulate the internal flow of the motor, thereby predicting the churning loss. The paper also investigates churning loss caused by the thread air gap in the wet motor, examining the effects of thread geometry, size, and motor speed on churning loss. Strategies such as optimizing thread design and adjusting operational parameters are proposed to mitigate churning losses. In summary, churning loss of WTPMSM is significantly influenced by the thickness of the air gap and the depth of the threads. These findings provide guidance for the design of electric motors. Future research should delve deeper into the specific impacts of various design parameters on churning losses and explore methods to reduce churning losses through enhanced motor design. © The Institution of engineering & Technology 2024.

关键词： Computational fluid dynamics

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Probabilistic Back-ends for Online Speaker Recognition and Clustering 48

Probabilistic Back-ends for Online Speaker Recognition and C...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Sholokhov, Alexey Kuzmin, Nikita Lee, Kong Aik Chng, Eng Siong Federal Research Center "Computer Science and Control"of the Russian Academy of Sciences Moscow Russia Nanyang Technological University Singapore A∗STAR Institute for Infocomm Research Singapore

ISBN: (纸本)9781728163277

This paper focuses on multi-enrollment speaker recognition which naturally occurs in the task of online speaker clustering, and studies the properties of different scoring back-ends in this scenario. First, we show that popular cosine scoring suffers from poor score calibration with a varying number of enrollment utterances. Second, we propose a simple replacement for cosine scoring based on an extremely constrained version of probabilistic linear discriminant analysis (PLDA). The proposed model improves over the cosine scoring for multi-enrollment recognition while keeping the same performance in the case of one-to-one comparisons. Finally, we consider an online speaker clustering task where each step naturally involves multi-enrollment recognition. We propose an online clustering algorithm allowing us to take benefits from the PLDA model such as the ability to handle uncertainty and better score calibration. Our experiments demonstrate the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Calibration

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Study on Removal of PCDD/Fs from Flue Gas Processed by Pulse Corona Discharge Composite Technology 6

Study on Removal of PCDD/Fs from Flue Gas Processed by Pulse...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Weng, Lingang Qi, Keji Zheng, Licheng Luo, Anfei Liu, Yun Zhu, Jianjun Zhou, Fangzhi Zhejiang Doway Advanced Technology Co. Ltd Hangzhou China Zhejiang Engineering Research Center of Odor Control Hangzhou China

ISBN: (纸本)9798350346671

In this study, the pulse corona discharge composite technology is used to treat flue gas. The pulse corona discharge technology is the main technology, and the bag filter and activated carbon adsorption are the auxiliary processes. The pulse corona discharge adopts the nanosecond narrow pulse power supply to achieve the intense pulse electric field, the electric field intensity is adjustable, and the multi-level discharge ionization superposition is used to remove the dioxins (PCDD/Fs) in the flue gas step by step. Under the given electric field intensity, PCDD/Fs in flue gas will undergo material dissociation and free radical oxidation reaction. With the increase of electric field intensity, the removal efficiency of PCDD/Fs will be increased gradually, and the maximum comprehensive removal efficiency of more than 97% can be achieved. This study shows that the efficient removal of PCDD/Fs in incineration flue gas without secondary pollution can be successfully achieved via the pulsed corona discharge composite technology proposed, and this technology can also be extended to the removal of PCDD/Fs in similar flue gas. This study provides effective theoretical basis for the large-scale promotion and application of this technology. © 2023 IEEE.

关键词： Flue gases

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Tailoring the d-band electronic structure of FePc by direct oxygen bridge on ZIF-8 derived ultrathin carbon shell to improve the oxygen reduction performance

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Nano research 2025年第3期18卷 132-141页

作者： Xilin Zhang Shan Wang Zhiyi Sun Zhongjun Ma Huixuan Wang Zongxian Yang Qingfang Chang Wenxing Chen School of Physics Henan Normal UniversityXinxiang 453007China Energy&Catalysis Center School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Key Laboratory of Yellow River and Huai River Water Environmental and Pollution Control Ministry of EducationSchool of EnvironmentHenan Normal UniversityXinxiang 453007China

Molecular catalysts with well-defined single atom sites and coordination environments exhibit significant potential as oxygen reduction electrocatalysts,but suffering from the activity and stability ***,the ultrathin carbon shell supported FePc molecule electrocatalysts(FePc/TA-ONG-N),featuring with a direct oxygen bridging between FePc and carbon substrate,were designed and *** direct connection with oxygen atom on carbon substrate,certified by the Fourier transform infrared spectroscopy(FTIR)and extended X-ray absorption fine structure(EXAFS),can remarkably enhance the interaction and facilitate electron transfer from Fe,leading to an improved activity by reducing adsorption strength of intermediate species through lowering the d-band center *** resultant half-wave potential of 0.902 V together with a Tafel slope of 23.64 mV·dec^(−1)is superior to Pt/C and control *** catalyst holds a promise as air-cathode electrocatalyst in Zn-air battery with excellent operation stability exceeding 80 *** density functional theory(DFT)calculations and molecular dynamic simulations unveiled that the O-bridge can effectively stabilize the FePc molecule and function as electron buffer to donate/gain electrons to/from Fe atom during the adsorption of *** current findings are insightful for developing molecular catalysts with high performance through substrate engineering and axial coordination.

关键词： metal-organic framework axial coordination interfacial electron transfer iron phthalocyanine oxygen reduction reaction

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Stability of artificial intelligence methods in computed tomography metal artifacts reduction task 5

Stability of artificial intelligence methods in computed tom...

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5th Symposium on Pattern Recognition and Applications, SPRA 2024

作者： Gilmanov, Marat Kirkicha, Andrey Ingacheva, Anastasia Chukalina, Marina Nikolaev, Dmitrii Smart Engines Service LLC Moscow117312 Russia Institute for Information Transmission Problems RAS Moscow Russia Federal Research Center Computer Science and Control RAS Moscow Russia

ISBN: (数字)9781510688803

ISBN: (纸本)9781510688797

Reducing image artifacts in modern computed tomography is one of the most important directions, which also receives a research boost from the rapid development of artificial intelligence and machine learning. The neural network based methods often allow the achievement of the high artifact reduction quality unattainable by classical approaches. Simultaneously, these models tend to be less robust and generalize worse than algorithmic approaches. The output result may degrade severely under the use in cases not represented in learning datasets. In the present work, the robustness and generalization properties of neural network models are studied in the task of metal-like artifact reduction for computed tomography reconstruction. The pipeline for data augmentation is developed for the metal artifacts severity and geometry variations parameters. The pipeline is validated by augmentation of DICDNet model test dataset and evaluating of the corresponding pre-trained DICDNet model. The generated data consisted of 192000 samples for 12×8 combinations of experiment parameters. It was demonstrated that DICDNet is reasonably robust to geometry variations with a maximum deviation of PSNR≈1.5%. At the same time, even small artifact severity growth leads to rapid quality degradation and blurring of studied model output. The degradation reaches ≈22% PSNR deterioration from the baseline algorithmic approach, which is also one of the inputs for the studied model. Copyright © 2025 SPIE.

关键词： Computerized tomography

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