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Ultrasonic enhancement of persulfate oxidation system governs emerging pollutants decontamination

Green Energy & Environment 2024年第11期9卷 1666-1678页

作者： Yanpan Li Yanbo Zhou Yi Zhou National Engineering Research Center of Industrial Wastewater Detoxication and Resource Recovery State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical ProcessEast China University of Science and Technology130 Meilong RoadShanghai200237China Shanghai Engineering Research Center for Multi-media Environmental Catalysis and Resource Utilization East China University of Science and Technology130 Meilong RoadShanghai200237China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092China

Emerging contaminants (ECs) are widely present in aquatic environments, posing potential risks to both ecosystems and human health. Theultrasound-assisted persulfate oxidation process has attracted considerable attention in the degradation of ECs due to its ability to generate bothsulfate radicals and cavitation effects, enhancing degradation effects. In this paper, the principle of ultrasonic synergistic Fenton-like oxidationsystem for degrading organic pollutants was reviewed, divided into homogeneous system, non-homogeneous system, and single-atom system toexplore the synergistic effect of ultrasound-enhanced persulfate technology in three aspects, and the effects of environmental factors such asultrasonic frequency and power, system pH, temperature, and initial oxidant concentration on the system's decontamination performance werediscussed. Finally, future research on ultrasonically activated persulfate technology is summarized and prospected.

关键词： Ultrasound Persulfate Emerging contaminants Reaction mechanism Synergistic effects

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Identification of important factors influencing nonlinear counting systems

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Frontiers of Information Technology & Electronic engineering 2022年第1期23卷 123-133页

作者： Xinmin ZHANG Jingbo WANG Chihang WEI Zhihuan SONG State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou310027China

Identifying factors that exert more influence on system output from data is one of the most challenging tasks in science and *** this work,a sensitivity analysis of the generalized Gaussian process regression(SA-GGPR)model is proposed to identify important factors of the nonlinear counting *** SA-GGPR,the GGPR model with Poisson likelihood is adopted to describe the nonlinear counting *** GGPR model with Poisson likelihood inherits the merits of nonparametric kernel learning and Poisson distribution,and can handle complex nonlinear counting ***,understanding the relationships between model inputs and output in the GGPR model with Poisson likelihood is not readily accessible due to its nonparametric and kernel ***-GGPR addresses this issue by providing a quantitative assessment of how different inputs affect the system *** application results on a simulated nonlinear counting system and a real steel casting-rolling process have demonstrated that the proposed SA-GGPR method outperforms several state-of-the-art methods in identification accuracy.

关键词： Important factors Nonlinear counting system Generalized Gaussian process regression Sensitivity analysis Steel casting-rolling process

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HoLens:A visual analytics design for higher-order movement modeling and visualization

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Computational Visual Media 2024年第6期10卷 1079-1100页

作者： Zezheng Feng Fang Zhu Hongjun Wang Jianing Hao Shuang-Hua Yang Wei Zeng Huamin Qu Department of Computer Science and Engineering The Hong Kong University of Science and TechnologyHong KongChina Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Thrust of Computational Media and Arts(CMA) The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 511458China Department of Computer Science University of ReadingBerkshire RG66AHUK Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet Southern University of Science and TechnologyShenzhen 518055China

Higher-order patterns reveal sequential multistep state transitions,which are usually superior to origin-destination analyses that depict only first-order geospatial movement *** methods for higher-order movement modeling first construct a directed acyclic graph(DAG)of movements and then extract higher-order patterns from the ***,DAG-based methods rely heavily on identifying movement keypoints,which are challenging for sparse movements and fail to consider the temporal variants critical for movements in urban *** overcome these limitations,we propose HoLens,a novel approach for modeling and visualizing higher-order movement patterns in the context of an urban *** mainly makes twofold contributions:First,we designed an auto-adaptive movement aggregation algorithm that self-organizes movements hierarchically by considering spatial proximity,contextual information,and tem-poral ***,we developed an interactive visual analytics interface comprising well-established visualization techniques,including the H-Flow for visualizing the higher-order patterns on the map and the higher-order state sequence chart for representing the higher-order state *** real-world case studies demonstrate that the method can adaptively aggregate data and exhibit the process of exploring higher-order patterns using *** also demonstrate the feasibility,usability,and effectiveness of our approach through expert interviews with three domain experts.

关键词： data visualization movement modeling state sequence visualization movement visualization urban visual analytics

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An activated variable parameter gradient‐based neural network for time‐variant constrained quadratic programming and its applications

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 670-679页

作者： Guancheng Wang Zhihao Hao Haisheng Li Bob Zhang PAMI Research Group Department of Computer and Information ScienceUniversity of MacaoTaipaMacaoChina China Industrial Control Systems Cyber Emergency Response Team BeijingChina Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijingChina

This study proposes a novel gradient‐based neural network model with an activated variable parameter,named as the activated variable parameter gradient‐based neural network(AVPGNN)model,to solve time‐varying constrained quadratic programming(TVCQP)*** with the existing models,the AVPGNN model has the following advantages:(1)avoids the matrix inverse,which can significantly reduce the computing complexity;(2)introduces the time‐derivative of the time‐varying param-eters in the TVCQP problem by adding an activated variable parameter,enabling the AVPGNN model to achieve a predictive calculation that achieves zero residual error in theory;(3)adopts the activation function to accelerate the convergence *** solve the TVCQP problem with the AVPGNN model,the TVCQP problem is transformed into a non‐linear equation with a non‐linear compensation problem function based on the Karush Kuhn Tucker ***,a variable parameter with an activation function is employed to design the AVPGNN *** accuracy and convergence rate of the AVPGNN model are rigorously analysed in ***,numerical experiments are also executed to demonstrate the effectiveness and superiority of the proposed ***,to explore the feasibility of the AVPGNN model,appli-cations to the motion planning of a robotic manipulator and the portfolio selection of marketed securities are illustrated.

关键词： computational intelligence mathematics computing optimisation

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Pager Explosion:Cybersecurity Insights and Afterthoughts

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2359-2362页

作者： Chuan Sheng Wanlun Ma Qing-Long Han Wei Zhou Xiaogang Zhu Sheng Wen Yang Xiang Fei-Yue Wang Swinburne University of Technology Hawthorn VIC 3122Australia IEEE the School of Computer and Mathematical Sciences the University of AdelaideAdelaideSouth Australia 5005Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

PAGER EXPLOSION:THE *** 2024 Lebanon pager explosions represent one of the most unexpected and devastating technological incidents in recent *** September 17 and 18,2024,thousands of pagers and walkie-talkies exploded simultaneously across Lebanon and parts of Syria,resulting in 42 deaths and more than 3500 *** handheld communication devices,previously regarded as secure and low-profile,were rigged with concealed explosives and remotely triggered by attackers.

关键词： injuries thoughts explosion

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Distributed Estimation of a Flow Field using Cooperative Underwater Vehicles 63

Distributed Estimation of a Flow Field using Cooperative Und...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： He, Yi Zheng, Ronghao Zhang, Senlin Liu, Meiqin Zhejiang University College of Electrical Engineering Hangzhou310027 China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Xi'an Jiaotong University The National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Xi'an710049 China

ISBN: (纸本)9798350316339

This paper presents a distributed method of cooperative flow field estimation using a group of underwater vehicles in GPS-denied environments without directly measuring the ambient flow velocity. We consider that the vehicle can measure the relative positions of its neighbors and the absolute position when it surfaces. By formulating the measurements into the relative and absolute motion-integration error constraints, the flow field estimation problem is converted into an inverse problem that solves a determined system of nonlinear equations in a distributed way. We then propose a distributed consensus algorithm to solve the above equations, in which each vehicle first shares local flow estimate with its neighbors, and then updates the estimate using local constraints. The convergence of the proposed algorithm is strictly guaranteed, and simulations are provided to validate its effectiveness. © 2024 IEEE.

关键词： Inverse problems

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Synergistic Cu single-atoms and clusters on tubular carbon nitride for efficient photocatalytic performances

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Rare Metals 2024年第11期43卷 5891-5904页

作者： Yu-Xiao Feng Hui-Jun Yu Tian-Guang Lu Zi-Ye Zheng Shuang Tian Li Xiang Shan Zhao Shu-Guang Wang Zuo-Li He Shandong Key Laboratory of Water Pollution Control and Resource Reuse School of Environmental Science and EngineeringShandong UniversityQingdao 266237China Weihai Research Institute of Industrial Technology of Shandong University Shandong UniversityWeihai 264209China School of Electrical Engineering Shandong UniversityJinan 250061China CEDAR Knight Cancer InstituteSchool of MedicineOregon Health and Science UniversityPortland 97201USA

Metal clusters or even single-atoms dispersed and anchored on the photocatalysts'surface can enhance photocatalytic performances on organic pollutant ***,a simple photoreduction method was used to create atomically dispersed metal single-atoms/clusters(MSCs,M=Cu,Pd,Au and Ag)on P-modulated tubular carbon nitride(TCN).The obtained MSCs@TCN demonstrated excellent photocatalytic performances for the degradation of sulfamethazine(SMZ).In particular,the photocatalyst with 2 wt%Cu loading showed ultrahigh SMZ oxidation efficiency(k=0.06110 min^(-1)),almost three times that of TCN(k=0.02066 min^(-1)).It also shows excellent stability in the 5th-cycle *** improved photocatalytic activity of the CuSCs@TCN is ascribed to the synergistic promotion of photogenerated charge separation by Cu single-atoms/clusters as active sites,accelerated charge transfer from bulk TCN to Cu sites through Cu-N_(x)***,the active sites of Cu single-atoms/clusters could promote the production of·O_(2)^(-),which participates in organic oxidation with strong oxidizing holes(h^(+)).This strategy paves a new avenue for designing high-performance photocatalysts decorated with metal single-atoms and clusters.

关键词： Carbon nitride Photocatalysis Cu single-atom Sulfamethazine Degradation

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Privacy-Preserving Deep Learning on Big Data in Cloud

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China Communications 2023年第11期20卷 176-186页

作者： Yongkai Fan Wanyu Zhang Jianrong Bai Xia Lei Kuanching Li State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing 100024China Industrial and Commercial Bank of China Zhuhai Branch Zhuhai 519000China Dept.of Computer Science and Information Engineering Providence UniversityTaichung 43301China

In the analysis of big data,deep learn-ing is a crucial *** data analysis tasks are typically carried out on the cloud since it offers strong computer capabilities and storage ***-ertheless,there is a contradiction between the open nature of the cloud and the demand that data own-ers maintain their *** use cloud resources for privacy-preserving data training,a viable method must be found.A privacy-preserving deep learning model(PPDLM)is suggested in this research to ad-dress this preserving *** preserve data privacy,we first encrypted the data using homomorphic en-cryption(HE)***,the deep learn-ing algorithm’s activation function—the sigmoid func-tion—uses the least-squares method to process non-addition and non-multiplication operations that are not allowed by ***,experimental re-sults show that PPDLM has a significant effect on the protection of data privacy *** with Non-Privacy Preserving Deep Learning Model(NPPDLM),PPDLM has higher computational effi-ciency.

关键词： big data cloud computing deep learning homomorphic encryption privacy-preserving

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Rethinking Distribution Alignment for Inter-class Fairness 1

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1st International Conference on Artificial Intelligence Security and Privacy, AIS and P 2023

作者： Ye, Jinhuang Wu, Jiawei Li, Zuoyong Zheng, Xianghan College of Computer and Big Data Fuzhou University Fuzhou350108 China School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen518107 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9789819997886

ISBN: (纸本)9789819997879

Semi-supervised learning (SSL) is a successful paradigm that can use unlabelled data to alleviate the labelling cost problem in supervised learning. However, the excellent performance brought by SSL does not transfer well to the task of class imbalance. The reason is that the class bias of pseudo-labelling further misleads the decision boundary. To solve this problem, we propose a new plug-and-play approach to handle the class imbalance problem based on a theoretical extension and analysis of distribution alignment. The method, called Basis Transformation Based Distribution Alignment (BTDA), efficiently aligns class distributions while taking into account inter-class *** implements the basis transformation through a learnable transfer matrix, thereby reducing the performance loss caused by pseudo-labelling biases. Extensive experiments show that our proposed BTDA approach can significantly improve performance in class imbalance tasks in terms of both accuracy and recall metrics when integrated with advanced SSL algorithms. Although the idea of BTDA is not complex, it can show advanced performance on datasets such as CIFAR and SVHN. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image classification

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Lean methane combustion over zeolite-supported Pd catalysts:Structure-performance relationship and deactivation mechanism

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Journal of Environmental Sciences 2024年第11期145卷 128-138页

作者： Xingyu Liu Jingkun Chen Bowen Han Renna Li Le Shi Zhongbiao Wu Xiaole Weng Key Laboratory of Environment Remediation and Ecological Health Ministry of EducationCollege of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang UniversityHangzhou 311200China Zhejiang Provincial Engineering Research Centre of Industrial Boiler&Furnace Flue Gas Pollution Control Hangzhou 310058China

Zeolites are a promising support for Pd catalysts in leanmethane(CH_(4))***,three types of zeolites(H-MOR,H-ZSM-5 and H-Y)were selected to estimate their structural effects and deactivation mechanisms in CH_(4)*** show that variations in zeolite structure and surface acidity led to distinct changes in Pd ***/H-MOR with external high-dispersing Pd nanoparticles exhibited the best apparent activity,with activation energy(Ea)at 73 kJ/mol,while Pd/H-ZSM-5 displayed the highest turnover frequency(TOF)at 19.6×10^(−3)sec^(−1),presumably owing to its large particles with more step sites providing active sites in one particle for CH_(4)***/H-Y with dispersed PdO within pore channels and/or Pd2+ions on ion-exchange sites yielded the lowest apparent activity and ***,Pd/H-MOR and Pd/H-ZSM-5 were both stable under a dry condition,but introducing 3 vol.%H_(2)O caused the CH_(4)conversion rate on Pd/H-MOR drop from 100%to 63%and that on Pd/H-ZSM-5 decreased remarkably from 82%to 36%.The former was shown to originate fromzeolite structural dealumination,and the latter principally owed to Pd aggregation and the loss of active PdO.

关键词： Methane combustion Pd catalysts Zeolite Structure-performance relationship Deactivation mechanism

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