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Machine learning insights in predicting heavy metals interaction with biochar

Biochar 2024年第1期6卷 157-167页

作者： Xin Wei Yang Liu Lin Shen Zhanhui Lu Yuejie Ai Xiangke Wang School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206People’s Republic of China. School of Mathematics and Physics North China Electric Power UniversityBeijing 102206People’s Republic of China. MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environment and Chemical EngineeringNorth China Electric Power UniversityBeijing 102206People’s Republic of China. Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of ChemistryBeijing Normal UniversityBeijing 100875People’s Republic of China.

The use of machine learning(ML)in the field of predicting heavy metals interaction with biochar is a promising field of research,mainly because of the growing understanding of how removal efficiency is affected by characteristic variables,reaction conditions and biochar *** practical application in biochar still faces large challenges,such as difficulties in data collection,inadequate algorithm development,and insufficient ***,the quantity,quality,and representation of data have a large impact on the accuracy,efficiency,and generalizability of machine learning *** this perspective,the present data descriptors,the efficiency of machine learning-aided property and performance prediction,the interpretation of underlying mechanisms and complicated relationships,and some potential ways to augment the data are discussed regarding the interactions of heavy metals with ***,future perspectives and challenges are discussed,and an enhanced model performance is proposed to reinforce the feasibility of a particular perspective.

关键词： Biochar Heavy metals Interaction mechanism Machine learning

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An Isomerism Learning Model to Solve Time-Varying Problems Through Intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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Improving Small License Plate Detection with Bidirectional Vehicle-Plate Relation 1

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Dai, Songkang Chen, Song-Lu Liu, Qi Zhu, Chao Liu, Yan Chen, Feng Yin, Xu-Cheng School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China EEasy Technology Company Ltd. Zhuhai China

ISBN: (数字)9783031533082

ISBN: (纸本)9783031533075

License plate detection is a critical component of license plate recognition systems. A challenge in this domain is detecting small license plates captured at a considerable distance. Previous researchers have proved that pre-detecting the vehicle can enhance small license plate detection. However, this approach only utilizes the one-way relation that the presence of a vehicle can enhance license plate detection, potentially resulting in error accumulation if the vehicle fails to be detected. To address this issue, we propose a unified network that can simultaneously detect the vehicle and the license plate while establishing bidirectional relationships between them. The proposed network can utilize the vehicle to enhance small license plate detection and reduce error accumulation when the vehicle fails to be detected. Extensive experiments on the SSIG-SegPlate, AOLP, and CRPD datasets prove our method achieves state-of-the-art detection performance, achieving an average detection AP0.5 of 99.5% on these three datasets, especially for small license plates. When incorporating a license plate recognizer that relies on character detection, we can achieve an average recognition accuracy of 95.9%, surpassing all comparative methods. Moreover, we have manually annotated the vehicles within the CRPD dataset and have made these annotations publicly available at https://***/kiki00007/CRPDV. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： License plates (automobile)

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A Time-delay Approach for Extremum Seeking of Nonlinear Static Maps:

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IFAC-PapersOnLine 2023年第1期56卷 258-263页

作者： Yang Zhu Emilia Fridman Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology Zhejiang University China School of Electrical Engineering Tel-Aviv University Israel

This paper develops a constructive time-delay approach to averaging for gradient-based extremum seeking (ES) control of nonlinear static maps of non-quadratic form. Under the assumption that some prior knowledge of the nonlinear map with its derivatives is available, for the first time, we derive a quantitative analysis for ES close-loop systems with upper bounds on the tuning parameter that preserves the exponential stability and on the convergence error of extremum seeking. By transforming the ES system into a time-delay neutral type system with distributed delays, the developed method gives an accurate perturbed system of ES without employing any approximate calculation, and suggests a direct Lyapunov-Krasovskii approach in the form of linear matrix inequalities (LMIs), for the transformed time-delay plant to derive efficient stability conditions.

关键词： Extremum Seeking Time-delay Nonlinear Static Non-quadratic

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RBP-Former: Joint Prediction of RNA-protein Binding Sites on Full-length RNA Transcripts for Multiple RBPs

RBP-Former: Joint Prediction of RNA-protein Binding Sites on...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Li, Yichong Liu, Xiaojian Cheng, Fan Pan, Xiaoyong Yang, Yang Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai200240 China

ISBN: (纸本)9798350386226

RNA-binding proteins (RBPs) are essential for gene expression, and the complex RNA-protein interaction mechanisms require analysis of global RNA information. Therefore, accurate prediction of RBP binding sites on full-length RNA transcripts is crucial for understanding these mechanisms and their roles in diseases. While machine learning methods can predict RBP binding to RNA fragments, extending this to full-length transcripts presents challenges due to sequence length and data imbalance. In this paper, we introduce RBP-Former, a binding site joint prediction model designed specifically for full-length RNA transcripts that can be used for multiple RBPs. This model processes information at both coarse and fine-grained levels to fully exploit sequence data and its interactions with multiple RBPs. We develop multi-level imbalance learning strategies, achieving favorable results on imbalanced data. Our method outperforms existing methods in predicting binding sites on full-length RNA transcripts for multiple RBPs, demonstrating its effectiveness in handling imbalanced label and sample distributions. © 2024 IEEE.

关键词： Binding sites

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Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2222-2232页

作者： Juanjuan Li Junqing Li Xiao Wang Rui Qin Yong Yuan Fei-Yue Wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China the School of Artificial Intelligence Anhui UniversityHefei 266114 the Qingdao Academy of Intelligent Industries Qingdao 230031China the School of Mathematics Renmin University of ChinaBeijing 100872China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive *** security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing *** this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary ***,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and ***,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic *** incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading *** temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation ***,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

关键词： Auction data trading markets multi-blockchain pricing mechanisms

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Energy management of solid oxide fuel cell/lithium battery hybrid system

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CSEE Journal of Power and Energy Systems 2022年 1-14页

作者： Li, Dong Zhong, Xiao Bo Xu, Yuan Wu Wei, Chong Yang Zhao, Song Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China

The research of fuel cell and lithium battery hybrid system has attracted more and more researchers because of its advantages of low emission. However, the lower efficiency of energy management has been a critical factor that obstruct the commercialization of hybrid system. In this work, based on finite element ideas, a solid oxide full cell node model is developed to accurately estimate the operating status of the fuel cell. As for lithium battery, previous energy management studies generally only focused on state of charge, however, state of health is also a key parameter for lithium battery. In this paper, considering the strong coupling between variables we use particle filter algorithm to jointly estimate the state of charge and state of health. To reasonably distribute and manage the energy in the hybrid system, a T-S fuzzy controller for the hybrid system is designed by controlling the state variables in the SOFC model and the state of lithium battery. Finally, our algorithm is verified by DSPACE simulation platform. The result shows that the hybrid system with the energy management strategy not only meets the real-time sharply changing demand but also ensures the hybrid system working efficiently and safely. © 2022 China Electric Power Research Institute. All rights reserved.

关键词： Hybrid systems

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94LVI Algorithms of OIpU(One-Iteration-per-Update) Type Handling Time-Dependent QP(Quadratic Programming) with Two Constraints 41

94LVI Algorithms of OIpU(One-Iteration-per-Update) Type Hand...

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第41届中国控制会议

作者： Yunong Zhang Zhiwen Yuan School of Computer Science and Engineering Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Research Institute of Sun Yat-sen University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents three relatively effective numerical algorithms,i.e.,94 LVI algorithms of OIpU(one-iteration-perupdate) type,to handle time-dependent QP(quadratic programming) problems subject to two constraints respectively(i.e.,equality and inequality constraints,equality and bound constraints,or inequality and bound constraints).Specifically,two "bridges" play essential parts of the methods(i.e.,the first "bridge" makes a QP problem convert to an LVI [linear variational inequality],and the second "bridge" makes the LVI convert to a PLPE [piecewise-linear projection equation]).On the basis of the standard94 LVI algorithm,the methods only update once through the solution of the previous sampling time ***,we conduct a number of experiments to substantiate the three algorithms respectively,which use exponential functions,log functions,and trigonometric functions in corresponding coefficients of the experimental examples.

关键词： Quadratic programming Time-dependent Numerical algorithms Linear variational inequalities(LVI)

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Design of Vehicle Profile for Autonomous Vehicles in Roundabouts used to improve Lane Change Strategy based on Multi-vehicle Collaboration 6

Design of Vehicle Profile for Autonomous Vehicles in Roundab...

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6th IEEE International Conference on Smart Internet of Things, SmartIoT 2022

作者： Cao, Dong Fa Hu, Chuang Ye Ding, N. College of Computer Science and Technology Xinjiang Normal University Urumqi China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Dalian China

ISBN: (数字)9781665479523

ISBN: (纸本)9781665479523

Intelligent and connected vehicles (ICVs) is developed based on Internet of Vehicles (IOV) and intelligent vehicles, has become an effective solution to optimize vehicle traffic and alleviate traffic congestion based on the collaborative strategy of vehicle - road - environment. This paper proposes a lane-changing strategy of vehicles at the exit of roundabout based on the Vehicle Profile(VP) which achieved by the driving characteristics of vehicles in traffic roundabout. Initially, Vehicle Profile(VP) is defined due to the hybrid problem of multi-source heterogeneous data existing in ICVs, then the multi-source heterogeneous data is represented by VP. Moreover, the random forest algorithm is used to dynamically obtain and update the label weight of Vehicle Profile because of the problem of label weight existing in the practical application. In addition, the dynamic weight of the Vehicle Profile is introduced into the design of the vehicle payoff function involved in lane change decision, which solves the problem that the weight of each part of the payoff function is used as a parameter. Finally, the performance of the algorithm is tested and verified by SUMO in roundabout general traffic conditions, congested traffic conditions and sparse traffic conditions. The experimental results show that this algorithm can improve the Efficiency and comfort of vehicle driving in general traffic environment more greatly compared with the situation of traffic congestion and sparse traffic flow. Meanwhile, this algorithm verifies the optimization effect of introducing Vehicle Profile on roundabout traffic strategy. © 2022 IEEE.

关键词： Decision trees

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Indoor Target Tracking Based on Extended Kalman Filter without Velocity Constraint 11

Indoor Target Tracking Based on Extended Kalman Filter witho...

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11th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2023 - Proceedings

作者： Zhou, Jianyu Tian, Zengshan Li, Ze Yuan, Zhengwu Chongqing University of Posts and Telecommunication School of Communications and Information Engineering Chongqing400065 China Chongqing University of Posts and Telecommunication Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China

ISBN: (纸本)9798350326277

This paper presents an enhanced localization algorithm based on the Extended Kalman Filter (EKF). The algorithm takes into account the unknown motion state of the target, omitting the inclusion of velocity in the motion state equation. Additionally, we introduce a Human Motion Characteristics (HMC)-based optimization algorithm to address the issue of estimated locations with significant deviations. To evaluate the performance of the proposed algorithm, we conducted simulations using commercial-grade wireless ray propagation modeling software. The results demonstrate that the algorithm achieves a median error that is 25.8 cm lower than that of the least square (LS) algorithm. Notably, the algorithm exhibits improved localization accuracy, particularly in low signal-to-noise ratio (SNR) environments. © 2023 IEEE.

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