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A Facile Recovery Process for Cathodes from Spent Lithium Iron Phosphate Batteries by Using Oxalic Acid

CSEE Journal of Power and Energy systems 2018年第2期4卷 219-225页

作者： Li Li Jun Lu Longyu Zhai Xiaoxiao Zhang Larry Curtiss Yi Jin Feng Wu Renjie Chen Khalil Amine School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081China Chemical Sciences and Engineering Division Argonne National LaboratoryIL 60439USA Material Science Division Argonne National LaboratoryIL 60439USA State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems China Electric Power Research Institute.Beijing 100192China

A simplistic and novel leaching process is developed to dispose spent lithium iron phosphate(LiFePO_(4))*** this paper,oxalic acid is selected as a leaching reagent to recover lithium as a resource and remove phosphorus from LiFePO_(4) batteries,benefiting from its low natural *** physical properties of spent cathode materials(before leaching)and residues(after leaching)are identified by X-ray diffraction(XRD)and scanning electronic microscopy(SEM)with energy dispersive X-ray spectroscopy(EDS).The total amounts of Li and Fe are analyzed by inductively coupled plasma-atomic emission spectroscopy(ICP-AES).The process occurs under conditions of a 0.3 mol·L^(-1) oxalic acid concentration,a temperature of 80℃,a reaction time of 60 min and a solid/liquid ratio of 60 g·L^(-1).It can effectively precipitate92%ferrum in terms of FeC_(2)O_(4)·2H_(2)O from LiFePO4,with the leaching efficiency of Li achieving up to 98%.This method demonstrates a new strategy for dealing with spent lithium iron phosphate batteries with a low cost and low environmental impact.

关键词： Leaching oxalic acid precipitation spent lithium-ion batteries

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Optimal Feature Selection for EMG-Based Finger Force Estimation Using LightGBM Model

Optimal Feature Selection for EMG-Based Finger Force Estimat...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Yuhang Ye Chao Liu Nabil Zemiti Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Department of Robotics LIRMM CNRS-University of Montpellier Montpellier France Bristol Robotics Laboratory University of the West of England Bristol UK

Electromyogram (EMG) signal has been long used in human-robot interface in literature, especially in the area of rehabilitation. Recent rapid development in artificial intelligence (AI) has provided powerful machine learning tools to better explore the rich information embedded in EMG signals. For our specific application task in this work, i.e. estimate human finger force based on EMG signal, a LightGBM (Gradient Boosting Machine) model has been used. The main contribution of this study is the development of an objective and automatic optimal feature selection algorithm that can minimize the number of features used in the LightGBM model in order to simplify implementation complexity, reduce computation burden and maintain comparable estimation performance to the one with full features. The performance of the LightGBM model with selected optimal features is compared with 4 other popular machine learning models based on a dataset including 45 subjects in order to show the effectiveness of the developed feature selection method.

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Contraction analysis on primal-dual gradient optimization

arXiv

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arXiv 2019年

作者： Su, Yanxu Shi, Yang Sun, Changyin School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Southeast University Nanjing210096 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 3P6 Canada

This paper analyzes the contraction of the primaldual gradient optimization via contraction theory in the context of discrete-time updating dynamics. The contraction theory based on Riemannian manifolds is first established for convergence analysis of a convex optimization algorithm. The equality and inequality constrained optimization cases are studied, respectively. Under some reasonable assumptions, we construct the Riemannian metric to characterize a contraction region. It is shown that if the step-sizes of the updating dynamics are properly designed, the convergence rates for both cases can be obtained according to the contraction region in which the convergence can be ***, the augmented Lagrangian function which is projection free is adopted to tackle the inequality constraints. Some numerical experiments are simulated to demonstrate the effectiveness of the presented contraction analysis results on primal-dual gradient optimization algorithm. Copyright © 2019, The Authors. All rights reserved.

关键词： Convex optimization

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A new Chinese standard for testing of quality control in medical proton/heavy ion beam radiotherapy equipment

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Radiation Medicine and Protection 2023年第4期4卷 177-181页

作者： Jilong Yuan Xiangjie Ma Quanfu Sun Haikuan Liu Shouping Xu Yinxiangzi Sheng Xiaoyun Ma Xiangkui Mu Xinguo Liu Tao Yang Xin Zhang Hsiao-Ming Lu Jinsheng Cheng Key Laboratory of Radiological Protection and Nuclear Emergency China CDCNational Institute for Radiological ProtectionChinese Center for Disease Control and PreventionWHO Collaboration Center for Radiation and HealthBeijing 100088China Institute of Radiation Medicine Fudan UniversityShanghai 200032China National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Medical Physics Shanghai Proton and Heavy Ion Center Shanghai Engineering Research Center of Proton and Heavy Ion Radiation TherapyShanghai 201315China Heavy Ion Center of Wuwei Cancer Hospital Gansu Wuwei Academy of Medical SciencesGansu Wuwei Tumor HospitalWuwei 733000China Department of Radiation Oncology Shandong Cancer Hospital and InstituteShandong First Medical University and Shandong Academy of Medical SciencesJinan 250117China Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China Department of Radiation Oncology The First Medical Center of Chinese PLA General HospitalBeijing 100853China Varian Medical Systems China Co. LtdBeijing 100176China Hefei Ion Medical Center Hefei230088China Ion Medical Research Institute University of Science and Technology of ChinaHefei 230088China

With the development of social economy and radiotherapy technique,proton/heavy ion radiotherapy has been applied widely to clinical *** present,there are at least 29 hospitals in China at various stages of planning,construction,commissioning or clinical operation of medical proton/heavy ion beam radiotherapy *** with common radiotherapy accelerators used in conventional external beam radiotherapy,the proton/heavy ion therapy system has more stringent requirements for quality control so as to achieve an optimum therapeutic *** order to protect the health rights of patients undergoing radiotherapy,to facilitate the relevant administrative supervision departments to carry out standard-based approval and routine supervision and to promote the development of related medical undertakings,the standard for testing of quality control for medical proton/heavy ion beam radiotherapy equipment is drafted to fill the gap in this regard in China and even *** standard contains five indicators and corresponding testing methods for radiological protection and safety and 16 indicators for quality control of equipment *** standard is a mandatory standard and is based on the relevant Chinese legal requirements for the testing of radiotherapy equipment,so all the indicators listed in the standard shall be *** the drafting of the standard,the opinions from hospitals that are currently using proton/heavy ion medical accelerators for radiotherapy purpose and from the related equipment manufacturers were taken into *** draft standard was revised with reference to these opinions and the feasibility of the related quality control *** official version of the standard was released on March 7,2023,and implementation is scheduled to begin on March 1,2024.

关键词： Chinese standard Proton Heavy ion Radiotherapy Quality control

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Distributed model predictive control under inexact primal-dual gradient optimization based on contraction analysis

arXiv

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arXiv 2019年

This paper develops a distributed model predictive control (DMPC) strategy for a class of discrete-time linear systems with consideration of globally coupled constraints. The DMPC under study is based on the dual problem concerning all subsystems, which is solved by means of the primal-dual gradient optimization in a distributed manner using Laplacian consensus. To reduce the computational burden, the constraint tightening method is utilized to provide a capability of premature termination with guaranteeing the convergence of the DMPC optimization. The contraction theory is first adopted in the convergence analysis of the primal-dual gradient optimization under discrete-time updating dynamics towards a nonlinear objective function. Under some reasonable assumptions, the recursive feasibility and stability of the closed-loop system can be established under the inexact solution. A numerical simulation is given to verify the performance of the proposed strategy. Copyright © 2019, The Authors. All rights reserved.

关键词： Closed loop systems

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Vascular environment modeling and verification for the virtual vessel interventional surgery training system 15

Vascular environment modeling and verification for the virtu...

引用

15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Guo, Shuxiang Zhan, Qi Guo, Jian Meng, Cheng Jin, Xiaoliang Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Binshui Xidao Tianjin391 China Intelligent Mechanical Systems Engineering Department Kagawa University 2217-20 Hayashi-cho Takamatsu761-0396 Japan

ISBN: (纸本)9781538660720

At present, cerebrovascular disease has become the number one killer of endangering human health, and minimally invasive interventional surgery is its main treatment method. However, the vascular intervention surgery places high demands on doctors' surgical procedures, and the actual model and training cost are relatively high. Therefore, the research of vascular interventional surgeon training system based on virtual reality technology becomes more and more important. The quality of a training system depends on whether it can provide a training environment that is close to reality. Based on the study of the training system of vascular interventional surgeons before the laboratory, the concept of blood flow resistance and viscous resistance was increased to improve the authenticity of training system. In this paper, the original vascular model was cut into discrete cylindrical containers, and then the Poiseuille's law and Stokes's law were used to calculate the blood flow resistance and viscous resistance in each container. The blood flow resistance module and the viscous drag module were added to the previous model to simulate blood flow resistance and viscous resistance in a virtual environment. This study helps trained doctors to provide a more realistic training environment. Finally, the relevant verification experiment was carried out in this paper, which proved that the training system with added blood flow resistance and viscous resistance was closer to the real environment. © 2018 IEEE.

关键词： Virtual reality

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Wheat Drought Assessment by Remote Sensing Imagery Using Unmanned Aerial Vehicle

Wheat Drought Assessment by Remote Sensing Imagery Using Unm...

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第37届中国控制会议

作者： Jinya Su Matthew Coombes Cunjia Liu Lei Guo Wen-Hua Chen Department of Aeronautical and Automotive Engineering Loughborough University Key Laboratory of Measurement and Control of Complex Systems of Engineering (Southeast University) Ministry of Education School of Electrical Engineering and Automation Beihang University

This work aims at evaluating the usability of remote sensing RGB imagery by an Unmanned Aerial Vehicle（UAV） in assessing wheat drought status. A UAV survey is conducted to collect high-resolution RGB imageries by using DJI S1000 for the experimental wheat fields of Gucheng town, Heibei Province, China. The soil moisture for different plots of the experimental filed is kept at an approximately constant level for the whole growing season in a well controlled environment, where field measurements are performed just after the UAV survey to obtain the soil water content for each plot. A machine learning based wheat drought assessment framework is proposed in this work. In the proposed framework, wheat pixels are first segmented from the soil background using the classical normalized excess green index（NEx G）. Rather than using pixel-wise classification,a pixel square of appropriate dimension is defined as the samples, based on which various features are extracted for the wheat pixels including statistical features and spectral index features. Different classification algorithms are experimented to identify a suitable one in terms of classification accuracy and computation time. It is discovered that Support Vector Machine with Gaussian kernel can obtain an accuracy over 90%, which demonstrates the usefulness of RGB imagery in wheat drought assessment.

关键词： Classification Remote sensing UAV imagery Wheat drought

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Exploring optimal nitrogen management strategies to mitigate nitrogen losses from paddy soil in the middle reaches of the Yangtze River

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Agricultural Water Management 2020年 228卷

作者： Shi, Xinrui Hu, Kelin Batchelor, William D. Liang, Hao Wu, Yali Wang, Qihui Fu, Jin Cui, Xiaoqing Zhou, Feng College of Resources and Environmental Sciences China Agricultural University Key Laboratory of Arable Land Conservation (North China) Ministry of Agriculture Beijing 100193 China Biosystems Engineering Department Auburn University Auburn 36849 AL United States College of Agricultural Engineering Hohai University Nanjing 100193 China National Engineering Laboratory for Lake Pollution Control and Ecological Restoration Chinese Research Academy of Environmental Sciences Beijing 100021 China Sino-France Institute of Earth Systems Science Laboratory for Earth Surface Processes College of Urban and Environmental Sciences Peking University Beijing 100871 China

Excessive fertilization in rice paddy fields leads to surface water eutrophication, groundwater contamination and air pollution. Determining optimum nitrogen (N) management is essential for maintaining rice yield while reducing the environmental risk caused by N loss. A two-year field experiment (2017–2018) was carried out in a typical paddy field in the middle reaches of the Yangtze River. The WHCNS (soil Water Heat Carbon Nitrogen Simulator) model was calibrated and evaluated for simulations of measured ponding water depth, evapotranspiration, aboveground dry matter, yield, runoff and crop N. The model was then used to evaluate the effects of different N fertilizer rates and split-N application ratios (SNR) practices on crop growth and N losses. Results showed that the model performed well in simulating rice growth and N losses in the region. Ammonia volatilization and denitrification were the mainly pathways of N loss in paddy field, and their two-year average losses were 34% and 38% of the total N loss, respectively. N leaching accounted for 23%, and runoff N loss accounted for 5% of total N loss. N losses were evaluated for two different scenarios and simulated ratios of ammonia volatilization, denitrification, N leaching, and runoff to total N loss under different N management scenarios were 15%–53%, 33%–55%, 6%–30%, and 4%–8%, respectively. Ammonia volatilization and N runoff exponentially increased with an increase of N fertilizer rate, whereas denitrification and N leaching showed an increasing and then a decreasing trend. Yield increased by 36 kg ha⁻¹, and the total N loss decreased by 32.6 kg N ha⁻¹ when the N fertilizer rate was reduced from 231 kg N ha⁻¹ to 155 kg N ha⁻¹ and the SNR was changed from 5:3:1 to 1:1:4. Therefore, reducing the N fertilizer rate and increasing the SNR in the late rice growing season can significantly reduce N loss and effectively improve N use efficiency. © 2019 Elsevier B.V.

关键词： N loss Optimal N management Rice Split-N application WHCNS model

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A Brief Research and Lookback of the Development of Iris Recognition

A Brief Research and Lookback of the Development of Iris Rec...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Xiaoshuang Li Shenhua Hu Chengkan Lv Haojun Qin Fenghua Zhu Feiyue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences Beijing China School of electrical engineering and aotumation Wuhan University Wuhan China

Personal identification has been used more and more widely in information society. Iris recognition, as one of numerous identification methods, has already been applied in many situations, because the iris patterns have stable, unique and non-invasive features. We analyze the general process of iris recognition in this paper, including image preprocessing, feature extraction, classification and recognition. We also study the progress in iris recognition brought by deep learning method. It is our belief that traditional approaches play a very significant role in iris recognition field, while deep learning methods will make a great difference to iris recognition.

关键词： Iris recognition Feature extraction Iris Image edge detection Wavelet transforms Automation

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A review and discussion of decomposition-based hybrid models for wind energy forecasting applications

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Applied Energy 2019年 235卷 939-953页

作者： Zheng Qian Yan Pei Hamidreza Zareipour Niya Chen School of Instrumentation Science and Opto-electronics Engineering Beihang University Beijing China Key Laboratory of Precision Opto-Mechatronics Technology Ministry of Education Beihang University Beijing China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing 100192 China Department of Electrical and Computer Engineering University of Calgary Calgary Alberta Canada ABB Corporate Research Center Beijing China

With the continuous growth of wind power integration into the electrical grid, accurate wind power forecasting is an important component in management and operation of power systems. Given the challenging nature of wind power forecasting, various methods are presented in the literature to improve wind power forecasting accuracy. Among them, combining different techniques to construct hybrid models has been frequently reported in the literature. Decomposition-based models are a family of hybrid models that firstly decompose the wind speed/power time series into relatively more stationary subseries, and then build forecasting models for each subseries. In this paper, we present a comprehensive review of decomposition-based wind forecasting methods in order to explore their effectiveness. Decomposition-based hybrid forecasting models are classified into different groups based on the decomposition methods, such as, wavelet, empirical mode decomposition, seasonal adjust methods, variational mode decomposition, intrinsic time-scale decomposition, and bernaola galvan algorithm. We discuss decomposition methods in the context of alternative forecasting algorithms, and explore the challenges of each method. Comparative analysis of various decomposition-based models is also provided. We also explore current research activities and challenges, and identify potential directions for future research on this subject.

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