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Detection of toluene at ppb levels using Au catalyst supported on Al-doped ZnO

Journal of Environmental chemical Engineering 2025年第4期13卷

作者： Jiali Hong keyu Chen Kaiping Yuan Mingyue Lin Qi Cao Jialong Lin XinLin Wang Xiaoqian Bai Tamao Ishida Toru Murayama Guangli Xiu State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process Shanghai Environmental Protection Key Laboratory on Environmental Standard and Risk Management of Chemical Pollutants School of Resources and Environmental Engineering East China University of Science and Technology Shanghai 200237 PR China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092 PR China Department of Chemistry Fudan University Shanghai 200433 China Frontier Institute of Chip and System State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai 200433 China Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and Environment Southeast University Nanjing 210096 China Research Center for Artificial Photosynthesis (ReCAP) Osaka Metropolitan University 3-3-138 Sugimoto Sumiyoshi-ku Osaka 558-8585 Japan Institute for Catalysis Hokkaido University Kita21 Nishi10 Kita-ku Sapporo Hokkaido 001-0021 Japan

Toluene, a carcinogen widely used in industrial production, necessitates precise detection for environmental and human safety. The semiconductor gas sensor is an efficient and portable test instrument, but most semiconductor gas sensors face the challenge of high detection limit and low sensitivity when detecting trace levels of toluene. Herein, aluminum-doped zinc oxide supported gold nanoparticles (Au/ZnO-Al) material with a small Au nanoparticle size ( d  = 2.80 ± 0.70 nm) was prepared by the deposition precipitation method. Au/ZnO-Al sensor can detect ppb-level toluene with a low detection limit of 1.1 parts per billion (ppb). Additionally, Au/ZnO-Al sensor also shows high response value of 18.3 and excellent selectivity towards 5 parts per million (ppm) toluene at 275 ℃. Meanwhile, Au/ZnO-Al sensor exhibits excellent reproducibility with no significant change in the resistance over five consecutive cycles of the same concentration of 3 ppm and 500 ppb toluene. The developed Au/ZnO-Al sensor can improve the performance of toluene mainly ascribed to the perimeter interface between Au nanoparticles and ZnO as well as the formation of Schottky junction. Furthermore, the co-effect of Au deposition and Al doping significantly increases the amount of adsorbed oxygen, which is beneficial for enhancing the sensing response. Hence, the Au/ZnO-Al sensor has great potential in detecting trace toluene for human safety.

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Event-triggered feedback control for piecewise-affine systems via convex combination 4

Event-triggered feedback control for piecewise-affine system...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Ma, Yifei Wu, Wei Cui, Baotong Ministry of Education Key Laboratory of Advanced Process Control for Light Industry Jiangnan University Wu Xi China

ISBN: (纸本)9781538683392

The problem of event-triggered control for discretetime piecewise-affine system with convex combination is investigated. The condition of asymptotic stability is proposed in the form of linear matrix inequalities (LMIs). The state-feedback control gain under the event-triggered strategy can be obtained by solving the LMIs. Subsequently, an optimization problem for minimizing the upper bound of quadratic cost function for quantifying the control performance are formulated. Unique state-feedback control gain under the event-triggering strategy can be obtained by solving the LMIs optimization problem. The effectiveness of our approach is illustrated by simulations of numerical example, where the number of control input updates is reduced, while the control performance is still guaranteed. © 2018 IEEE.

关键词： Linear matrix inequalities

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An improved approach for automatic spine canal segmentation using probabilistic boosting tree (PBT) with fuzzy support vector machine

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Journal of Ambient Intelligence and Humanized Computing 2020年第6期12卷 6527-6536页

作者： Viji, C. Rajkumar, N. Suganthi, S. T. Venkatachalam, K. kumar, T. Rajesh Pandiyan, Sanjeevi Department of CSE Akshaya College of Engineering and Technology Coimbatore India Department of Computer Engineering Lebanese French University Erbil Iraq School of CSE VIT University Bhopal Bhopal India Department of Information Technology Sri Krishna College of Technology Kovaipudur India Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

Spine canal segmentation is an emerging zone in research proposed to help interpretation and processing of advanced MRI and CT images. For instance, high resolution three-dimensional volumes can be divided to provide an estimation of spine canal atrophy. Spine canal segmentation is complex because of assortment of MRI contrasts and variation in human life structures. This investigation illustrates the details of spine canal segmentation techniques and gives a few measurements that can be utilized to contrast with other segmentation strategies. The details of background and foreground subtraction techniques, spine canal segmentation approach and optimization approach which are utilized in the different applications have been considered. In this paper, spine canal segmentation on probabilistic booting tree (PBT) with fuzzy support vector machine performance measures and metrics are analysed in state-of-the art technologies. Proposed approach is performed on the base of the automatic spine canal segmentation with the group of data MR. This proposed segmentation continue with fuzzy support vector machine (FSVM) technique to make fully automatic stream pipeline. The declaration in an automatic segmentation of stream pipeline was implemented with flexible voxel wise classification accompanying dimensions analogous with 3D Haar and labelled machine learning algorithms i.e. probabilistic boosting tree combined fuzzy support vector machine (PBT-FSVM). The novel segmentation technique correlated with MR data sets provides better accuracy than the exiting techniques and it is shown in experimental outcomes. To still improve performance of the results, online learning classification method can be in the proposed work.

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Quantum Go Machine

arXiv

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arXiv 2020年

作者： Qiao, Lu-Feng Gao, Jun Jiao, Zhi-Qiang Zhang, Zhe-Yong Cao, Zhu Ren, Ruo-Jing Zhang, Chao-Ni Hu, Cheng-Qiu Xu, Xiao-Yun Tang, Hao Ma, Zhi-Hao Jin, Xian-Min School of Physics and Astronomy State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai200240 China CAS Center for Excellence Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui230026 China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China School of Mathematical Sciences Shanghai Jiao Tong University Shanghai200240 China

Go has long been considered as a testbed for artificial intelligence. By introducing certain quantum features, such as superposition and collapse of wavefunction, we experimentally demonstrate a quantum version of Go by using correlated photon pairs entangled in polarization degree of freedom. The total dimension of Hilbert space of the generated states grows exponentially as two players take turns to place the stones in time series. As nondeterministic and imperfect information games are more difficult to solve using nowadays technology, we excitedly find that the inherent randomness in quantum physics can bring the game nondeterministic trait, which does not exist in the classical counterpart. Some quantum resources, like coherence or entanglement, can also be encoded to represent the state of quantum stones. Adjusting the quantum resource may vary the average imperfect information (as comparison classical Go is a perfect information game) of a single game. We further verify its nondeterministic feature by showing the unpredictability of the time series data obtained from different classes of quantum state. Finally, by comparing quantum Go with a few typical games that are widely studied in artificial intelligence, we find that quantum Go can cover a wide range of game difficulties rather than a single point. Our results establish a paradigm of inventing new games with quantum-enabled difficulties by harnessing inherent quantum features and resources, and provide a versatile platform for the test of new algorithms to both classical and quantum machine learning. Copyright © 2020, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

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Corrigendum to "Cynapanoside A exerts protective effects against obesity-induced diabetic nephropathy through ameliorating TRIM31-mediated inflammation, lipid synthesis and fibrosis" [Int. Immunopharmacol. 113 (Part B) (2022) 109395]

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International immunopharmacology 2023年第PT A期125卷 111119页

作者： Jing Luo Jun Tan Junjie Zhao Longyan Wang Jin Liu Xianling Dai Yan Sun Qin Kuang Junmin Hui Jinfeng Chen Gang Kuang Shaocheng Chen Yangli Wang Chenxu Ge Minxuan Xu Chongqing Key Laboratory of Medicinal Resources in the Three Gorges Reservoir Region School of Biological and Chemical Engineering Chongqing University of Education Chongqing 400067 PR China Experiment Center School of Biological and Chemical Engineering Chongqing University of Education Chongqing 400067 PR China. Research Center of Brain Intellectual Promotion and Development for Children Aged 0-6 Years Chongqing University of Education Chongqing 400067 PR China Key Laboratory of Biorheological Science and Technology (Chongqing University) Ministry of Education College of Bioengineering Chongqing University Chongqing 400030 PR China. Electronic address: tanjun@***. Research Center of Brain Intellectual Promotion and Development for Children Aged 0-6 Years Chongqing University of Education Chongqing 400067 PR China. Key Laboratory of Biorheological Science and Technology (Chongqing University) Ministry of Education College of Bioengineering Chongqing University Chongqing 400030 PR China. Chongqing Key Laboratory of Medicinal Resources in the Three Gorges Reservoir Region School of Biological and Chemical Engineering Chongqing University of Education Chongqing 400067 PR China. Chongqing Institute for Food and Drug Control & Chongqing Engineering Research Center for Pharmaceutical Process and Quality Control Chongqing 401121 PR China. Key Laboratory of Biorheological Science and Technology (Chongqing University) Ministry of Education College of Bioengineering Chongqing University Chongqing 400030 PR China. Electronic address: minxuanxu@***.

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optimization of Agrobacterium sp Fermentation process with Improved Bird Swarm Algorithm

Optimization of Agrobacterium sp Fermentation Process with I...

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第30届中国过程控制会议（CPCC 2019）

作者： Yuan Zong Deng-feng Liu Yu-qian Shao Yi-an Liu School of Internet of Things Engineering Jiangnan University Key Laboratory of Industrial Advanced Process Control for Light Industry of Ministry of Education Jiangnan University

To overcome the weakness of slow convergence rate, local optimum and poor overall stability of the Bird Swarm Al gorithm(BSA) in solving high-dimensional nonlinear complex functions, an Improved Bird Swarm Algorithm(IBSA) was dev *** coefficients in the original algorithm were adjusted by a nonlinear function, and the update formula of the bir d position was replaced by the Levi flight formula when the birds maintain vigilance and attempt to move to the center of the p ***, in the optimization process, the BSA was improved by adding chaotic perturbation to the optimal solution a nd using the Simulated Annealing Algorithm(SAA) to re-optimize when the optimal solution of the algorithm remains unchan *** experimental results show that the IBSA is better than the BSA, the Differential Evolution(DE) algorithm and the Par ticle Swarm optimization(PSO) in terms of convergence speed, optimization precision, and *** IBSA was used to so lve the parameters' values of the fermentation process dynamics model of Agrobacterium ***31749, and compared with the group intelligence algorithms such as BSA, GA, and *** experimental results show that the IBSA has significant ad vantages in optimization accuracy and stability, and the IBSA is more suitable for identifying the parameters of the ATCC31749 fermentation process dynamics model.

关键词： Bird swarm algorithm Fermentation process modeling Nonlinear adjustment Levi Flight Chaos disturbance, Simulated annealing

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流程工业制造系统智能化——人工智能与流程制造深度融合

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Engineering 2019年第6期 980-981页

作者：钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

近年来,流程工业制造系统智能化得到了国内外学术界和工业界的高度关注和重视。各国政府联合学术界、工业界纷纷推出了智能制造的战略计划,其主要理念是在工业物联网基础上"通过融合知识的企业级资源计划优化、调度优化和生产过程... 详细信息

近年来,流程工业制造系统智能化得到了国内外学术界和工业界的高度关注和重视。各国政府联合学术界、工业界纷纷推出了智能制造的战略计划,其主要理念是在工业物联网基础上"通过融合知识的企业级资源计划优化、调度优化和生产过程优化实现过程工业的升级转型"。然而,

关键词：人工智能流程制造流程工业深度融合

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LWS based PCA subspace ensemble model for soft sensor development

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IFAC-PapersOnLine 2018年第18期51卷 649-654页

作者： Shi, Xudong Xiong, Weili School of Internet of Things Engineering Jiangnan University WuxiJiangsu Province China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University WuxiJiangsu Province China

Most regression approaches, such as principal component analysis (PCA), are based on an assumption that the process data follow a Gaussian distribution. However, the process data usually dissatisfy that assumption. Thus, the locally weighted standardization (LWS) method is employed for transforming data into an approximate Gaussian distribution. Furthermore, the LWS based subspace PCA ensemble modeling method is developed. The subspace PCA can select important variables in each subspace for ensemble modeling. As a result, the proposed method gives a weaker assumption constrain and a better regression performance. The effectiveness of this approach is testified by two study cases. © 2018

关键词： Gaussian distribution Metadata Principal component analysis Ensemble learning Ensemble modeling Non Gaussian data PCA subspaces process data Soft sensors Study case

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Closed-Loop RBF-PID control Method for Position and Attitude control of Stewart Platform

Closed-Loop RBF-PID Control Method for Position and Attitude...

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第三十八届中国控制会议

作者： Tianyu Huang Liang Shan Jun Li Zhen Yu Chenglin Liu School of Automation Nanjing University of Science and Technology Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University

Stewart platform has the characteristics of high nonlinearity and strong coupling, and conventional control method can not eliminate assembly and theoretical model errors. In this paper, the closed-loop control strategy is used to realize the position and attitude control of Stewart platform. For the closed-loop controller, the online tuning method of controller parameters based on RBF neural network is studied. The simulation results show that the control strategy is better than the conventional control strategy, and the tracking performance and control precision are significantly improved.

关键词： RBF neural network Stewart Platform 6-DOF Parallel Robot Position and Attitude control

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An improved multi-stage nonlinear model predictive control with application to semi-batch polymerization

An improved multi-stage nonlinear model predictive control w...

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Asian control Conference

作者： Jinggao Sun Wuyue Yuan Rui Xue Mengling Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai China School of Information Science and Engineering East China University of Science and Technology Shanghai China

ISBN: (纸本)9781728102634

Nonlinear model predictive control (NMPC) has been widely applied in the chemical industry for its performance of dealing with the multiple input multiple output problem (MIMO) and handling constraints. However, the performance of NMPC would be affected by the accuracy of the model. The NMPC controller has to be robust to uncertainties in the model. In this paper, the scenario-tree based on multi-stage NMPC approach has been applied to the semi-batch polymerization reactor. In this approach, in order to ensure the reasonableness of the uncertain variables and scenario tree number, a Monte Carlo-based second-order nonlinear model and K-means cluster algorithm have been proposed. The weights of each scenario branches are also considered into variable. The simulation results show that the performance of the improved method is better and the variable weights has a good ability of improving the performance of controller.

关键词： Uncertainty optimization Polymers Inductors process control Monte Carlo methods chemicals

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