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Tailoring Classical Conditioning Behavior in TiO_(2) Nanowires:ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware

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Nano-Micro Letters 2024年第7期16卷 265-280页

作者： Wenxiao Wang Yaqi Wang Feifei Yin Hongsen Niu Young-Kee Shin Yang Li Eun-Seong Kim Nam-Young Kim School of Information Science and Engineering University of JinanJinan 250022People’s Republic of China rfic centre NDAC CentreKwangwoon UniversityNowon-guSeoul 139-701South Korea Department of Electronics Engineering Kwangwoon UniversityNowon-GuSeoul 139-701South Korea School of Microelectronics Shandong UniversityJinan 250101People’s Republic of China Department of Molecular Medicine and Biopharmaceutical Sciences Seoul National UniversitySeoul 08826South Korea

Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial ***,research into synaptic devices exhibiting complex associative learning behaviors is still ***,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning *** implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical *** the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual *** importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,*** training through associative pairs,reflexes could be triggered solely using light ***-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly *** work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.

关键词： Artificial intelligence Classical conditioning Neuromorphic computing Artificial visual memory Optoelectronic memristors ZnO Quantum dots

A Tutorial on Quantized Feedback Control

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 5-17页

作者： Minyue Fu IEEE the School of system Design and Intelligent Manufacturing Shenzhen Key Laboratory of Control Theory and Intelligent Systems and Centre for Control Science and TechnologySouthern University of Science and TechnologyShenzhen 518055China

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

关键词： Consensus control high-precision control networked control quantized estimation quantized feedback control robust control

Optimal Operation with Dynamic Partitioning Strategy for Centralized Shared Energy Storage Station with Integration of Large-scale Renewable Energy

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Journal of Modern Power systems and Clean Energy 2024年第2期12卷 359-370页

作者： Jianlin Li Zhijin Fang Qian Wang Mengyuan Zhang Yaxin Li Weijun Zhang Beijing Future Technology Innovation centre for Electrochemical Energy Storage system Integration North China University of Technology Beijing China State Grid Fujian Electric Power Research Institute Fuzhou China

As renewable energy continues to be integrated into the grid,energy storage has become a vital technique supporting power system *** effectively promote the efficiency and economics of energy storage,centralized shared energy storage(SES)station with multiple energy storage batteries is developed to enable energy trading among a group of *** this paper,we propose the optimal operation with dynamic partitioning strategy for the centralized SES station,considering the day-ahead demands of large-scale renewable energy power *** implement a multi-entity cooperative optimization operation model based on Nash bargaining *** model is decomposed into two subproblems:the operation profit maximization problem with energy trading and the leasing payment bargaining *** distributed alternating direction multiplier method(ADMM)is employed to address the subproblems *** reveal that the optimal operation with a dynamic partitioning strategy improves the tracking of planned output of renewable energy entities,enhances the actual utilization rate of energy storage,and increases the profits of each participating *** results confirm the practicality and effectiveness of the strategy.

关键词： Shared energy storage(SES) dynamic partitioning strategy optimal operation Nash bargaining theory actual utilization rate of energy storage

Advances in advanced solution-synthesis-based structural materials for tactile sensors and their intelligent applications

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InfoMat 2024年第1期6卷 31-64页

作者： Hongsen Niu Ning Li Eun-Seoung Kim Young Kee Shin Nam-Young Kim Guozhen Shen Yang Li School of Information Science and Engineering University of JinanJinanthe People's Republic of China rfic centre Department of Electronics EngineeringKwangwoon UniversitySeoulRepublic of Korea Department of Molecular Medicine and Biopharmaceutical Sciences Seoul National UniversitySeoulRepublic of Korea School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijingthe People's Republic of China School of Microelectronics Shandong UniversityJinanthe People's Republic of China

Intelligent applications,with tactile sensors at their core,represent significant advancement in the field of artificial ***,achieving perception abilities in tactile sensors that match or exceed human skin remains a formidable ***,the design and implementation of hierarchical structural materials are considered the optimal solution to this *** contrast to conventional methods,such as complicated lithography and three-dimensional printing,the cost-effective and scalable nature of advanced solution-synthesis methods makes them ideal for preparing diverse tactile sensors with hierarchical structural ***,the process and applicability of advanced solution synthesis methods have yet to form a seamless ***,the development and intellectualization of tactile sensors based on advanced solution synthesis methods are still in their early stages,and require a comprehensive and systematic review to usher in *** study delves into the advantages and disadvantages of various advanced solution synthesis methods,providing detailed ***,the positive effects of hierarchical structural materials constructed using these methods in tactile sensors and their intelligent applications are also discussed in ***,the challenges and future opportunities faced by this emerging field are summarized.

关键词： aqueous phase reduction artificial intelligence hydrothermal growth in situ polymerization tactile sensor

Multi-Time-Scale Variational Mode Decomposition-Based Robust Fault Diagnosis of Railway Point Machines Under Multiple Noises

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Chinese Journal of Electronics 2024年第3期33卷 814-822页

作者： Junqi LIU Tao WEN Guo XIE Yuan CAO Clive Roberts Shaanxi Key Laboratory of Complex system Control and Intelligent Information Processing Xi'an University of Technology The School of Electronic and Information Engineering Beijing Jiaotong University Birmingham centre for Railway Research and Education University of Birmingham

The fault diagnosis of railway point machines(RPMs) has attracted the attention of engineers and *** have studies considered diverse noises along the *** fulfill this aspect,a multi-time-scale variational mode decomposition(MTSVMD) is proposed in this paper to realize the accurate and robust fault diagnosis of RPMs under multiple *** decomposes condition monitoring signals after coarse-grained processing in varying *** this manner,the information contained in the signal components at multiple time scales can construct a more abundant feature space than at a single *** the experimental validation,a random position,random type,random number,and random length(4R) noise-adding algorithm helps to verify the robustness of the *** adequate experimental results demoristrate the superiority of the proposed MTSVMD-based fault diagnosis.

关键词： Fault diagnosis Condition monitoring Noise Signal processing algorithms Aerospace electronics Rail transportation Robustness

Refinement of α′Martensite by Oxygen in Selective Laser Melted Ti-6Al-4V

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Acta Metallurgica Sinica(English Letters) 2024年第5期37卷 777-792页

作者： Hasfi FNurly Jinhu Zhang Dechun Ren Yusheng Cai Haibin Ji Dongsheng Xu Zhicheng Dong Hao Wang Qingmiao Hu Jiafeng Lei Rui Yang School of Materials Science and Engineering University of Science and Technology of ChinaShenyang 110016China Shi-Changxu Innovation Center for Advanced Materials Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Materials and Chemistry/Interdisciplinary centre for Additive Manufacturing University of Shanghai for Science and TechnologyShanghai 200093China centre for Adaptive system Engineering ShanghaiTech UniversityShanghai 201210China

Oxygen is crucial in influencing the microstructure evolution of selective laser melted(SLMed)Ti–6Al–4V,significantly impacting its applicability in various ***,this study investigates the influnce of oxygen on microstructure evolution,particularlyα′martensite transformation and refinement *** alloys,Ti–6Al–4V–xO(x=0.11,0.16,0.21,and 0.25 wt%),were fabricated by the SLM *** martensite start temperature(M_(s))of Ti–6Al–4V,as evaluated by computation,is 656.8°C,and oxygen was found to increase the M_(s) by about 10°C per 0.1 wt%.The SLMed alloy samples exhibit[001]_(β)growth texture along the build *** analysis of martensite morphology suggests internal twinning on{1011}planes as the lattice invariant strain,which becomes more predominant with increasing oxygen *** of α′martensite plates by oxygen is due to increased lattice distortion,reduced prior β grain size,and oxygen segregation toβgrain *** findings contribute to improving the understanding of the effect of oxygen on the transformation mechanism ofα′martensite during SLM of Ti–6Al–4V.

关键词： Selective laser melting α′Martensite Martensite start temperature Oxygen Ti-6Al-4V

An Initial Perturbation Method for the Multiscale Singular Vector in Global Ensemble Prediction

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Advances in Atmospheric Sciences 2024年第3期41卷 545-563页

作者： Xin LIU Jing CHEN Yongzhu LIU Zhenhua HUO Zhizhen XU Fajing CHEN Jing WANG Yanan MA Yumeng HAN School of Atmospheric Sciences Nanjing University of Information Science&TechnologyNanjing 210044China Chinese Academy of Meteorological Sciences Beijing 100081China CMA Earth system Modeling and Prediction centre(CEMC) Beijing 100081China Key Laboratory of Earth system Modeling and Prediction of China Meteorological Administration Beijing 100081China Tianjin Meteorological Observatory Tianjin 300074China China Meteorological Administration Xiong’an Atmospheric Boundary Layer Key Laboratory Hebei 071799China

Ensemble prediction is widely used to represent the uncertainty of single deterministic Numerical Weather Prediction(NWP) caused by errors in initial conditions(ICs). The traditional Singular Vector(SV) initial perturbation method tends only to capture synoptic scale initial uncertainty rather than mesoscale uncertainty in global ensemble prediction. To address this issue, a multiscale SV initial perturbation method based on the China Meteorological Administration Global Ensemble Prediction system(CMA-GEPS) is proposed to quantify multiscale initial uncertainty. The multiscale SV initial perturbation approach entails calculating multiscale SVs at different resolutions with multiple linearized physical processes to capture fast-growing perturbations from mesoscale to synoptic scale in target areas and combining these SVs by using a Gaussian sampling method with amplitude coefficients to generate initial perturbations. Following that, the energy norm,energy spectrum, and structure of multiscale SVs and their impact on GEPS are analyzed based on a batch experiment in different seasons. The results show that the multiscale SV initial perturbations can possess more energy and capture more mesoscale uncertainties than the traditional single-SV method. Meanwhile, multiscale SV initial perturbations can reflect the strongest dynamical instability in target areas. Their performances in global ensemble prediction when compared to single-scale SVs are shown to(i) improve the relationship between the ensemble spread and the root-mean-square error and(ii) provide a better probability forecast skill for atmospheric circulation during the late forecast period and for short-to medium-range precipitation. This study provides scientific evidence and application foundations for the design and development of a multiscale SV initial perturbation method for the GEPS.

关键词： multiscale uncertainty singular vector initial perturbation global ensemble prediction system

Added Benefit of the Early-Morning-Orbit Satellite Fengyun-3E on the Global Microwave Sounding of the Three-Orbit Constellation

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Advances in Atmospheric Sciences 2024年第1期41卷 39-52页

作者： Juan LI Zhengkun QIN Guiqing LIU Jing HUANG CMA Earth system Modeling and Prediction centre Beijing 100081China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Joint Center for Data Assimilation Research and Applications School of Atmospheric SciencesNanjing University of Information Science&TechnologyNanjing 210044China

The three-orbit constellation can comprehensively increase the spatial coverage of polar-orbiting satellites,but the polar-orbiting satellites currently in operation are only mid-morning-orbit and afternoon-orbit ***-3E(FY-3E)was launched successfully on 5 July 2021 in *** an early-morning-orbit satellite,FY-3E can help form a complete three-orbit observation system together with the mid-morning and afternoon satellites in the current mainstream operational *** this study,we investigate the added benefit of FY-3E microwave sounding observations to the midmorning-orbit Meteorological Operational satellite-B(Met Op-B)and afternoon-orbit Fengyun-3D(FY-3D)microwave observations in the Chinese Meteorological Administration global forecast system(CMA-GFS).The results show that the additional FY-3E microwave temperature sounder-3(MWTS-3)and microwave humidity sounder-2(MWHS-2)data can increase the global coverage of microwave temperature and humidity sounding data by 14.8% and 10.6%,*** enables the CMA-GFS to achieve nearly 100% global coverage of microwave-sounding observations at each analysis ***,after effective quality control and bias correction,the global biases and standard deviations of the differences between observations and model simulations are also *** on the Advanced Microwave Sounding Unit A and the Microwave Humidity Sounder onboard Met Op-B,and the MWTS-2 and MWHS-2 onboard FY-3D,adding the microwave sounding data of FY-3E can further reduce the errors of analysis results and improve the global prediction skills of CMA-GFS,especially for the southern-hemisphere forecasts within 96 hours,all of which are significant at the 95% confidence level.

关键词： data assimilation microwave temperature sounder MWTS-3

Deep-learning-assisted online surface roughness monitoring in ultraprecision fly cutting

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Science China(Technological Sciences) 2024年第5期67卷 1482-1497页

作者： SHEHZAD Adeel RUI XiaoTing DING YuanYuan ZHANG JianShu CHANG Yu LU HanJing CHEN YiHeng Institute of Launch Dynamics Nanjing University of Science and TechnologyNanjing210094China National Key Laboratory of Complex Multibody system Dynamics Nanjing210094China Automotive Engineering centre University of Engineering and TechnologyLahore54890Pakistan School of Science Nanjing University of Science and TechnologyNanjing210094China College of Engineering Peking UniversityBeijing100871China

Surface roughness is one of the most critical attributes of machined components,especially those used in high-performance *** surface roughness monitoring offers advancements comparable to post-process inspection methods,reducing inspection time and costs and concurrently reducing the likelihood of ***,online monitoring approaches for surface roughness are constrained by several limitations,including the reliance on handcrafted feature extraction,which necessitates the involvement of human experts and entails time-consuming ***,the prediction models trained under one set of cutting conditions exhibit poor performance when applied to different experimental *** address these challenges,this work presents a novel deep-learning-assisted online surface roughness monitoring method for ultraprecision fly cutting of copper workpieces under different cutting *** acceleration signals were acquired during each cutting experiment to develop two datasets,and no handcrafted features were *** deep learning models were developed and evaluated using standard performance metrics.A convolutional neural network stacked on a long short-term memory network outperformed all other network models,yielding exceptional results,including a mean absolute percentage error as low as 1.51%and an R2value of 96.6%.Furthermore,the robustness of the proposed model was assessed via a validation cohort analysis using experimental data obtained using cutting parameters different from those previously *** performance of the model remained consistent and commendable under varied conditions,asserting its applicability in real-world scenarios.

关键词： online surface roughness monitoring UPFC deep learning CNN-LSTM vibration signal