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Physics-informed deep learning for fringe pattern analysis

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Opto-Electronic Advances 2024年第1期7卷 4-15页

作者： Wei Yin Yuxuan Che Xinsheng Li Mingyu Li Yan hu Shijie Feng Edmund Y.Lam Qian Chen Chao Zuo Smart Computational Imaging Laboratory(SCILab) School of Electronic and Optical EngineeringNanjing University of Science and TechnologyNanjing 210094China Smart Computational Imaging Research Institute(SCIRI)of Nanjing University of Science and Technology Nanjing 210019China Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense Nanjing 210094China Department of Electrical and Electronic Engineering The University of Hong KongPokfulamHong Kong SAR 999077China

Recently,deep learning has yielded transformative success across optics and photonics,especially in optical *** neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe ***,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning *** this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) *** parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning *** by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end *** results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during *** proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging.

关键词： optical metrology deep learning physics-informed neural networks fringe analysis phase retrieval

Artificial neural network-based method for discriminating Compton scattering events in high-purity germaniumγ-ray spectrometer

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Nuclear Science and Techniques 2024年第2期35卷 64-84页

作者： Chun-Di Fan Guo-Qiang Zeng Hao-Wen Deng Lei Yan Jian Yang Chuan-Hao hu Song Qing Yang Hou College of Nuclear Technology and Automation Engineering Chengdu University of TechnologyChengdu 610059China

To detect radioactive substances with low activity levels,an anticoincidence detector and a high-purity germanium(HPGe)detector are typically used simultaneously to suppress Compton scattering background,thereby resulting in an extremely low detection limit and improving the measurement ***,the complex and expensive hardware required does not facilitate the application or promotion of this ***,a method is proposed in this study to discriminate the digital waveform of pulse signals output using an HPGe detector,whereby Compton scattering background is suppressed and a low minimum detectable activity(MDA)is achieved without using an expensive and complex anticoincidence detector and *** electric-field-strength and energy-deposition distributions of the detector are simulated to determine the relationship between pulse shape and energy-deposition location,as well as the characteristics of energy-deposition distributions for fulland partial-energy deposition *** relationship is used to develop a pulse-shape-discrimination algorithm based on an artificial neural network for pulse-feature *** accurately determine the relationship between the deposited energy of gamma(γ)rays in the detector and the deposition location,we extract four shape parameters from the pulse signals output by the *** learning is used to input the four shape parameters into the ***,the pulse signals are identified and classified to discriminate between partial-and full-energy deposition *** partial-energy deposition events are removed to suppress Compton *** proposed method effectively decreases the MDA of an HPGeγ-energy dispersive *** results show that the Compton suppression factors for energy spectra obtained from measurements on ^(152)Eu,^(137)Cs,and ^(60)Co radioactive sources are 1.13(344 keV),1.11(662 keV),and 1.08(1332 keV),respectively,and that the corresponding MDAs are 1.4%,5.

关键词： High-purity germaniumγ-ray spectrometer Pulse-shape discrimination Compton scattering Artificial neural network Minimum detectable activity

Process-driven susceptibility assessment of glacial lake outburst debris flow in the Himalayas under climate change

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Advances in Climate Change Research 2024年第3期15卷 500-514页

作者： Bin ZHOU Qiang ZOU hu JIANG Tao YANG Wen-Tao ZHOU Si-Yu CHEN Hong-Kun YAO Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041China University of Chinese Academy of Sciences Beijing 100049China School of Environment and Resource Southwest University of Science and TechnologyMianyang 621010China

Global warming is causing glaciers to retreat and glacial lakes to expand in the Himalayas,which amplifies the risk of glacial lake outburst debris flows(GLODFs)and poses a significant threat to downstream lives and ***,the complex interplay between GLODF occurrences and associated indicators,coupled with the lack of a comprehensive susceptibility indicator system that considers the entire GLODF process,presents a substantial challenge in assessing GLODF susceptibility in the *** study proposes a process-driven GLODF susceptibility assessment indicator system responding to climate change that considers the complete process of GLODF formation,incorporating relevant parameters about upstream,themselves,and downstream of glacial ***,to mitigate subjective factors associated with traditional evaluation methods,we developed three novel hybrid machine-learning models by integrating classic machine-learning algorithms with the whale optimization algorithm(WOA)to delineate the distribution of GLODF susceptibility in the *** the hybrid models effectively predicted the GLODFs occurrence,with the WOA-SVC model demonstrating the highest prediction *** 34%of the catchments exhibit high and very high susceptibility levels,primarily concentrated along the north and south sides of the Himalayan ridge,particularly in the eastern and central *** capturing the physical formation process of hazards,such as topographic potential(highest relative importance value of 40%),can precisely identify GLODF.A total of 128 catchments pose potential transboundary threats,with 24 classified as having a very high susceptibility level and 25 as having a high susceptibility ***,the border region between China and Nepal is a prominent hotspot for transboundary threats of *** findings can provide valuable clues for disaster prevention,mitigation,and cross-border coordination in the Himalayas.

关键词： Glacial lake outburst debris flow Susceptibility assessment Climate change Himalayas

Flotation separation of feldspar from quartz using sodium fluosilicate as a selective depressant

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Rare Metals 2024年第3期43卷 1288-1300页

作者： Xin hu Xian-Ping Luo Zi-Shuai Liu Yong-Bing Zhang He-Peng Zhou Zhi-Zhao Yang Xue-Kun Tang Faculty of Resource and Environmental Engineering Jiangxi University of Science and TechnologyGanzhou341000China Yichun Lithium New Energy Industry Research Institute Jiangxi University of Science and TechnologyYichun336000China

The physical and chemical properties of feldspar and quartz are highly similar,thus they cannot be easily separated *** this work,the flotation separation of feldspar from quartz using sodium fluosilicate(Na_(2)SiF_(6);SF)as a selective depressant was ***,the influence mechanism of SF on the selective flotation separation of feldspar and quartz was investigated via flotation tests,chemical analysis of flotation solution,Fourier transform infrared spectroscopy(FTIR),X-ray photoelectron spectroscopy(XPS)and contact angle *** results of the flotation tests show that feld spar and quartz without SF treatment have good *** SF treatment,feldspar still has good floatability,whereas quartz has significantly reduced *** solution chemical analysis shows that the functional group plays an important role in depressing the quartz is[SiF_(6)]^(2-).FTIR,XPS and contact angle analysis results show that[SiF_(6)]^(2-)is adsorbed only on the surface of ***,a thin hydrophilic SiOF layer is generated on the surface,which interferes with the adsorption of the collector on the surface of the *** phenomenon leads to a significant reduction in quartz's ***,SF has a good ability to separate feldspar from quartz by flotation.

关键词： Flotation separation Depressants Sodium fluorosilicate Quartz Feldspar

基于SOA的综合配置激活系统设计及价值分析

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电信科学 2014年第10期30卷 161-167页

作者：李永强胡俊锋中国移动通信集团广东有限公司广州510623

随着通信行业混业运营的不断加深,市场竞争日益加剧,为了抢占市场先机,快速的业务开通和高品质的网络服务质量成为当前运营商急需解决的难题。为了实现客户业务端到端的快速开通,提出一种基于SOA的网络数据配置激活方法 ,并利用该方法... 详细信息

随着通信行业混业运营的不断加深,市场竞争日益加剧,为了抢占市场先机,快速的业务开通和高品质的网络服务质量成为当前运营商急需解决的难题。为了实现客户业务端到端的快速开通,提出一种基于SOA的网络数据配置激活方法 ,并利用该方法建设了网络数据的综合配置激活系统,实现了"一键式"端到端的业务开通,不仅大幅度提升了业务开通效率,同时避免了业务开通过程中人为的网络数据配置错误,不仅可以确保网络数据配置工作的准确率,而且提升了网络服务质量。

关键词：面向服务的架构业务开通配置激活

Tuning the membrane rejection behavior by surface wettability engineering for an effective water-in-oil emulsion separation

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Chinese Chemical Letters 2024年第6期35卷 480-485页

作者： Yan Zou Yin-Shuang hu Deng-hui Tian Hong Wu Xiaoshu Lv Guangming Jiang Yu-Xi huang Engineering Research Center for Waste Oil Recovery Technology and Equipment Ministry of EducationChongqing Technology and Business UniversityChongqing 400067China School of Environmental Science and Engineering Sun Yat-sen UniversityGuangzhou 510275China Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology(Sun Yat-sen University) Guangzhou 510275China

Membrane-based separation is a promising technology to eliminate water impurities from the oil ***,it remains a great challenge to separate water from highly emulsified viscous oil owing to the high stability of the water droplets in *** we report a surface wettability engineering on an alumina ceramic membrane to achieve an efficient separation of a water-in-oil(W/O)*** with different carbon chain lengths and fluorinated status were introduced to endow the alumina membrane with different surface *** all the modified membranes exhibited excellent separation of the W/O without Span 80(surfactant),the one with amphiphobic wettability and lowest surface energy failed to separate the Span 80 stabilized W/*** presence of Span 80 reduced the interfacial tension of water droplets,making them easier to deform and penetrate the modified membrane with the lowest surface *** reveals that engineering proper surface wettability is the key to separating the oil and water ***,the modified membranes maintained decent separation performance and stability under long-term run separation of the emulsified W/O.

关键词： Water-in-oil emulsion Ceramic membrane Membrane separation Surface wettability

Safer solid-state lithium metal batteries:Mechanisms and strategies

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InfoMat 2024年第2期6卷 1-27页

作者： Shi-Jie Yang Jiang-Kui hu Feng-Ni Jiang Hong Yuan Ho Seok Park Jia-Qi huang School of Materials Science&Engineering Beijing Institute of TechnologyBeijingthe People's Republic of China Advanced Research Institute of Multidisciplinary Science Beijing Institute of TechnologyBeijingthe People's Republic of China College of Chemical Engineering and Technology Taiyuan University of TechnologyTaiyuanShanxithe People's Republic of China Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical EngineeringTsinghua UniversityBeijingthe People's Republic of China Center for Next-Generation Energy Materials and School of Chemical Engineering Sungkyunkwan UniversitySuwonRepublic of Korea

Solid-state batteries that employ solid-state electrolytes(SSEs)to replace routine liquid electrolytes are considered to be one of the most promising solutions for achieving high-safety lithium metal *** with high mechanical modulus,thermal stability,and non-flammability can not only inhibit the growth of lithium dendrites but also enhance the safety of lithium metal ***,several internal materials/electrodes-related thermal hazards demonstrated by recent works show that solid-state lithium metal batteries(SSLMBs)are not ***,understanding the potential thermal hazards of SSLMBs is critical for their more secure and widespread *** this contribution,we provide a comprehensive overview of the thermal failure mechanism of SSLMBs from materials to ***,strategies to improve the thermal safety performance of SSLMBs are included from the view of material enhancement,battery design,and external ***,the future directions are further *** hope that this work can shed bright insights into the path of constructing energy storage devices with high energy density and safety.

关键词： lithium metal batteries safety improvements solid-state batteries thermal failures thermal runaway

Optimization and experimental analysis of sweet potato ship-shaped transplanting trajectory using particle swarm algorithm

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INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING 2024年第3期17卷 100-107页

作者： Liu, Zhengduo hua, Lin Lyu, Zhaoqin hu, Jiaji Zheng, Wenxiu West Anhui Univ Coll Mech & Vehicle Engn Luan 237000 Anhui Peoples R China West Anhui Univ Tradit Chinese Med Inst Anhui Dabie Mt Luan 237012 Anhui Peoples R China Shandong Agr Univ Coll Mech & Elect Engn Tai An 271018 Shandong Peoples R China Anhui Zhengyang Machinery Technol Co Ltd Luan 237012 Anhui Peoples R China

The mechanization of ship-shaped transplanting is currently an urgent problem that should be solved. The movement trajectory of the transplanting mechanism is the key technology to perform ship-shaped transplanting. In this study, a shipshaped transplanting trajectory was built and a mathematical model of a four-link transplanting mechanism was developed based on the requirements of the sweet potato transplanting agronomic technology. The particle swarm optimization algorithm was used, with the length of the four-bar mechanism and the installation angle of the fixed bar serving as the variables to optimize. The objective was to minimize the deviation of the ship-shaped transplanting trajectory, yielding an iterative optimization solution. The MATLAB simulation results showed that the penalty factors of different proportions in the adaptive particle swarm optimization algorithm affected the transplanting trajectory. The optimal penalty factor parameters are alpha=0.6, beta=0.4. They ensure that the transplanting trajectory fulfills the agronomic requirements, and limit the deviation in the return trajectory of the mechanism. The sizes of the optimized four-bar mechanism were 110, 312, 245, 160, 360, and, 160 mm. The determined installation angle was 100 degrees. The results of the field experiments demonstrated that the optimized four-bar transplanting mechanism can better fulfill the agronomic technical requirements of sweet potato ship-shaped transplanting. For a transplanting speed of 0.2 m/s, the average qualified rates of insertion depth, insertion length, and tail height were equal to 94.00%, 93.83%, and 91.67%. The results obtained in this study provide a theoretical basis and technical support for studying and developing sweet potato ship-shaped transplanting machinery.

关键词： sweet potato oblique insertion method mechanical arm particle swarm DESIGN SEPARATION SYSTEM DEVICE

Organic heterojunction synaptic device with ultra high recognition rate for neuromorphic computing

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Nano Research 2024年第6期17卷 5614-5620页

作者： Xuemeng hu Jialin Meng Tianyang Feng Tianyu Wang Hao Zhu Qingqing Sun David Wei Zhang Lin Chen School of Microelectronics State Key Laboratory of Integrated Chips and SystemsFudan UniversityShanghai 200433China National Integrated Circuit Innovation Center Shanghai 201203China

Traditional computing structures are blocked by the von Neumann bottleneck,and neuromorphic computing devices inspired by the human brain which integrate storage and computation have received more and more ***,a flexible organic device with 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene(C8-BTBT)and 2,9-didecyldinaphtho[2,3-b:2′,3′-f]thieno[3,2-b]thiophene(C10-DNTT)heterostructural channel having excellent synaptic behaviors was fabricated on muscovite(MICA)substrate,which has a memory window greater than 20 *** device shows better electrical characteristics than organic field effect transistors with single organic semiconductor ***,the device simulates organism synaptic behaviors successfully,such as paired-pulse facilitation(PPF),long-term potentiation/depression(LTP/LTD)process,and transition from short-term memory(STM)to long-term memory(LTM)by optical and electrical ***,the neuromorphic computing function was verified using the Modified National Institute of Standards and Technology(MNIST)pattern recognition,with a recognition rate nearly 100%without *** research proposes a flexible organic heterojunction with the ultra-high recognition rate in MNIST pattern recognition and provides the possibility for future flexible wearable neuromorphic computing devices.

关键词： organic heterojunction neuromorphic computing synapse behaviors optical modulation Modified National Institute of Standards and Technology(MNIST)pattern recognition