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Entropy feature extraction on flow pattern of gas/liquid two-phase flow based on cross-section measurement

Journal of Physics: Conference Series 2009年第1期147卷

作者： J Han F Dong Y Y Xu Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering & Automation Tianjin University Tianjin 300072 CHINA Department of Educational Technology Capital Normal University Beijing 100037 CHINA

This paper introduces the fundamental of cross-section measurement system based on Electrical Resistance Tomography (ERT). The measured data of four flow regimes of the gas/liquid two-phase flow in horizontal pipe flow are obtained by an ERT system. For the measured data, five entropies are extracted to analyze the experimental data according to the different flow regimes, and the analysis method is examined and compared in three different perspectives. The results indicate that three different perspectives of entropy-based feature extraction are sensitive to the flow pattern transition in gas/liquid two-phase flow. By analyzing the results of three different perspectives with the changes of gas/liquid two-phase flow parameters, the dynamic structures of gas/liquid two-phase flow is obtained, and they also provide an efficient supplementary to reveal the flow pattern transition mechanism of gas/liquid two-phase flow. Comparison of the three different methods of feature extraction shows that the appropriate entropy should be used for the identification and prediction of flow regimes.

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Three-dimensional force simulation prediction of flexible sensor based on BP neural network

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Journal of Physics: Conference Series 2020年第1期1678卷

作者： Feilu Wang Yufeng Chen Yang Song Yong Hu Rungen Ye Yanan Jiang School of Electronics and Information Engineering Anhui Jianzhu University Hefei 230601 China Key laboratory of building information acquisition and measurement control technology Anhui Jianzhu University Hefei 230601 China

When the robot grabs the object, the force information detection of the object is the basis for the smooth grabbing process. The force information of the object can be fully reflected by detecting the force in the three-dimensional direction. In this paper, with polydimethylsiloxane (PDMS) as the substrate and embedded into the sensitive unit prepared by conductive rubber, a new flexible sensor which can detect three-dimensional force is designed. Firstly, based on the piezoresistive effect of conductive rubber, COMSOL Multiphysics software was used to carry out multi-physical field simulation experiment for the sensor. Furthermore, based on the nonlinear approximation ability of BP neural network and the resistance of simulation output, the training sample set and the test sample set were constructed by using the 5-fold cross validation method, and the BP neural network model was constructed to achieve the accurate prediction of three-dimensional force. Finally, the number of hidden layer neurons was adjusted to optimize the BP network model. The results of cross-validation experiments show that the sensor designed in this paper can effectively detect the three-dimensional force information, and the optimized BP neural network can significantly improve the accuracy of the three-dimensional force prediction.

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Unsupervised Domain Adaptation on Person Re-Identification via Dual-level Asymmetric Mutual Learning

arXiv

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arXiv 2023年

作者： Wu, Qiong Li, Jiahan Dai, Pingyang Ye, Qixiang Cao, Liujuan Wu, Yongjian Ji, Rongrong Institute of Artificial Intelligence The Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen University Xiamen361005 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221000 China The Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen University Xiamen361005 China The Peng Cheng Laboratory Shenzhen518066 China The School of Electronics Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China The Media Analytics and Computing Lab Department of Computer Science School of Informatics Xiamen University Xiamen361005 China The Youtu Laboratory Tencent Shanghai200233 China The Fujian Engineering Research Center of Trusted Artificial Intelligence Analysis and Application Institute of Artificial Intelligence Xiamen University Xiamen361005 China

Unsupervised domain adaptation person re-identification (Re-ID) aims to identify pedestrian images within an unlabeled target domain with an auxiliary labeled source-domain dataset. Many existing works attempt to recover reliable identity information by considering multiple homogeneous networks. And take these generated labels to train the model in the target domain. However, these homogeneous networks identify people in approximate subspaces and equally exchange their knowledge with others or their mean net to improve their ability, inevitably limiting the scope of available knowledge and putting them into the same mistake. This paper proposes a Dual-level Asymmetric Mutual Learning method (DAML) to learn discriminative representations from a broader knowledge scope with diverse embedding spaces. Specifically, two heterogeneous networks mutually learn knowledge from asymmetric subspaces through the pseudo label generation in a hard distillation manner. The knowledge transfer between two networks is based on an asymmetric mutual learning manner. The teacher network learns to identify both the target and source domain while adapting to the target domain distribution based on the knowledge of the student. Meanwhile, the student network is trained on the target dataset and employs the ground-truth label through the knowledge of the teacher. Extensive experiments in Market-1501, CUHK-SYSU, and MSMT17 public datasets verified the superiority of DAML over state-of-the-arts. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation

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Research on the Influence of Non-Conductor on the Weight Function of Electromagnetic Flowmeter

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Journal of Physics: Conference Series 2021年第3期1952卷

作者： Xuejing Li Lijun Sun Shanghai Institute of Measurement and Testing Technology Shanghai 201203 China Shanghai Key Laboratory of On-line Testing and Control Technology Shanghai 201203 China School of Electrical and Information Engineering Tianjin University Tianjin 300072 China.

The demand for multiphase flow measurement is widespread in petrochemical and other fields. Due to its small size, easy maintenance, and no moving parts, electromagnetic flowmeters are widely used in single fluid measurement. With the increasing application of traditional electromagnetic flowmeters in petrochemical and other fields, the problems of traditional electromagnetic flowmeters in multiphase flow measurement applications have been discovered. How to optimize the structure of the electromagnetic flowmeter and how to improve the measurement accuracy has become a new research focus. On the basis of a large number of literature studies, this research is based on the finite element method, and systematically studies the influence of multiphase flow on the weight function of electromagnetic flowmeters. Firstly, modeling the existence of non-conductive objects in the electromagnetic flowmeter. Secondly, analyze the weight function characteristics of the non-conductive objects on the electromagnetic flowmeter from two angles of different radii and different positions. The conclusions of this study can provide a certain reference basis for the electromagnetic flowmeter in the measurement of multiphase flow.

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Origins of Diamond Surface Noise Probed by Correlating Single-Spin measurements with Surface Spectroscopy

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Physical Review X 2019年第3期9卷 031052-031052页

作者： Sorawis Sangtawesin Bo L. Dwyer Srikanth Srinivasan James J. Allred Lila V. H. Rodgers Kristiaan De Greve Alastair Stacey Nikolai Dontschuk Kane M. O’Donnell Di Hu D. Andrew Evans Cherno Jaye Daniel A. Fischer Matthew L. Markham Daniel J. Twitchen Hongkun Park Mikhail D. Lukin Nathalie P. de Leon Department of Electrical Engineering Princeton University Princeton New Jersey 08544 USA Department of Physics Harvard University Cambridge Massachusetts 02138 USA Centre for Quantum Computation and Communication Technology School of Physics University of Melbourne Parkville Victoria 3010 Australia Department of Physics Astronomy and Medical Radiation Science Curtin University Bentley Western Australia 6102 Australia Department of Physics Aberystwyth University SY23 3BZ Aberystwyth United Kingdom Material Measurement Laboratory National Institute of Standards and Technology Gaithersburg Maryland 20899 USA Element Six Harwell OX11 0QR United Kingdom Department of Chemistry and Chemical Biology Harvard University Cambridge Massachusetts 02138 USA

The nitrogen-vacancy (NV) center in diamond exhibits spin-dependent fluorescence and long spin coherence times under ambient conditions, enabling applications in quantum information processing and sensing. NV centers near the surface can have strong interactions with external materials and spins, enabling new forms of nanoscale spectroscopy. However, NV spin coherence degrades within 100 nm of the surface, suggesting that diamond surfaces are plagued with ubiquitous defects. Prior work on characterizing near-surface noise has primarily relied on using NV centers themselves as probes; while this has the advantage of exquisite sensitivity, it provides only indirect information about the origin of the noise. Here we demonstrate that surface spectroscopy methods and single-spin measurements can be used as complementary diagnostics to understand sources of noise. We find that surface morphology is crucial for realizing reproducible chemical termination, and use this insight to achieve a highly ordered, oxygen-terminated surface with suppressed noise. We observe NV centers within 10 nm of the surface with coherence times extended by an order of magnitude.

关键词： NV centers Quantum sensing Surface & interfacial phenomena

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Investigating Correlation of Rough Surface Diffuse Scattering in Frequency Domain

Investigating Correlation of Rough Surface Diffuse Scatterin...

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European Conference on Antennas and Propagation, EuCAP

作者： Yang MIAO Mingming Gan Claude Oestges Katsuyuki Haneda Ke Guan Andrés Alayón Glazunov Wei Wang Yi Gong Dept. of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen China Universite catholique de Louvain Louvain-la-Neuve BE Institute of Information and Communication Technologies Electronics and Applied Mathematics (ICTM) Universit Catholique de Louvain Louvain-la-Neuve Belgium Dept. of Electronics and Nanoengineering Aalto University Espoo Finland State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Dept. of Electrical Engineering University of Twente Enschede Netherlands School of Information Engineering Chang’an University Xi’an China

This paper investigates numerically the correlation function in the frequency domain due to diffuse scattering originated from rough surfaces. The scattered fields are computed by means of physical optics methods. The irregularities of the rough surface are modeled as a correlated Gaussian process. The correlation of the channel transfer function comprising only diffuse scattering components is analyzed. In the analysis, radio propagation channels comprising orthogonally oriented dipoles at the link ends are considered while assuming different Gaussian roughness profiles. This study offers a useful characterization of the channel behavior in a multipath-rich environment due to diffuse scattering. The presented results are of particular interest to wireless systems based on orthogonal frequency-division multiplexing.

关键词： Rough surfaces Surface roughness Correlation Optical surface waves Scattering Surface impedance Frequency-domain analysis

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[email protected] nanorods：Synthesis and their wide controllable range for the local surface plasmon

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Optical Materials 2022年 134卷

作者： Wenlong Yang Xingchen Meng Xinmei Liu Liuyang Zhang Chenwei Wang Xiaoyang Yu Ying Yang School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin 150080 PR China Key Laboratory of Laser Spectroscopy Technology and Application of Heilongjiang Province Harbin 150080 PR China State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing 210016 PR China School of Material Science and Chemical Engineering Harbin University of Science and Technology Harbin 150080 PR China

This work demonstrated the wide controllable range of the Local Surface Plasmon Resonance (LSPR) characteristic peak of the KTa x-1 Nb x O 3 @Ag ( [email protected] ). [email protected] nanocubes ( [email protected] NCs) and [email protected] nanorods ( [email protected] NRs) with different Ag loading rate have been prepared. Compared with [email protected] NCs, the LSPR characteristic peak of [email protected] NRs showed a wider controllable range and the enhanced factor could reach 5.48. This result could be derived from the higher aspect ratio of [email protected] NRs, resulting in an enhanced the coupling effect between KTN and Ag. This viewpoint could also be verified by the FDTD (Finite-Difference Time-Domain) calculation. With the increase of Ag loading rate, the coupling between KTN and Ag was weakened. And the characteristic peak of [email protected] show a blue shift, which shifts to the characteristic peak of Ag nanocrystal gradually. With the increase of Ag loading rate from 11 to 21 wt%, the LPSR characteristic peak of [email protected] NCs showed a blue shift from 569 to 547 nm, whereas peak for [email protected] NRs was shifted from 762 to 646 nm. This work combined the coupling effect of nanostructured KTN and Ag nanocrystals. And the anisotropy would be beneficial to broaden the LSPR controllable range of the characteristic extinction spectra of [email protected] Considering the low price of KTN, the [email protected] NRs should be a promising material applied in optical detection devices.

关键词： FDTD calculation LSPR Coupling effect Loading rate Blue shift

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Generation and storage of spin squeezing via learning-assisted optimal control

arXiv

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arXiv 2020年

作者： Tan, Qing-Shou Zhang, Mao Chen, Yu Liao, Jie-Qiao Liu, Jing Key Laboratory of Hunan Province on Information Photonics and Freespace Optical Communication College of Physics and Electronics Hunan Institute of Science and Technology Yueyang414000 China MOE Key Laboratory of Fundamental Physical Quantities Measurement Hubei Key Laboratory of Gravitation and Quantum Physics PGMF and School of Physics Huazhong University of Science and Technology Wuhan430074 China Tencent Lightspeed & Quantum Studios Shenzhen China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan Province Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China

The generation and storage of spin squeezing is an attractive topic in quantum metrology and the foundations of quantum mechanics. The major models to realize the spin squeezing are the one- and two-axis twisting models. Here, we consider a collective spin system coupled to a bosonic field, and show that proper constant-value controls in this model can simulate the dynamical behavior of these two models. More interestingly, a better performance of squeezing can be obtained when the control is time-varying, which is generated via a reinforcement learning algorithm. However, this advantage becomes limited if the collective noise is involved. To deal with it, we propose a four-step strategy for the construction of a new type of combined controls, which include both constant-value and time-varying controls, but performed at different time intervals. Compared to the full time-varying controls, the combined controls not only give a comparable minimum value of the squeezing parameter over time, but also provides a better lifetime and larger full amount of squeezing. Moreover, the amplitude form of a combined control is simpler and more stable than the full time-varying control. Therefore, our scheme is very promising to be applied in practice to improve the generation and storage performance of squeezing. © 2020, CC BY-NC-SA.

关键词： Reinforcement learning

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Opportunity and shift of nitrogen use in China

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Geography and Sustainability 2024年第1期5卷 33-40页

作者： Wangzheng Shen Jing He Sisi Li Yanhua Zhuang Hongyuan Wang Hongbin Liu Liang Zhang Andreas Kappler Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China University of Chinese Academy of Sciences Beijing 100049China School of Environmental Studies China University of Geosciences(Wuhan)Wuhan 430078China State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution Ministry of Ecology and Environment of the People's Republic of ChinaWuhan 430078China Hubei Key Laboratory of Yangtze River Basin Environmental Aquatic Science Wuhan 430078China Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural SciencesBeijing 100081China Geomicrobiology Group Center for Applied Geosciences(ZAG)University of TuebingenTuebingen D-72076Germany

It is never an easy task for China to feed 1.4 billion people with only 7%of the world's arable *** nearly 30%of the world's nitrogen(N)fertilizer applied,China achieves high crop yields while facing N pollution result-ing from excessive N ***,we calculate the farmland N budget on the national and regional *** N use efficiency(NUE)in China increased by 28.0%during *** improvement is due to the reduction in fertilization and the improvement of crop *** fragmented farmland is changing to large-scale farmland with the increase in cultivated land area per rural population and the development of agricultural *** opportunity brings more possibilities for precision farmland management,thus further improving *** goal of an NUE of 0.6 may be achieved in the 2040s based on the current development *** striking N use shift in China has important implications for other developing countries.

关键词： Environmental Kuznets curve Nitrogen surplus Greenhouse gas emission Climate change Non-point source pollution

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, Computer Retrospective Study

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