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arXiv 2019年

作者： Wang, Dong Sahoo, Sujit Kumar Dang, Cuong Nanyang Technological University Singapore 50 Nanyang Avenue 639798 Singapore Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Shanxi Province College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan030024 China School of Electrical Sciences Indian Institute of Technology Goa Goa 403401 India

Super-resolution imaging with advanced optical systems has been revolutionizing technical analysis in various fields from biological to physical sciences. However, many objects are hidden by strongly scattering media such as rough wall corners or biological tissues that scramble light paths, create speckle patterns and hinder object’s visualization, let alone super-resolution imaging. Here, we realize a method to do non-invasive super-resolution imaging through scattering media based on stochastic optical scattering localization imaging (SOSLI) technique. Simply by capturing multiple speckle patterns of photo-switchable emitters in our demonstration, the stochastic approach utilizes the speckle correlation properties of scattering media to retrieve an image with more than five-fold resolution enhancement compared to the diffraction limit, while posing no fundamental limit in achieving higher spatial resolution. More importantly, we demonstrate our SOSLI to do non-invasive super-resolution imaging through not only optical diffusers, i.e. static scattering media, but also biological tissues, i.e. dynamic scattering media with decorrelation of up to 80%. Our approach paves the way to non-invasively visualize various samples behind scattering media at unprecedented levels of detail. Copyright © 2019, The Authors. All rights reserved.

关键词： Stochastic systems

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SVR-PSO based short-term wind power prediction by using multi-source numerical weather prediection 8

SVR-PSO based short-term wind power prediction by using mult...

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8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Zhou, Hao Ding, Min Li, Danyun Wang, Qingyi Tan, Zhili Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China

With the large-scale application of wind power, the wind power prediction has been highlighted. In order to improve the prediction accuracy of wind power and ensure the resource utilization rate, a wind power prediction method based on support vector machine regression and particle swarm optimization based on multi-source NWP (numerical weather prediction) is proposed. Firstly, the SVR (support vector regression) algorithm is introduced to model the multi-source wind speed data, which can effectively extract the main features and improve the wind speed prediction accuracy. Then, the PSO (particle swarm optimization) is used to model the historical predicted power data and the actual power data for power prediction. Finally, the proposed approach provides wind power forecasts for future 1 day in steps of 15 min. The effectiveness of the proposed method is verified by experiments on wind farms and the results show that the proposed method is more accurate and effective than SVR. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Weather forecasting

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Efficiency enhancement of perovskite solar cells via electrospun CuO nanowires as buffer layers

Efficiency enhancement of perovskite solar cells via electro...

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第五届新型太阳能电池学术研讨会

作者： Qinjun Sun Shaolong Zhou Yuying Hao Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Shanxi Province College of Physics and Optoelectronics Taiyuan University of Technology

CuO nanowires（NWs） with the diameters range from 130 nm to 275 nm have been successfully prepared by electrospinning and calcination technique. Inverted planar heterojunction perovskite solar cells（PSCs） with the structure of ITO/CuO NWs/PEDOT:PSS/CHNHPbI/PCBM/Bphen/Ag were fabricated and a best power conversion efficiency（PCE） of 16.87% was obtained under standard AM 1.5 G simulated solar irradiation, with an average increase of about 21 % compared with that of the control PSCs without CuO NWs. By compared with ZnO NWs with the same diameters and quantitative analysis based on a simple model, we concluded that the improvement of PCE by about 13% can be ascribed to the increase of the PEDOT:PSS/CHNHPbI interface area, and the remaining increase of 8% attributed to the higher hole mobility of CuO NWs/PEDOT:PSS composite film.

关键词： perovskite solar cell CuO nanowires electrospin

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Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network 23rd

Cerebrovascular Segmentation in MRA via Reverse Edge Attenti...

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23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Zhang, Hao Xia, Likun Song, Ran Yang, Jianlong Hao, Huaying Liu, Jiang Zhao, Yitian College of Information Engineering Capital Normal University Beijing China Cixi Institute of Biomedical Engineering Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo China School of Control Science and Engineering Shandong University Jinan China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China International Science and Technology Cooperation Base of Electronic System Reliability and Mathematical Interdisciplinary Capital Normal University Beijing China Laboratory of Neural Computing and Intelligent Perception Capital Normal University Beijing China Beijing Advanced Innovation Center for Imaging Theory and Technology Capital Normal University Beijing China

ISBN: (纸本)9783030597245

Automated extraction of cerebrovascular is of great importance in understanding the mechanism, diagnosis, and treatment of many cerebrovascular pathologies. However, segmentation of cerebrovascular networks from magnetic resonance angiography (MRA) imagery continues to be challenging because of relatively poor contrast and inhomogeneous backgrounds, and the anatomical variations, complex geometry and topology of the networks themselves. In this paper, we present a novel cerebrovascular segmentation framework that consists of image enhancement and segmentation phases. We aim to remove redundant features, while retaining edge information in shallow features when combining these with deep features. We first employ a Retinex model, which is able to model noise explicitly to aid removal of imaging noise, as well as reducing redundancy within an image and emphasizing the vessel regions, thereby simplifying the subsequent segmentation problem. Subsequently, a reverse edge attention module is employed to discover edge information by paying particular attention to the regions that are not salient in high-level semantic features. The experimental results show that the proposed framework enables the reverse edge attention network to deliver a reliable cerebrovascular segmentation. © 2020, Springer Nature Switzerland AG.

关键词： Image enhancement

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Vibration Absorption Efficiency and Higher Branches Elimination of Variable-Stiffness Nonlinear Energy Sink

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Journal of Harbin Institute of Technology 2020年第1期

作者： Rui Zhong Jian’en Chen Weimin Ge Jun Liu Xiaofeng Wang Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System National Demonstration Center for Experimental Mechanical and Electrical Engineering Education

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Research on Fast Error Calibration Methods for Flexible Measuring Arm

Research on Fast Error Calibration Methods for Flexible Meas...

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International Conference on Artificial Intelligence and advanced Manufacturing (AIAM)

作者： Xinhua Zhao Lei Zhao Liangping Ji Jiaxing Zhang School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

Based on the structure of the joint coordinate measuring machine, the error calibration of the flexible measuring arm is systematically and deeply researched. The straightness error data of the two linear guide rails are obtained by measuring the high-precision square box. Then, the slope of the straightness error curve is obtained by least squares method, and the verticality error can be also calculated. The parallelism error for two rotation axes can be calibrated by test a precision flat. Its result can be quickly compute based on the sampling data. The proposing calibration methods have low cost, easy operation, high efficiency and small environmental restrictions than external calibration by expensive instruments. The experiment has proved the validity and feasibility of the above method.

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Simulation of crystal plasticity of P92 heat resistant steel considering martensitic lath structure

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Journal of Physics: Conference Series 2021年第1期2079卷

作者： Xinyu Wang Junjie Shen Xiangru Guo Jixin Qiao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin 300384 China

Based on the theory of crystal plasticity, coupled with dislocation and lath hardening models, this paper establishes a crystal plasticity finite element model describing the high temperature creep of P92 steel. Open source software was used to generate lath models with an average size of 350nm, 650nm and 950nm to explore the effect of lath coarsening on the high-temperature creep behavior of P92 steel. The results show that the roughening of the slats increases the rate of creep deformation, resulting in a decrease in the service life of the material. Observing the slat model, it can be seen that the roughening of the slats enlarges the numerical gradient of stress and strain, and aggravates the overall plastic strain of the model. The coarsening of the slats accelerates the movement of dislocations, causing the density of movable dislocations to increase, and at the same time the shear strain amplitude of the slip system increases, thereby reducing the hardening behavior of the material.

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Augmented Reality and Quick Response Code Technology in Engineering Drawing Course

Augmented Reality and Quick Response Code Technology in Engi...

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IEEE International Conference on Mechatronics and Automation

作者： Xiaofei Wang Chenfei Chen Zhaotong Li Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin China School of Mechanical Engineering Tianjin University of Technology Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Augmented reality (AR) technology is a cutting technology. It can enhance the perception of reality and provide more information of the real world. AR technology is used in many fields, like medical, industry, and education. In this paper, AR is introduced into engineering drawing course. Engineering drawing course is difficult to learn as it is a knowledge that students rarely contact with. To have a close contact with the models and the views, a convenient AR application (AR app) is proposed in the paper. With the help of the AR app, virtual models and real views are combined well. The models can be moved and rotated by touching the screen. Some videos of model assembly and disassembly can be obtained when scanning the quick response code (QR code). Thus, it is convenient for students to use mobile phone to study engineering drawing effectively. The interactive teaching environment enhances students' spatial thinking and cultivates their sense of innovation.

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Artificial Neural Network Based Maximum Power Point Tracking for PV system

Artificial Neural Network Based Maximum Power Point Tracking...

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第三十八届中国控制会议

作者： Al-wesabi Ibrahim Min Ding Xiaoling Jin Xianzhong Dai Mohammad Abu Sarhan Muhammed Badeaa Shafik Hao Zhou School of Automation China University of Geoscience Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute School of electrical engineering and automation Wuhan university

Nowadays PV systems is suffering from two main problems: high production cost and low efficiency especially under variable weather conditions. Therefore, to reduce such associated problems, PV systems are being connected with various optimization controllers such as maximum power point tracking. In this paper, an artificial neural network maximum power point method has been designed to be linked between a PV system and DC-DC buck converter, and each part of the system is fully explained. The whole system was modeled under MATLAB/Simulink environment, simulation results demonstrated the efficiency of the proposed method. The proposed method has been examined to track the maximum power point under different weather conditions which shows a rapid and accurate tracking of the maximum power point(MPP) of PV system. The whole system which consists of PV arrays, Buck converter, ANN tracker, and load has been modeled using MATLAB/Simulink environment. This Simulink model has been examined using different levels of temperature and irradiation and the output results of both P-V and I-V characteristics, output power, and the system efficiency clearly demonstrate the validation of the modeled system. This demonstration has been done by comparing between the result of experimental platform and the results of simulated model which approves that ANN is highly recommended to be used in the field of maximum power point tracking of PV system.

关键词： Artificial neural network(ANN) Photovoltaic(PV) Maximum power point tracking(MPPT) Buck converter

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Correction to: Dielectric properties and nonlinear I–V electrical behavior of (Li1+, Al3+) co-doped CaCu3Ti4O12 ceramics

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Applied Physics A 2019年第9期125卷 1-2页

作者： Sun, Li Ni, Qing Guo, Jianqin Cao, Ensi Hao, Wentao Zhang, Yongjia Ju, Lin Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan People’s Republic of China College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan People’s Republic of China College of Physics and Electrical Engineering Anyang Normal University Anyang People’s Republic of China

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