2021
2021
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Record 229 of
Title:Modified scaling angular spectrum method for numerical simulation in long-distance propagation
Author(s):Chen, Xiao-Yi(1,2); Duan, Ya-Xuan(1); Xiang, Bin-Bin(3); Li, Ming(1); Da, Zheng-Shang(1)Source: Chinese Physics B Volume: 30 Issue: 3 DOI: 10.1088/1674-1056/abd38d Published: March 2021Abstract:The angular method (AS) cannot be used in long-distance propagation because it produces severe numerical errors due to the sampling problem in the transfer function. Two ways can solve this problem in AS for long-distance propagation. One is zero-padding to make sure that the calculation window is wide enough, but it leads to a huge calculation burden. The other is a method called band-limited angular spectrum (BLAS), in which the transfer function is truncated and results in that the calculation accuracy decreases as the propagation distance increases. In this paper, a new method called modified scaling angular spectrum (MSAS) to solve the problem for long-distance propagation is proposed. A scaling factor is introduced in MSAS so that the sampling interval of the input plane can be adjusted arbitrarily unlike AS whose sampling interval is restricted by the detector's pixel size. The sampling interval of the input plane is larger than the detector's pixel size so the size of calculation window suitable for long-distance field propagation in the input plane is smaller than the size of the calculation window required by the zero-padding. Therefore, the method reduces the calculation redundancy and improves the calculation speed. The results from simulations and experiments show that MSAS has a good signal-to-noise ratio (SNR), and the calculation accuracy of MSAS is better than BLAS. ? 2021 Chinese Physical Society and IOP Publishing LtdAccession Number: 20211610229638 -
Record 230 of
Title:Nonlinear Full-Spectrum Quantitative Analysis Algorithm of Complex Water Based on IERT
Author(s):Liu, Jia-Cheng(1,2); Hu, Bing-Liang(1); Yu, Tao(1); Wang, Xue-Ji(1); Du, Jian(1); Liu, Hong(1); Liu, Xiao(1); Huang, Qi-Xing(3)Source: Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis Volume: 41 Issue: 12 DOI: 10.3964/j.issn.1000-0593(2021)12-3922-09 Published: December 2021Abstract:Water is a finite resource, essential for agriculture, industry and even human existence. A good water environment is an important guarantee for sustainable development. The scientific monitoring of water quality information is the basis for optimal allocation and efficient use of water resources. The United Nations Environment Program (UNEP) and the World Health Organization (WHO) pointed out that national water quality monitoring networks in developing countries should be strengthened, including improving analytical capabilities and data quality assurance. As an emerging water quality analysis method, spectral method has the characteristics of "fast response, synchronization of multiple parameters, environmental protection and pollution-free" compared with traditional chemical water quality monitoring methods. The traditional single-band, multi-band linear model, relies on the absorption characteristics of water at specific bands, and it cannot be used for multi-component mixed solutions and has poor universality. Therefore, this paper proposes a non-linear full-spectrum quantitative analysis algorithm based on IERT. The concentration prediction model suitable for multi-component mixed solution is established to use full spectrum information to predict concentration information. We use the COD, BOD5, TOC multi-component mixed solution and NO3-N, turbidity, chroma multi-component mixed solution configured in the laboratory as the experimental sample, use the spectrometer to collect the spectral curve of the sample, and conduct the concentration prediction experiment through the full spectrum data. The experimental results show that for COD, BOD5, TOC multi-component mixed solutions, the determination coefficients (R2) of this algorithm for the three components are 0.999 3, 0.991 4 and 0.999 3. The root means square error (RMSE) is 0.024 4, 0.057 7 and 0.000 4. For the multi-component mixed solution of NO3-N, turbidity, and colority, the coefficient of determination (R2) is 0.983 4, 0.868 4 and 0.981 0. The root means square error (RMSE) is 0.100 5, 0.326 4 and 0.120 2. By comparing the experimental results of this algorithm with partial least squares (PLS), support vector regression (SVR), decision tree (DT), and extreme random tree (ERT) for the same set of data, the results show that in the experiment of mixed solution, this algorithm is the best alternative to the coefficient of determination (R2) of each component.The root means square error (RMSE) has been greatly reduced compared with other comparison algorithms. This algorithm can use spectral information to analyze the multi-component mixed solution quantitatively. It can effectively improve the concentration prediction accuracy and reduce the root-mean-square error of the quantitative analysis in the case of equivalent calculation time. Moreover, this algorithm can provide a theoretical basis for spectral methods on water quality monitoring. ? 2021, Peking University Press. All right reserved.Accession Number: 20215011303033 -
Record 231 of
Title:Biomimetic multispectral curved compound eye camera for real-time multispectral imaging in an ultra-large field of view
Author(s):Zhang, Yuanjie(1,2); Xu, Huangrong(1,2); Guo, Quan(1,2); Wu, Dengshan(1,2); Yu, Weixing(1,2)Source: Optics Express Volume: 29 Issue: 21 DOI: 10.1364/OE.438710 Published: October 11, 2021Abstract:In this work, we demonstrate a prototype of a biomimetic multispectral curved compound eye camera (BMCCEC). In comparison with traditional multispectral imaging systems, the BMCCEC developed in this work has the distinct features of multi-spectral imaging on multiple targets in real time in an ultra-large field of view (FOV), which can be attributed to its biomimetic curved compound eye structure as well as the multispectral cluster network. Specifically, the BMCCEC has a total of 104 multispectral ommatidia and a FOV of 98°×98°, which is able to realize 7-band multispectral imaging with center wavelengths of 500 nm, 560 nm, 600 nm, 650 nm, 700 nm, 750 nm and 800 nm and a spectral resolution of 10 nm. A prototype of BMCCEC was then manufactured and multispectral imaging experiments were performed based on it. As a result, the red edge feature of the spectrum of green plants has been successfully obtained and retrieved with a good accuracy. ? 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.Accession Number: 20214010984750 -
Record 232 of
Title:A time-correlated single photon counting signal denoising method based on elastic variational mode extraction
Author(s):Wang, Shu-Chao(1,2,3); Su, Xiu-Qin(1,3); Zhu, Wen-Hua(1,2,3); Chen, Song-Mao(1,3); Zhang, Zhen-Yang(1,2,3); Xu, Wei-Hao(1,2); Wang, Ding-Jie(1,2)Source: Wuli Xuebao/Acta Physica Sinica Volume: 70 Issue: 17 DOI: 10.7498/aps.70.20210149 Published: September 5, 2021Abstract:The performance of the method of measuring the time-correlated single photon counting signal is the key to improving the ranging accuracy of single photon light detection and ranging (LiDAR) technique, where noise elimination is a critically essential step to obtain the characteristics of signal. In this paper, a new method called elastic variational mode extraction (EVME) is proposed to extract the feature of the reflected photons from noisy environment. The method takes into account the characteristic of photon counting signal, and improves variational mode decomposition (VMD) method by adopting a new assumption that the extractive mode signal should be compact around desired center frequency. The proposed method also uses the elastic net regularization to solve ill-posed problem instead of Tikhonov regularization mentioned in VMD. Elastic net regularization takes into account both L2-norm regularization and L1-norm regularization, which can add an extra analysis dimension compared with the Tikhonov regularization. The method is validated with real data which are acquired on condition that average transmitting power is 25 nW while the average background noise power is 19.51 μW. The root mean square error of the reconstruction accuracy reaches 1.414 ns. Furthermore, compared with VMD, Haar wavelet, Hibert envelope, empirical mode decomposition (EMD) and complete ensemble empirical mode decomposition method based on adaptive noise (CEEMDAN) under different conditions, the proposed method show fast and stable performance under an extreme case. ? 2021 Chinese Physical Society.Accession Number: 20213710891807 -
Record 233 of
Title:Vision-to-Language Tasks Based on Attributes and Attention Mechanism
Author(s):Li, Xuelong(1); Yuan, Aihong(2,3); Lu, Xiaoqiang(3)Source: IEEE Transactions on Cybernetics Volume: 51 Issue: 2 DOI: 10.1109/TCYB.2019.2914351 Published: February 2021Abstract:Vision-to-language tasks aim to integrate computer vision and natural language processing together, which has attracted the attention of many researchers. For typical approaches, they encode image into feature representations and decode it into natural language sentences. While they neglect high-level semantic concepts and subtle relationships between image regions and natural language elements. To make full use of these information, this paper attempt to exploit the text-guided attention and semantic-guided attention (SA) to find the more correlated spatial information and reduce the semantic gap between vision and language. Our method includes two-level attention networks. One is the text-guided attention network which is used to select the text-related regions. The other is SA network which is used to highlight the concept-related regions and the region-related concepts. At last, all these information are incorporated to generate captions or answers. Practically, image captioning and visual question answering experiments have been carried out, and the experimental results have shown the excellent performance of the proposed approach. ? 2013 IEEE.Accession Number: 20210409831033 -
Record 234 of
Title:Development of Underwater Hyperspectral Imaging Detecting Technology (Invited)
Author(s):Xue, Qingsheng(1); Bai, Haoxuan(1); Li, Hui(1); Wang, Yajun(2); Zhang, Dongxue(3)Source: Guangzi Xuebao/Acta Photonica Sinica Volume: 50 Issue: 12 DOI: 10.3788/gzxb20215012.1201001 Published: December 25, 2021Abstract:With the development of marine economy and ocean exploration, the demand about the detection methods with high accuracy and efficiency becomes urgent. As a technology which combined the spectral technology and imaging technology, the hyperspectral imaging technology can bridge the gap of underwater high-precision detection demand to some degree, so the researchers begin to develop it and use it in the underwater detection. The background of the development of underwater hyperspectral imaging technology is first introduced, then the different methods of hyperspectral imaging technology and the components of underwater hyperspectral detection system are summarized. The research progress of underwater hyperspectral imaging detecting technology is summarized after that. The challenges which underwater hyperspectral imaging technology faces are pointed out, and the expectation of the underwater hyperspectral imaging technology is given. ? 2021, Science Press. All right reserved.Accession Number: 20220611611444 -
Record 235 of
Title:Decoupling control of fast steering mirror based on dual feedforward + dual neural network adaptive
Author(s):Wang, Rui(1,2); Su, Xiuqin(1,3); Qiao, Yongming(1); Lv, Tao(1); Wang, Xuan(1,2); Wang, Kaidi(1,2)Source: Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering Volume: 50 Issue: 11 DOI: 10.3788/IRLA20210194 Published: November 25, 2021Abstract:Two-axis fast steering mirror based on flexure hinge support and voice coil motor drive is a strong coupling system with two inputs and two outputs. The coupling between X-axis and Y-axis greatly reduces the positioning accuracy of the fast steering mirror. It is difficult to achieve high precision decoupling control by using traditional PID control algorithm. Based on the centrosymmetric and axisymmetric two-axis fast steering mirror, the coupling sources of the two-axis fast steering mirror-DC coupling component and non-DC coupling component were analyzed theoretically, and the coupling physical model of between X-axis and Y-axis was established. A dual feedforward + dual neural network adaptive decoupling control algorithm was proposed to respectively compensate DC coupling components and non-DC coupling components. Experimental results show that, compared with the traditional PID control algorithm, the coupling degree of the proposed algorithm is reduced from about 5% to less than 1.0‰, which significantly improves the positioning accuracy from about 2.5% to less than 0.5‰. ? 2021, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.Accession Number: 20214911288628 -
Record 236 of
Title:Multisource Remote Sensing Data Classification with Graph Fusion Network
Author(s):Du, Xingqian(1); Zheng, Xiangtao(1); Lu, Xiaoqiang(1); Doudkin, Alexander A.(2)Source: IEEE Transactions on Geoscience and Remote Sensing Volume: 59 Issue: 12 DOI: 10.1109/TGRS.2020.3047130 Published: December 1, 2021Abstract:The land cover classification has been an important task in remote sensing. With the development of various sensors technologies, carrying out classification work with multisource remote sensing (MSRS) data has shown an advantage over using a single type of data. Hyperspectral images (HSIs) are able to represent the spectral properties of land cover, which is quite common for land cover understanding. Light detection and ranging (LiDAR) images contain altitude information of the ground, which is greatly helpful with urban scene analysis. Current HSI and LiDAR fusion methods perform feature extraction and feature fusion separately, which cannot well exploit the correlation of data sources. In order to make full use of the correlation of multisource data, an unsupervised feature extraction-fusion network for HSI and LiDAR, which utilizes feature fusion to guide the feature extraction procedure, is proposed in this article. More specifically, the network takes multisource data as input and directly output the unified fused feature. A multimodal graph is constructed for feature fusion, and graph-based loss functions including Laplacian loss and t-distributed stochastic neighbor embedding (t-SNE) loss are utilized to constrain the feature extraction network. Experimental results on several data sets demonstrate the proposed network can achieve more excellent classification performance than some state-of-the-art methods. ? 1980-2012 IEEE.Accession Number: 20210409830330 -
Record 237 of
Title:Offline Signature Authentication Algorithm Based on the Fuzzy Set
Author(s):Qiu, Shi(1); Fei, Fengchang(2); Cui, Ying(3)Source: Mathematical Problems in Engineering Volume: 2021 Issue: DOI: 10.1155/2021/5554341 Published: 2021Abstract:There exists a problem that it is difficult to identify the authenticity of offline signatures. Firstly, a segmentation model is established based on the theory of fuzzy sets to extract signatures completely. Secondly, statistical shape model (SSM) and variance distance discretization of intraclass signatures are introduced for stability analysis and quantification. Finally, multilayer classifiers are constructed to realize signature authentication. The algorithm has low false detection rate and short authentication time. ? 2021 Shi Qiu et al.Accession Number: 20211510186719 -
Record 238 of
Title:Theoretical and Experimental Analysis of the Directional RI Sensing Property of Tilted Fiber Grating
Author(s):Sun, Yuezhen(1); Lu, Tean(1); Moreno, Yarien(1); Li, Liangye(1); Wang, Hushan(2); Zhou, Kaiming(3); Sun, Qizhen(1); Liu, Deming(1); Yan, Zhijun(1); Zhang, Lin(3)Source: Journal of Lightwave Technology Volume: 39 Issue: 2 DOI: 10.1109/JLT.2020.3027947 Published: January 15, 2021Abstract:In this article, we have theoretically and experimentally investigated the unique vector refractive index (RI) sensing property of tilted fiber grating (TFG). Due to the orthogonal symmetric grating structure, TFGs would mainly achieve the coupling between the fiber core mode and the two orthogonal polarization LP1m of cladding mode. And the numerical simulation results showed that the coupling coefficient between fundamental core mode to the LP1m cladding mode is higher than the others. In the experiment, we have furthermore observed the cladding mode field distribution of excessively TFG (Ex-TFG) and long period fiber grating (LPFG), which indicated that the evanescent field distribution of cladding mode of TFG shows an asymmetric near field distribution with two lobes oriented along the fast axis of TFG, and the one of LPFG has a circularly symmetric cladding mode field distribution. In addition, by employing side-immersion method, we have measured the azimuth RI sensitivities of Ex-TFG, tilted fiber Bragg grating (TFBG) and LPFG, which exhibited that both Ex-TFG and TFBG have shown a direction-dependency RI sensitivity, and the RI sensitivity with side-immersion along fast axis is almost half of the one along slow axis, and the RI sensitivity of LPFG is azimuth independent. Overall, the experiment results show that the TFGs inherently show unique directional RI sensing property, which could be potentially applied in vector sensing area. ? 1983-2012 IEEE.Accession Number: 20210209741076 -
Record 239 of
Title:Flexible dynamic structural color based on an ultrathin asymmetric Fabry-Perot cavity with phase-change material for temperature perception
Author(s):ZHAO, JIANCUN(1,2,3); ZHOU, YI(4); HUO, YIHUI(5); GAO, BO(6); MA, YUNGUI(7); YU, YITING(8)Source: Optics Express Volume: 29 Issue: 15 DOI: 10.1364/OE.431906 Published: July 19, 2021Abstract:Dynamic structural color has attracted considerable attentions due to its good tunable characteristics. Here, an ultrathin asymmetric Fabry-Perot (FP)-type structural color with phase-change material VO2 cavity is proposed. The color-switching performance can be realized by temperature regulation due to the reversible monoclinic-rutile phase transition of VO2. The various, vivid structural color can be generated by simply changing the thickness of VO2 and Ag layers. Moreover, the simple structural configuration enables a large-scale, low-cost preparation on both rigid and flexible substrates. Accordingly, a flexible dynamic structural color membrane is adhered on a cup with a curved surface to be used for temperature perception. The proposed dynamic structural color has potential applications in anti-counterfeiting, temperature perception, camouflage coatings among other flexible optoelectronic devices. ? 2021 Optical Society of America.Accession Number: 20212810622274 -
Record 240 of
Title:Peregrine combs and rogue waves on a bright soliton background
Author(s):Guo, Lehui(1,2,3); Chen, Ping(1,2); Tian, Jinshou(1,3)Source: Optik Volume: 227 Issue: DOI: 10.1016/j.ijleo.2020.165455 Published: February 2021Abstract:The dynamics of the modulation rogue waves in an inhomogeneous nonlinear optical fiber with the periodic modulation are studied. We find that for different modulation amplitudes and modulation frequencies, the modulation rogue wave solution can be Peregrine comb, rogue wave, or the transition state in between, respectively. In particular, the phase diagram of the three kinds of nonlinear states is given at the modulation amplitude and modulation frequency plane. Moreover, the dynamics characteristics of the Peregrine comb and the rogue wave are discussed on the localized soliton background. It is interesting that the main excitation characteristics of the Peregrine combs and the rogue waves on an infinitely wide plane wave background are well maintained on the soliton background. These results pave the way for exciting and manipulating the rogue waves on a local background. ? 2020 Elsevier GmbHAccession Number: 20205009599322