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Record 337 of
Title:Localized dark solitons and vortices in defocusing media with spatially inhomogeneous nonlinearity
Author(s):Zeng, Jianhua(1,3); Malomed, Boris A.(2,3)
Source: arXiv Volume: Issue: DOI: Published: May 4, 2017
Abstract:Recent studies have demonstrated that defocusing cubic nonlinearity with local strength growing from the center to the periphery faster than rD, in space of dimension D with radial coordinate r, supports a vast variety of robust bright solitons. In the framework of the same model, but with a weaker spatial-growth rate, ～rα with α ≤ D, we here test the possibility to create stable localized continuous waves (LCWs) in one- and twodimensional (1D and 2D) geometries, localized dark solitons (LDSs) in 1D, and localized dark vortices (LDVs) in 2D, which are all realized as loosely confined states with a divergent norm. Asymptotic tails of the solutions, which determine the divergence of the norm, are constructed in a universal analytical form by means of the Thomas-Fermi approximation (TFA). Global approximations for the LCWs, LDSs, and LDVs are constructed on the basis of interpolations between analytical approximations available far from (TFA) and close to the center. In particular, the interpolations for the 1D LDS, as well as for the 2D LDVs, are based on a "deformed-tanh" expression, which is suggested by the usual 1D dark-soliton solution. The analytical interpolations produce very accurate results, in comparison with numerical findings, for the 1D and 2D LCWs, 1D LDSs, and 2D LDVs with vorticity S = 1. In addition to the 1D fundamental LDSs with the single notch, and 2D vortices with S = 1, higher-order LDSs with multiple notches are found too, as well as double LDVs, with S = 2. Stability regions for the modes under the consideration are identified by means of systematic simulations, the LCWs being completely stable in 1D and 2D, as they are ground states in the corresponding settings. Basic evolution scenarios are identified for those vortices which are unstable. The settings considered in this work may be implemented in nonlinear optics and in Bose-Einstein condensates. Copyright ? 2017, The Authors. All rights reserved.
Accession Number: 20200185004
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Record 338 of
Title:Learning k for kNN Classification
Author(s):Zhang, Shichao(1); Li, Xuelong(2); Zong, Ming(1); Zhu, Xiaofeng(1); Cheng, Debo(1)
Source: ACM Transactions on Intelligent Systems and Technology Volume: 8 Issue: 3 DOI: 10.1145/2990508 Published: January 2017
Abstract:The K Nearest Neighbor (kNN) method has widely been used in the applications of data mining andmachine learning due to its simple implementation and distinguished performance. However, setting all test data with the same κvalue in the previous kNN methods has been proven to make these methods impractical in real applications. This article proposes to learn a correlation matrix to reconstruct test data points by training data to assign different κ values to different test data points, referred to as the Correlation Matrix kNN (CM-kNN for short) classification. Specifically, the least-squares loss function is employed to minimize the reconstruction error to reconstruct each test data point by all training data points. Then, a graph Laplacian regularizer is advocated to preserve the local structure of the data in the reconstruction process. Moreover, an 1-norm regularizer and an 2,1-norm regularizer are applied to learn different κ values for different test data and to result in low sparsity to remove the redundant/noisy feature from the reconstruction process, respectively. Besides for classification tasks, the kNNmethods (including our proposed CM-kNN method) are further utilized to regression and missing data imputation.We conducted sets of experiments for illustrating the efficiency, and experimental results showed that the proposed method was more accurate and efficient than existing kNN methods in data-mining applications, such as classification, regression, and missing data imputation. Copyright is held by the owner/author(s). Publication rights licensed to ACM.
Accession Number: 20170603327886
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Record 339 of
Title:Graph Regularized Non-Negative Low-Rank Matrix Factorization for Image Clustering
Author(s):Li, Xuelong(1); Cui, Guosheng(1,2); Dong, Yongsheng(1,3)
Source: IEEE Transactions on Cybernetics Volume: 47 Issue: 11 DOI: 10.1109/TCYB.2016.2585355 Published: November 2017
Abstract:Non-negative matrix factorization (NMF) has been one of the most popular methods for feature learning in the field of machine learning and computer vision. Most existing works directly apply NMF on high-dimensional image datasets for computing the effective representation of the raw images. However, in fact, the common essential information of a given class of images is hidden in their low rank parts. For obtaining an effective low-rank data representation, we in this paper propose a non-negative low-rank matrix factorization (NLMF) method for image clustering. For the purpose of improving its robustness for the data in a manifold structure, we further propose a graph regularized NLMF by incorporating the manifold structure information into our proposed objective function. Finally, we develop an efficient alternating iterative algorithm to learn the low-dimensional representation of low-rank parts of images for clustering. Alternatively, we also incorporate robust principal component analysis into our proposed scheme. Experimental results on four image datasets reveal that our proposed methods outperform four representative methods. ? 2013 IEEE.
Accession Number: 20163002643546
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Record 340 of
Title:MAM-RNN: Multi-level attention model based RNN for video captioning
Author(s):Li, Xuelong(1); Zhao, Bin(2); Lu, Xiaoqiang(1)
Source: IJCAI International Joint Conference on Artificial Intelligence Volume: 0 Issue: DOI: 10.24963/ijcai.2017/307 Published: 2017
Abstract:Visual information is quite important for the task of video captioning. However, in the video, there are a lot of uncorrelated content, which may cause interference to generate a correct caption. Based on this point, we attempt to exploit the visual features which are most correlated to the caption. In this paper, a Multi-level Attention Model based Recurrent Neural Network (MAM-RNN) is proposed, where MAM is utilized to encode the visual feature and RNN works as the decoder to generate the video caption. During generation, the proposed approach is able to adaptively attend to the salient regions in the frame and the frames correlated to the caption. Practically, the experimental results on two benchmark datasets, i.e., MSVD and Charades, have shown the excellent performance of the proposed approach.
Accession Number: 20174304308495
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Record 341 of
Title:Analysis and test study of thermal deformation on a grid reinforced CFRP mirror
Author(s):Xu, Liang(1); Ding, Jiao-Teng(1); Wang, Yong-Jie(1); Xie, Yong-Jie(1); Ma, Zhen(1); Fan, Xue-Wu(1)
Source: ICCM International Conferences on Composite Materials Volume: 2017-August Issue: DOI: Published: 2017
Abstract:Due to the low density and extremely low thermal expansion, carbon fibre reinforced plastic (CFRP) is one of potential materials applied as precise dimension components. High precise structures, such as antenna reflectors and mirrors, require very strict thermal stability. However, the CFRP laminate usually companied with large thermal deformation, because of align error, thickness error, fiber and resin uneven distribution in the preparation. Therefore, a novel grid reinforced structure was adopted to improve stiffness and resistance of thermal deformation. The validity of the design is verified by finite element method. The thermal deformation test based on the vacuum tank verifies the reliability of the finite element analysis results. For 150mm CFRP mirror, the test results show that the thermal deformation RMS is only 16nm when 4.5 raised, so thermal stability is just about 3.5nm/, and satisfied the requirements in high precise structure application. ? 2017 International Committee on Composite Materials. All rights reserved.
Accession Number: 20183705812406
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Record 342 of
Title:Development of submicron high precision CFRP reflector
Author(s):Xu, Liang(1); Xie, Yongjie(1); Ding, Jiaoteng(1); Wang, Yongjie(1); Ma, Zhen(1); Fan, Xuewu(1)
Source: 27th International Symposium on Space Terahertz Technology, ISSTT 2016 Volume: Issue: DOI: Published: 2017
Abstract:Antenna gain affected by reflector surface figure accuracy and dimension stability directly, so one of the most important tasks is how to ensure the surface precision and dimensional stability. It is hard to control surface precision for springback of metal, so carbon fibre reinforced polymer (CFRP) usually be adopted to fabricate high precision reflector. With the rapid development of electronic technology, especially millimetre and terahertz wave technology, the precision of reflector needed increasingly. A Φ300mm CFRP flat reflector is developed for process study. In order to improve the thermal stability, a special "all CFRP" structure adopted. Optical replica process used to realize surface modification of CFRP reflector blank, final surface figure accuracy RMS reaching 0.1μm, and roughness Ra reaching 2nm. Further thermal stability tests show that the thermal stability reaching 13nm/C. AΦ500mm CFRP aspherical reflector also fabricated, and surface accuracy reaching 0.4μm. The study is of certain reference value for the development of CFRP reflector in millimetre wave and terahertz wave band.
Accession Number: 20172703873544
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Record 343 of
Title:An target tracking of structure algorithm based on skeleton and corner for extended objects
Author(s):Zhai, Bo(1); He, Tian-Bing(1); Qu, You-Shan(1); Xu, Fan(1); Ge, Yong-Jiao(1)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 10462 Issue: DOI: 10.1117/12.2284381 Published: 2017
Abstract:Due to extended objects are influenced by occluded and blurred edge, the stability of target tracking is not good by the figure algorithms or the corner algorithms. In order to solute this problem, an improved multi-resolution(MR) fuzzy clustering algorithm based on Markov random field(MRF) is firstly used to segment the candidate targets of the extended objects from the observed images, then a new proposed target tracking structure algorithm, based on the stabilization of the extended objects' skeletons and the partially unoccluded and unblurred edge feature of the extended objects, is applied to extract the skeletons, corners, intersection points and their spatial location relationship of the candidate extended targets to detemine the true tracking target or not. The experimental results show that the established algorithm can effectively complete the segmentation and extraction of the partially occluded and blurred extended objects with a very satisfied reliability and robustness. ? 2017 SPIE.
Accession Number: 20180404670985
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Record 344 of
Title:Sheared-beam imaging target reconstruction based on all-phase spectrum analysis
Author(s):Chen, Ming-Lai(1); Luo, Xiu-Juan(1); Zhang, Yu(1); Lan, Fu-Yang(1); Liu, Hui(1); Cao, Bei(1); Xia, Ai-Li(1)
Source: Wuli Xuebao/Acta Physica Sinica Volume: 66 Issue: 2 DOI: 10.7498/aps.66.024203 Published: January 20, 2017
Abstract:Sheared-beam imaging technique is considered to be a non-conventional speckle technique for remote imaging through turbulent medium. In this high resolution imaging technique, three beams are splitted from one laser source and illuminate a remote target simultaneously in shearing distribution. Each beam is modulated by a tiny frequency shift so that these beams can interfere and beat together. The returning speckle signals are received by an array of detectors. The primary algorithm for the signal processing and image reconstruction has been developed previously. However, the reconstructed image is deteriorated by the frequency drifting error and spectrum leakage. These frequency errors are always from the transmitter and scattered signals that are caused by spectrum-shift errors from acoustic-optic modulators, atmospheric turbulence, Doppler effects of moving targets, etc. To solve the problems mentioned above, in this paper we propose a new image reconstruction algorithm based on the all-phase spectrum analysis theory. The all-phase fast Fourier transform (FFT) spectrum analysis theory, which can effectively inhibit spectral leakage and correct speckle spectrum, is used to process the scattered signals. By searching for the accurate positions of the beat frequency components in the transformed frequency domain data, the speckle amplitude and phase difference frames can be extracted accurately. Based on the speckle phase-difference frames, the phase distribution of the wavefront is derived by least-square algorithm. The phase distribution in grid is highly coherent, in which each point is related to the phases of its four nearest neighbors. If an initial phase map is given or preset, the phase map of the wavefront can be estimated accurately by Gauss-Seidel method. Meanwhile, the amplitude of wavefront is obtained by the algebraic operation of speckle amplitude frames. The reconstructed wavefront is inverse Fourier transformed to yield a two dimensional image. A series of speckled images of the same object are averaged to reduce the speckle noise. The proposed method improves the ability of system imaging in the actual imaging environment. Simulation experiments validate the effectiveness of the proposed algorithm, and simulation results show that the proposed image reconstruction algorithm can inhibit the frequency errors from influencing imaging quality when there exist frequency errors in scattered signals. Thus, the imaging quality of the algorithm based on the all-phase FFT method is much better than that of the algorithm based on the traditional FFT method. The substantial usage of this technique is widely spread after the reconstruction algorithm has been optimized. ? 2017 Chinese Physical Society.
Accession Number: 20170603332883
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Record 345 of
Title:Radiometric calibration of photographic camera with a composite plane array CCD in laboratory
Author(s):Li, Jing(1); Zhao, Jian-Ke(1); Chang, Ming(1); Hu, Xin-Rong(1)
Source: Guangxue Jingmi Gongcheng/Optics and Precision Engineering Volume: 25 Issue: 1 DOI: 10.3788/OPE.20172501.0073 Published: January 1, 2017
Abstract:To eliminate the serious vignetting phenomenon and to solve the difficulty of choosing a relatively positioning target value problems among CCDs during the radiometric calibration of the whole image plane of the photographic camera with a composite plane array CCD, a method for radiometric calibration of multi-CCDs was proposed. After the dark signal calibration on each pixel, the gray value of the pixel in the vignetting area was revised, and by choosing the appropriate relative calibration target gray value of the whole image plane, the radiometric calibration of the photographic camera with a composite plane array CCD was eventually completed. Through analysis of the gray distribution characteristics of vignetting area, the gray correction method for all kinds of explosion time and radiance was proposed. With calculation of fitting coefficient between each CCD gray value and the input radiance respectively, the coefficient with global minimum fitting error was chosen to calculate the relative calibration target gray value corresponding to radiance. After the radiometric calibration using this method, the non-uniformity of the whole image plane of the photographic camera with a composite plane array CCD is reduced from above 20% to better than 2%, and the accuracy of the absolute calibration is 4.23%. The result indicates that the proposed calibration method is appropriate for the calibration of composite planes array CCD. The accuracy of the calibration satisfies the radiometric calibration requirement of aerial cameras. ? 2017, Science Press. All right reserved.
Accession Number: 20172203698744
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Record 346 of
Title:A new image fusion algorithm based on bayer format
Author(s):Wang, Hao(1); Yan, Su(1); Yang, Lei(1); Wang, Hua(1); Feng, Jia(1); Wang, Huawei(1); Liu, Qing(1); Yan, Aqi(1); Liao, Jiawen(1); Liu, Guangsen(1)
Source: 2016 13th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2017 Volume: 2018-February Issue: DOI: 10.1109/ICCWAMTIP.2017.8301469 Published: July 2, 2017
Abstract:At present, all the algorithms are based on RGB image fusion, and in fact most of the image acquisition and imaging equipment but not the RGB image, a color filter array based on the most common color in the array is the BAYER image format. This paper mainly expands a fusion algorithm based BAYER format. The new algorithm is better than RGB in standard deviation, spatial frequency and information entropy. From comparison of calculation amount, the algorithm of Bayer is less than that of RGB. ? 2017 IEEE.
Accession Number: 20183105636554
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Record 347 of
Title:In-situ growth amorphous carbon nanotube on silicon particles as lithium-ion battery anode materials
Author(s):Zhao, Tingkai(1); She, Shengfei(1,2); Ji, Xianglin(1); Jin, Wenbo(1); Dang, Alei(1); Li, Hao(1); Li, Tiehu(1); Shang, Songmin(3); Zhou, Zhongfu(4)
Source: Journal of Alloys and Compounds Volume: 708 Issue: DOI: 10.1016/j.jallcom.2017.03.019 Published: 2017
Abstract:A novel silicon core/amorphous carbon nanotube (ACNT) shell composite that can be used as lithium-ion batteries anode material was in-situ synthesized in the chemical vapor deposition (CVD) growth process. The hypothesized core/shell structure was evidenced by SEM/TEM/XRD, suggesting that the ACNTs composed of carbon clusters with short-range order and long-range disorder were successfully deposited onto the surface of the silicon particles. This Si/ACNT composite delivered a high capacity of 1496?mAh?g?1 at a current density of 100?mA?g?1, and a superior cycling stability with 80% capacity retention after 300 cycles. This observed specific capacity improvement of Si/ACNT composite is likely attributed to the formed three-dimensional conductive networks between silicon particles and interwoven ACNTs in the composite. ? 2017 Elsevier B.V.
Accession Number: 20171103434545
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Record 348 of
Title:High-energy femtosecond fiber laser system and pulse selection based on high-repetition rate KTiOPO4 Pockels cell
Author(s):Li, Feng(1,2,3); Yang, Zhi(1); Lv, Zhiguo(1); Yang, Yang(1); Zhu, Wenqi(1); Jiang, Baoning(1); Li, Qianglong(1); Yang, Xiaojun(1); Wang, Yishan(1,3); Zhao, Wei(1,3)
Source: Optical Engineering Volume: 56 Issue: 10 DOI: 10.1117/1.OE.56.10.106101 Published: October 1, 2017
Abstract:A fiber chirped-pulse amplification system with pulse energy as high as 105 μJ is achieved at 200-kHz repetition rate using the rod-type photonic crystal fiber. The whole system's nonlinearity accumulated in the fiber amplification is effectively suppressed, and the compressed pulse duration of 808 fs is obtained. A 500-kHz high-repetition rate KTiOPO4 Pockels cell is also applied to make the ultrafast laser pulse selection for generating pulse trains with controllable pulse number and pulse splitting without changing the pulse energy. The demonstrated pulse selection and splitting method are useful for processing of different materials and parallel processing. The pulse selection efficiency of the Pockels cell is as high as 96%. ? 2017 Society of Photo-Optical Instrumentation Engineers (SPIE).
Accession Number: 20174304305834
