大气湍流图像像素偏差机理分析

对大气湍流导致图像畸变和像素偏差的因素进行了深入分析,对大气湍流状态下激光发射远距离光束的光束漂移均方值进行仿真,分析光束漂移均方值曲线,为后续对图像畸变、像素偏差校正及克服湍流影响提供有效的理论依据。     

数据归一化方法综述

当今,人工智能已经广泛应用到各个领域中,并取得了显著的效果。数据归一化是人工智能应用落地中的一个重要环节,它有助于避免神经网络因数据量纲的复杂性对数据进行错误建模。在大数据场景下,相当一部分数据是以流的形式先后到达训练点,所以在流场景下数据归一化研究是当前亟待解决的关键问题。目前关于归一化研究的综述较多,大多仅仅针对于批数据的归一化研究,而缺乏对流数据的归一化方法的总结,不具参考性。在批数据归一化研究基础之上,系统化整理并详尽分析了流数据归一化的相关文献,凝练提出了基于流数据的归一化分类方法,并将数据归一化方法划分为批数据的归一化方法和流数据的归一化方法。同时,对这些方法的原理、优势和可以解决的主要问题进行了对比分析,在不同场景下对数据归一化的未来研究方向进行了展望。     

An adaptive threshold in joint approximate diagonalization by assuming exponentially distributed errors

Joint approximate diagonalization (JAD) is one of well-known methods for solving blind source separation. JAD diagonalizes many cumulant matrices of given observed signals as accurately as possible, where the optimization for each pair of signals is repeated until the convergence. In each pair optimization, JAD should decide whether the pair is actually optimized by a convergence decision condition, where a fixed threshold has been employed in many cases. Though a sufficiently small threshold is desirable for the accuracy of results, the speed of convergence is quite slow if the threshold is too small. In this paper, we propose a new decision condition with an adaptive threshold for JAD under a probabilistic framework. First, it is assumed that the errors in JAD (non-diagonal elements in cumulant matrices) are given by the exponential distribution. Next, it is shown that the maximum likelihood estimation of the probabilistic model is equivalent to JAD. Then, an adaptive threshold is theoretically derived by utilizing the model selection theory. Numerical experiments verify the efficiency of the proposed method for blind source separation of artificial sources and natural images. It is also shown that the proposed method is especially effective when the number of samples is limited.     

An efficient Earth Mover's Distance algorithm for robust histogram comparison

We propose EMD-L1: a fast and exact algorithm for computing the Earth Mover's Distance (EMD) between a pair of histograms. The efficiency of the new algorithm enables its application to problems that were previously prohibitive due to high time complexities. The proposed EMD-L1 significantly simplifies the original linear programming formulation of EMD. Exploiting the L1 metric structure, the number of unknown variables in EMD-L1 is reduced to O(N) from O(N2) of the original EMD for a histogram with N bins. In addition, the number of constraints is reduced by half and the objective function of the linear program is simplified. Formally, without any approximation, we prove that the EMD-L1 formulation is equivalent to the original EMD with a L1 ground distance. To perform the EMD-L1 computation, we propose an efficient tree-based algorithm, Tree-EMD. Tree-EMD exploits the fact that a basic feasible solution of the simplex algorithm-based solver forms a spanning tree when we interpret EMD-L1 as a network flow optimization problem. We empirically show that this new algorithm has an average time complexity of O(N2), which significantly improves the best reported supercubic complexity of the original EMD. The accuracy of the proposed methods is evaluated by experiments for two computation-intensive problems: shape recognition and interest point matching using multidimensional histogram-based local features. For shape recognition, EMD-L1 is applied to compare shape contexts on the widely tested MPEG7 shape data set, as well as an articulated shape data set. For interest point matching, SIFT, shape context and spin image are tested on both synthetic and real image pairs with large geometrical deformation, illumination change, and heavy intensity noise. The results demonstrate that our EMD-L1-based solutions outperform previously reported state-of-the-art features and distance measures in solving the two tasks.     

Electrical and structural properties of ortho-chloranil doped zinc phthalocyanine films

Electrical conductivity of evaporated zinc phthalocyanine (ZnPc) films, doped with orthochloranil (o-CA) molecules, is investigated. Benzoico-CA solution is introduced in the film and benzene is removed by vapourization afterwards. The film conductivity at first increased and then decreased with incremental doping. The maximum conductivity of the sample appeared at doping level × (=o-CA/ZnPc) 0.2 and is about 10³ times as large as that of the as-evaporated one. About a ten-fold further increase in the conductivity is obtained by the heat-treatment of 150 °C for 12 h. The conductivity change by doping is explained by taking into account thato-CA molecules behave not only as acceptors in the film but destructively for the film structure. The phase change of ZnPc by benzoic solution is also discussed.     

Efficient blind dereverberation and echo cancellation based on independent component analysis for actual acoustic signals

This letter presents a new algorithm for blind dereverberation and echo cancellation based on independent component analysis (ICA) for actual acoustic signals. We focus on frequency domain ICA (FD-ICA) because its computational cost and speed of learning convergence are sufficiently reasonable for practical applications such as hands-free speech recognition. In applying conventional FD-ICA as a preprocessing of automatic speech recognition in noisy environments, one of the most critical problems is how to cope with reverberations. To extract a clean signal from the reverberant observation, we model the separation process in the short-time Fourier transform domain and apply the multiple input/output inverse-filtering theorem (MINT) to the FD-ICA separation model. A naive implementation of this method is computationally expensive, because its time complexity is the second order of reverberation time. Therefore, the main issue in dereverberation is to reduce the high computational cost of ICA. In this letter, we reduce the computational complexity to the linear order of the reverberation time by using two techniques: (1) a separation model based on the independence of delayed observed signals with MINT and (2) spatial sphering for preprocessing. Experiments show that the computational cost grows in proportion to the linear order of the reverberation time and that our method improves the word correctness of automatic speech recognition by 10 to 20 points in a RT??= 670 ms reverberant environment.     

SiO2 thin film deposition on the inner surface of a poly(tetra-fluoroethylene) narrow tube by atmospheric-pressure glow microplasma

SiO₂ thin films were deposited on the inner surfaces of a commercial poly(tetrafluoroethylene) narrow tube with an inner diameter of 0.5 mm using tetraethoxysilane/O₂ feedstock gases and He carrier gas by atmospheric-pressure microplasma-enhanced chemical vapor deposition. A glow microplasma was generated inside the tube by radio frequency (RF) capacitively coupled discharge. X-ray photoelectron spectroscopy spectra showed that the tube inner surface was covered by a SiO₂ thin film. Transparent SiO₂ thin films were obtained with a deposition rate of 230 nm/min at an RF power of 6 W and substrate temperature of 100 °C. The wettability of the SiO₂-coated tube was about 3 times as large as that of an untreated sample tube.     

Encapsulation of radioactive metals inside multilayered polyhedral shells of carbon as a barrier to radionuclide release

A carbon nanoencapsulate has a polyhedral outer shell of nested, concentric layers of carbon. The shell defines an internal cavity where a metal is encapsulated. Although the rare-earth carbides readily hydrolyze in moist air, the carbides in these carbon shells did not degrade after exposure to air for considerable lengths of time. This means that the carbide particle is physically enclosed within the carbon cavity completely, and the cavity protects it perfectly against attack of water molecules. Considering intrinsic chemical stability of carbon under oxygen free condition, this structure may be a perfect barrier to extremely long-term release of radionuclides. Because encapsulation of LaC₂ within carbon nanoparticles increased drastically from by-product to major product, it would be possible to find the optimized condition that complete encapsulation is achieved. Intrinsic stability of carbon and carbon coated waste nanoparticles may provide an improved barrier to radionuclide release by groundwater.     

使用EBIC的软件故障特征选择方法

软件故障预测中若采用大量度量指标建立预测模型,可能因其中含有无关特征使预测模型性能受到不良影响,故障预测中的特征选择步骤选取一定维度的部分故障数据建立预测模型来提高模型性能,以达到压缩特征维度,提高模型预测精度,降低预测模型复杂度,节约计算资源的目的。传统特征排序方法仅评估单个特征对类标的影响,建立的预测模型有效性较低;特征子集选择方法需搜索所有特征子集,耗费计算资源且所选特征维数较高。针对以上问题,提出一种基于拓展贝叶斯信息准则的特征选择方法(EBIC-FS),该方法对数据进行线性回归,并计算出残差平方和较小且数据维数较少的特征模型。在公开数据集M&R及Promise上进行实验,结果表明该方法能有效压缩特征维度,且预测模型性能与5种基线方法相比有较大提升。