An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods.     

NeuDATool：支持GPU硬件加速和计算机集群跨节点并行的开源中子散射数据分析软件

实验势精修是20世纪80年代英国散裂中子源无定型材料组开发的用于分析中子散射实验数据的软件. 实验势精修的目标是根据中子散射数据重建样品的三维原子结构. 在过去的几十年,实验势精修被广泛用于中子散射实验数据分析,为实验用户提供了可靠的分析结果. 但是实验势精修是基于共享内存并行计算(OpenMP)的Fortran程序,不支持计算机服务器集群跨节点并行加速和GPU加速;这限制了它的分析速度. 随着计算机服务器集群的广泛建设和GPU加速技术的普遍使用,有必要重新编写EPSR程序以提高运算速度. 本文使用面向对象的C++语言,开发了一套实现EPSR算法的开源软件包NeuDATool;软件通过MPI和CUDA C实现了计算机集群跨节点并行和GPU加速. 使用液态水和玻璃态二氧化硅的中子散射实验数据对软件进行了测试. 测试显示软件可以正确重建出样品的三维原子结构;并且模拟体系达到10万原子以上时,使用GPU加速可以比串行的CPU算法提高400倍以上的模拟速度. NeuDATool为中子实验用户尤其是对熟悉C++编程并希望定义特殊分析算法的实验科学家提供了一种新的选择.     

3D building reconstruction from aerial CCD image and sparse laser sample data

An approach for 3D building reconstruction automatically based on aerial CCD image and sparse laser scanning sample points is presented in this paper. The geometry shape of a building is shown very clearly in the aerial high-resolution CCD image, so we use Laplacian sharpening operator and threshold segmentation to extract the edges of CCD image first, and then pixel connectivity is used to extract the linear features in the CCD image. Bi-direction projection histogram and line matching are proposed to extract the contours of buildings. The height of the building is determined from sparse laser sample points which are within the contour of the buildings extracted from CCD image; therefore the 3D information of each building is reconstructed. We reconstruct 3D buildings correctly by this approach using real aerial CCD and sparse laser rangefinder data.     

Sulfur speciation in two typical soil samples using X-ray absorption near-edge structure spectroscopy and chemical fractionation

Sulfur K-edge X-ray absorption near-edge structure spectroscopy and chemical sequential extraction was respectively used to study the speciation of sulfur in two sulfur-rich soils samples. Sulfur K-edge X-ray absorption near-edge structure spectroscopy analysis obtained a variety of spectra. Spectral fitting of the X-ray absorption near-edge structure spectra utilizing a large set of model compounds showed great differences between these two sulfur-rich soil samples. It was found that both of the soil samples had high sulfur content (8.40 and 11.57?g?kg^?1, respectively). Chemical extraction results suggested that sulfur mainly existed as organic in the ancient paddy soil (7.37?g?kg^?1) and more reduced sulfur was identified in it. X-ray absorption near-edge structure spectroscopy also got similar results. These organic forms of sulfur existed in organic matter across a range of oxidation states. There was high proportion of oxidized sulfur in the sulfuric acid plant that mainly existed as sulfate.     

Preparation,characterization, and performance study of beeswax/expanded graphite composite as thermal storage material

In this study, beeswax as a new energy storage material and its composite with expanded graphite were prepared and characterized for their surface and thermal properties. Surface characterization showed no chemical interaction between beeswax and expanded graphite. The thermal conductivity of the composite was improved with 117% enhancement. The thermal performance of beeswax and its composite as a heat storage material was studied in a rectangular shell-and-tube thermal storage unit. The melting point of the composite remained almost same as that of beeswax; however, the melting time was reduced considerably, from 540 to 360 min with inlet water at 80°C and a 2-lpm flow rate.     

基于扫描相机的激光三维成像研究

随着条纹管器件技术的发展,条纹管作为瞬态光学器件的应用不再局限于高速摄影和光谱学研究领域。建立以单狭缝条纹管为核心器件的扫描相机激光成像系统,对目标进行推扫成像,获得原始条纹图像,并进行特征数据提取和三维重建。理论计算出的两目标的距离差与实际距离差较接近,从而验证采用该系统作激光雷达成像的可行性。实验结果表明,基于扫描相机激光雷达具有高分辨率,具有较好的应用前景。     

结合空间和光谱信息的高光谱影像端元光谱自动提取

端元光谱提取是高光谱影像混合像元分解的关键。现有的端元提取方法多是仅利用了影像的光谱信息,忽略了像元间的空间相关性。现有研究基础上,提出了一种结合影像空间和光谱信息的高光谱影像端元光谱自动提取方法(integration of spatial-spectral information based endmember extraction,ISEE)。该方法首先进行影像子空间划分以增强影像局部的光谱信息特征,然后通过特征空间投影分析获得影像候选端元,最后依次在影像空间信息约束下和端元光谱信息约束下进行优化,得到最终的影像端元光谱集。仿真高光谱影像和真实高光谱影像的实验结果表明,结合影像空间和光谱信息的ISEE方法是有效的,且比一些常用方法提取的端元光谱更为准确。     

基于光谱曲线响应特性的油膜厚度估计模型分析

如今,海上溢油事故频发,如何对溢油的油量进行估计,是一个重要课题。如果可以得到溢油量,那么对后续的处理以及损失的评估都会有较大的帮助。高光谱遥感技术的快速发展使对油膜厚度的定量估计成为可能。采用AvaSpec光谱仪测量不同厚度的油膜,然后对得到的光谱曲线的多种曲线特征进行提取,分析其与油膜厚度之间的关系。结果表明,油膜厚度与基于高光谱位置变量的Rg和Ro、三角植被指数的RDVI和TVI以及Haboudane关系式相关性较大。分别采用曲线拟合、BP神经网络和基于SVD的迭代方法建立油膜曲线特征与油膜厚度之间的预测关系,并以此对不同的油膜光谱曲线进行油膜厚度估计,对得到的结果进行精度检测和运行时间分析,最终得出对每个估计模型的分析评价。     

Deterministic Joint Remote Preparation of an Arbitrary Two-Qubit State Using the Cluster State

Recently, deterministic joint remote state preparation (JRSP) schemes have been proposed to achieve 100% success probability. In this paper, we propose a new version of deterministic JRSP scheme of an arbitrary two-qubit state by using the six-qubit cluster state as shared quantum resource. Compared with previous schemes, our scheme has high efficiency since less quantum resource is required, some additional unitary operations and measurements are unnecessary. We point out that the existing two types of deterministic JRSP schemes based on GHZ states and EPR pairs are equivalent.     

光谱特征提取对近似矿物光谱差异性影响分析

矿物光谱特征是基于光学遥感数据对矿物进行种类识别及定量反演的理论基础,光谱特征提取是高光谱数据常用的技术手段,但在多光谱数据中较少涉及。近似矿物识别是矿物光谱分类应用中的难点,目前还缺少有效指标来指示近似矿物类别光谱的差异性。光谱特征提取有望提高矿物分类精度,但该处理对近似矿物光谱差异性的影响还缺少相关研究。本文从矿物光谱差异性的原理出发,通过类间和类内光谱角的比值体现不同类别群体差异,并引入样本量因素,提出了类别可分比作为近似矿物光谱差异性的指标。以明矾石和高岭石两种近似矿物为例,对USGS光谱库光谱及Hyperion,ASTER,OLI等传感器的模拟数据进行光谱特征提取处理,通过对比处理前后矿物光谱差异性的变化,分析光谱特征提取对近似矿物光谱差异性的影响。实验结果表明,有效的光谱特征提取可以显著提高近似矿物光谱差异性,并且光谱分辨率越高,近似矿物光谱差异性越大。此外,光谱分辨率及中心波长设置对于包络线去除结果有很大影响,多光谱数据吸收特征提取效果有待进一步提高。该研究为今后近似矿物光谱识别精度的提高奠定了基础,也为未来新型遥感找矿传感器参数设置提供了参考。