纸页受力微损伤演化过程的声发射及多元统计特征

纸页受载后的损伤断裂行为涉及其使用性能,对其损伤断裂过程的研究不仅有助于揭示纸页破坏行为的物理本质,而且有助于对纸页质量及其生产、加工工艺作出更加科学合理的评定。本文基于声发射(Acoustic Emission,AE)实验研究纸页内部微损伤演化过程,给出了评估纸页宏观损伤断裂性能的定量描述方法。首先,根据AE信号与微损伤事件之间存在本质上的关联性,通过采集和观测纸页试样受载过程中的AE信号来研究纸页损伤断裂的基本特征;其次,针对所采集AE信号的数据量大、蕴含信息丰富导致数据分析和处理困难的特点,本文采用多元随机变量的分析方法。利用概率熵和Andrews曲线法等统计分析手段对AE数据展开研究分析,并最终利用一条损伤状态轨迹曲线实现了对纸页微损伤演化过程的完整宏观描述。结果表明,纸页微损伤演化过程呈现明显阶段性变化特征;Andrews曲线的聚类结果有效地区分了不同损伤阶段的相似性和差异性,同时,不同损伤阶段中纸样的微观形貌观测提供了实验性的证据。本文以一种典型的牛皮箱板纸为试件,验证了上述方法的有效性。     

自适应小波算法用于近红外光谱的多元校正

实现了一种构建自适应小波滤波器的方法,并将其用于近红外光谱数据的多元校正。该方法根据一定的目标函数,针对信号的特性自适应地构造小波滤波器。用该法构建的滤波器对烟草样品的近红外光谱进行压缩,并将压缩后的数据采用偏最小二乘法建模,实现了烟草样品常规组分的定量分析。     

A novel second-order standard addition analytical method based on data processing with multidimensional partial least-squares and residual bilinearization

In the presence of analyte-background interactions and a significant background signal, both second-order multivariate calibration and standard addition are required for successful analyte quantitation achieving the second-order advantage. This report discusses a modified second-order standard addition method, in which the test data matrix is subtracted from the standard addition matrices, and quantitation proceeds via the classical external calibration procedure. It is shown that this novel data processing method allows one to apply not only parallel factor analysis (PARAFAC) and multivariate curve resolution-alternating least-squares (MCR-ALS), but also the recently introduced and more flexible partial least-squares (PLS) models coupled to residual bilinearization (RBL). In particular, the multidimensional variant N-PLS/RBL is shown to produce the best analytical results. The comparison is carried out with the aid of a set of simulated data, as well as two experimental data sets: one aimed at the determination of salicylate in human serum in the presence of naproxen as an additional interferent, and the second one devoted to the analysis of danofloxacin in human serum in the presence of salicylate.     

Independent rule in classification of multivariate binary data

We consider the performance of the independent rule in classification of multivariate binary data. In this article, broad studies are presented including the performance of the independent rule when the number of variables, d, is fixed or increased with the sample size, n. The latter situation includes the case of d=O(n^τ) for τ>0 which cover “the small sample and the large dimension”, namely dn when τ>1. Park and Ghosh [J. Park, J.K. Ghosh, Persistence of plug-in rule in classification of high dimensional binary data, Journal of Statistical Planning and Inference 137 (2007) 3687–3707] studied the independent rule in terms of the consistency of misclassification error rate which is called persistence under growing numbers of dimensions, but they did not investigate the convergence rate. We present asymptotic results in view of the convergence rate under some structured parameter space and highlight that variable selection is necessary to improve the performance of the independent rule. We also extend the applications of the independent rule to the case of correlated binary data such as the Bahadur representation and the logit model. It is emphasized that variable selection is also needed in correlated binary data for the improvement of the performance of the independent rule.     

基于Pulic智力资本模型的上市公司财务危机预警研究

智力资本在知识经济时代对企业的发展至关重要.本文考察Pulic智力资本评测模型是否能够用于企业财务危机预警.首先基于2003年至2007年中国A股市场新增ST公司样本及配对样本的前三年数据对Pulic模型综合指标进行单变量分析证实了该模型的预警可行性,然后根据三项因素驱动指标分别运用多元判别、逻辑回归、神经网络和最小二乘支持向量机方法建立预警模型进行回判和外推.结果表明,Pulic模型在ST前两年具有较高的判断准确性,可以通过对智力资本的考察而预知企业未来的财务状况.     

Multivariate irregular sampling theorem

In this paper,we prove a Marcinkiewicz-Zygmund type inequality for multivariate entire functions of exponential type with non-equidistant spaced sampling points. And from this result,we establish a multivariate irregular Whittaker-Kotelnikov-Shannon type sampling theorem.     

Constructive Approximation by Superposition of Sigmoidal Functions

In this paper, a constructive theory is developed for approximating functions of one or more variables by superposition of sigmoidal functions. This is done in the uniform norm as well as in the $L^p$ norm. Results for the simultaneous approximation, with the same order of accuracy, of a function and its derivatives (whenever these exist), are obtained. The relation with neural networks and radial basis functions approximations is discussed. Numerical examples are given for the purpose of illustration.     

WEIGHTED ESTIMATES FOR MULTIVARIATE HAUSDORFF OPERATORS

In this paper,some weighted estimates for the multivariate Hausdorff operators are obtained.It is proved that the multivariate Hausdorff operators are bounded on L p spaces with power weights,which is based on the boundedness of multivariate Hausdorff operators on Herz spaces,and are bounded on weighted L p spaces with the weights satisfying the homogeneity of degree zero.     

Decomposition of in vivo spatially offset Raman spectroscopy data using multivariate analysis techniques

The decomposition of spatially offset Raman spectra for complex multilayer systems, such as biological tissues, requires advanced techniques such as multivariate analyses. Often, in such situations, the decomposition methods can reach their limits of accuracy well before the limits imposed by signal‐to‐noise ratios. Consequently, more effective reconstruction methods could yield more accurate results with the same data set. In this study we process spatially offset Raman spectroscopy (SORS) data with three different multivariate techniques (band‐target entropy minimization (BTEM), multivariate curve resolution and parallel factor analysis (PARAFAC)) and compare their performance when analysing a spectrally challenging plastic model system and an even more challenging problem, the analysis of human bone transcutaneously in vivo. For the in vivo measurements, PARAFAC's requirement of multidimensional orthogonal data is addressed by recording SORS spectra both at different spatial offsets and at different anatomical points, the latter providing added dimensionality through the variation of skin/soft tissue thickness. The BTEM and PARAFAC methods performed the best on the plastic system with the BTEM more faithfully reconstructing the major Raman bands and PARAFAC the smaller more heavily overlapped features. All three methods succeeded in reconstructing the bone spectrum from the transcutaneous data and gave good figures for the phosphate‐to‐carbonate ratio (within 2% of excised human tibia bone); the PARAFAC gave the most accurate figure for the mineral‐to‐collagen ratio (20% less than excised human tibia bone). Previous studies of excised bones have shown that certain bone diseases (such as osteoarthritis, osteoporosis and osteogenesis imperfecta) are accompanied by compositional abnormalities that can be detected with Raman spectroscopy, the utility of a technique which could reconstruct bone spectra accurately is manifest. The results have relevance on the use of SORS in general. © 2014 Crown copyright. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.