高精度渗碳控制方法

在采用电阻法直接测控碳势的方法中,提出了一种分段参数调节增量式PID算法,通过实际调试和理论推导表明,渗碳工艺过程控制具有控制超调量小、过渡时间短、精度高、软件实现方便等优点,稳定后碳势控制精度可达±0.03%。     

谈歌唱教学中的气息运用

歌唱教学中呼吸的运用十分重要,本文集作者多年教学经验,从正确运用呼吸控制音准及呼吸与情感变化,呼吸与歌曲内容的转化等几方面作以论述。     

铁磁性金属簿膜磁特性的研究

讨论了铁磁性金属薄膜中的各向弄性磁阻效应。通过对晶体结构分析和实验验证,提出了一种假设:在外磁场作用下,产生了原子对的方向有序化,导致感生磁各向异性,并使晶体织构消失。根据对5种样品的实测数据,讨论了薄膜的动态磁化过程。     

Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

平稳性检验方法的有效性研究

平稳性检验是时间序列分析的重要研究内容,现有检验方法的性能缺乏系统的比较分析。文章从样本长度的视角研究平稳性检验方法的性能,采用ADF检验、PP检验、KPSS检验和LMC检验四种方法展开实证研究。仿真实验结果表明:时间序列数据长度会对检验方法的准确率产生明显的影响,数据长度较小时检验准确率偏低;数据长度增大时可以提升检验方法的准确率,但仍未能达到100%的上限值。当样本长度较小时,这些方法的检验统计量的渐进分布难以满足,因此其实际检验效果值得探究。样本长度是有限的,因此渐进分布检验方式的改进空间有限,新的检验方式值得探究。     

论校园导向标识的人性化设计

校园导向标识系统中引入人性化设计理念,体现了"为人而设计"的本质,具有文化性、关怀性、形象性、连续性和统一性等五个特征,校园导向标识人性化设计的表现方法可从地图标识、指示标识、名称标识和安全规范标识四方面尝试。     

导数与微分概念的推广

本文将数学分析中单值函数f:R→R 的导数与微分的概念推广到向量值函数f :Rn →Rm 和集值函数f:Rn → 2 Rm 上     

Small‐sphere distributions for directional data with application to medical imaging

We propose novel parametric concentric multi‐unimodal small‐subsphere families of densities for p ? 1 ≥ 2‐dimensional spherical data. Their parameters describe a common axis for K small hypersubspheres, an array of K directional modes, one mode for each subsphere, and K pairs of concentrations parameters, each pair governing horizontal (within the subsphere) and vertical (orthogonal to the subsphere) concentrations. We introduce two kinds of distributions. In its one‐subsphere version, the first kind coincides with a special case of the Fisher–Bingham distribution, and the second kind is a novel adaption that models independent horizontal and vertical variations. In its multisubsphere version, the second kind allows for a correlation of horizontal variation over different subspheres. In medical imaging, the situation of p ? 1 = 2 occurs precisely in modeling the variation of a skeletally represented organ shape due to rotation, twisting, and bending. For both kinds, we provide new computationally feasible algorithms for simulation and estimation and propose several tests. To the best knowledge of the authors, our proposed models are the first to treat the variation of directional data along several concentric small hypersubspheres, concentrated near modes on each subsphere, let alone horizontal dependence. Using several simulations, we show that our methods are more powerful than a recent nonparametric method and ad hoc methods. Using data from medical imaging, we demonstrate the advantage of our method and infer on the dominating axis of rotation of the human knee joint at different walking phases.     

Classification with minimum ambiguity under distribution heterogeneity

The traditional classification is based on the assumption that distribution of indicator variable X in one class is homogeneous. However, when data in one class comes from heterogeneous distribution, the likelihood ratio of two classes is not unique. In this paper, we construct the classification via an ambiguity criterion for the case of distribution heterogeneity of X in a single class. The separated historical data in each situation are used to estimate the thresholds respectively. The final boundary is chosen as the maximum and minimum thresholds from all situations. Our approach obtains the minimum ambiguity with a high classification accuracy allowing for a precise decision. In addition, nonparametric estimation of the classification region and theoretical properties are derived. Simulation study and real data analysis are reported to demonstrate the effectiveness of our method.