一种抗噪声的M型星视向速度测量方法

M矮星是银河系中最普遍的恒星,它们的运动状况能提供银河系演化的线索,视向速度(RV)是反映M矮星运动状况的重要参数之一。我国的大科学工程LAMOST巡天项目已经获得了数十万M型星光谱,测量这些恒星的视向速度需要自动、高效的程序。计算M矮星视向速度的一般方法是将观测光谱与模板光谱进行交叉相关得出。然而在实际处理过程中,由于本质上的不同或者噪声的影响,一些观测光谱和模板光谱错误匹配,从而使得这些光谱的视向速度测量产生偏差。为了减少噪声等因素的影响,对于信噪比较高、但局部有较强噪声的光谱,采用统计与经验特征相结合的方法选取光谱中的有效特征段、避开噪声污染的波段计算M型星的视向速度。利用该方法对LAMOST DR3 M型星星表中的部分实测光谱测量了视向速度,将之与APOGEE星表中的对应视向速度进行了对比。结果表明该方法有效地减少了局部噪声对视向速度的影响,提高了视向速度测量的准确率。     

基于标准序列浮动前向特征选择的改进算法研究

随着信息技术的高速发展,信息特征的表述方法和内涵不断扩充,高维特征大幅涌现。这些高维特征中可能存在许多不相关和冗余特征,造成了维度灾难,对分类识别算法提出了更高的要求,需要利用特征选择算法,降低特征向量维数并消除数据噪音的干扰。针对高维特征向量引入的维度灾难等问题,围绕目标分类识别的具体应用,对标准的序列浮动前向特征选择算法进行了研究,并通过优化正确分类样本数目的置信上限及交叉验证的重复次数,提出了一种改进的序列浮动前向特征选择算法。通过仿真实验表明,在利用贝叶斯分类器开展识别时,改进算法能够在确保分类识别正确率的前提下,有效提升特征选择的计算速度,并随着特征选择步骤的增加,能够维持一个相对更为收敛且稳定的置信区间,具备良好的准确度。     

基于多模型的参数空间预测推断

当建立多个模型对工程结构进行数值仿真时,为了得到更可靠的预测结果,需要综合考虑模型选择不确定性和模型形式不确定性对预测结果的影响. 联合贝叶斯方法与实验数据计算不同模型的可信度,采用调节因子方法传播模型选择不确定性得到系统响应置信区间,并叠加模型形式不确定性的影响获得综合模型计算结果的置信区间,再通过插值得到关心量在预测点的置信区间. 最后通过某飞行器气动力系数的预测推断检验了该方法的可行性.     

投资组合模型的改进研究:基于企业社会责任视角的实证分析

在尊重和借鉴前人对企业社会责任研究,尤其是在企业社会责任评价研究基础之上,本文从投资者的角度在投资组合过程中研究企业社会责任。在Markowitz(均值—方差)理论模型上添加企业社会责任的三个一级指标期望作为目标函数,由此将传统的投资组合模型扩展为五个目标函数的投资组合选择模型,而且我们根据经济学中经典的效用函数理论证明了此模型的正确性。本文引入主流的企业社会责任评价标准,并对一些典型公司进行打分量化。在此基础之上建立了以期望回报率、回报率的方差、核心利益相关者期望、蛰伏利益相关者期望和边缘利益相关者期望为目标函数的投资组合选择模型,在最小方差曲面上选取10个点构造投资组合,并以样本外的数据验证了模型的有效性。研究发现:根据此模型计算出来的部分投资组合回报率显著高于同期的市场指数。研究结果表明,这种关注企业社会责任的多目标投资组合选择模型,不仅让投资者可以直接控制企业社会责任,而且实际数据证明了此模型的优势之处,从而为关注企业社会责任的投资者提供一种投资的方法和思路。     

子宫内膜癌组织近红外光谱预处理与波段选择研究

应用近红外光谱技术对子宫内膜组织病理切片进行快速无损检测。收集了154样品光谱,其中正常样本的个数36个,增生的60个,癌变的58个。由于原始光谱中包含大量干扰信息,所以光谱预处理方法和波段选取的方法在近红外光谱分析中占有非常重要的地。利用多种预处理方法,包括一阶导数、多元散射校正、多项式最小二乘拟合求导、标准归一化、平滑、移动窗口中值滤波,对样品光谱进行了预处理。利用标准偏差谱来选取最优波段,选取的最优波段范围为4 000~6 000 cm-1。然后用处理后的光谱数据进行主成分分析,分类准确率达到100%。研究结果表明近红外光谱技术结合化学计量学方法可以作为一种癌症快速诊断的新技术,对于癌症的早期诊断和癌症组织的恶化过程研究具有重要的意义。     

Comparison analysis of optical burst switched network architectures

Optical burst switching (OBS) is a promising paradigm for the next-generation Internet infrastructure. In this paper, a novel efficient network architecture for OBS has been presented and compared with conventional OBS architectures. To enhance OBS system performance, the architecture employs a novel proposed burst assembly algorithm, fiber delay lines (FDLs) and dynamic route selection technique. A queuing model is used to predict the system behavior for both classless and prioritized traffic. Simple closed-form expressions are obtained for the burst-loss probability of both classless and prioritized traffic. Numerical results show that the proposed architecture provides an accurate fit for the performance of the highest traffic class and lower bounds for the other traffic classes that are tighter than earlier known results.     

Fluctuation theorem for the mutation process in in vitro evolution

A proposition based on the fluctuation theorem in thermodynamics is formulated to quantitatively describe molecular evolution processes in biology.Although we cannot give full proof of its generality,we demonstrate via computer simulation its applicability in an example of DNA in vitro evolution.According to this theorem,the evolution process is a series of exponentially rare fluctuations fixed by the force of natural selection.     

Determination of calcium and magnesium in the Solanaceae plant by near infrared spectroscopy combined with interval combination optimization algorithm

Determination of the content of inorganic nutrients was done as part of a project to improve crop yield by use of fertilizers. Near-infrared spectroscopy coupled with interval combination optimization was used to determine the inorganic nutrients of calcium and magnesium in the Solanaceae plant. Interval combination optimization was employed to choose effective intervals with the merit of assigning smaller weights to less significant variables. Compared with full spectrum partial least squares regression, interval combination optimization improved the predictive accuracy and precision for both calcium and magnesium. The result was a high predictive ability for calcium, with a root mean squared error prediction of 0.159%, and for magnesium, with a root mean squared error prediction of 0.064%. In this study, the superiority of interval combination optimization over full spectrum partial least squares was shown in the aspects of effective variables and accurate results. Near-infrared spectroscopy combined with interval combination optimization was efficient for the determination of inorganic nutrients, calcium and magnesium, in the Solanaceae plant.     

Impact of local diffusion on macroscopic dispersion in three-dimensional porous media

While macroscopic longitudinal and transverse dispersion in three-dimensional porous media has been simulated previously mostly under purely advective conditions, the impact of diffusion on macroscopic dispersion in 3D remains an open question. Furthermore, both in 2D and 3D, recurring difficulties have been encountered due to computer limitation or analytical approximation. In this work, we use the Lagrangian velocity covariance function and the temporal derivative of second-order moments to study the influence of diffusion on dispersion in highly heterogeneous 2D and 3D porous media. The first approach characterizes the correlation between the values of Eulerian velocity components sampled by particles undergoing diffusion at two times. The second approach allows the estimation of dispersion coefficients and the analysis of their behaviours as functions of diffusion. These two approaches allowed us to reach new results. The influence of diffusion on dispersion seems to be globally similar between highly heterogeneous 2D and 3D porous media. Diffusion induces a decrease in the dispersion in the direction parallel to the flow direction and an increase in the dispersion in the direction perpendicular to the flow direction. However, the amplification of these two effects with the permeability variance is clearly different between 2D and 3D. For the direction parallel to the flow direction, the amplification is more important in 3D than in 2D. It is reversed in the direction perpendicular to the flow direction.     

近红外光谱预测稻谷水分含量特征谱区选择及其效率分析

对364份水分含量在2.24%～32.66%之间的“冈优916”稻谷样品,经均值中心化、一阶微分、标准归一化和多元散射校正等预处理后,采用分段间隔法、组合分段法、滑动窗口法和反向分段法等进行特征谱区选择,分别使用偏最小二乘法(PLS)和主成分回归(PCR)两种定量分析方法,获得稻谷含水量近红外光谱预测模型最佳的特征谱区。首次给出了分段间隔法、组合分段法、滑动窗口法和反向分段法等传统的特征谱区选择方法的计算复杂度的计算公式,并对比分析了这几种特征谱区选择方法的程序运行效率。结果表明：采用PLS建模对稻谷含水量光谱的预测性能优于PCR建模,但PLS建模的效率低于PCR建模;在PLS建模中,采用反向分段法对稻谷光谱含水量的预测性能最好,其预测集的相关系数R_P为0.995 6,预测均方根偏差RMSEP为0.78%;其次是滑动窗口法,其R_P为0.994 3,RMSEP为0.89%;但这两种特征谱区选择方法的程序运行效率较低,反向分段法的平均运行时间为4.87 h,滑动窗口法的平均运行时间为29.82 h。该研究结果为今后在并行计算或分布式计算上开发近红外光谱预测模型的快速算法提供参考。