桁梁结构空间计算的三节点截面桁段有限元法

利用二次多项式位移函数导出了一个桁架结构的三节点截面桁段单元,提出了桁梁空间计算的三节点截面桁段有限元法,该方法适当地考虑了主桁弦杆节点刚性,桥面系横梁局部弯曲,斜桥门架及横联横梁局部弯曲的影响.算例表明,计算结果可靠、自由度较少,比较适用于大跨度桁梁桥的空间结构计算分析.     

多项式余代数的零阶Hochschild同调群的计算

在对代数上的模范畴研究的基础上,开展余代数的余模范畴的研究对讨论余代数的结构与表示有重要意义。所以,根据Y.Doi提出的Hochschild同调群的理论,研究多项式余代数上的双余模的零阶Hochschild同调群,并且把得到的结论应用到多项式余代数上的二元多项式环的双余模和矩阵双余模中,得到其多项式余代数的零阶Hochschild同调群。     

SRAM的一种可测性设计

用ETCO算法对SRAM进行了内建自测试设计．首先说明了设计的原理，进而对电路中所用的各个单元电路进行了设计，主要包括地址计数器、数据计数器和BIST控制器等．设计出的电路可针对具体的故障模型设置相应的测试长度，从而获得预期的故障覆盖率．测试时不需存储正确响应，并可通过一个响应标志位表示检测的结果．可测性部分对电路硬件的开销较小，所设计的电路在工作站上已成功通过仿真，此电路可广泛应用于嵌入式SRAM，以降低电路的测试难度．     

正交多项式回归在高蛋白大豆施肥及经济效益中的预测模型应用

为进一步探索高蛋白大豆最优施肥模式组合,获得高蛋白大豆最佳经济效益。以高蛋白大豆‘冀豆12’为供试材料,对氮、磷、钾三因素分别设置3个处理,以不同氮、磷、钾施用量为自变量,以相应大豆经济效益为依变量,采用正交多项式回归方法,建立高蛋白大豆经济效益预测模型方程,并对各项进行显著性(F)检验。结果表明：钾磷肥只有在氮肥达到一定水平(60~90 kg/hm²)才能更好的发挥肥效作用;施钾量过低或过高均不利于大豆经济效益值的增加;在施磷量50~110 kg/hm²水平间,大豆经济效益值与施磷量基本呈正相关关系。经F检验,氮肥对高蛋白大豆经济效益影响最大,其次为磷,钾效应最小。方差估计值$hat{σ}$=134.5508,预报高蛋白大豆每公顷经济效益$hat{W}$的95%的置信区间为$hat{W}$±1.96s=W±263.7196,预测效果较好;模型拟合下氮钾磷施用分别为54.67,62.38,140 kg/hm²,大豆经济效益最高,为13276.13元/hm²。多元正交多项式回归模型对预测多因素施肥水平下高蛋白大豆经济效益有实际参考价值。     

基于星-机光谱融合的棉花叶片SPAD值反演

【目的】为提高棉花叶片叶绿素含量的反演精度,并掌握其在山东省夏津县的空间分布特征。【方法】本研究以山东省德州市夏津县为研究区,以夏津县大李庄棉田为试验区,通过SPAD（soil and plant analyzer development,SPAD）仪实地测定试验区棉花叶片叶绿素含量的相对值（SPAD值）,并获取同期试验区无人机（unmanned aerial vehicle,UAV）近地多光谱图像和研究区Sentinel-2A MSI（MSI）卫星影像;然后分别基于UAV和MSI的光谱反射率,构建并筛选最优光谱参量,采用多元线性回归（multiple linear regression,MLR）建立SPAD值定量反演模型;最后采用二次多项式拟合法融合UAV和Sentinel-2A MSI对应的最优光谱参量,对比分析融合前后模型效果,优选最佳反演模型,实现研究区SPAD值反演。【结果】研究表明,(REG-R)/(REG+R)、R/G、CL(red edge)、NDVI可作为SPAD值的最优光谱参量;基于UAV图像的定量反演模型精度优于基于MSI影像的模型;基于二次多项式拟合后建模R ²提高了0.015—0.057,RMSE降低了0.457—0.638,验证R ²提高了0.040—0.085,RMSE降低了0.387—0.397,RPD提高了0.020—0.139;将融合后的MSI光谱参量代入基于UAV图像的反演模型（Fused MSI-Mod_UAV）,也可获得较高的反演精度,建模R ²达0.672,RMSE为3.982,验证R ²达0.713,RMSE为3.859,RPD为1.685;基于上述模型进行研究区棉花叶片SPAD值反演分析,试验区整体呈南高北低的分布趋势,研究区呈中间低、四周高的分布趋势,均与实地情况一致,具有较好的预测效果。【结论】采用二次多项式拟合法融合无人机和卫星影像数据,可较好地实现区域高精度作物生长指标的定量反演,研究结果可丰富多源遥感融合理论与技术,为后续棉花长势监测与精准生产提供技术参考和数据支持。     

概率加密方案的一个注记

The two-valued unapproximable trapdoor predicate of probabilistic encryption is extended to the multivalued unapproximable trapdoor predicate in this paper. The corresponding encryption and deoryption algorithm are given. It is proved that the extended pr     

Random regression models to estimate genetic parameters for test‐day milk yield in Brazilian Murrah buffaloes

The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo’s test‐day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test‐day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from ?0.07 (second with eighth week) to ?0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes.     

高阶欧拉多项式与交错等幂和多项式的对称等式

推广了一个关于欧拉数与交错等幂和多项式的对称关系式,获得了包含多个高阶欧拉多项式和交错等幂和多项式的对称等式。     

A tutorial on the statistical analysis of factorial experiments with qualitative and quantitative treatment factor levels

Agronomic experiments are often complex and difficult to interpret, and the proper use of appropriate statistical methodology is essential for an efficient and reliable analysis. In this paper, the basics of the statistical analysis of designed experiments are discussed using real examples from agricultural field trials. Factorial designs allow for the study of two or more treatment factors in the same experiment, and here we discuss the analysis of factorial designs for both qualitative and quantitative level treatment factors. Where treatment factors have quantitative levels, models of treatment effects are essential for efficient analysis and in this paper we discuss the use of polynomials for empirical quantitative modelling of treatment effects. The example analyses cover experiments with a single quantitative level factor, experiments with mixtures of quantitative and qualitative level factors, polynomial regression designs with two quantitative level factors, split‐plot designs with quantitative level factors and repeated‐measures designs with correlated data and a quantitative treatment response over time. Modern mixed model computer software for routine analysis of experimental data is now readily available, and we demonstrate the use of two alternative software packages, the SAS package and the R language. The main purpose of the paper is to exemplify standard statistical methodology for routine analysis of designed experiments in agricultural research, but in our discussion we also provide some references for the study of more advanced methodology.     

基于五次多项式的四足机器人轨迹规划

为达到四足机器人在地面上稳定、连续行走,不出现打滑、侧翻等现象的目的,提出一种基于walk静步态的五次多项式足端轨迹规划方法。首先利用D-H坐标法推导四足机器人单腿的运动学方程,由运动学逆解得到四足机器人足端轨迹和关节角之间的关系。将水平和竖直方向的约束方程代入五次多项式,分别求出支撑相和摆动相的足端轨迹方程。最后通过将轨迹方程代入MATLAB和ADAMS中进行仿真验证,实验结果验证了该轨迹规划方法的正确性。