经济发展、林产品贸易对木材消耗的影响研究

随着全球生态危机加剧,森林的生态环境功能日益突出,全球森林数量持续减少、质量不断下降,使涉嫌消耗大量木材的经济发展、林产品贸易备受争议。本文以木材消耗作为森林资源的压力指标,分析了影响木材消耗的关键因素,以世界具有代表性的61个国家2010年的相关截面数据,运用多元线性回归模型,进行了实证分析,结果表明:经济发展对木材消耗的影响为正,人均木材消耗指标与经济发展指标呈现一种向右上方倾斜的N形关系;林产品出口贸易与木材消耗的关系为负向,有利于减少人均木材消耗;林产品进口贸易与木材消耗的关系为正向,但相较于使用本国木材来说更有利于减少人均木材消耗;木材产量与木材消耗同方向变化,是影响人均木材消耗的最为显著的因素;林产品贸易规模、森林资源的丰富程度以及技术进步因素的影响不显著。据此,本文从世界和中国林业发展的角度提出了林产品贸易自由化、保持木材供应适度偏紧等相关建议。     

Influence of sex and specialty on the prediction of middle-distance running performances using the Mercier et al.’s nomogram

The aim was to test the influence of sex and specialty (3000, 5000 and 10000 m) on the validity of middle-distance running performance predictions obtained from the Mercier et al.’s nomogram. Consequently, we examined all official French track running rankings for the 3000-, 5000- and 10000-m events (men and women) from 2006 to 2012. A scoring table was used to determine the runners’ specialties. Only runners who performed in the three distance events within the same year were included (75 women and 400 men). The Mercier et al.’s nomogram was used to predict one running performance from the other two. The results showed no significant difference between actual and predicted running performances (P = 0.77). Female runners had significantly lower performances than male runners (P < 0.001). Specialty did not influence performances (P = 0.11). Very high correlations were found between actual and predicted performances (0.91 < r < 0.99), with the exception of women (r = 0.85) in 5000 m. Moreover, low limits of agreement were obtained for male and female runners, whatever the specialty. These results support the validity of the nomogram to predict running performance in the 3000-, 5000- and 10000-m events for male and female runners, whatever the specialty. The predicted running performances may be used in training programmes (e.g., to prescribe tempo runs) and competitions (e.g., to establish split times).     

基于Simulink的燃料电池汽车混合动力电驱动系统仿真

首先分析了燃料电池汽车混合动力电驱动系统基本结构并给出了等效电路,建立了电驱动系统的动态数学模型,主要包括:燃料电池系统、动力蓄电池、电动机和DC/DC转换器四个模块。采用最小二乘法对模型的参数进行了估计,典型工况下的估计结果显示模型的准确性。其次根据设计目标要求,设计了主要部件的功率参数,并提出了适合不同工作模式的车辆控制策略。然后基于Simulink软件平台,建立了前向式仿真模型。最后进行仿真试验,其结果分析表明,建立的电驱动系统模型有较好的动力性、经济性和平顺性,为燃料电池汽车整车研究提供了仿真平台。     

非齐次等式约束线性回归模型回归系数的广义条件岭估计

时非齐次等式约束线性回归模型回归系数提出广义条件岭估计.证明了在一定的条件下,在均方误差矩阵、均方误差及广义均方误差意义下,广义条件岭估计都优于约束最小二乘估计和狭义条件岭估计.     

基于EM算法的MIMO-OFDM系统半盲信道估计研究

文章通过对MIMO-OFDM(Multiple Input Multiple Output Orthogonal Frequency Division Mul-tiPlexing)系统及其信道估计的分析,针对MIMO-OFDM系统提出一种基于EM的半盲信道估计算法。不仅有利于减少MIMO-OFDM的系统开销,且有助于提高系统的信道估计精度,降低了计算的复杂度。     

高速铣削中的几何因素对加工表面粗糙度影响与实验

在高速铣削中由球头铣刀的几何因素致使加工表面残留高度发生相应改变,而其影响因素是多方面的,通过对铝合金试件的表面粗糙度实验分析出不同几何因素对加工表面质量的影响程度。     

经验似然在正态分布中的应用

正态分布为概率论中很重要的一种分布,在科学研究中有着重要的地位,该分布由均值和方差两个变量决定。常用的参数估计法为矩法估计和极大似然估计,经验似然作为一种新的估计方法,同样适用于其它常用的分布。     

MIMO-OFDM 系统中同信道干扰抑制

针对 MIMO-OFDM 系统,提出了一种最大后验概率的信道矩阵和干扰协方差矩阵估计方法,并设计了迭代求解算法。利用所估计的信道矩阵和干扰协方差矩阵,采用 IRC 接收机完成同信道干扰的抑制。利用干扰协方差阵的共轭对称与半正定等特性,提出2种干扰协方差矩阵的处理方案以提高其估计精度。第1种方案将每个子载波上干扰协方差矩阵表征为一系列时域矩阵之和,第2种方案将每个子载波上的干扰协方差矩阵用低阶模型来建模,其中模型阶数通过最小描述长度算法估计。仿真结果表明了所提方案的有效性。     

Estimation of a Nonlinear Intervention Phase Trajectory for Multiple-Baseline Design Data

A multilevel logistic model for estimating a nonlinear trajectory in a multiple-baseline design is introduced. The model is applied to data from a real multiple-baseline design study to demonstrate interpretation of relevant parameters. A simple change-in-levels (ΔLevels) model and a model involving a quadratic function (Quadratic) for the nonlinear intervention phase data were also estimated. In addition, a simulation study was conducted to assess Markov chain Monte Carlo estimation of the logistic model and compare its trajectory recovery with use of the ΔLevels and Quadratic models. While most of the logistic model's parameter values were recovered well, trajectory recovery was very reasonable using the simpler Quadratic model. Results are discussed along with recommendations for practitioners and directions for future research.     

一种改进的DV-HOP算法在WSN中的定位研究

如何能够更好的提高节点定位一直都是WSN研究的重点,本文在DV-HOP定位算法的基础上,从误差精度,锚节点稳定度和反向学习选择-最小二乘估计来对节点定位的3个方面进行改进。首先在定位误差精度中引入混沌优化算法,其次在锚节点处理中引入稳定度概念,最后在未知节点定位中引入反向学习和最小二乘估计。改进后的算法在通信半径和拓扑结构两个方面进行了仿真实验,实验表明,本文算法能够有效的减少计算带来的定位误差,提高定位精度。