自然环境变化的加速度规律

自然环境越来越受到社会的关注 ,近些年来 ,自然环境污染破坏日益严重 ,严重威胁着人类的生存和发展。就森林减少、生物物种减少和土地沙漠化、空气、水体污染加剧等几个方面进行了讨论 ,并分析了自然环境变化的原因 ,同时还对未来自然环境变化进行了预测 ,提出了自然环境变化存在一个加速度的观点     

Reliability acceptance sampling plans for the Weibull distribution under accelerated Type-I censoring

Type-I censored reliability acceptance sampling plans (RASPs) are developed for the Weibull lifetime distribution with unknown shape and scale parameters such that the producer and consumer risks are satisfied. It is assumed that the life test is conducted at an accelerated condition for which the acceleration factor (AF) is known, and each item is continuously monitored for failure. Sensitivity analyses are also conducted to assess the effect of the uncertainty in the assumed AF on the actual producer and consumer risks, and a method is developed for constructing RASPs that can accommodate the uncertainty in AF.     

Robust models in probability sampling

In the estimation of a population mean or total from a random sample, certain methods based on linear models are known to be automatically design consistent, regardless of how well the underlying model describes the population. A sufficient condition is identified for this type of robustness to model failure; the condition, which we call 'internal bias calibration', relates to the combination of a model and the method used to fit it. Included among the internally bias-calibrated models, in addition to the aforementioned linear models, are certain canonical link generalized linear models and nonparametric regressions constructed from them by a particular style of local likelihood fitting. Other models can often be made robust by using a suboptimal fitting method. Thus the class of model-based, but design consistent, analyses is enlarged to include more realistic models for certain types of survey variable such as binary indicators and counts. Particular applications discussed are the estimation of the size of a population subdomain, as arises in tax auditing for example, and the estimation of a bootstrap tail probability.     

MEMS器件平板运动空气阻尼研究

针对微电子机械系统中平行板间的气膜阻尼问题,通过将平板沿垂直方向的位移运动方程展开为傅里叶级数,得到了微平面机构所受的空气阻尼力和阻尼系数的解析公式。结果表明,空气阻尼系数近似与两平板间气隙厚度的三次方成反比。通过对微加速度开关质量块工作时所受的空气阻尼进行仿真分析,得出该开关的阻尼系数在工作过程中为变阻尼的结论,并分析了空气阻尼系数对于开关性能的影响。     

关于加快云南新型工业化进程的思考

通过外源性经济和内源性经济特点的分析,结合云南地区经济发展的实际,就如何协调发展内、外源经济,加快云南地区新型工业化发展进程提出意见和建议。     

电子秒表自动计时的研究

利用光电原理，对常用的计时工具——电子秒表实现自动控制，能有效地消除手动操作所带来的误差。它可广泛应用于对运动物体的速度、加速度的测量实验，还可用来验证牛顿第二定律、机械能守恒等物理实验，同时也适用于对时间测量精度要求较高的场合。     

加速度瞬心的径迹方程

导出了加速度瞬心的空间径迹方程和本体径迹方程,给出了彼此间的变换关系,并对速度瞬心与加速度瞬心的不同进行了讨论.     

加快转变经济发展方式的时代内涵

经济发展方式的转变是个老问题,但是加快转变经济发展方式却是一个新提法。随着国内外形势的变化,加快转变经济发展方式有着其特定的时代内涵。加快转变经济发展方式的前提是以人为本;重点是经济结构调整;目标是统筹协调发展;核心是自主创新;根本保证是社会主义基本经济制度。只有深刻认识和准确把握加快转变经济发展方式的时代内涵,才能实现经济发展方式转变的实质性突破。     

“当前”统计模型机动加速度分布的研究

利用机动目标"当前"统计模型的自适应卡尔曼滤波对两种不同的机动加速度模型进行计算机仿真研究中发现,在跟踪变加速目标时,运用两种不同分布模型分析计算的结果出现较大的差别.在利用修正的瑞利分布密度函数模型对目标位置和速度跟踪时产生较大的滞后,而利用截断正态分布密度函数模型时没有出现这种现象.通过对分布函数和计算机仿真结果的分析,初步找出产生跟踪滞后的原因,并提出相应的修正办法.     

Tourist number prediction of historic buildings by singular spectrum analysis

A wooden historic building located in Tibet, China, experienced structural damage when subjected to tourists visit. This kind of ancient building attends to too many visitors every day because heritage sites never fail to attract tourists. There should be a balance between accepting the visitors and the protection of historic buildings considering the importance of the cultural relics. In this paper, the singular spectrum analysis (SSA) is used for forecasting the number of tourist for the building management to exercise maintenance measures to the structure. The analyzed results can be used to control the tourist flow to avoid excessive pedestrian loading on the structure. The relationship between the measured acceleration from the structure and the tourist number is firstly studied. The root-mean-square (RMS) value of the measured acceleration in the passage route of the tourist is selected for forecasting future tourist number. The forecasting results from different methods are compared. The SSA is found slightly outperforms the autoregressive integrated moving average model (ARIMA), the X-11-ARIMA model and the cubic spline extrapolation in terms of the RMS error, mean absolute error and mean absolute percentage error for long-term prediction, whereas the opposite is observed for short-term forecasting.