硫化胶交联结构及其性能

综合讨论了聚合物／聚合物之间的交联结构及聚合物／填料之间的偶联结构对硫化胶抗硫化返牟性，抗氧老化性及动态疲劳性能的影响。     

Fe73.5Cu1Nb3Si13.5B9非晶合金的晶化动力学

用ＤＴＡ结合ＸＲＤ了Ｆｅ７３．５Ｃｕ１Ｎｂ３Ｓｉ１３．５Ｂ９晶合金的晶化动力学。表明，该事金在５００℃时析出α－Ｆｅ（Ｓｉ）相。晶化初期激活能最小为２４２ｋＪ／ｍｏｌ，它随晶化量的增加，在ＸＣ为０．４－０．８时，呈极大值为５２０ｋＪ／ｍｏｌ。在６２４℃时析出Ｆｅ２Ｂ相。     

PVC／NBR（HNBR）／HDPE共混体系相容性研究（Ⅲ）共混体系动态力学行为和结晶行为研究

用ＤＭＡ和ＤＳＣ研究了ＮＢＲ和氢化ＮＢＲ对ＰＶＣ／ＨＤＰＥ共混体系的增容作用。由于增容剂在相界面与ＰＶＣ和ＨＤＰＥ所产生的作用改变了界面分子的作用形式，使体系中ＰＶＣ和ＨＤＰＥ相的内耗峰内移。而ＤＳＣ的结果表明，增容剂降低了体系中结晶相ＨＤＰＥ的熔点，说明增容剂增加了ＰＶＣ／ＨＤＰＥ的相容性。     

非线性系统鲁棒吸引的动态补偿方法

考虑非线性不确定系统的鲁棒吸引问题,借助于动态输出反馈,构造了两类控制律。这两类控制律分别可使相应的闭环系统被一任意小的区域鲁棒吸引,或被一预先设置的区域有限吸引。     

Locally Weighted Learning

This paper surveys locally weighted learning, a form of lazy learning and memory-based learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, assessing predictions, handling noisy data and outliers, improving the quality of predictions by tuning fit parameters, interference between old and new data, implementing locally weighted learning efficiently, and applications of locally weighted learning. A companion paper surveys how locally weighted learning can be used in robot learning and control.     

连续重整装置仿真系统的设计开发

为提高操作人员对连续重整装置开停工及事故处理的熟练程度，并对生产进行指导，采用半机理模型结合设计和现场数据介发的连续重整装置仿真系统已在现场成功投用。介绍了该仿真系统的软硬件结构、动态模型及仿真功能。     

分子振动态及其跃迁的激光相干控制

讨论了激光合成相干叠加态的原理及其性质 ,针对 XY2 型分子 ,证明了合成局域模振动的可行性 ,然后给出相干叠加态的跃迁几率特征 ,发现它仍表现出相干的特性 ,对之进行分析研究表明 ,分子的振动态具有可控性 ,态跃迁几率具有可控性。     

单词排版的两种算法

在对英文排版时，我们既应考虑单词之间的间隔，以便清晰可读，又应考虑节省版面，以便降低费用，本文通过详细地讨论两种算法可以解决这一矛盾。     

一种新的机器人手臂控制方法

从机器人手臂的关节电机力学出发，本文提出了一种独立于现行机器人关节控制器的离线补偿方法，通过对－２自由度机器人的数值研究，证明该法不仅能有效地克服由于惯性负载，关节间耦合与重力效应给控制系统带来的动态精度问题，而且还可以消除由于控制系统本身的固有特性所决定的系统的跟踪误差。     

Best L1 Piecewise Monotonic Data Modelling

Let us consider n data measurements of a univariate process that have been altered by random errors. We assume that an underlying model function has a substantially smaller number of turning points than the observed ones. We propose algorithms that make least the sum of the moduli of the errors by requiring k monotonic sections, alternately increasing and decreasing, in the sequence of the smoothed values. The main difficulty in this calculation is that the optimal positions of the joins of the monotonic sections have to be found automatically among so many combinations that it is impossible to test each one separately. Moreover, the calculation seems to be very intractable to general optimization techniques because O(n^k) local minima can occur. It is shown that dynamic programming can be used for separating the data into optimal disjoint sections of adjacent data, where each section requires a single L₁ monotonic calculation. This procedure is highly efficient, requiring at most O(kn²) computer operations and O(n) best L₁ monotonic calculations to subranges of data for a global minimum.