中国小说理论与批评的哲性因子

“依经论文”、“依道论文”在中国古代小说评论中是一个重要的角度和原则,这些论述都在强调小说的思想性即哲性因子。那么,这是否就意味着中国古代文化人对小说就不采取“依史论文”的视角和原则呢?当然不是。余虹先生以及持相同见解的先生的观点是有大量史料为基础的,我们之所以特别突出地强调中国古代小说理论与批评中的哲性因子,是意在与余虹先生的见解构成互补,以防止偏误和片面的认识。     

泡沫塑料衬垫缓冲性能11参数模型及其参数识别

提出了 11参数性粘弹塑性模型 ,反映了泡沫塑料衬垫缓冲性能的特征 .     

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of This Variability for Risk Analysis

Physical property values are used in environmental risk assessments to estimate media and risk-based concentrations. However, considerable variability has recently been reported with such values. To evaluate potential variability in physical parameter values supporting a variety of regulatory programs, eight data sources were chosen for evaluation, and chemicals appearing in at least four sources were selected. There were 755 chemicals chosen. In addition, chemicals in seven environmentally important subgroups were also identified for evaluation. Nine parameters were selected for analysis-molecular weight (MolWt), melting point (MeltPt), boiling point (BoilPt), vapor pressure (VP), water solubility (AqSOL), Henry's law constant (HLC), octanol-water partition coefficient (Kow), and diffusion coefficients in air (Dair) and water (Dwater). Results show that while 71% of constituents had equal MolWts across data sources, <3% of the constituents had equivalent parameter values across data sources for AqSOL, VP, or HLC. Considerable dissimilarity between certain sources was also observed. Furthermore, measures of dispersion showed considerable variation in data sets for Kow, VP, AqSOL, and HLC compared to measures for MolWt, MeltPt, BoilPt, or Dwater. The magnitude of the observed variability was also noteworthy. For example, the 95th percentile ratio of maximum/minimum parameter values ranged from 1.0 for MolWt to well over 1.0E + 06 for VP, and HLC. Risk and exposure metrics also varied by similar magnitudes. Results with environmentally important subgroups were similar. These results show that there is considerable variability in physical parameter values from standard sources, and that the observed variability could affect potential risk estimates and perhaps risk management decisions.     

平行带状线间加孔栅的抗耦合干扰技术研究

针对平行带状线间的耦合问题,比较了平行带状线间不加孔栅和加孔栅的耦合干扰问题,研究了平行带状线间距不同时加不同孔栅结构的抗耦合干扰情况,分析了孔径与反射损耗的关系。通过计算与仿真,得到了一种新型的孔栅结构,有效地抑制了平行带状线间的耦合干扰。     

KS,χ~2检验方法的K分布杂波参数估计研究

提出了一种基于矩估计的KS,χ2检验方法,用于对K分布杂波进行参数估计。该方法从拟合最优的角度进行参数估计,结合矩估计将二维优化转化为一维优化问题。仿真结果表明,该参数估计方法相比于二四阶矩估计方法有明显的改善,KS与分数阶矩法相比,仿真效果较好。χ2法在小v值时与分数阶矩法相当,当v增大时,性能下降。     

奥氏带改进INA法的系統稳定性証明

利用Ostrowski带(下称奥氏带)来改善INA法(逆乃氏阵列法)是多变量控制系统设计中一种熟知的方法,但这种方法对系统稳定性的影响在一般的书籍和文献中却未给出证明,本文对这个稳定性问题提出一种证明,其主要结论是用INA法设计的稳定系统,再按奥氏带的位置改变一个反馈系数后,只要改变后的反馈值不侵犯奥氏带,系统的稳定性就不致被破坏,也即系统仍然稳定。     

改进非平稳信号的分析方法

研究了WVD和短时傅里叶变换两种时频分析方法的优势和局限性,从两种方法的定义出发,分析了两者间存在的联系,通过构造窗函数,提出一种改进的非平稳信号分析方法,并进行了相应的计算机仿真,结果表明信号的时频特性得到了改善,该方法还适用于多分量非平稳信号的分析。     

Genetic algorithms for numerical optimization

Genetic algorithms (GAs) are stochastic adaptive algorithms whose search method is based on simulation of natural genetic inheritance and Darwinian striving for survival. They can be used to find approximate solutions to numerical optimization problems in cases where finding the exact optimum is prohibitively expensive, or where no algorithm is known. However, such applications can encounter problems that sometimes delay, if not prevent, finding the optimal solutions with desired precision. In this paper we describe applications of GAs to numerical optimization, present three novel ways to handle such problems, and give some experimental results.     

自组织理论对技术发展极限问题的启示

技术的发展从内史和外史的角度来说都会遇到发展极限的问题,自组织理论对技术发展极限问题的认识有重要的启示:技术系统的涨落对技术发展的极限实现维持与突破;技术系统的开放性对技术发展的极限实现促进与制约;技术系统的序参量对技术发展的极限实现役使和规导。正确认识技术发展的极限问题,对于促进技术的完善与革新,对于更好地规范技术的社会价值取向有重要的意义。     

Sensitivity Analysis Using Risk Measures

In a quantitative model with uncertain inputs, the uncertainty of the output can be summarized by a risk measure. We propose a sensitivity analysis method based on derivatives of the output risk measure, in the direction of model inputs. This produces a global sensitivity measure, explicitly linking sensitivity and uncertainty analyses. We focus on the case of distortion risk measures, defined as weighted averages of output percentiles, and prove a representation of the sensitivity measure that can be evaluated on a Monte Carlo sample, as a weighted average of gradients over the input space. When the analytical model is unknown or hard to work with, nonparametric techniques are used for gradient estimation. This process is demonstrated through the example of a nonlinear insurance loss model. Furthermore, the proposed framework is extended in order to measure sensitivity to constant model parameters, uncertain statistical parameters, and random factors driving dependence between model inputs.