基于集值统计的模糊神经网络专家系统及其应用

建立基于集值统计的模糊神经网络专家评审系统，并应用于科研项目评审工作，实际应用表明该系统是可行的。     

Size effect upon grained materials tensile strength: The increase of the statistical dispersion at the smaller scales

The present paper provides a statistical model to the size effect on grained materials tensile strength; it is based on an Extreme Value Theory approach. Since the weakest link in grained materials is usually represented by the interface between the matrix and the aggregates, it is assumed that the flaw distribution can be represented by the aggregate distribution, expressed as a probability density function (pdf) of the grain diameters. Under the hypothesis that the strength of the material depends on the largest flaw, the tensile strength is computed as a function of the specimen size. In this way, two remarkable results are obtained: (i) a size effect for the average tensile strength that substantially agrees with the multifractal scaling law (MFSL) proposed by the first author and (ii) an increase of scatter of the tensile strength values when testing small specimens. Both these trends are confirmed by experimental data available in the literature.     

Amplified spontaneous emission in dye-laser systems for single photon amplification

A longitudinally pumped dye-laser amplifier is numerically investigated for the amplification of a very low intensity signal (as low as one photon per pulse), which is easily hindered by the simultaneous amplification of spontaneous emission. From the relevant set of coupled rate equations for population and photon fluxes the spatial dependence of these quantities is accounted for. The equations are solved numerically in some significant practical situations. The results describe the dependence of the amplified-spontaneous-emission (ASE) output flux on the pumping rate, on the spectral narrowing process and on the total spontaneous emission for a pulse in the selected angular width. The performance of dye-laser amplifiers is described by the same set of equations, and the gain characteristics of such systems are analyzed as functions of the pumping rate.     

Exploring college students’ mental representations of inferential statistics

We report a case study that explored how three college students mentally represented the knowledge they held of inferential statistics, how this knowledge was connected, and how it was applied in two problem solving situations. A concept map task and two problem categorization tasks were used along with interviews to gather the data. We found that the students’ representations were based on incomplete statistical understanding. Although they grasped various concepts and inferential tests, the students rarely linked key concepts together or to tests nor did they accurately apply that knowledge to categorize word problems. We suggest that one reason the students had difficulty applying their knowledge is that it was not sufficiently integrated. In addition, we found that varying the instruction for the categorization task elicited different mental representations. One instruction was particularly effective in revealing students’ partial understandings. This finding suggests that modifying the task format as we have done could be a useful diagnostic tool.     

A new class of estimators of a “scale” second order parameter

For a large class of heavy-tailed distribution functions F in the domain of attraction for maxima of an Extreme Value distribution with tail index γ>0, the function A(t), controlling the speed of convergence of maximum values, linearly normalized, towards a non-degenerate limiting random variable, may be parameterized as , ρ < 0, β∈ℝ, where β and ρ are second order parameters. The estimation of ρ, the “shape” second order parameter has been extensively addressed in the literature, but practically nothing has been done related to the estimation of the “scale” second order parameter β. In this paper, and motivated by the importance of a reliable β-estimation in recent reduced bias tail index estimators, we shall deal with such a topic. Under a semi-parametric framework, we introduce a class of β-estimators and study their consistency. We deal with the conditions enabling us to get the asymptotic normality of the members of this class, and we illustrate the behaviour of the estimators, through Monte Carlo simulation techniques. Research partially supported by FCT / POCTI and POCI / FEDER.     

Universal fluctuations of the AEX index

We compute the analytic expression of the probability distributions F_AEX,+ and F_AEX,− of the normalized positive and negative AEX (Netherlands) index daily returns r(t). Furthermore, we define the α re-scaled AEX daily index positive returns r(t)^α and negative returns (−r(t))^α, which we call, after normalization, the α positive fluctuations and α negative fluctuations. We use the Kolmogorov-Smirnov statistical test as a method to find the values of α that optimize the data collapse of the histogram of the α fluctuations with the Bramwell-Holdsworth-Pinton (BHP) probability density function. The optimal parameters that we found are α⁺=0.46 and α⁻=0.43. Since the BHP probability density function appears in several other dissimilar phenomena, our result reveals a universal feature of stock exchange markets.     

Dyck paths with a first return decomposition constrained by height

We study the enumeration of Dyck paths having a first return decomposition with special properties based on a height constraint. We exhibit new restricted sets of Dyck paths counted by the Motzkin numbers, and we give a constructive bijection between these objects and Motzkin paths. As a byproduct, we provide a generating function for the number of Motzkin paths of height $k$ with a flat (resp. with no flats) at the maximal height.     

运用心理规律增强“概率统计”教学的实效性

学生在学习"概率统计"课时,常常会产生一些困惑,感到难学,尤其是对概念的理解以及知识间的联系、深化更让部分学生感到抽象、甚至模糊不清.教学中科学运用学生心理发展规律,可以及时有效地消除学生学习中的困惑,澄清模糊认识,提高学习效率,增强教学的实效性.