数据库技术在滚齿机挂轮选择中的应用

利用数据库技术选择滚齿机上的差动挂轮,只需在计算机上输入待加工齿轮的螺旋角β、模数m_n和滚刀的头数K,即可自动检索到既满足精度要求,又是机床所具备的若干组差动挂轮的齿数。文中介绍了建库的方法及程序。     

一个集值映射的不动点定理

本文在Hausdorff 拓扑向量空间的仿紧集合上,给出了所谓弱下半连续的集值映射的概念和一个近似选择定理.类似于Ky Fan 不动点定理,本文所建立的一个新的不动点定理,将弱下半连续性条件取代了Fan 定理中的上半连续性条件.     

对“非”达尔文革命的多视角透视(对话)——兼论同时发现者华莱士的境遇

我们从科学思想史、科学哲学、科学知识社会学、系统科学的观点,对达尔文革命进行多视角、全方位的透视:(1)作为达尔文革命的功臣,华莱士确实受了许多委屈,对这种科学史中的"异化"现象,可以用科学知识社会学来进行解读。(2)达尔文的思想历经四次革命的飞跃。(3)达尔文的"自然选择"纲领可以用系统科学观点得到合理解释。(4)作为达尔文纲领的对立面,"宇宙完美设计"纲领仍包含合理内核和启发性。(5)借助于系统科学理解模式,进化论的科学语言与自然神论的宗教语言之间通过转译,有可能进行对话。     

关于当代生命科学研究对象的划界、分析与表征的讨论

本文讨论了当代生命科学研究对象的划界、分析与表征的问题,首先围绕三个分主题对国际生物学的历史、哲学和社会学研究协会(ISHPSSB)2011年双年会的相关报告进行介绍并评论:关于基因组学与后基因组学的本体论和认识论问题;关于自然选择理论的扩展性的研究;对于生物学个体性概念的讨论,然后介绍了作者在共生语境下对生物学个体概念的研究进展。文章指出,对同一对象的不同表征模式以及对同一概念的不同分析方式,体现了两种科学传统在当代生命科学中的冲突与交汇;系统生物学力图综合不同研究范式,整合不同生命组织的层次,对其独特的研究方法、概念体系进行分析和讨论,将是未来生物学哲学的热门研究课题。     

原因、假说选择与最佳解释推理

科学哲学领域的方法论研究者提出了各种对“最佳解释”,“融贯性”或者“统合性”的概率测度.这些测度如果有用,至少在某些情况下依赖它们作解释性推理应该比因果推理中通常用的统计方法更准确.格拉斯(2012)发现,大多数此类测度在小样本的情况下都不优于通常统计方法中用的似然度(likelihood)或后验概率.此后,格拉斯(2013)比较了他定义的测度和后验概率对解决一类假说选择问题的优劣.在该类问题中,需要从一组互不相容且非此即彼的假说中择一,但假说的概率未知.他的结果显示,在似然度已知而主观的先验概率和真实的概率分布不同的情况下,如果样本很小,极大化他的测度选择假说可以比极大化后验概率更准确.本文在格拉斯的框架下探究一些一致的模型选择方法在有限样本下的准确性.笔者发现不同方法在准确性上的优劣依赖于真实假说的分布以及所采用的主观先验概率.虽然很多方法可能在所有设置下都不是最优,但也没有方法在所有设置下都是最优.笔者认为,如果对真实假说的分布和主观先验概率没有限定,讨论哪种方法在样本量不大的情况下能更准确的选出真假说意义不大.     

Genetic determinants of individual differences in avoidance learning: Behavioral and endocrine characteristics

Bidirectional genetic selection for good and poor active avoidance learning in a shuttle box has been carried out in three independent laboratories using remarkably similar discrete-trial training procedures. The resulting strains are known as the Roman High and Low Avoidance (RHA and RLA), the Syracuse High and Low Avoidance (SHA and SLA) and the Australian High and Low Avoidance (AHA and ALA) strains, respectively. An additional unidirectionally selected strain, known as the Tokai High Avoider (THA) strain was developed in Japan using a free-operant Sidman avoidance procedure in a Skinner box. This paper reviews the selection of the Syracuse strains, enumerates the various behavioral and endocrine characteristics of the strains, and compares them to the other similarly selected strains. The behavioral work suggests that genetic selection from diverse breeding stocks has resulted in common characteristics that differentiate the strains in the emotional, not learning, domain. The endocrine data, however, are somewhat at odds. The Syracuse strains differentiate one way with respect to endocrine function, and the Roman strains differentiate in the opposite way. We suggest, therefore, that the endocrine correlates are not tightly linked to the avoidance genotype. Genetic analysis of all of the selected strains for both the avoidance phenotype and the endocrine correlates will be needed to test this hypothesis.Preparation of this paper was supported by research grant MH-39230-3 from the National Institute of Mental Health.     

Neural model identification,variable selection and model adequacy

In recent years an impressive array of publications has appeared claiming considerable successes of neural networks in modelling financial data but sceptical practitioners and statisticians are still raising the question of whether neural networks really are ‘a major breakthrough or just a passing fad’. A major reason for this is the lack of procedures for performing tests for misspecified models, and tests of statistical significance for the various parameters that have been estimated, which makes it difficult to assess the model's significance and the possibility that any short‐term successes that are reported might be due to ‘data mining’. In this paper we describe a methodology for neural model identification which facilitates hypothesis testing at two levels: model adequacy and variable significance. The methodology includes a model selection procedure to produce consistent estimators, a variable selection procedure based on statistical significance and a model adequacy procedure based on residuals analysis. We propose a novel, computationally efficient scheme for estimating sampling variability of arbitrarily complex statistics for neural models and apply it to variable selection. The approach is based on sampling from the asymptotic distribution of the neural model's parameters (‘parametric sampling’). Controlled simulations are used for the analysis and evaluation of our model identification methodology. A case study in tactical asset allocation is used to demonstrate how the methodology can be applied to real‐life problems in a way analogous to stepwise forward regression analysis. Neural models are contrasted to multiple linear regression. The results indicate the presence of non‐linear relationships in modelling the equity premium. Copyright © 1999 John Wiley & Sons, Ltd.     

协同多点传输中迫零预编码和天线选择技术

MIMO无线传输技术极大地提高了系统的容量,在实际通信系统中,整个网络是一个干扰受限的系统,小区间干扰对MIMO系统传输的影响是显著的,每个相邻小区的基站天线都可以看成一个干扰源．由于基站端数据处理能力的提升和回程容量的增加,多个小区协同多点传输技术引起了人们的广泛关注．目前的大部分工作都是集中于研究系统的容量（吞吐量）,而在实际系统中,每个用户的接收等效信噪比（即公平性）对系统的性能如误帧率等有重要的影响．对于每个用户为单天线的情形,研究了总功率受限和每天线功率受限下采用迫零预编码的系统容量和公平性．对两种功率约束条件下的公平性进行了分析,得到了公平性算法的闭式表达式．当每个用户为多天线的情形,为了降低计算的复杂度,引入了信道范数最大的接收天线选择算法,把每个用户为多天线的情形转化成等效的每个用户单天线情形,推导的每用户为单天线的公平性算法仍然适用．仿真结果显示,采用迫零预编码的多小区协作可以使系统性能显著提升．在相同的迫零预编码下,不同的功率分配策略对系统的容量和公平性有显著的影响．和用户为单天线相比,采用天线选择算法可以提升系统的容量和公平性．考虑了用户公平性时的吞吐量和最大系统吞吐量之间的折中关系,并给出了仿真结果．     

On the Predictive Content of Autoregression Residuals: A Semiparametric,Copula‐Based Approach to Time Series Prediction

This paper proposes an adjustment of linear autoregressive conditional mean forecasts that exploits the predictive content of uncorrelated model residuals. The adjustment is motivated by non‐Gaussian characteristics of model residuals, and implemented in a semiparametric fashion by means of conditional moments of simulated bivariate distributions. A pseudo ex ante forecasting comparison is conducted for a set of 494 macroeconomic time series recently collected by Dees et al. (Journal of Applied Econometrics 2007; 22: 1–38). In total, 10,374 time series realizations are contrasted against competing short‐, medium‐ and longer‐term purely autoregressive and adjusted predictors. With regard to all forecast horizons, the adjusted predictions consistently outperform conditionally Gaussian forecasts according to cross‐sectional mean group evaluation of absolute forecast errors and directional accuracy. Copyright © 2012 John Wiley & Sons, Ltd.