浅谈新版TP317下位类类目注释存在的问题

通过对新旧版《中图法》TP3 17及其下位类的比较 ,详细分析了新版该类类目采用“使用分离”时类目注释所存在的一些问题 ,并依考虑的侧重点不同 ,给出了两种可行性解决方法     

光通信中光束瞄准的误差分析

对自由空间光通信中光束瞄准的误差进行了分析,并对典型的ＡＴＰ系统及其关键技术作了论述。     

A generalized step-up-down multiple test procedure

A generalization of step-up and step-down multiple test procedures is proposed. This step-up-down procedure is useful when the objective is to reject a specified minimum number, q, out of a family of k hypotheses. If this basic objective is met at the first step, then it proceeds in a step-down manner to see if more than q hypotheses can be rejected. Otherwise it proceeds in a step-up manner to see if some number less than q hypotheses can be rejected. The usual step-down procedure is the special case where q = 1, and the usual step-up procedure is the special case where q = k. Analytical and numerical comparisons between the powers of the step-up-down procedures with different choices of q are made to see how these powers depend on the actual number of false hypotheses. Examples of application include comparing the efficacy of a treatment to a control for multiple endpoints and testing the sensitivity of a clinical trial for comparing the efficacy of a new treatment with a set of standard treatments.     

A learning vector quantization neural network model for the classification of industrial construction projects

In several key functional areas of contemporary engineering and management science, neural networks have steadily been gaining recognition as robust and reliable tools for classification problems. This paper describes a new application of the learning vector quantization neural network: the classification of the degree of modularization appropriate for the construction of an industrial facility. This neural network uses variables related to plant location, labor issues, organizational issues, plant characteristics, project risks, and environmental issues as inputs to perform the classification. The neural network training and performance evaluation is also discussed.     

Transport schemes for topology-transparent scheduling

Transport protocols provide reliable, end-to-end communication between a source and a destination in a network. The Transmission Control Protocol (TCP) uses backward error correction, where the destination explicitly returns feedback to the source. Forward error correction (FEC) can also be used for transport; here the source includes enough redundancy in the encoding symbols to allow the destination to decode the message. In this paper, we compare the performance of two transport schemes, TCP and LT, a scheme based on rateless FEC codes, in a wireless ad hoc network when topology-transparent scheduling is used for channel access. These schedules are derived from cover-free families, a type of combinatorial design. They provide a mechanism to guarantee collision-free communication between any two nodes provided that each of the N nodes of the network has at most a specified number D of active (transmitting) neighbours. We find that LT outperforms TCP in more strenuous network conditions. To Frank Hwang on the occasion of his sixty-fifth birthday.     

区间数多指标决策中确定指标权重的一种客观赋权法

研究了指标值以区间数形式给出的不确定性多指标决策中确定指标权重的问题。依据传统的客观赋权法—离差最大化方法,给出了一种确定区间数指标权重的误差分析方法。该方法具有概念清晰、实用的特点,得出的指标权重能够较好地反映各指标信息的差异程度。最后通过一个算例说明了该方法的实用性和有效性。     

不确定性支持向量分类预警算法

支持向量分类从理论上可以保证好的预警外推能力。但历史警度的确定是一个十分棘手的问题。论文提出了不确定性支持向量分类预警方法。将支持向量分类预警问题转化为各个历史样本的惩罚系数的合理变化,从而大大减少了约束的个数,体现了专家决策在预警系统的作用。不仅实现了专家意见的综合,而且是对SVM理论本身的拓广。证明了模糊支持向量机是不确定性支持向量分类的特例,从而给出了模糊支持向量机的确切含义。数据试验表明,未确知支持向量分类预警方法具有一定的实际应用价值。     

Organizations in Public Management: Guest Editors' Introduction

This brief introduction sets the scene for the symposium. It identifies three factors which prompted its preparation, and then outlines the six contributions to it.     

A Three‐step Method for Choosing the Number of Bootstrap Repetitions

This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap standard errors, confidence intervals, confidence regions, hypothesis tests, p‐values, and bias correction. For each of these problems, the paper provides a three‐step method for choosing B to achieve a desired level of accuracy. Accuracy is measured by the percentage deviation of the bootstrap standard error estimate, confidence interval length, test's critical value, test's p‐value, or bias‐corrected estimate based on B bootstrap simulations from the corresponding ideal bootstrap quantities for which B=∞. The results apply quite generally to parametric, semiparametric, and nonparametric models with independent and dependent data. The results apply to the standard nonparametric iid bootstrap, moving block bootstraps for time series data, parametric and semiparametric bootstraps, and bootstraps for regression models based on bootstrapping residuals. Monte Carlo simulations show that the proposed methods work very well.     

英语语法学习中母语负迁移问题探析

语言迁移即母语迁移,是指语言学习者在学习新知识的过程中,对已有知识进行自动的潜意识的利用过程。任何人在第二语言习得过程中都或多或少地受到母语的影响。文章着重研究英语语法学习中的母语负迁移现象及应对策略,旨在帮助人们掌握一些应对母语负迁移的方法,减少母语负迁移,提高英语语法学习的成效。