The persistence of firms’ knowledge base: a quantile approach to Italian data

The paper investigates the patterns of persistence of innovation and of the properties of firms’ knowledge base (KB) across a sample of Italian firms in the period 1998–2006. The analysis draws upon a theoretical representation of knowledge as a collective good, stemming from the recombination of knowledge bits that are fragmented and dispersed across economic agents. On this basis, we derived properties of the KB like the coherence, the cognitive distance and the variety, and investigated their patterns of persistence over time. The empirical analysis is implemented by exploring the autocorrelation structure of such properties within a quantile regression framework. The results suggest that the properties of knowledge are featured by somewhat peculiar patterns as compared with knowledge stock, and that such evidence is also heterogeneous across firms in different quantiles.     

Financial cycle and business cycle: An empirical analysis based on the data from the U.S

In this paper, we first study the relationship between the financial cycle and the business cycle in the time and frequency domain. Then we also explore the interactions and dynamic mechanisms of the financial cycle, the business cycle, real interest rate and exchange rate by the VAR model. The empirical results show that the financial cycle is closely related to the business cycle, especially at medium-term frequencies (8–30 years), the business cycle leads the financial cycle with a high positive correlation. However, the relationship between them is not significant during the Great Moderation at business-cycle (2–4 years). In addition, the financial cycle not only becomes a main driver of real interest rate, the financial cycle and the business cycle, but also serves as an important source of the business cycle fluctuations. In general, our results lay some theoretical foundation for the policy practice of financial and economic stability.     

Wavelet domain correlation between the futures prices of natural gas and oil

This paper studies the relationship between futures prices of natural gas and oil. Using wavelet analysis, our research reveals that, throughout the sampled period: (1) the prices of natural gas futures and oil futures have high covariance at high frequencies but not so much at low frequencies; (2) an increase in financialization of commodities commensurate with investors search for yield results in higher covariance between the futures prices of natural gas and oil; and (3) the volatility of neither time series consistently leads the other even at high frequencies.     

基于LabVIEW的OCT信号采集和分析

虚拟仪器技术,使我们能够在计算机上按照自己的需求来设计实验与仪器,与相应的硬件设备结合使用,方便灵活而且开发周期短。它可以提高实验效率、降低实验成本。本文介绍了自行组建的双波长全光纤OCT系统以及实现该系统信号采集和分析的LabVIEW模块。     

前束一致性的控制方法分析

由于硬点坐标参数容差引起的,汽车悬架外特性参数随轮跳变化曲线的变化称为汽车悬架外特性的一致性,它是评价一种汽车产品整体质量一个重要指标。目前,还没有文献提出汽车悬架外特性一致性的具体控制方法,在汽车动力学软件中也没有汽车悬架外特性参数一致性分析的模块。所以,本文旨在利用区间数学的方法建立其一致性分析的数学模型,并用影响其一致性的硬点坐标参数容差作为区间参数,最后用区间分析方法计算其一致性结果。通过使用这种方法对双横臂独立悬架模型的前束角一致性进行分析,证明了区间分析方法计算汽车悬架外特性的一致性是可行的。     

寿险市场与股市的关联性研究——基于小波变换方法

运用定性和定量方法研究寿险市场发展与股市的关联性,分析股市波动可能引发的寿险市场系统性风险。从理论上分析寿险市场与投资环境具有关联性的原因,结合国内外研究成果和中国寿险市场的实证分析,提出寿险保费收入与股市具有密切联系;同时基于MATLAB7.0和Eviews5.0等软件,运用小波分析的方法和格兰杰检验法定量分析寿险保费收入与股市的关系,判断其领先滞后性,最后提出保险业应当如何防范系统性风险、根据经济周期变动正确引导消费者选择合适产品分散风险、匹配资产的建议。     

基于瞬时幅度与小波分析相结合的数字调制制式的自动识别

本文提出了一种基于信号瞬时幅度与小波分析相结合的数字调制制式的自动识别新算法。该算法计算简单、实时性强,能够成功识别2ASK、4ASK、2FSK、4FSK及2PSK5种信号。仿真结果表明,该算法具有较高的识别率。     

Gas system failure rate

Gasunie buys and sells gas. This paper is about calculating the failure rate of the gas transport system of Gasunie in the Netherlands. The pipes in the network are connected at certain stations which may operate at degraded levels due to technical problems. The transport system, modelled as an optimization problem, needs to be checked for feasibility for every configuration of the degradation levels at all stations in order to see whether the system fails or not. The discrete probability distributions of the degradation levels at every station in the network are given. The number of possible combinations of degradation levels is huge and the computations for the feasibility of the gas network are computer-intensive. This paper presents a new algorithm for approximating this rate and it is parsimonious in actually checking for feasibility.     

词汇模式理论在语篇实践中的应用研究

词汇衔接是一种非结构性衔接手段,是实现语篇连贯的多种衔接机制之一,但多年来未受到足够重视。近年来,人们认识到词汇衔接在语言习得过程中发挥着重要作用。尽管衔接不是语篇连贯的唯一手段,但衔接机制对语篇阅读理解有着很大的帮助、促进作用。在阅读理解中,在文中出现频率极高的词项一定与篇章的中心思想有着千丝万缕的联系。在现代语言教学中,阅读仍旧是获取信息的重要手段。在阅读教学中,教师有必要以语篇中的词汇衔接为突破口,有意识地锻炼学生恰当运用词汇衔接手段的能力,以提高他们的语篇阅读理解能力。     

基于AIW-PSO小波神经网络的上证指数预测

针对小波神经网络(Wavelet Neural Network,WNN)的学习算法的不足,采用一种自适应惯性权重粒子群优化算法(Adaptive Inertia Weight Particle Swarm Optimization,AIW-PSO)作为小波神经网络的学习算法,建立AIW-PSO小波神经网络模型对上证指数进行预测,并将预测结果传统小波神经网络模型比较。结果表明,AIW-PSO小波神经网络模型对上证指数具有更好的预测效果。