论城市竞争力中的文化产业因素

目前,文化产业越来越成为影响城市竞争力的关键因素。信息产业是知识经济初级阶段的主要智力产业形态,而文化产业是知识经济高级阶段的主要智力形态。美国许多城市的兴衰过程、当局振兴城市的经验措施以及我国一些城市竞争力的变化证明:文化是城市的软件,是软国力,而文化产业则是城市的硬件,是硬国力;未来城市竞争力日益取决于文化产业的发展。以市场化为文化大产业的突破口,注重借鉴和吸取西方发达国家在这方面的经验和教训,化解负面效应,加快改革步伐,变拨款为投资基金,变扶持文化单位为扶持文化项目,力推文化产品出口创汇等是提升城市竞争力当务之急。     

采用CCSK承载非同步随机接入信息的方法

未来的移动通信系统要求提供的数据传输速率将高达100Mb/s以上,支持的业务也将从语音业务扩展到多媒体业务(包括实时的流媒体业务)。该文提出采用m序列的不同循环移位来构建CCSK序列,并在前导CAZAC序列上叠加CCSK序列,以用于隐含承载接入信息。为了减少两个序列之间的相互影响,调整两种序列之间的能量比例以及采用干扰消除,将显著提高两种序列的检测性能。     

企业竞争优势的内涵及其培养

企业竞争优势实质上是一种比对手强的相对实力,它直接表现为使企业获取超出行业平均水平的利润.但是,能够获利并不意味着企业具有竞争优势,企业的竞争优势主要来自于外部适应性和内部创新两个方面.为了保证竞争优势的持续性,企业必须永葆创新精神,并有效地防止对手的模仿,必要的时候还应该采取措施,加大对手的经营难度.     

A Note on the Poisson Likelihood Ratio Test Statistic for Kulldorff's Scan Methods

Methods based on scan statistics are widely used in health-related applications to detect clusters of disease. The most common methods are based on the Bernoulli and Poisson models. Kulldorff (1997 Kulldorff , M. ( 1997 ). A spatial scan statistic . Communications in Statistics—Theory and Methods 26 : 1481 – 1496 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) derived the likelihood ratio test statistic for his scan method for both of these models. His scan statistic is widely used with freely available software, SaTScan^? (see Kulldorff, 2005 Kulldorff , M. ( 2005 ). SaTScan: software for the spatial, temporal, and space-time scan statistics , version 5.1 [computer program]. Information Management Services 2005; Available: http://www.satscan.org/. Accessed July 2007 . [Google Scholar]). We provide an alternative derivation of the likelihood ratio test statistic in the Poisson case. Our derivation is simpler and more general in the sense that it applies when the incidences are not aggregated into subregional counts.     

A Method for Measuring Distance From a Training Data Set

A new method is proposed for measuring the distance between a training data set and a single, new observation. The novel distance measure reflects the expected squared prediction error when a quantitative response variable is predicted on the basis of the training data set using the distance weighted k-nearest-neighbor method. The simulation presented here shows that the distance measure correlates well with the true expected squared prediction error in practice. The distance measure can be applied, for example, in assessing the uncertainty of prediction.     

Spatial Cluster Detection for Longitudinal Outcomes Using Administrative Regions

This article proposes a new spatial cluster detection method for longitudinal outcomes that detects neighborhoods and regions with elevated rates of disease while controlling for individual level confounders. The proposed method, CumResPerm, utilizes cumulative geographic residuals through a permutation test to detect potential clusters which are defined as sets of administrative regions, such as a town or group of administrative regions. Previous cluster detection methods are not able to incorporate individual level data including covariate adjustment, while still being able to define potential clusters using informative neighborhood or town boundaries. Often, it is of interest to detect such spatial clusters because individuals residing in a town may have similar environmental exposures or socioeconomic backgrounds due to administrative reasons, such as zoning laws. Therefore, these boundaries can be very informative and more relevant than arbitrary clusters such as the standard circle or square. Application of the CumResPerm method will be illustrated by the Home Allergens and Asthma prospective cohort study analyzing the relationship between area or neighborhood residence and repeated measured outcome, occurrence of wheeze in the last six months, while taking into account mobile locations.     

Infiuence functions for certain parameters in discriminant analysis when a single discriminant function is not adequate

The influence function introduced by Hampel (1968, 1973, 1974) i s a tool that can be used for outlier detection. Campbell (1978) has derived influence function for ~ahalanobis's distance between two populations which can be used for detecting outliers i n discriminant analysis. Radhakrishnan and Kshirsagar (1981) have obtained influence functions for a variety of parametric functions i n multivariate analysis. Radhakrishnan (1983) obtained influence functions for parameters corresponding to "residual" wilks's A and i t s "direction" and "collinearity" factors i n discriminant analysis when a single discriminant function is ade- quate while discriminating among several groups. In this paper influence functions for parameters that correspond to "residual" wilks's A and its "direction" and "coplanarity" factors used to test the goodness of f i t of s (s>l) assigned discriminant func- tions for discriminating among several groups are obtained. These influence functions can be used for outlier detection i n m u l t i -variate data when a single discriminant function is not adequate.     

Two tests for sequential detection of a change-point in a nonlinear model

In this paper, two tests, based on weighted CUSUM of the least squares residuals, are studied to detect in real time a change-point in a nonlinear model. A first test statistic is proposed by extension of a method already used in the literature but for the linear models. It is tested under the null hypothesis, at each sequential observation, that there is no change in the model against a change presence. The asymptotic distribution of the test statistic under the null hypothesis is given and its convergence in probability to infinity is proved when a change occurs. These results will allow to build an asymptotic critical region. Next, in order to decrease the type I error probability, a bootstrapped critical value is proposed and a modified test is studied in a similar way. A generalization of the Hájek–Rényi inequality is established.