Evaluating the probability and the impact of a failure in GMPLS based networks

In this paper, we define a new scheme to develop and evaluate protection strategies for building reliable GMPLS networks. This is based on what we have called the network protection degree (NPD). The NPD consists of an a priori evaluation, the failure sensibility degree (FSD), which provides the failure probability, and an a posteriori evaluation, the failure impact degree (FID), which determines the impact on the network in case of failure, in terms of packet loss and recovery time. Having mathematical formulated these components, experimental results demonstrate the benefits of the utilization of the NPD, when used to enhance some current QoS routing algorithms in order to offer a certain degree of protection

Distribution and statistics of African mesoscale convective weather systems based on the ISCCP Meteosat imagery

This paper provides for the first time an objective short-term (8 yr) climatology of African convective weather systems based on satellite imagery. Eight years of infrared International Satellite Cloud Climatology Project-European Space Agency's Meteorological Satellite (ISCCP-Meteosat) satellite imagery has been analyzed using objective feature identification, tracking, and statistical techniques for the July, August, and September periods and the region of Africa and the adjacent Atlantic ocean. This allows various diagnostics to be computed and used to study the distribution of mesoscale and synoptic-scale convective weather systems from mesoscale cloud clusters and squall lines to tropical cyclones. An 8-yr seasonal climatology (1983-90) and the seasonal cycle of this convective activity are presented and discussed. Also discussed is the dependence of organized convection for this region, on the orography, convective, and potential instability and vertical wind shear using European Centre for Medium-Range Weather Forecasts reanalysis data.

Calculating the exclusion probability and paternity index for X-chromosomal loci in the presence of substructure

There has been recent interest in the use of X-chromosomal loci for forensic and relatedness testing casework, with many authors developing new X-linked short tandem repeat (STR) loci suitable for forensic use. Here we present formulae for two key quantities in paternity testing, the average probability of exclusion and the paternity index, which are suitable for Xchromosomal loci in the presence of population substructure.

Assessment and statistics of Brazilian hydroelectric power plants: Dam areas versus installed and firm power

The Brazilian relief, predominantly composed by small mountains and plateaus, contributed to formation of rivers with high amount of falls. With exception to North-eastern Brazil, the climate of this country are rainy, which contributes to maintain water flows high. These elements are essential to a high hydroelectric potential, contributing to the choice of hydroelectric power plants as the main technology of electricity generation in Brazil. Though this is a renewable source, whose utilized resource is free, dams must to be established which generates a high environmental and social impact. The objective of this study is to evaluate the impact caused by these dams through the use of environmental indexes. These indexes are ratio formed by installed power with dam area of a hydro power plant, and ratio formed by firm power with this dam area. In this study, the greatest media values were found in South, Southeast, and Northeast regions respectively, and the smallest media values were found in North and Mid-West regions, respectively. The greatest encountered media indexes were also found in dams established in the 1950s. In the last six decades, the smallest indexes were registered by darns established in the 1980s. These indexes could be utilized as important instruments for environmental impact assessments, and could enable a dam to be established that depletes an ecosystem as less as possible.

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Concordance Probability and Discriminatory Power in Proportional Hazards Regression

The concordance probability is used to evaluate the discriminatory power and the predictive accuracy of nonlinear statistical models. We derive an analytic expression for the concordance probability in the Cox proportional hazards model. The proposed estimator is a function of the regression parameters and the covariate distribution only and does not use the observed event and censoring times. For this reason it is asymptotically unbiased, unlike Harrell's c-index based on informative pairs. The asymptotic distribution of the concordance probability estimate is derived using U-statistic theory and the methodology is applied to a predictive model in lung cancer.