Techniques for the mechanical characterisation of civil structures

Broadly speaking, structural defects include all those changes affecting a structure so that its behaviour is no longer in keeping with its intended use characteristics or differs from the behaviour it was originally designed for. In recent years, damage recognition and location methods, relying on the measurement of parameters that are indicative of a structure's mechanical behaviour, have benefitted from the introduction of innovative approaches, which make it possible to process and correlate an unprecedented wealth of measurble data. The aim of this work is to illustrate the basic problems associated with the different methods used for structural identification (parametric and non-parametric, linear and non-linear, with known and unknown inputs, etc.) and to report on some interesting applications for civil structural diagnosis.     

Is implementation of continuous improvement possible? An evolutionary model of enablers and inhibitors

The purpose of this article is to present an evolutionary model of the enablers and inhibitors affecting the implementation and sustainability of continuous improvement. With this aim, a qualitative study using the grounded theory was carried out. Interviews were conducted with managers responsible for continuous improvement in first‐tier suppliers in the automotive sector. As a result, two existing lines of research in the continuous improvement literature are synthesized: on one hand, the literature concerning the enablers and barriers associated with continuous improvement sustainability; and on the other, the literature concerning the evolutionary model. © 2011 Wiley Periodicals, Inc.     

Effect of the metal oxide loading on the activity of silica supported MoO3 and V2O5 catalysts in the selective partial oxidation of methane

Precipitated silica catalysts loaded with either MoO₃ (0.2–4.0 wt%) or V₂O₅ (0.2–5.3 wt%) have been studied in the selective partial oxidation of methane to formaldehyde with molecular oxygen at 520 °C. The functionality of the SiO₂ surface towards the formation of HCHO is significantly promoted by V₂O₅, while it is depressed by the MoO₃.     

Classification of vegetable oils by high-resolution <Superscript>13</Superscript>C NMR spectroscopy using chromatographically obtained oil fractions

¹³C NMR spectra of oil fractions obtained chromatographically from 109 vegetable oils were obtained and analyzed to evaluate the potential use of those fractions in the classification of vegetable oils and to compare the results with the NMR analysis of complete oils. The oils included the following: virgin olive oils from different cultivars and regions of Europe and north Africa; “lampante” olive, refined olive, refined olive pomace, hazelnut, rapeseed, high-oleic sunflower, corn, grapeseed, soybean, and sunflower oils; and mixtures of virgin olive oils from different geographical origins. Oils were divided into two sets of samples. The training set (98 samples) was employed to select the variables that resulted in significant discrimination among the different oil classes. By using stepwise discriminant analysis, more than 98% of correct validated assignments were obtained; these results were confirmed when applied to the test set (11 blind samples). Results suggest that the use of oil fractions considerably increases the discriminating power of NMR in the analysis of vegetable oils.     

A multi-agent legal recommender system

Infonorma is a multi-agent system that provides its users with recommendations of legal normative instruments they might be interested in. The Filter agent of Infonorma classifies normative instruments represented as Semantic Web documents into legal branches and performs content-based similarity analysis. This agent, as well as the entire Infonorma system, was modeled under the guidelines of MAAEM, a software development methodology for multi-agent application engineering. This article describes the Infonorma requirements specification, the architectural design solution for those requirements, the detailed design of the Filter agent and the implementation model of Infonorma, according to the guidelines of the MAAEM methodology.     

Estimation of predictive accuracy in survival analysis using R and S-PLUS

When the purpose of a survival regression model is to predict future outcomes, the predictive accuracy of the model needs to be evaluated before practical application. Various measures of predictive accuracy have been proposed for survival data, none of which has been adopted as a standard, and their inclusion in statistical software is disregarded. We developed the surev library for R and S-PLUS, which includes functions for evaluating the predictive accuracy measures proposed by Schemper and Henderson. The library evaluates the predictive accuracy of parametric regression models and of Cox models. The predictive accuracy of the Cox model can be obtained also when time-dependent covariates are included because of non-proportional hazards or when using Bayesian model averaging. The use of the library is illustrated with examples based on a real data set.