Improving the convergence of gene expression programming in impedance spectroscopy

Peer Reviewe

Experiencing Poverty in an Online Simulation: Effects on Players’ Beliefs, Attitudes and Behaviors about Poverty

Digital simulations are increasingly used to educate about the causes and effects of poverty, and inspire action to alleviate it. Drawing on research about attributions of poverty, subjective well-being, and relative income, this experimental study assesses the effects of an online poverty simulation (entitled Spent) on participants’ beliefs, attitudes, and actions. Results show that, compared with a control group, Spent players donated marginally more money to a charity serving the poor and expressed higher support for policies benefitting the poor, but were less likely to take immediate political action by signing an online petition to support a higher minimum wage. Spent players also expressed greater subjective well-being than the control group, but this was not associated with increased policy support or donations. Spent players who experienced greater presence (perceived realism of the simulation) had higher levels of empathy, which contributed to attributing poverty to structural causes and support for anti-poverty policies. We draw conclusions for theory about the psychological experience of playing online poverty simulations, and for how they could be designed to stimulate charity and support for anti-poverty policies

Gene expression programming and genetic algorithms in impedance circuit identification

Impedance circuit identification through spectroscopy is often used to characterize sensors. When the circuit topology is known, it has been shown that the component values can be obtained by genetic algorithms. Also, gene expression programming can be used to search for an adequate circuit topology. In this paper, an improved version of the impedance circuit identification based on gene expression programming and hybrid genetic algorithm is presented to both identify the circuit and estimate its parameters. Simulation results are used to validate the proposed algorithm in different situations. Further validation is presented from measurements on a circuit that models a humidity sensor and also from measurements on a viscosity sensor

Using classifiers to predict linear feedback shift registers

Proceeding of: IEEE 35th International Carnahan Conference on Security Technology. October 16-19, 2001, LondonPreviously (J.C. Hernandez et al., 2000), some new ideas that justify the use of artificial intelligence techniques in cryptanalysis are presented. The main objective of that paper was to show that the theoretical next bit prediction problem can be transformed into a classification problem, and this classification problem could be solved with the aid of some AI algorithms. In particular, they showed how a well-known classifier called c4.5 could predict the next bit generated by a linear feedback shift register (LFSR, a widely used model of pseudorandom number generator) very efficiently and, most importantly, without any previous knowledge over the model used. The authors look for other classifiers, apart from c4.5, that could be useful in the prediction of LFSRs. We conclude that the selection of c4.5 by Hernandez et al. was adequate, because it shows the best accuracy of all the classifiers tested. However, we have found other classifiers that produce interesting results, and we suggest that these algorithms must be taken into account in the future when trying to predict more complex LFSR-based models. Finally, we show some other properties that make the c4.5 algorithm the best choice for this particular cryptanalytic problem.Publicad

Valuation and modeling of EQ-5D-5L health states using a hybrid approach

Background: The EQ-5D instrument is the most widely used preference-based health-related quality of life questionnaire in cost-effectiveness analysis of health care technologies. Recently, a version called EQ-5D-5L with 5 levels on each dimension was developed. This manuscript explores the performance of a hybrid approach for the modeling of EQ-5D-5L valuation data. Methods: Two elicitation techniques, the composite time trade-off, and discrete choice experiments, were applied to a sample of the Spanish population (n=1000) using a computer-based questionnaire. The sampling process consisted of 2 stages: stratified sampling of geographic area, followed by systematic sampling in each area. A hybrid regression model combining composite time trade-off and discrete choice data was used to estimate the potential value sets using main effects as starting point. The comparison between the models was performed using the criteria of logical consistency, goodness of fit, and parsimony. Results: Twenty-seven participants from the 1000 were removed following the exclusion criteria. The best-fitted model included 2 significant interaction terms but resulted in marginal improvements in model fit compared to the main effects model. We therefore selected the model results with main effects as a potential value set for this methodological study, based on the parsimony criteria. The results showed that the main effects hybrid model was consistent, with a range of utility values between 1 and -0.224. Conclusion: This paper shows the feasibility of using a hybrid approach to estimate a value set for EQ-5D-5L valuation data.</p

Sistema de informação para a gestão de uma frota

Actualmente, vivemos num mundo complexo em que as organizações são entidades nas quais a Informação e os Sistemas de Informação são imprescindíveis para garantir a sua sobrevivência e para responder às suas necessidades. O desenvolvimento de um Sistema de Informação para a gestão de uma organização tem como papel principal o de apoiar a tomada de decisão, de forma a aumentar o sucesso e a competitividade da organização. Este artigo apresenta a tecnologia associada a um sistema de apoio à decisão que permite efectuar a gestão de uma frota, dentro de uma organização. Para efectuar a gestão de uma frota é necessário analisar e controlar os custos de utilização, manutenção e reparação de viaturas

Provenance does matter: links between winter trophic segregation and the migratory origins of European robins

Amongst migratory species, it is common to find individuals from different populations or geographical origins sharing staging or wintering areas. Given their differing life histories, ecological theory would predict that the different groups of individuals should exhibit some level of niche segregation. This has rarely been investigated because of the difficulty in assigning migrating individuals to breeding areas. Here, we start by documenting a broad geographical gradient of hydrogen isotopes (δ2H) in robin Erithacus rubecula feathers across Europe. We then use δ2H, as well as wing-tip shape, as surrogates for broad migratory origin of birds wintering in Iberia, to investigate the ecological segregation of populations. Wintering robins of different sexes, ages and body sizes are known to segregate between habitats in Iberia. This has been attributed to the despotic exclusion of inferior competitors from the best patches by dominant individuals. We find no segregation between habitats in relation to δ2H in feathers, or to wing-tip shape, which suggests that no major asymmetries in competitive ability exist between migrant robins of different origins. Trophic level (inferred from nitrogen isotopes in blood) correlated both with δ2H in feathers and with wing-tip shape, showing that individuals from different geographic origins display a degree of ecological segregation in shared winter quarters. Isotopic mixing models indicate that wintering birds originating from more northerly populations consume more invertebrates. Our multi-scale study suggests that trophic-niche segregation may result from specializations (arising in the population-specific breeding areas) that are transported by the migrants into the shared wintering grounds