Empirical likelihood confidence intervals for complex sampling designs

We define an empirical likelihood approach which gives consistent design-based confidence intervals which can be calculated without the need of variance estimates, design effects, resampling, joint inclusion probabilities and linearization, even when the point estimator is not linear. It can be used to construct confidence intervals for a large class of sampling designs and estimators which are solutions of estimating equations. It can be used for means, regressions coefficients, quantiles, totals or counts even when the population size is unknown. It can be used with large sampling fractions and naturally includes calibration constraints. It can be viewed as an extension of the empirical likelihood approach to complex survey data. This approach is computationally simpler than the pseudoempirical likelihood and the bootstrap approaches. The simulation study shows that the confidence interval proposed may give better coverages than the confidence intervals based on linearization, bootstrap and pseudoempirical likelihood. Our simulation study shows that, under complex sampling designs, standard confidence intervals based on normality may have poor coverages, because point estimators may not follow a normal sampling distribution and their variance estimators may be biased.<br/

MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense

Present attack methods can make state-of-the-art classification systems based on deep neural networks misclassify every adversarially modified test example. The design of general defense strategies against a wide range of such attacks still remains a challenging problem. In this paper, we draw inspiration from the fields of cybersecurity and multi-agent systems and propose to leverage the concept of Moving Target Defense (MTD) in designing a meta-defense for 'boosting' the robustness of an ensemble of deep neural networks (DNNs) for visual classification tasks against such adversarial attacks. To classify an input image, a trained network is picked randomly from this set of networks by formulating the interaction between a Defender (who hosts the classification networks) and their (Legitimate and Malicious) users as a Bayesian Stackelberg Game (BSG). We empirically show that this approach, MTDeep, reduces misclassification on perturbed images in various datasets such as MNIST, FashionMNIST, and ImageNet while maintaining high classification accuracy on legitimate test images. We then demonstrate that our framework, being the first meta-defense technique, can be used in conjunction with any existing defense mechanism to provide more resilience against adversarial attacks that can be afforded by these defense mechanisms. Lastly, to quantify the increase in robustness of an ensemble-based classification system when we use MTDeep, we analyze the properties of a set of DNNs and introduce the concept of differential immunity that formalizes the notion of attack transferability.Comment: Accepted to the Conference on Decision and Game Theory for Security (GameSec), 201

Sector primario, sustentabilidad y turismo: el problema de valoración de los recursos naturales y culturales en turismo

Se plantean las dificultades que supone valorar los recursos naturales y culturales en el campo teórico-práctico del turismo, recurriendo a una conexión entre la categoría sector primario, la temática de la sustentabilidad, y la actividad turística, con toda la complejidad que ello implica. Se propone que el valor de tales recursos se subestima si se equipara con el precio y que sería necesario incorporar un valor simbólico y un pago en grado de conciencia

Baryogenesis after Hyperextended Inflation

We study a baryogenesis mechanism operating in the context of hyperextended inflation and making use of a coupling between the scalar field and a standard model global current, such as B or B-L. The method is efficient at temperatures at which these currents are not conserved due to some higher dimensional operator. The particle physics and cosmological phenomenology are discussed. We consider constraints stemming from nucleosynthesis and solar system experiments.Comment: 7 pages, 1 figure, uses RevTe

Continuity, Not Change: The Latino Vote in 2004

This paper describes the Latino vote in the 2004 presidential election. It pays particular attention to conflicting claims regarding the extent to which Latinos voted for President Bush. It also evaluates the overall impact Latinos had on the results of the election. The 2004 election lived down to expectations. It closely followed the pattern set in 2000. That is, President Bush’s victory slightly expanded his electoral base by adding Iowa and New Mexico to the states he carried previously while only losing New Hampshire from the states he won in 2000. Additionally while he lost the popular vote in 2000 by 539,947 votes, in 2004 he won it by 3,311,608, increasing his percentage of the vote from 48% to 51%. President Bush, thus, won in 2004 with a small minority that provides a legitimate basis for claiming a clear victory but not a mandate

El voto latino en 2004

Este artículo examina el modo en que las estructuras electorales y las inclinaciones políticas interactúan con el tamaño y la distribución de la población hispana para determinar el papel que los hispanos desempeñarán en las elecciones presidenciales de 2004. El crecimiento de la población latina ha llevado a afirmar que los hispanos representarán un papel fundamental en las elecciones presidenciales estadounidenses de este año. No obstante, estas afirmaciones resultan engañosas, puesto que se basan exclusivamente en el tamaño de la población, pasando por alto una serie de factores estructurales y de comportamiento que determinan la influencia final del voto latino. Este artículo examina el modo en que factores institucionales tales como el papel del Colegio Electoral y el acercamiento de cada uno de los partidos a esta comunidad afectan a la participación de este colectivo. También analiza el modo en que la distribución de la población influye en el peso electoral latino. Por último examina patrones históricos, preferencias políticas y patrones de identificación con los distintos partidos para explicar por qué la mayoría de los latinos votará al Partido Demócrata en 2004