All liaisons are dangerous when all your friends are known to us

Online Social Networks (OSNs) are used by millions of users worldwide. Academically speaking, there is little doubt about the usefulness of demographic studies conducted on OSNs and, hence, methods to label unknown users from small labeled samples are very useful. However, from the general public point of view, this can be a serious privacy concern. Thus, both topics are tackled in this paper: First, a new algorithm to perform user profiling in social networks is described, and its performance is reported and discussed. Secondly, the experiments --conducted on information usually considered sensitive-- reveal that by just publicizing one's contacts privacy is at risk and, thus, measures to minimize privacy leaks due to social graph data mining are outlined.Comment: 10 pages, 5 table

Perception of Fa by non-native listeners in a study abroad context

The present study aims at exploring the under-investigated interface between SA and L2 phonological development by assessing the impact of a 3-month SA programme on the pronunciation of a group of 23 Catalan/Spanish learners of English (NNSs) by means of phonetic measures and perceived FA measures. 6 native speakers (NS) in an exchange programme in Spain provided baseline data for comparison purposes. The participants were recorded performing a reading aloud task before (pre-test) and immediately after (post-test) the SA. Another group of 37 proficient non-native listeners, also bilingual in Catalan/Spanish and trained in English phonetics, assessed the NNS' speech samples for degree of FA. Phonetic measures consisted of pronunciation accuracy scores computed by counting pronunciation errors (phonemic deletions, insertions and substitutions, and stress misplacement). Measures of perceived FA were obtained with two experiments. In experiment 1, the listeners heard a random presentation of the sentences produced by the NSs and by the NNSs at pre-test and post-test and rated them on a 7-point Likert scale for degree of FA (1 = “native” , 7 = “heavy foreign accent”). In experiment 2, they heard paired pre-test/post-test sentences (i.e. produced by the same NNS at pre-test and posttest) and indicated which of the two sounded more native-like. Then, they stated their judgment confidence level on a 7-point scale (1 = “unsure”, 7 = “sure”). Results indicated a slight, non-significant improvement in perceived FA after SA. However, a significant decrease was found in pronunciation accuracy scores after SA. Measures of pronunciation accuracy and FA ratings were also found to be strongly correlated. These findings are discussed in light of the often reported mixed results as regards pronunciation improvement during short-term immersion

Assessing learners' changes in foreign accent during Study Abroad

The present study aims to contribute to the field of Study Abroad (SA) research by exploring the under-investigated interface between SA and the measurement of pronunciation gains in terms of improvement in degree of foreign accent (FA). It is an exploratory study which analyzes changes in FA measures as a result of a short-term, 3-month SA program preceded by a Formal Instruction (FI) period. Data were collected from a group of non-native speakers (NNSs) consisting of 8 undergraduate, upper-intermediate learners of English as a second language (L2) with Catalan and Spanish as first languages (L1s), and from 3 undergraduate L1 English native speakers (NSs), who served as controls. Data from the NNSs were collected at the beginning of their degree (T1), after an 80-hour FI period (T2), and upon their return from SA (T3); data from the NSs were collected only once (T0). Thirteen L1 English listeners rated the speech samples from the NSs and the NNS for degree of FA by means of a rating experiment using a Likert scale. Analyses failed to yield a significant effect of SA on FA ratings and did not reveal a significant difference in FA ratings following SA as compared to FI. These findings are in line with the inconclusive and mixed results which are often reported for L2 pronunciation in short-term SA contexts

Nepotistic relationships in Twitter and their impact on rank prestige algorithms

Micro-blogging services such as Twitter allow anyone to publish anything, anytime. Needless to say, many of the available contents can be diminished as babble or spam. However, given the number and diversity of users, some valuable pieces of information should arise from the stream of tweets. Thus, such services can develop into valuable sources of up-to-date information (the so-called real-time web) provided a way to find the most relevant/trustworthy/authoritative users is available. Hence, this makes a highly pertinent question for which graph centrality methods can provide an answer. In this paper the author offers a comprehensive survey of feasible algorithms for ranking users in social networks, he examines their vulnerabilities to linking malpractice in such networks, and suggests an objective criterion against which to compare such algorithms. Additionally, he suggests a first step towards ―desensitizing‖ prestige algorithms against cheating by spammers and other abusive use

Translating nations in a global era: Valeria Luiselli´s approach to the child migrant crisis

American public opinion toward immigration policies and the legal status of Latinx immigrants have been heavily impacted by economic and political tides throughout the twentieth century. While the Trump era has been regarded by many scholars as an inflection point, this research contends that his electoral victory was merely one of the numerous symptoms lying at the heart of a nativist wave that has engulfed the public sphere in various guises for years. In order to carry out this task, I focus on Valeria Luiselli´s representation of the child migrant crisis during the Obama era in her nonfiction work, Tell Me How It Ends: An Essay in Forty Questions (2017). This article examines the way in which Luiselli´s work opens a discursive space revolving around the metaphor of the translation that adopts different layers of meaning related to connectivity

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use

Les frontières de l’UE et les conflits potentiels entre les nouvelles technologies et les droits de l’homme

Immigrants and asylum seekers have been arriving at the borders of the European Union (EU) continuously for decades. Although there was a noticeable decline during the pandemic, their numbers have already picked up again. Their identification is crucial, also in case of failure in their attempt to cross the border. This is the case of migrants who die at sea and whose bodies cannot be identified. The agencies of the Area of Freedom, Security and Justice together with the member states have addressed the border identification of migrants and asylum seekers by progressively resorting to artificial intelligence (AI) technologies to develop a system that guarantees security at European borders. The European Union Agency for the Operational Management of Large-Scale IT Systems in the Area of Freedom, Security and Justice (EU-LISA) has had its mandate extended to focus on the implementation of EU border and asylum management and migration areas. The purpose of this note is to point out some potential risks in the current management at the border of AI systems in relation to the human rights of migrants and asylum seekers.Los inmigrantes y los solicitantes de asilo han venido llegando a las fronteras de la Unión Europea (UE) de forma ininterrumpida desde hace décadas. Aunque hubo una disminución notable durante la pandemia, su número ya ha vuelto a recuperarse. Su identificación es crucial, también en caso de fracasar en su intento de cruzar la frontera. Este es el caso de los migrantes que mueren en el mar y cuyos cuerpos no pueden ser identificados. Las agencias del Espacio de Libertad, Seguridad y Justicia junto con los Estados miembros han abordado la identificación fronteriza de migrantes y solicitantes de asilo recurriendo progresivamente a las tecnologías de inteligencia artificial (IA) para desarrollar un sistema que garantice la seguridad en las fronteras europeas. La Agencia de la Unión Europea para la gestión operativa de sistemas informáticos a gran escala en el espacio de libertad, seguridad y justicia (EU-LISA) ha visto ampliado su mandato para centrarse en la implementación de la gestión de asilo y fronteras de la UE y áreas de migración. El propósito de esta nota es señalar algunos riesgos potenciales en la gestión actual de los sistemas de IA en relación con los derechos humanos de los migrantes y los solicitantes de asilo.Les immigrés et les demandeurs d’asile arrivent aux frontières de l’Union européenne (UE) sans interruption depuis des décennies. Bien qu’il y ait eu une baisse notable pendant la pandémie, leur nombre a déjà repris. Leur identification est cruciale, même en cas d’échec dans leur tentative de franchir la frontière. C’est le cas des migrants qui meurent en mer et dont les corps ne peuvent être identifiés. Les agences de l’Espace de Liberté, de Sécurité et de Justice ainsi que les États membres ont abordé l’identification aux frontières des migrants et des demandeurs d’asile en recourant progressivement aux technologies de l’intelligence artificielle (IA) pour développer un système garantissant la sécurité aux frontières européennes. L’Agence de l’Union Européenne pour la Gestion Opérationnelle des Systèmes d’Information à grande échelle au sein de l’Espace de Liberté, de Sécurité et de Justice (EU-LISA) a vu son mandat étendu pour se concentrer sur la mise en œuvre des zones de gestion des frontières et de l’asile et de la migration de l’UE. L’objectif de cette note est de souligner certains risques potentiels dans la gestion actuelle des systèmes d’IA en ce qui concerne les droits humains des migrants et des demandeurs d’asile

Assessing learners' changes in foreign accent during Study Abroad

The present study aims to contribute to the field of Study Abroad (SA) research by exploring the under-investigated interface between SA and the measurement of pronunciation gains in terms of improvement in degree of foreign accent (FA). It is an exploratory study which analyzes changes in FA measures as a result of a short-term, 3-month SA program preceded by a Formal Instruction (FI) period. Data were collected from a group of non-native speakers (NNSs) consisting of 8 undergraduate, upper-intermediate learners of English as a second language (L2) with Catalan and Spanish as first languages (L1s), and from 3 undergraduate L1 English native speakers (NSs), who served as controls. Data from the NNSs were collected at the beginning of their degree (T1), after an 80-hour FI period (T2), and upon their return from SA (T3); data from the NSs were collected only once (T0). Thirteen L1 English listeners rated the speech samples from the NSs and the NNS for degree of FA by means of a rating experiment using a Likert scale. Analyses failed to yield a significant effect of SA on FA ratings and did not reveal a significant difference in FA ratings following SA as compared to FI. These findings are in line with the inconclusive and mixed results which are often reported for L2 pronunciation in short-term SA contexts