Non-zero torsion and late cosmology

In this work, we study some thermodynamical aspects associated with torsion in a flat FLRW spacetime cosmic evolution. By implementing two Ansatze for the torsion term, we find that the model admits a phantom regime or a quintessence behavior. This scheme differs from the $\Lambda$CDM model at the thermodynamical level. The resulting cosmic expansion is not adiabatic, the fulfillment of the second law of thermodynamics requires a positive torsion term, and the temperature of the cosmic fluid is always positive. The entropy of the torsion phantom scenario is negative, but introducing chemical potential solves this issue. For a Dirac-Milne type Universe, the torsion leads to a growing behavior for the temperature of the fluid but has no incidence on the rate of expansion.Comment: 20 pages, 1 figure. Accepted version in EPJ

Technologies may help thinking

The objective of teachers’ personal and professional development is an excellent reason to reflect upon the innovation issues in education and a rare opportunity to implement the use of portfolios in the teaching practices. The most recent developments of digital technologies allow experiencing new organisational and knowledge building that state the diversity and multiplicity of purposes, both alone and as a group. From the reflection on these two aspects comes up the present proposal for the analysis and evaluation of the technologies which may easily be accessed by the educational community and may be used in the process of electronic portfolios building. In what teachers are concerned the use of portfolios can become a powerful means helping the change of the educational practices (Cardoso, Peixoto, Serrano and Moreira, 1996) if it is adopted as a metacognitive and reflexive strategy about teaching about them (Galvão, 2005). However there is a lack of information about what portfolios are, which technologies can be used, how they are prepared and how to take advantage of them. All these questions point out to the need of a specific training in this field. Accordingly, this chapter especially aims at helping teachers in that process, providing an analysis and evaluation technologies grid based on their pedagogical potentialities for the building of digital portfolios

Managing personal learning environments: the voice of the students

The main purpose of this paper is to contribute to a better understanding of the kind of educational work to be done with higher education students (undergraduate) in order to encourage them to create and use personal learning environments (PLEs) as a strategy for learning (Attwell, 2007). Based on our current classroom work with students of the 2nd year of a degree in Education and mainly using the functionalities of the Ning system (Copyright © 2010 Ning, Inc.), as well as other tools available on the Internet, we tried to implement a strategy based not only on the presentation of content by the teacher, but also on the recognition of the importance of student’s leadership in the organisation and management of their own learning. Therefore, in addition to face-to-face lectures, we tried to extend the discussion outside the classroom walls using the different services offered by Ning, proposing to integrate the work done by students in their individual evaluation (50% of the final classification). At the end of the semester we observed evidence of a general difficulty felt by the students, particularly in terms of self-regulation and personal organisation. So we decided to try to understand the problem observed in depth. For the purpose of understanding the nature and the extent of these difficulties, we used a methodology focused on analysis of a questionnaire applied to the students about their perception of the difficulties in managing the learning process and about the strategies used for dealing with those difficulties. Although the students acknowledge that the development of the individual online portfolio in a PLE requires that, for the most part, largely they themselves have to get organised and manage of their own learning (Barrett, 2000; Attwell, 2007), one can see that they do not feel prepared for this, experiencing difficulties in personal organisation, time management and regular participation in the proposed activities. In strategic terms, they value the appraisals and/or suggestions given by the teachers, but do not adopt an attitude of reflection or interaction and sharing with others, as catered for by the platform and its functionalities

Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Deep Learning has recently become hugely popular in machine learning, providing significant improvements in classification accuracy in the presence of highly-structured and large databases. Researchers have also considered privacy implications of deep learning. Models are typically trained in a centralized manner with all the data being processed by the same training algorithm. If the data is a collection of users' private data, including habits, personal pictures, geographical positions, interests, and more, the centralized server will have access to sensitive information that could potentially be mishandled. To tackle this problem, collaborative deep learning models have recently been proposed where parties locally train their deep learning structures and only share a subset of the parameters in the attempt to keep their respective training sets private. Parameters can also be obfuscated via differential privacy (DP) to make information extraction even more challenging, as proposed by Shokri and Shmatikov at CCS'15. Unfortunately, we show that any privacy-preserving collaborative deep learning is susceptible to a powerful attack that we devise in this paper. In particular, we show that a distributed, federated, or decentralized deep learning approach is fundamentally broken and does not protect the training sets of honest participants. The attack we developed exploits the real-time nature of the learning process that allows the adversary to train a Generative Adversarial Network (GAN) that generates prototypical samples of the targeted training set that was meant to be private (the samples generated by the GAN are intended to come from the same distribution as the training data). Interestingly, we show that record-level DP applied to the shared parameters of the model, as suggested in previous work, is ineffective (i.e., record-level DP is not designed to address our attack).Comment: ACM CCS'17, 16 pages, 18 figure

PROMESA INCUMPLIDA

Fernando Cruz trae la historia de un jóven padre de familia llamado Raúl Borges de Tunkás, Yucatán. Lo más probable es que Raúl emigre a Estados Unidos dejando atrás a su esposa y a su hijo. Se irá con la promesa de volver pronto, la misma promesa que no cumplió su padre.Dr. Lenin Martell de la Universidad Autónoma del Estado de México y el Dr. Thorne Anderson de la Universidad del Norte de Texas

Usos e representações dos espaços “públicos” na cidade virtual: os novos espaços de sociabilidade e cultura

O aparecimento e o desenvolvimento dos shopping centers, na década de 1970, revolucionou os hábitos e os itinerários da população urbana. De modo geral, a maioria dos centros comerciais provoca uma rutura com o tecido urbano em que se encontra inserido. O interior garantindo, através da vigilância eletrónica, segurança aos seus utentes, está carregado de estímulos para fixar consumidores, sem que estes sintam necessidade do exterior ou de outras atividades. A “cidade de fantasia” ou “cidade da ilusão” é tematicocêntrica, patrocinada por grandes companhias ou multinacionais e agressivamente publicitada. Todos os aspetos negativos da cidade tendem a ser eliminados como a sujidade, a toxicodependência, o trânsito e a pobreza. Estes espaços tornaram-se locais de encontro social, criando mesmo uma programação de animação e lazer, por forma, a que as pessoas encontrem aí mais motivos para os frequentar. Assim, tendo em conta a pesquisa etnográfica desenvolvida entre 2007 e 2011, propomos a partir de eventos organizados no Arrábida Shopping, na Área Metropolitana do Porto (Portugal), proceder à identificação dos objetivos, destinatários e motivações inerentes à organização dos referidos eventos, tendo em conta as representações dos seus organizadoresPeer Reviewe

DeepPermNet: Visual Permutation Learning

We present a principled approach to uncover the structure of visual data by solving a novel deep learning task coined visual permutation learning. The goal of this task is to find the permutation that recovers the structure of data from shuffled versions of it. In the case of natural images, this task boils down to recovering the original image from patches shuffled by an unknown permutation matrix. Unfortunately, permutation matrices are discrete, thereby posing difficulties for gradient-based methods. To this end, we resort to a continuous approximation of these matrices using doubly-stochastic matrices which we generate from standard CNN predictions using Sinkhorn iterations. Unrolling these iterations in a Sinkhorn network layer, we propose DeepPermNet, an end-to-end CNN model for this task. The utility of DeepPermNet is demonstrated on two challenging computer vision problems, namely, (i) relative attributes learning and (ii) self-supervised representation learning. Our results show state-of-the-art performance on the Public Figures and OSR benchmarks for (i) and on the classification and segmentation tasks on the PASCAL VOC dataset for (ii).Comment: Accepted in IEEE International Conference on Computer Vision and Pattern Recognition CVPR 201