Abstract
Big data is a term that has risen to prominence describing data that exceeds the processing capacity of conventional database systems. Big data is a disruptive force that will affect organizations across industries, sectors, and economies. Hidden in the immense volume, variety, and velocity of data that is produced today is new information, facts, relationships, indicators, and pointers that either could not be practically discovered in the past, or simply did not exist before. This new information, effectively captured, managed, and analyzed, has the power to enhance profoundly the effectiveness of government. This chapter looks to the main challenges and issues that will have to be addressed to capture the full potential of big data. Additionally, the authors present a conceptual framework for big data analysis structured in there layers: (a) data capture and preprocessing, (b) data processing and interaction, and (c) auxiliary tools. Each has a different role to play in capturing, processing, accessing, and analyzing big data.

Abstract

Abstract
The aggregation and estimation of values over networks is fundamental for distributed applications, such as wireless sensor networks. Estimating the average, minimal and maximal values has already been extensively studied in the literature. In this paper, we focus on estimating empirical distributions of values in a network with anonymous agents. In particular, we compare two different estimation strategies in terms of their convergence speed, accuracy and communication costs. The first strategy is deterministic and based on the average consensus protocol, while the second strategy is probabilistic and based on the max consensus protocol.

Abstract
We use Adler, Tresser and Worfolk decomposition of Anosov automorphisms to give an explicit construction of the stable and unstable C1+ self-renormalizable sequences.

Abstract
Higher education institutions (HEI) and students are highly dependent of information systems, implemented as web applications. Students must be able to access this applications, thought accessible web interfaces, in order to perform their academic activities. This paper presents an overview of a typical set of web applications used by students and the main concerns regarding accessibility compliance. The analysis was conducted using the systems at the University of Trás-os-Montes e Alto Douro. © 2013 Springer-Verlag Berlin Heidelberg.

Abstract
As formal verification tools gain popularity, the problem arises of making them more accessible to engineers. A correct understanding of the logics used to express the properties of a system's behaviour is needed in order to guarantee that properties correctly encode the intent of the verification process. Writing appropriate properties, in a logic suitable for verification, is a skilful process. Errors in this step of the process can create serious problems since a false sense of safety is gained from the analysis. However, when compared to the effort put into developing and applying modelling languages, little attention has been devoted to the process of writing properties that accurately capture verification requirements. In this paper we illustrate how a collection of property patterns can help in simplifying the process of generating logical formulae from informally expressed requirements.