Abstract
In recent years there has been a boom of different natural interaction paradigms, such as touch, tangible or gesture-based interfaces, that make better use of human's innate skills rather than imposing new learning processes. However, no work has been reported that systematically evaluates how these interfaces influence users' performance with regard to their level of digital literacy or even age. Furthermore, it is also important to understand the interaction paradigms' impact when performing basic operations, such as data selection, insertion and manipulation, and which interface could be the most efficient for each task. This paper reports the first step of an exploratory evaluation about the relationship between different interaction paradigms and specific target-audiences: dealing with a selection task. We conducted an experiment with 60 subjects to evaluate how different interfaces may influence the performance of specific groups of users. Four input modalities are evaluated in a selection task and results for these different user groups are reported in terms of performance, efficacy (error rate) and user preference. For each group of users, we determined there was a statistically significant difference between the mean time taken to complete the task in each interface. Also, the one input modality every user was accustomed with (the computer mouse) was the one that showed the most discrepancy regarding performance between the groups. We believe that this study raises new issues for future research.

Abstract
Model finders are becoming useful in many software engineering problems. Kodkod [19] is one of the most popular, due to its support for relational logic (a combination of first order logic with relational algebra operators and transitive closure), allowing a simpler specification of constraints, and support for partial instances, allowing the specification of a priori (exact, but potentially partial) knowledge about a problem's solution. However, in some software engineering problems, such as model repair or bidirectional model transformation, knowledge about the solution is not exact, but instead there is a known target that the solution should approximate. In this paper we extend Kodkod's partial instances to allow the specification of such targets, and show how its model finding procedure can be adapted to support them (using both PMax-SAT solvers or SAT solvers with cardinality constraints). Two case studies are also presented, including a careful performance evaluation to assess the effectiveness of the proposed extension. © 2014 Springer-Verlag.

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Abstract
Renewable energy sources (RES) used in small-scale distributed generation systems are a promising alternative for additional energy supply toward smarter and more sustainable cities. However, their proper integration as new infrastructures of the smart city (SMCT) requires understanding the SMCT architecture and promoting changes to the existing regulation, business models, and power grid topology and operation, constituting a new challenging energy supply paradigm. This chapter addresses the use of renewable energy systems on small scale, oriented to distributed generation (DG) for households or districts, integrated in an SMCT. In this context, the main renewable energies and companion technologies are reviewed, and their profitability investigated to highlight their current economic feasibility. A simplified architecture for SMCT development is presented, consisting of three interconnected layers, the intelligence layer, the communication layer, and the infrastructure layer. The integration and impact of distributed renewable energy generation and storage technologies in this architecture is analyzed. Special attention is paid to the grid topology for their technical and efficient integration, and to the business models for facilitating their economic integration and feasibility. © Springer International Publishing Switzerland 2014.

Abstract
Renewable energy is essential for global sustainability. Wind power gave a great contribution to this energy paradigm. The paper describes a maintenance management system for inshore and offshore wind farms, as well as a method to schedule maintenance using genetic algorithms. Under this subject there exists a sub-problem that concerns with the determination of the cheapest path between two points. The paper compares the performance of three methods: genetic algorithms, Dijkstra's algorithm and ant optimization algorithm to the determination of the cheapest path between different wind parks for maintenance.

Abstract