Abstract
This paper presents an architecture that supports Quality of Service (QoS) in an Arrowhead-compliant System of Systems (SoS). The Arrowhead Framework supports local cloud functionalities for automation applications, provided by means of a Service Oriented Architecture (SOA), by offering a number of services that ease application development. On such applications the QoS guarantees are required for service fruition, and are themselves requested as services from the framework. To fulfil this objective we start by describing the Arrowhead architecture and the components needed to dynamically in run-time negotiate a system configuration that guarantees the QoS requirements between application services. © 2016 IEEE.

Abstract
Meta-heuristics have been applied for a long time to the Travelling Salesman Problem (TSP) but information is still lacking in the determination of the parameters with the best performance. This paper examines the impact of the Simulated Annealing (SA) and Discrete Artificial Bee Colony (DABC) parameters in the TSP. One special consideration of this paper is how the Neighborhood Structure (NS) interact with the other parameters and impacts the performance of the meta-heuristics. NS performance has been the topic of much research, with NS proposed for the best-known problems, which seem to imply that the NS influences the performance of meta-heuristics, more that other parameters. Moreover, a comparative analysis of distinct meta-heuristics is carried out to demonstrate a non-proportional increase in the performance of the NS.

Abstract

Abstract
Human capital is identified as one of the main determinants of economic growth and plays an important role in the technological progress of countries. Nevertheless, existing studies have to some extent neglected the importance of human capital in the growth process via the interaction it can have with a country's industrial specialization. Additionally, the emphasis is mainly placed on supply-side determinants, while demand-side factors are neglected, particularly the relevance of the processes of structural change. Thus, using a growth model which integrates variables from both the supply side and demand side, we assess the direct and indirect effects of human capital on economic growth, including in the latter the interaction of human capital with the industrial specialization of countries. Based on dynamic panel data estimations, we found that human capital and the countries' productive specialization dynamics are crucial factors for economic growth. Moreover, the interaction between human capital and structural change in high knowledge-intensive industries impacts significantly on economic growth. However, the sign of this effect depends on the type of country and the period of analysis. Specifically, over a longer time span (1960-2011) and for more highly developed (OECD) countries, the impact of the interaction between human capital and structural change is positive. When we also include transition and Mediterranean countries over a shorter time period (1990-2011), we find that human capital significantly and positively impacts on the countries' economic growth but the effect of human capital via specialization in high-tech and knowledge-intensive activities is negative. The latter result indicates that the lack of industrial structures able to properly integrate highly educated individuals into the productive system leads countries to experience disappointing economic returns.

Abstract
In this paper, the optimal operation of a neighborhood of smart households in terms of minimizing the total energy procurement cost is analyzed. Each household may comprise several assets such as electric vehicles, controllable appliances, energy storage and distributed generation. Bi-directional power flow is considered both at household and neighborhood level. Apart from the distributed generation unit, technological options such as vehicle-to-home and vehicle-to-grid are available to provide energy to cover self-consumption needs and to inject excessive energy back to the grid, respectively. The energy transactions are priced based on the net-metering principles considering a dynamic pricing tariff scheme. Furthermore, in order to prevent power peaks that could be harmful for the transformer, a limit is imposed to the total power that may be drawn by the households. Finally, in order to resolve potential competitive behavior, especially during relatively low price periods, a simple strategy in order to promote the fair usage of distribution transformer capacity is proposed.

Abstract
Two-dimensional irregular strip packing problems are cutting and packing problems where small pieces have to be cut from a larger object, involving a non-trivial handling of geometry. Increasingly sophisticated and complex heuristic approaches have been developed to address these problems but, despite the apparently good quality of the solutions, there is no guarantee of optimality. Therefore, mixed-integer linear programming (MIP) models started to be developed. However, these models are heavily limited by the complexity of the geometry handling algorithms needed for the piece non-overlapping constraints. This led to pieces simplifications to specialize the developed mathematical models. In this paper, to overcome these limitations, two robust MIP models are proposed. In the first model (DTM) the non-overlapping constraints are stated based on direct trigonometry, while in the second model (NFP - CM) pieces are first decomposed into convex parts and then the non-overlapping constraints are written based on nofit polygons of the convex parts. Both approaches are robust in terms of the type of geometries they can address, considering any kind of non-convex polygon with or without holes. They are also simpler to implement than previous models. This simplicity allowed to consider, for the first time, a variant of the models that deals with piece rotations. Computational experiments with benchmark instances show that NFP CM outperforms both DTM and the best exact model published in the literature. New real-world based instances with more complex geometries are proposed and used to verify the robustness of the new models.