Abstract
This paper presents an exploratory study to assess the efficiency level of construction companies worldwide, exploring in particular the effect of location and activity in the efficiency levels. This paper also provides insights concerning the convergence in efficiency across regions. The companies are divided in three regions (Europe, Asia and North America), and in the three main construction activities (Buildings, Heavy Civil and Specialty Trade). We analyze a sample of 118 companies worldwide between 1995 and 2003. Data envelopment analysis is used to estimate efficiency, and the Malmquist index is applied for the evaluation of productivity change. Both methods were complemented by bootstrapping to refine the estimates obtained. A panel data truncated regression with categorical regressors is used to explore the impact of location and activity in the efficiency levels. The results reveal that the efficiency of North American companies is higher than the European and Asian counterparts. Other important conclusion points to a convergence in efficiency levels across regions as in North America productivity remains stable, whereas in Asia and Europe productivity improves.

Abstract
The gravitational search algorithm is proposed to design PID control structures. The controller design is performed considering the objectives of set-point tracking and disturbance rejection, minimizing the integral of the absolute error criterion. A two-degrees-of-freedom control configuration with a feed-forward prefilter inserted outside the PID feedback loop is used to improve system performance for both design criteria. The prefilter used is a Posicast three-step shaper designed simultaneously with a PID controller. Simulation results are presented which show the merit of the proposed technique.

Abstract
There has been a considerable increase in the literature devoted to innovation in the past few decades. This research area is characterized by prolific interdisciplinary connections and no single domain is able to embrace all aspects of science, technology and innovation. By analyzing nearly 60,000 references included in the 1442 articles published between 1974 and 2007 in the area's seed journal, Research Policy (RP), we have uncovered the following patterns: (1) the most important sources of knowledge are associated with core economics (mostly mainstream) and management sources, even though the importance of innovation-related sources has been rising; (2) the degree of autonomy of science, technology and innovation research is still weak, revealing its incipience and lack of a unified theoretical framework; (3) the most influential authors and studies follow heterodox approaches, namely the evolutionary approach (e.g. Richard R. Nelson) and the European approach to innovation (e.g. Keith Pavitt and Chris Freeman), although it is rather surprising that one of the most widely recognized founding fathers of innovation-related studies, Joseph Schumpeter, is absent from the top-10 cited authors list; and (4) the ranking of the most influential studies highlights the relevance of the evolutionary paradigm, with its focus on the capabilities and routines of firms, and the policy-driven nature of topics, evidencing the pervasiveness of the literature on the National System of Innovation.

Abstract
This paper presents an automatic approach for the estimation of Arteriolar-to-Venular Ratio (AVR) in retinal images. The method was assessed using the images of the INSPIRE-AVR database. A mean error of 0.05 was obtained when the method's results were compared with reference AVR values provided with this dataset, thus demonstrating the adequacy of the proposed solution for AVR estimation.

Abstract
AEMOS is a simulator which aims to support the development of agent-based electronic markets capable of dealing with the natural semantic heterogeneity existent in this kind of environment. AEMOS simulates a marketplace which provides ontology matching services, enhanced with the exploitation of emergent social networks, enabling an efficient and transparent communication between agents, even when they use different ontologies. The system recommends possible alignments between the agent's ontologies, and lets them negotiate and decide which alignment should be used to translate the exchanged messages. In this paper we propose a new ontology alignment negotiation process, which promotes the reutilization and combination of already existent alignments, as well as the involvement of the business agents in the alignment composition process. With this new model, we aim to achieve a higher adequacy of the used alignments, as well as a more accurate and trustful evaluation of the alignments. © 2013 DIME UNIVERSITÀ DI GENOVA.

Abstract
Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players' profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paperscissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market. © Springer International Publishing Switzerland 2013.