Abstract

Abstract
In the last decade multi-agent systems (MAS) have been thoroughly investigated as a suitable paradigm for process control. Despite the difficulties in designing and maintaining a MAS architecture for real production scenarios, several EU research projects have been financed and many companies are looking at the improvement in the production efficiency of such systems. The EU FP7 GRACE project aims at the integration of process and quality control in a multi-agent environment. This paper discusses the integration of quality control stations into the GRACE MAS. The stations themselves will become autonomous agents, capable of self-reconfiguration according to the needs of the production to improve shop floor efficiency while maintaining the same (and possibly higher) quality level for the manufactured products. Details about the quality control agent behaviour, its integration with the physical hardware and communication with the other agents will be given. All the concepts have been tested in an experimental environment where a vision inspection station behaves as one of the agents of the MAS platform, communicating and exchanging data with the other agents and optimizing its operations over time.

Abstract
Aggregation of data values plays an important role on distributed computations, in particular, over peer-to-peer and sensor networks, as it can provide a summary of some global system property and direct the actions of self-adaptive distributed algorithms. Examples include using estimates of the network size to dimension distributed hash tables or estimates of the average system load to direct load balancing. Distributed aggregation using nonidempotent functions, like sums, is not trivial as it is not easy to prevent a given value from being accounted for multiple times; this is especially the case if no centralized algorithms or global identifiers can be used. This paper introduces Extrema Propagation, a probabilistic technique for distributed estimation of the sum of positive real numbers. The technique relies on the exchange of duplicate insensitive messages and can be applied in flood and/or epidemic settings, where multipath routing occurs; it is tolerant of message loss; it is fast, as the number of message exchange steps can be made just slightly above the theoretical minimum; and it is fully distributed, with no single point of failure and the result produced at every node.

Abstract
In this paper, we present an approach to identify top relevant dates in Web snippets with respect to a given implicit temporal query. Our approach is two-fold. First, we propose a generic temporal similarity measure called GTE, which evaluates the temporal similarity between a query and a date. Second, we propose a classification model to accurately relate relevant dates to their corresponding query terms and withdraw irrelevant ones. We suggest two different solutions: a threshold-based classification strategy and a supervised classifier based on a combination of multiple similarity measures. We evaluate both strategies over a set of real-world text queries and compare the performance of our Web snippet approach with a query log approach over the same set of queries. Experiments show that determining the most relevant dates of any given implicit temporal query can be improved with GTE combined with the second order similarity measure InfoSimba, the Dice coefficient and the threshold-based strategy compared to (1) first-order similarity measures and (2) the query log based approach. © 2012 ACM.

Abstract
The study of university-industry (U-I) relations has been the focus of growing interest in the literature. However, to date, a quantitative overview of the existing literature in this field has yet to be accomplished. This study intends to fill this gap through the use of bibliometric techniques. By using three different yet interrelated databases-a database containing the articles published on U-I links, which encompass 534 articles published between 1986 and 2011; a 'roots' database, which encompasses over 20,000 references to the articles published on U-I relations; and a 'influences' database which includes more than 15,000 studies that cited the articles published on U-I relations-we obtained the following results: (1) 'Academic spin offs', 'Scientific and technological policies' and (to a greater extent) 'Knowledge Transfer Channels' are topics in decline; (2) 'Characteristics of universities, firms and scientists', along with 'Regional spillovers', show remarkable growth, and 'Measures and indicators' can be considered an emergent topic; (3) clear tendency towards 'empirical' works, although 'appreciative and empirical' papers constitute the bulk of this literature; (4) the multidisciplinary nature of the intellectual roots of the U-I literature-an interesting blending of neoclassical economics (focused on licensing, knowledge transfer and high-tech entrepreneurship) and heterodox approaches (mainly related to systems of innovation) is observed in terms of intellectual roots; (5) the influence of the U-I literature is largely concentrated on the industrialized world and on the research area of innovation and technology (i.e., some 'scientific endogamy' is observed).

Abstract
This paper provides a general overview of the initial developments in the REIVE project (Smart Grids with Electric Vehicles). The main focus of the project is on smart grid infrastructures for large scale integration of EV and micro-generation units. It is a natural evolution of the InovGrid project promoted by the EDP Distribuição - the Portuguese Distribution Network Operator - and allows the development of seminal concepts and enabling technological developments within the Smart Grid paradigm. This paper presents the management and control architecture developed to allow electric vehicle integration in smart grid operation. Additionally, it presents the major impacts in distribution grids of the simultaneous deployment of electric vehicles, micro-generation and smart grid technologies.