Abstract
During the last few years, we have been witnessing a significant increase in research about the development and production of hardware and software components with low levels of energy consumption. Today, energy consumption is one of the most critical issues in the area of information technologies and communication. One of the fractions in which this concern is most evident is in the management of database systems, with particular emphasis on those commonly designated as data centers. On these systems daily run a large amount of data querying processes, monitored and controlled by high sophisticated database management systems, which are responsible to establish efficient processing plans to support them. Using the information provided by a querying execution plan, especially the one related to the operators they used to perform database operations, we designed and developed an alternative method to define energy consumption plans for database queries. In this paper we present how such method works on the estimation of the energy consumption of each database operator integrated in the execution plan of a query at compile time. With it, we build up its corresponding energy consumption plan for executing the query, taking into consideration as well the characteristics of the computational platforms used for that.

Abstract
In this paper it is applied a Rough Setapproach that takes into account an incomplete information system to study the steady-state security of an electric power system. The Rough Set Theory has been conceived as a tool to conceptualize, organize and analyze various types of data, in particular, to deal with inexact, uncertainor vague knowledge. The knowledge acquisition process is a complex task, since the experts have difficulty to explain how to solve a specified problem. So, an incomplete set of relevant information may arise. The study presents a systematicapproach to transform examples in a reduced set of rules. These rules can be used successfully to avoid security problems and provides a deeper insight into the influence of parameters on the steady-state system performance. © Springer Science+Business Media Dordrecht 2014.

Abstract
This paper proposes a fault tolerant control (FTC) scheme based on sliding mode control for multi-motor electric vehicles. A design method of a sliding mode tracking controller with control allocation is developed based on the information provide by fault detection and identification (FDI) mechanism. The vehicles states yaw rate and longitudinal velocity are simultaneously controlled to track their references. A particular attention is given to study the effect of non-perfect fault estimation. The control allocation explore the over actuated system in order to redistribute the control effort when a fault occurs. Simulations in various driving scenarios with different faults are carried out with a high-fidelity, CarSim, full-vehicle model. Simulation results show the effectiveness of the proposed FTC approach.

Abstract
The so-called "phase delay tracking" attempts to estimate the effects of the turbulence on the phase of the interferograms in order to numerically cophase the measured complex visibilities and to coherently integrate them. This is implemented by the "coherent fringe analysis" of MIDI instrument1 but has only been used for high SNR data. In this paper, we investigate whether the sensitivity of this technique can be pushed to its theoretical limits and thus applied to fainter sources. In the general framework of the maximum likelihood and exploiting the chromatic behavior of the turbulence effects, we propose a global optimization strategy to compute various estimators of the differential pistons between two data frames. The most efficient estimators appear to be the ones based on the phasors, even though they do not yet reach the theoretical limits.

Abstract
Innovation networks are seen as an important opportunity for organizational performance by facilitating the creation of new knowledge, not just transferring existing knowledge. Collaboration in innovation between manufacturing companies and research centers is a trend that continues to grow in importance linked to business success. Embedded in the literature on business models in the context of networks organizations, this paper propose key pillars and elements required in order to support the establishing of open business model for innovation networks. Subsequently the use of these elements in practice was verified through empirical research evidence in a case study.

Abstract
This research proposes a networked e-consumer profile based on consumers' characteristics and behavior: online shopping experience, Internet and social networks use, search behavior, recommendation behavior and demographics. Survey data from 308 participants who purchased from a leading online retailer and engaged in peer communications through online social networks were used in order to profile the networked e-consumer. The study empirically verifies that the typical networked e-consumer tends to be younger, highly educated which are in the highest occupation levels, e-experienced, skillful, give product and site recommendations to their connections and actively participate in several online social networks. Most of the results and conclusions are consistent with other antecedent research and provide useful orientations to guide e-business managers on actions they can take. Finally, some strategic recommendations and suggestions for further investigation are presented.