Abstract
Knowledge management practices are used in collaborative networks promoting innovation in order to share critical knowledge among network members towards improving organizational results. This paper proposes to explore the channels and practices for knowledge sharing in collaborative networks, by means of an exploratory multiple case study carried out in two types of collaborative networks: (i) industrial associations; and (ii) science and technology parks. Empirical evidence has been collected from interviews with managers of the collaborative networks and of organizations participating in the collaborative networks. The contribution of this paper to the knowledge management literature is twofold: (i) it provides a characterization of the channels and technology used for knowledge sharing in collaborative networks based on empirical evidence and (ii) it describes knowledge sharing practices used among organizations to foster new forms of connectivity between groups and individuals.

Abstract
In order to attain the promises of the Cloud Computing paradigm, systems need to be able to transparently adapt to environment changes. Such behavior benefits from the ability to predict those changes in order to handle them seamlessly. In this paper, we present a mechanism to accurately predict the resource usage of distributed key-value datastores. Our mechanism requires offline training but, in contrast with other approaches, it is sufficient to run it only once per hardware configuration and subsequently use it for online prediction of database performance under any circumstance. The mechanism accurately estimates the database resource usage for any request distribution with an average accuracy of 94 %, only by knowing two parameters: (i) cache hit ratio; and (ii) incoming throughput. Both input values can be observed in real time or synthesized for request allocation decisions. This novel approach is sufficiently simple and generic, while simultaneously being suitable for other practical applications.

Abstract
This paper investigates the impact of projection design on the reconstruction of high-dimensional signals from low-dimensional measurements in the presence of side information. In particular, we assume that both the signal of interest and the side information are described by a joint Gaussian mixture model (GMM) distribution. Sharp necessary and sufficient conditions on the number of measurements needed to guarantee that the average reconstruction error approaches zero in the low-noise regime are derived, for both cases when the side information is available at the decoder or at the decoder and encoder. Numerical results are also presented to showcase the impact of projection design on applications with real imaging data in the presence of side information. © 2016 IEEE.

Abstract

Abstract
The original purpose of component-based development was to provide techniques to master complex software, through composition, reuse and parametrisation. However, such systems are rapidly moving towards a level in which software becomes prevalently intertwined with (continuous) physical processes. A possible way to accommodate the latter in component calculi relies on a suitable encoding of continuous behaviour as (yet another) computational effect. This paper introduces such an encoding through a monad which, in the compositional development of hybrid systems, may play a role similar to the one played by 1+, powerset, and distribution monads in the characterisation of partial, nondeterministic and probabilistic components, respectively. This monad and its Kleisli category provide a universe in which the effects of continuity over (different forms of) composition can be suitably studied.

Abstract
In this paper, we present a Simulator Program that identifies the topologies and supports operation staff in decision-electrical power system operation consider load reestablishment procedures and topological possibilities to each event, offering a selection of the best settings. Facing a electrical power transmission system contingency, the Simulator considers the current state and uses special algorithms that detect the grid topology, interprets results and presents to the operators a rank of procedures with their respective degrees of reliability. For these actions the software Simulator make the circuits breakers states analysis and electric keys, load flow solution with the on line data, makes risk prediction and the mathematical analysis of remote sensing values. The software Simulator uses in some of his actions, special algorithms that are based on Paraconsistent Annotated Logic (PAL), which is a non-classical logic whose main property is to accept contradiction in their fundamentals. These algorithms based on PAL offer greater speed of processing and allows the Paraconsistent Simulator of topologies (ParaSimTop) to be implemented in real time.