Abstract
Replicating data under Eventual Consistency (EC) allows any replica to accept updates without remote synchronisation. This ensures performance and scalability in large-scale distributed systems (e.g., clouds). However, published EC approaches are ad-hoc and error-prone. Under a formal Strong Eventual Consistency (SEC) model, we study sufficient conditions for convergence. A data type that satisfies these conditions is called a Conflict-free Replicated Data Type (CRDT). Replicas of any CRDT are guaranteed to converge in a self-stabilising manner, despite any number of failures. This paper formalises two popular approaches (state- and operation-based) and their relevant sufficient conditions. We study a number of useful CRDTs, such as sets with clean semantics, supporting both add and remove operations, and consider in depth the more complex Graph data type. CRDT types can be composed to develop large-scale distributed applications, and have interesting theoretical properties.

Abstract
This paper reviews the concepts and the solution algorithm of the Fuzzy DC OPF problem admitting generation costs and load values modeled by fuzzy numbers and details the integration of this problem in the Monte Carlo simulation model. In this sense, the paper describes an hybrid approach in which generation cost and demand uncertainties are represented by fuzzy numbers and the life cycle of the system components is modeled by probabilistic approaches. On this topic, the paper addresses the sampling procedure, the analysis of sampled states, the convergence testing and the computation of the expected values of the system Power Not Supplied and system risk indices. Finally, the paper includes results based on the IEEE 24 bus/38 branch test system to illustrate the proposed approach. © 2011 IEEE.

Abstract
In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn.

Abstract
In plant development biology, the study of the structure of the plant's root is fundamental for the understanding of the regulation and interrelationships of cell division and cellular differentiation. This is based on the high connection between cell length and progression of cell differentiation and the nuclear state. However, the need to analyse a large amount of images from many replicate roots to obtain reliable measurements motivates the development of automatic tools for root structure analysis. We present a novel automatic approach to detect cell files, the main structure in plant roots, and extract the length of the cells in those files. This approach is based on the detection of local cell file characteristic symmetry using a wavelet based image symmetry measure. The resulting detection enables the automatic extraction of important data on the plant development stage and of characteristics for individual cells. Furthermore, the approach presented reduces in more than 90% the time required for the analysis of each root, improving the work of the biologist and allowing the increase of the amount of data to be analysed for each experimental condition. While our approach is fully automatic a user verification and editing stage is provided so that any existing errors may be corrected. Given five test images it was observed that user did not correct more than 20% of all automatically detected structure, while taking no more than 10% of manual analysis time to do so.

Abstract
Recently, a number of learning algorithms have been adapted for label ranking, including instance-based and tree-based methods. In this paper, we propose an adaptation of association rules for label ranking. The adaptation, which is illustrated in this work with APRIORI Algorithm, essentially consists of using variations of the support and confidence measures based on ranking similarity functions that are suitable for label ranking. We also adapt the method to make a prediction from the possibly conflicting consequents of the rules that apply to an example. Despite having made our adaptation from a very simple variant of association rules for classification, the results clearly show that the method is making valid predictions. Additionally, they show that it competes well with state-of-the-art label ranking algorithms.

Abstract
Fiber structures based on the combination of abrupt tapers and fiber Bragg gratings are studied. Two situations are exploredin one, the taper is fabricated in the fiber region with a fiber Bragg grating; in the other, the taper is first fabricated followed by the fiber Bragg grating. It is shown that the first device presents the properties of a Fabry-Perot cavity and the other of a phase-shifted Bragg grating, where the phase shift is associated to the tapered fiber region. The sensing characteristics of these structures are studied, and it is shown that the temperature sensitivities are similar but with observable different responses to strain.