Abstract
The advances in distribution system automation, smart metering and exploitation of microgrids call for the adoption of more flexible options for power flow calculation. This paper illustrates the structure of a tool implemented to deal with time-dependent and uncertain data, as well as changing network structures during time. The focus is then set on including data uncertainty in probabilistic power flow calculations extended over a time period, in which the changing load and generation patterns are generally represented by correlated random variables. Exemplificative results are shown for a case study application.

Abstract
Biometric systems based on iris are vulnerable to direct attacks consisting on the presentation of a fake iris to the sensor (a printed or a contact lenses iris image, among others). The mobile biometrics scenario stresses the importance of assessing the security issues. The application of countermeasures against this type of attacking scheme is the problem addressed in the present paper. Widening a previous work, several state-of-the-art iris liveness detection methods were implemented and adapted to a less-constrained scenario. The proposed method combines a feature selection step prior to the use of state-of-the-art classifiers to perform the classification based upon the "best features". Five well known existing databases for iris liveness purposes (Biosec, Clarkson, NotreDame and Warsaw) and a recently published database, MobBIOfake, with real and fake images captured in the mobile scenario were tested. The results obtained suggest that the automated segmentation step does not degrade significantly the results.

Abstract
Background: BioTextRetriever is a Web-based search tool for retrieving relevant literature in Molecular Biology and related domains from MEDLINE. The core of BioTextRetriever is the dynamic construction of a classifier capable of selecting relevant papers among the whole MEDLINE bibliographic database. “Relevant” papers, in this context, means papers related to a set of DNA or protein sequences provided as input to the tool by the user. Methods: Since the number of retrieved papers may be very large, BioTextRetriever uses a novel ranking algorithm to retrieve the most relevant papers first. We have developed a new methodology that enables the automation of the assessment process based on a multi-criteria ranking function. This function combines six factors: MeSH terms, paper’s number of citations, author’s h-index, journals impact factor, author number of publications and journal similarity function. Results: The best results highlight the number of citations and the h-index factors. Conclusions: We have developed and a multi-criteria ranking function, that contemplates six factors, and that seems appropriate to retrieve relevant papers out of a huge repository such as MEDLINE. © 2014, Gonçalves et al.; licensee Springer.

Abstract

Abstract
Multi-objective optimization inspired on genetic algorithms are population based search methods. The population elements, chromosomes, evolve using inheritance, mutation, selection and crossover mechanisms. The aim of these algorithms is to obtain a representative non-dominated Pareto front from a given problem. Several approaches to study the convergence and performance of algorithm variants have been proposed, particularly by accessing the final population. In this work, a novel approach by analyzing multi-objective algorithm dynamics during the algorithm execution is considered. The results indicate that Shannon entropy can be used as an algorithm indicator of diversity and convergence.

Abstract
Purpose - The purpose of this paper is to explore the concept of value co-creation in complex value networks with many actors. Electronic health records (EHRs) are innovations that warrant deep study to properly introduce such a complex system. Design/methodology/approach - The paper describes a qualitative study based on Grounded Theory to understand value co-creation from multiple actors' perspectives in a National EHR Service Project: the Portuguese Health Data Platform. Findings - Study results enabled further development of the value co-creation concept in complex environments with multiple actors. More specifically they allowed: operationalizing the value co-creation concept by identifying its factors and outcomes, understanding how value co-creation factors and outcomes are interconnected, and understanding of how value co-creation for each actor depends on his/her own actions and the actions of other actors, in a complex set of interactions and interdependencies. Practical implications - The findings have implications for service managers seeking to understand how actors participating in the network integrate resources and interact to co-create value. The study highlights the need for designing and managing services to co-create value, not only by enabling dyadic interactions between the customer and the service provider, but also by supporting and enabling value co-creation interactions among different actors in the network. Originality/value - This study responds to the need for empirical research on value co-creation in many-to-many contexts and for operationalizing the value co-creation concept.