Abstract
A cost-effective, accurate, and robust leak detection method is essential in gas network management in order to reduce inspection time and to increase reliability in the system. This work presents a model-based leakage detection method; the gas dynamics are described by a linearized system of partial differential equations that is further reduced to a one-dimensional spatial model. By using an electrical analogy, a pipeline can be represented by a two-port network, where mass flow behaves like current and pressure like voltage. Four transfer function quadripole models are then established to describe the gas pipeline dynamics, depending on the variables of interest at the pipeline boundaries. A leak detection method is devised by employing mass flow data at boundaries and pressure data at some point of the pipeline, as well as by assessing the effects of the leakage on the pressure and mass flow along the pipeline. A case study has been built from operational data supplied by REN Gasodutos (the Portuguese gas company) to show the advantages of the proposed models. © Springer International Publishing AG 2017.

Abstract
Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network's switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not significant.

Abstract
Enterprise Wi-Fi networks have been increasingly considering energy efficiency. In this paper, we present the Wi-Green project wherein we are investigating new techniques and innovative solutions that will allow the minimization of the energy consumption in Wi-Fi networks. In Wi-Green we will consider an enterprise network, in which there is equipment from different vendors, with different ages and different consumption profiles.

Abstract
The paper analises the use of recommender systems in academic libraries, examining the use of the " Related books in Aleph OPAC" recommendation system for academic libraries' online catalogues. A quantitative approach and descriptive methodology is used to collect, process and analyse the data from a usage log provided by the University of Dundee. The analysis of 13,654 posts and 6,347 sessions provided the following observations: the recommendation was used in 11% of the sessions, and 43.9% of the recorded document views on those sessions where generated by recommendation. 9.6% of the records of document views, were derived from recommendation. Sessions using recommendations were on average 1 minute 18 seconds shorter than the sessions without recommendations. In sessions with recommendation 4.30 records were viewed on average while in sessions without recommendation the average is 1.88. Using more than one type of recommendation is not common, as 82% of the sessions with recommendation have recorded the use of only one kind of recommendation. The analysis of recommendations by kind provided two results: "Related works include" appears in more sessions (348), while " People who borrowed this work also borrowed" has the highest number of posts (584).

Abstract
A system identification approach is used estimate linear time invariant models from the data of physical activity gathered in the Just Walk intervention conducted by the Designing Health Lab and the Control Systems Laboratory at Arizona State University A class of identification algorithms proposed elsewhere by one of the authors, denoted as MoliZoft, was reformulated and adapted to estimate models from data gathered in this experience. In this paper, the identification algorithms are described and the best models estimated for a particular participant are analysed and used to improve the results in future experiments.

Abstract
This paper addresses the issue of learning time series forecasting models in changing environments by leveraging the predictive power of ensemble methods. Concept drift adaptation is performed in an active manner, by dynamically combining base learners according to their recent performance using a non-linear function. Diversity in the ensembles is encouraged with several strategies that include heterogeneity among learners, sampling techniques and computation of summary statistics as extra predictors. Heterogeneity is used with the goal of better coping with different dynamic regimes of the time series. The driving hypotheses of this work are that (i) heterogeneous ensembles should better fit different dynamic regimes and (ii) dynamic aggregation should allow for fast detection and adaptation to regime changes. We extend some strategies typically used in classification tasks to time series forecasting. The proposed methods are validated using Monte Carlo simulations on 16 real-world univariate time series with numerical outcome as well as an artificial series with clear regime shifts. The results provide strong empirical evidence for our hypotheses. To encourage reproducibility the proposed method is publicly available as a software package.