Abstract
Forecasting the electricity consumption is one of the most challenging tasks for energy domain stakeholders. Having reliable electricity consumption forecasts can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study regarding the forecast of electricity consumption using a methodology based on Hybrid neural Fuzzy Inference System (HyFIS). The proposed approach considers two distinct strategies, namely one strategy using only the electricity consumption as the input of the method, and the second strategy uses a combination of the electricity consumption and the environmental temperature as the input. A case study considering the forecasting of the consumption of an office building using the proposed methodologies is also presented. Results show that the second strategy is able to achieve better results, hence concluding that HyFIS is an appropriate approach to incorporate different sources of information. In this way, the environmental temperature can help the HyFIS method to achieve a more reliable forecast of the electricity consumption. © 2016 IEEE.

Abstract

Abstract
Social media is strongly present in people's everyday life and Twitter is one example that stands out. The data within these types of services can be analyzed in order to discover useful knowledge. One interesting approach is to use data mining techniques to perceive hidden behaviours and patterns. The primary focus of this paper is the identification of patterns of retweets and to understand how information spreads over time in Twitter. The aim of this work lies in the adaptation of the GetMove tool, that is capable of extracting spatio-temporal pattern trajectories, and TweeProfiles, that identifies tweet profiles regarding several dimensions: spatial, temporal, social and content. We hope that the more flexible clustering strategy from TweeProfiles will enhance the results extracted by GetMove. We study the application of said mechanism to one case study and developed a visualization tool to interpret the results.

Abstract
OPTICON currently supports a Joint Research Activity (JRA) dedicated to providing easy to use image reconstruction algorithms for optical/IR interferometric data. This JRA aims to provide state-of-the-art image reconstruction methods with a common interface and comprehensive documentation to the community. These tools will provide the capability to compare the results of using different settings and algorithms in a consistent and unified way. The JRA is also providing tutorials and sample datasets to introduce the principles of image reconstruction and illustrate how to use the software products. We describe the design of the imaging tools, in particular the interface between the graphical user interface and the image reconstruction algorithms, and summarise the current status of their implementation.

Abstract
The compilation of high-level languages, such as software programming languages, to FPGAs is of paramount importance for the mainstream adoption of FPGAs. An efficient compilation process will improve designer productivity and will make the use of FPGA technology viable for software programmers. When targeting the hardware resources provided by FPGAs, a compilation process usually requires a stage known as High-Level Synthesis (HLS) which is responsible for generating application specific hardware architectures from the input source code or from an intermediate representation of the input application. This chapter briefly describes HLS and its main processing stages. The chapter provides the indispensable knowledge for readers who want to follow the remaining chapters of this book. © Springer International Publishing Switzerland 2016.

Abstract
Core diameter mismatch structures are proposed and experimentally investigated for curvature and vibration sensing. Two configurations are suggested, one approach uses a structure formed by splicing an uncoated short section of multimode fiber between two standard single-mode fibers (SMFs) single-mode-multimode-single-mode (SMS), combined to a fiber optical mirror at its end, and the other approach uses a structure made by splicing a section of SMF between two multimode fibers (SMSMS). In the curvature analysis, the proposed SMS sensor generates the destructive interference patterns when it is bent, varying only the attenuation of the optical signal without wavelength shifts. The SMSMS vibration sensor proved to be suitable to monitor very low frequencies such as 0.1 Hz. The configuration of the proposed sensors presents several interesting features, such as easy fabrication, low cost, high efficiency, and high sensitivity. These advantages make such sensors very useful in a wide range of applications, for instance, structural health monitoring.