Abstract
This paper presents a novel prototype device for domestic load energy consumption monitoring. Zigbee-based wireless connectivity is included as a basic feature of the prototype. The proposed device allows individual tracking of major energy consumption loads. Real time energy data is acquired and transmitted through a RF link to a wireless terminal unit, which works as a data logger and as a human-machine interface. Both voltage and current measurements are implemented using Hall Effect principle based transducers, while C code is developed on two 16-bit RISC MCU. The experimental setup is described and tests are conducted in order to assess its performance.

Abstract
Group behaviour characterisation is a topic not so well studied in the video surveillance community due to its difficulty and large variety of topics involved, but mainly because the lack of valid semantic concepts that relate collective activity to social context. In this work, our proposal is three-fold: a new definition of semantic concepts for social group analysis considering environment context, a novel video surveillance dataset that conveys a sociological perspective, and a descriptor that emphasises social interactions cues within a group. Promising results were revealed in order to deal with such complex problem.

Abstract
By understanding the need for a social, collaborative and participative learning process, an analysis to the existent learning and pedagogical models was made in order to identify the existence of a basis for the development of an e-learning course implemented over a social network site. As a complement, a systematic literature review on social media adoption and use was made, particularly focusing the adoption for educational purposes and aiming at achieving the set of variables which might impact the implementation of s-learning activities. The combination of these activities resulted in the presentation of a new learning assessment model designed to be applied over e-learning courses implemented on social media. With this in mind, a description on the referred assessment model is presented, thus considering the need for a comprehensive characterization of the inherent assessment process and inherent activities and technologies. Through the execution of the research and pedagogical activities performed in the scope of the present project it was also possible to acknowledge that learning activities performed over social networks sites are a solution for improving student's willingness and commitment towards studying and learning.

Abstract
The emergence of the so-called "European Paradox" shows that increasing Governmental R&D Investment is far from being a 'panacea' for stagnant growth. Surprisingly, Governmental R&D Employment does not contribute to 'mass-market' employment, despite its important role in reducing Youth-Unemployment. Despite the negative side-effect of Governmental R&D Employment on economic growth, University R&D Employment appears to have a quite important role in reducing Unemployment, especially Youth-Unemployment, while it also does not have a downside in terms of economic growth. Technological Capacity enhancement is the most effective instrument for reducing Youth-Unemployment and is a policy with a quite robust effect regarding sustainable economic development.

Abstract
This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

Abstract
While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.