Abstract
Open development has emerged as a method for creating versatile and complex products through free collaboration of individuals. This free collaboration gathers globally distributed teams. Similarly, it is common today to view businesses and other human organisations as ecosystems, where several participating companies and organisations cooperate and compete together. As an example, Free/Libre Open Source Software ( FLOSS) development is one area where community driven development provides a plausible platform for both development of products and establishing a software ecosystem where a set of businesses contribute their own innovations. Equally, open and informal learning environments and open innovation platforms are also gaining ground. While such initiatives are not limited to any specific area, they typically offer a technological, legal, social, and economic framework for development, relying always on people as open development would not exist without the active participation of them. This paper explores the participation of master students in FLOSS projects, while merging two different settings of learning: formal and open/informal education.

Abstract
This paper presents a Photovoltaic (PV) power conversion model and a forecasting approach which uses spatial dependency of variables along with their temporal information. The power produced by a PV plant is forecasted by a PV conversion model using the predictions of three weather variables, namely, irradiance on the tilted plane, ambient temperature, and wind speed. The predictions are accomplished using a spatio-temporal algorithm that exploits the sparsity of correlations between time series data of different meteorological stations in the same region. The performances of the forecasting algorithm as well as the PV conversion model are investigated using real data recorded at various locations in Italy. The comparisons with various benchmark methods show the effectiveness of the proposed approaches over short-term forecasts.

Abstract
The wide spread of food outlets has become an environmental and sanitation infrastructure problem, due to Fats, Oils and Grease (FOG). A grease box is used at the industrials facilities to collect the FOG, in a specific time window, while its quality is good for recycling (e.g., biodiesel) and it is economically valuable. After this period, it will be disposed at a cost. For the proper management of the grease boxes, it is necessary to know the quantity of FOG inside the boxes, which is a major problem, as the boxes are sealed and permanently filled with water. The lack of homogeneity of the FOG renders it not detectable by current probes for level detection in liquids. In this article, the design, development and testing of a set of probes for FOG level measurement, based on the principles used in sensors for the detection of liquids inside containers, is described. The most suitable probe, based on the capacitance principle, together with the necessary hardware and software modules for data acquisition and transmission, was developed and tested. After the development phase, the probe was integrated on a metropolitan system for FOG collection and grease box management in partnership with a grease box management company.

Abstract

Abstract
In the last decade, companies have become tend virtualized thanks to the use of outsourcing, the workforce has become more distributed, workplaces are increasingly distributed and outsourced and increasingly digital employees, with the philosophy of work anytime and anywhere. This development has, and has had a very big impact on mobile platforms and infrastructure, on the one hand, the adoption of the BYOD concept and the use of mobile devices and on the other hand, through the use of cloud computing will have profound implications in the way the technologies are and will be used as well as on the interaction between individuals and these technologies. By applying for a questionnaire and subsequent analysis showed that organizations have a lack of understanding, almost complete, the implications and consequences of using mobile devices and the cloud in organizations. A result of the Focus Group performed we propose the 4CM model.

Abstract
When designing clinical trials for testing novel cardiovascular therapies, it is highly relevant to understand what a given technology can provide in terms of information on the physiologic status of the heart and vessels. Ultrasound imaging has traditionally been the modality of choice to study the cardiovascular system as it has an excellent temporal resolution; it operates in real-time; it is very widespread and - not unimportant - it is cheap. Although this modality is mostly known clinically as a two-dimensional technology, it has recently matured into a true three-dimensional imaging technique. In this review paper, an overview is given of the available ultrasound technology for cardiac chamber quantification in terms of volume and function and evidence is given why these parameters are of value when testing the effect of new cardiovascular therapies.