Abstract
The ordering of events is a fundamental problem of distributed computing and has been extensively studied over several decades. From all the available orderings, total ordering is of particular interest as it provides a powerful abstraction for building reliable distributed applications. Unfortunately, deterministic total order algorithms scale poorly and are therefore unfit for modern large-scale applications. The main contribution of this paper is EPTO, a total order algorithm with probabilistic agreement that scales both in the number of processes and events. EPTO provides deterministic safety and probabilistic liveness: integrity, total order and validity are always preserved, while agreement is achieved with arbitrarily high probability. We show that EPTO is well-suited for large-scale dynamic distributed systems: it does not require a global clock nor synchronized processes, and it is highly robust even when the network suffers from large delays and significant churn and message loss.

Abstract
This project arose from the absence in the market of a modular smartphone controlled robot capable of encouraging high school students to program and apply the physics and math's knowledge learned into it. Therefore this project's intention was to study the best way to develop a do-it-yourself (DIY) cost effective robot using only components off the shelf (COTS) and benefit from the omnipresence of smartphones. With the objective of making this robot attractive to anyone with low programming skills, it was important to make it configurable in an easy to understand language and a simple user interface, like the ones provided by Scratch and the MIT AppInventor2. The functional, physical and non-functional requirements for this robot and the free software developed are presented and validated attesting that this project was successfully completed.

Abstract
The development of new technologies, information systems, decision support systems and clinical parameters prediction algorithms using machine learning and data mining, opens a new outlook in many areas of health. In this context, the concept of Quality of Life (QOL) has relevance in health and the possibility of integrate this measure in developing systems Decision Support Clinic (SADC). Through individual expectation of physical well-being, psychological, mental, emotional and spiritual patient, clinical variables and quality of life assessment, we intend to make a study of data to establish correlations with clinical data and pharmaceutical data, socio-economic factors, among others, for obtaining knowledge in terms of behavioral patterns of chronically ill, reaching a number of reliable data and easily accessible, capable of enhancing the decision-making process on the part of specialist medical teams, seeking to improve treatments and consequently the quality of life related to health chronically ill. This paper studied and compared related studies that develop systems for decision support and prediction in the clinical area, with emphasis on studies in the area of quality of life.

Abstract
The deployment of Smart Grid technologies opens new opportunities to develop new forecasting and optimization techniques. The growth of solar power penetration in distribution grids imposes the use of solar power forecasts as inputs in advanced grid management functions. This paper proposes a new forecasting algorithm for 6 h ahead based on the vector autoregression framework, which combines distributed time series information collected by the Smart Grid infrastructure. Probabilistic forecasts are generated for the residential solar photovoltaic (PV) and secondary substation levels. The test case consists of 44 micro-generation units and 10 secondary substations from the Smart Grid pilot in Evora, Portugal. The benchmark model is the well-known autoregressive forecasting method (univariate approach). The average improvement in terms of root mean square error (point forecast evaluation) and continuous ranking probability score (probabilistic forecast evaluation) for the first 3 lead-times was between 8% and 12%, and between 1.4% and 5.9%, respectively. (C) 2015 Published by Elsevier Ltd.

Abstract
In the last decade, companies tend to become virtualized. This virtualization is due in large part to developments in the use of mobile platforms and the impact on their infrastructure. The concept of BYOD (Bring Your Own Device) adoption and use of cloud computing are having profound implications for how the technologies are being used, as well as the interaction between individuals and these technologies. In this context, we conducted a study based on a questionnaire about the impact of the use of mobile devices and the cloud in organizations, taking into consideration their use in performing professional and personal tasks. With the questionnaire and its subsequent analysis it was found that organizations have a lack of understanding about almost all of the implications and consequences of the use of mobile devices and the cloud.

Abstract
The current operator displays of Distributed Control Systems (DCS) are designed for 2D environments. This limits the full awareness situation of the industrial process, since it is distributed across multiple operator displays and requires the operator to navigate among them. This inspired the idea of creating a single operator display. Through an accurate and systematic literature review and by following the guidelines of design science methodology, it was possible to achieve a set of indicators and artefacts that corresponded to the defined goals. By developing a 2.5D/3D DCS interface application, the authors aimed at creating a way of allowing a full view of the entire manufacturing process, thus increasing the amount and the quality of information that is given to the operator and preventing unnecessary operation navigation between displays.