Abstract
A new methodology for fault detection on wearable medical devices is proposed. The main strategy relies on correctly classifying the captured physiological signals, in order to distinguish whether the actual cause is a wearer health abnormality or a system functional flaw. Data fusion techniques, namely fuzzy logic, are employed to process the captured data, like the electrocardiogram and blood pressure, to increase the trust levels with which diagnostics are made. Concerning the wearer condition, additional information is provided after classifying the set of signals into normal or abnormal (e.g. arrhythmia, chest angina, and stroke). As for the monitoring system, once an abnormal situation is detected in its operation or in the sensors, a set of tests is run to check if actually the wearer shows a degradation of his health condition or if the system is reporting erroneous values.

Abstract
This article identifies and classifies the key obstacles to wind energy development, in order to better understand these barriers and provide guidelines to help public managers to develop and share new energy policies. The methodology used was a case study with documentary research, carried out through an analysis of the Global Wind Report - Annual Market Update, 2009 to 2013, published by Global Wind Energy Council - GWEC. The results showed a significant occurrence of technological and operational obstacles, especially concerning electricity grids. The results lead to the conclusion that the biggest issue for wind energy development is concentrated in technological and operational obstacles, especially concerning the management of transmission networks. In addition, the results indicate the possibility of countries, with common obstacles, to improve their energy policies in partnership, or share their successful expertises.

Abstract
Model-driven engineering (MDE) is a software engineering approach based on model transformations at different abstraction levels. It prescribes the development of software by successively transforming the models from abstract (specifications) to more concrete ones (code). Alloy is an increasingly popular lightweight formal specification language that supports automatic verification. Unfortunately, its widespread industrial adoption is hampered by the lack of an ecosystem of MDE tools, namely code generators. This paper presents a model transformation from Alloy to UML class diagrams annotated with OCL (UML+OCL) and shows how an existing transformation from UML+OCL to Alloy can be improved to handle dynamic issues. The proposed bidirectional transformation enables a smooth integration of Alloy in the current MDE contexts, by allowing UML+OCL specifications to be transformed to Alloy for validation and verification, to correct and possibly refine them inside Alloy, and to translate them back to UML+OCL for sharing with stakeholders or to reuse current model-driven architecture tools to refine them toward code.

Abstract
Three-dimensional virtual worlds (3DVW) have been growing fast in number of users, and are used for the most diverse purposes. In collaboration, 3DVW are used with good results due to features such as immersion, interaction capabilities, use of avatar embodiment, and physical space. In the particular cases of avatar embodiment and physical space, these features support nonverbal communication, but its impact on collaboration is not well known. In this work we present the initial steps for creation of a protocol for case study research, aiming to assert itself as a tool to collect data on how nonverbal communication influences collaboration in 3DVW. We define the propositions and units of analysis, and a pilot case to validate them.

Abstract
The problem of homing a mobile robot to a given reference location under unknown relative and absolute positions is addressed in this paper. This problem is easy to solve when all the positions and kinematic variables are known or are observable, but remains a challenge when only range is measured. Its complexity further increases when variable and unknown drifts are added to the motion, which is typical for marine vehicles. Based on the range measurements, it is possible to drive the robot arbitrarily close to the reference. This paper presents a complete solution and demonstrates the validity of the approach based on the Lyapunov theory. The use of models, which are often affected by uncertainties and/or unmodeled terms, is intended to be minimal and only some constraints are imposed on the speed of the robot. We derive a control law that makes the robot converge asymptotically to the reference and prove its stability theoretically. Nevertheless, as it is well known, practical limitations on the actuation can weaken some properties of convergence, namely when the system dynamics require increasing actuation along the approach trajectory. We will demonstrate that the robot reaches a positively invariant set around the reference whose upper bound is determined. Finally, we conclude our work by presenting simulation and experimental data and by demonstrating the validity and the robustness of the method.

Abstract
In this paper, smart objects embedded production and quality management functions are proposed, to promote accurately support decision-making processes, from the shop floor level up to higher decision-making levels. The proposed functions contribute for different kind of problems solving in production and quality management, such as production planning and control, scheduling, factory supervision, real-time data acquisition and processing, and real-time decision making. The web access at different middleware devices and tools, at different decision levels, along with the use of integrated algorithms and tools, embedded in smart objects, promotes conditions for better decision-making for optimized use of knowledge and resources in production systems. The relevance of the proposed smart objects embedded production and quality management functions has been validated positively in a manufacturing company.