Abstract
In the trend towards tolerating hardware unreliability, accuracy is exchanged for cost savings. Running on less reliable machines, functionally correct code becomes risky and one needs to know how risk propagates so as to mitigate it. Risk estimation, however, seems to live outside the average programmer's technical competence and core practice. In this paper we propose that program design by source-to-source transformation be risk-aware in the sense of making probabilistic faults visible and supporting equational reasoning on the probabilistic behaviour of programs caused by faults. a la Bird-Moor algebra of programming. This paper studies, in particular, the propagation of faults across standard program transformation techniques known as tupling and fusion, enabling the fault of the whole to be expressed in terms of the faults of its parts.

Abstract

Abstract
The work described in this paper addresses the development of a serious game to promote the learning of the Portuguese Sign Language supported by an automatic bi-directional translator between Portuguese Sign Language and Portuguese written text. The translator from sign language to text is supported by two devices, namely the Microsoft Kinect and 5DT Sensor Gloves in order to gather data about the motion and shape of the hands. The hands configurations are classified using Support Vector Machines. The classification of the movement and orientation of the hands is achieved through the use of Dynamic Time Warping algorithm. The translation of Portuguese text to Portuguese Sign Language is supported by a 3D avatar which interprets the entered text and performs the corresponding animations. A serious game directed to assist in the difficult task of learning the Portuguese Sign Language is presented.

Abstract
This paper presents a platform for adaptive production management developed in the ARUM1 (Adaptive pRodUct Management, http://arumproject.eu/) project. The design of ARUM platform started with applying a traditional enterprise Service-Oriented Architecture (SOA) paradigm to solving an integration problem for the production ramp-up of highly customized products such as aircrafts, ships, etc. The production of such articles is exceptionally challenging for planning and control, especially in small lot sizes. Often requests for changes at any stage of the production, immature products and processes bring serious additional risks for the producers and customers. To counter such issues requires new strategies, the core elements of most of them include early detection of unexpected situations followed by rapid mitigation actions. Furthermore, human beings cannot cope any longer with processing a massive volume of data that comes with a high velocity from various sources that is a requirement for any modern production shop floor. The traditional IT solutions also fall short when trying to satisfy all those requirements and this motivates the need for ARUM platform to help in effective decision making. © Springer International Publishing Switzerland 2015.

Abstract
Owing to the current trends for higher performance and the ever growing availability of multiprocessors in the embedded computing (EC) domain, there is nowadays a strong push towards the parallelization of modern embedded applications. Several real-time task models have recently been proposed to capture different forms of parallelism. However, they do not deal explicitly with control flow information as they assume that all the threads of a parallel task must execute every time the task is activated. In contrast, in this paper, we present a multi-DAG model where each task is characterized by a set of execution flows, each of which represents a different execution path throughout the task code and is modeled as a DAG of sub-tasks. We propose a two-step solution that computes a single synchronous DAG of servers for a task modeled by a multi-DAG and show that these servers are able to supply every execution flow of that task with the required cpu-budget so that the task can execute entirely, irrespective of the execution flow taken at run-time, while satisfying its precedence constraints. As a result, each task can be modeled by its single DAG of servers, which facilitates in leveraging the existing single-DAG schedulability analyses techniques for analyzing the schedulability of parallel tasks with multiple execution flows.

Abstract
The field of Robotics has become one of the most rapidly growing fields in the research and technological world. The development of flexible robots represents the possibility of them becoming a highly efficient operator in the industrial environment. Intelligent robots present key characteristics that enable the streamlining of automated processes associated to industry. Adding the adaptive component to such robots facilitates the design of solutions for a wide range of problems. Pick and Place operations have attracted considerable interest from the research and industrial community as they present one of the most effective solutions to typical problems such as handling or transportation. Another aspect to consider when developing a robotic solution for pick and place approaches is the methodology for recognition of the objects to be handled. In this paper, it will be presented a methodology that can be applicable to different scenarios in order to both identify the objects of a given scene and reply to the need of handling those objects. Furthermore it will be presented one specific case study that used the proposed methodology, the Amazon Picking Challenge - a challenge aiming to develop solutions for the complete automation of a dispatching warehouse. Our proposed methodology was built using the Robotic Operative System (ROS) framework and is based in three tiers: recognition, movement / actuation and control. ROS allows the decomplexation of typical problems associated to robotics as this framework promotes the development of modular and simple software that together fulfill the state-of-art requests of the industry. Since ROS is becoming an important tool in robotics, using a methodology developed in ROS allows for the development of a standard approach to pick and place operations. Another advantage of our methodology is the ability to have a robot safely and efficiently inserted in an unknown environment. This is possible due to adaptive control tier. Proposed improvements to currently available methods will be also described in this project. Throughout the document, the importance of this project and the development of novel robots will be described taken into consideration the need for robots in the industrial setting.