Abstract
System resilience is an important challenge that needs to be addressed in the era of extreme scale computing. Exascale supercomputers will be architected using millions of processor cores and memory modules. As process technology scales, the reliability of such systems will be challenged by the inherent unreliability of individual components due to extremely small transistor geometries, variability in silicon manufacturing processes, device aging, etc. Therefore, errors and failures in extreme scale systems will increasingly be the norm rather than the exception. Not all errors detected warrant catastrophic system failure, but there are presently no mechanisms for the programmer to communicate their knowledge of algorithmic fault tolerance to the system. We present a programming model approach for system resilience that allows programmers to explicitly express their fault tolerance knowledge. We propose novel resilience oriented programming model extensions and programming directives, and illustrate their effectiveness. An inference engine leverages this information and combines it with runtime gathered context to increase the dependability of HPC systems. © 2012 IEEE.

Abstract

Abstract
Pectus excavatum is the most common congenital deformity of the anterior thoracic wall. The surgical correction of such deformity, using Nuss procedure, consists in the placement of a personalized convex prosthesis into sub-sternal position to correct the deformity. The aim of this work is the CT-scan substitution by ultrasound imaging for the pre-operative diagnosis and pre-modeling of the prosthesis, in order to avoid patient radiation exposure. To accomplish this, ultrasound images are acquired along an axial plane, followed by a rigid registration method to obtain the spatial transformation between subsequent images. These images are overlapped to reconstruct an axial plane equivalent to a CT-slice. A phantom was used to conduct preliminary experiments and the achieved results were compared with the corresponding CT-data, showing that the proposed methodology can be capable to create a valid approximation of the anterior thoracic wall, which can be used to model/bend the prosthesis.

Abstract
This paper proposes a new approach to reduce the effort of building formal models representative of the structure and behaviour of Graphical User Interfaces (GUI). The main goal is to automatically extract the GUI model with a dynamic reverse engineering process, consisting in an exploration phase, that extracts information by interacting with the GUI, and in a model generation phase that, making use of machine learning techniques, uses the extracted information of the first step to generate a state-machine model of the GUI, including guard conditions to remove ambiguity in transitions. © 2012 IEEE.

Abstract

Abstract
Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.