Abstract
People with autism spectrum disorder (ASD) find it difficult to recognize and respond to emotions conveyed by the face. Most existing methodologies to teach people with ASD to recognize expressions use still images, and do not take into account that facial expressions have movement. We propose a new approach that uses state of the art technology to solve the problem and to improve interactivity. It is based on an avatar-user interaction model with real time response, which builds upon the patient-therapist relationship: it is designed to be used by the therapist and the patient. The core technology behind it is based on a technique we have developed for real time facial synthesis of 3D characters.

Abstract
This paper reflects a discussion at the SARC workshop, held in Venice, October 2008. This workshop addresses robustness and cooperation in holonic multi-agent systems within a context of self-organizing and self-adaptive systems. The paper first presents the basic principles underlying holonic systems. The holonic system reveals itself as a law of the artificial': in a demanding and dynamic environment, all the larger systems will be holonic. Next, it addresses robustness in holonic systems, including its relationship to self-organization and self-adaptation. These self-* systems indeed are capable of delivering superior robustness. Third, it addresses cooperation in holons and holonic systems, including its relationship with the autonomy of the individual holons. Cooperation imposes constraints on a holon such that its chances of survival and success increase.

Abstract
Although cryptographic software implementation is often performed by expert programmers, the range of performance and security driven options, as well as more mundane software engineering issues, still make it a challenge. The use of domain specific language and compiler techniques to assist in description and optimisation of cryptographic software is an interesting research challenge. In this paper we investigate two aspects of such techniques, focusing on Elliptic Curve Cryptography (ECC) in particular. Our constructive results show that a suitable language allows description of ECC based software in a manner close to the original mathematics; the corresponding compiler allows automatic production of an executable whose performance is competitive with that of a hand-optimised implementation. In contrast, we study the worrying potential for na < ve compiler driven optimisation to render cryptographic software insecure. Both aspects of our work are set within the context of CACE, an ongoing EU funded project on this general topic.

Abstract
This work address data stream mining front dynamic environments where the distribution underlying the observations may change over time. In these contexts, learning algorithms must be equipped with change detection mechanisms. Several methods have been proposed able to detect and react to concept drift;. When a drift is signaled, most of the approaches use a forgetting mechanism, by releasing the current; model, and start, learning a, new decision model, Nevertheless, it; is not rare for the, concepts front history to reappear, for example seasonal changes. In this work we present; method that memorizes learnt; decision models whenever a concept drift is signaled. The system uses meta-learning techniques that characterize the domain of applicability of previous learnt models. The meta-learner can detect, re-occurrence of contexts and take pro-active actions by activating previous learnt models. The main benefit of this approach is that the proposed meta-learner is capable of selecting similar historical concepts, if there is one, without the knowledge of true classes of examples.

Abstract
Recognizing the benefit that one can get by exploiting the Micro-Grid (MG) concept, as an active part of the Low Voltage (LV) network comprising several micro-generation (mu G) sources, controllable loads and storage devices, is a key issue towards the MG concept deployment. Furthermore, the MG concept is extended into Multi-Micro Grid (MMG) concept, identifying the benefits that can be obtained at Medium Voltage (MV) level. The main idea behind this research is to show what one gains and what one looses by setting up the MG concept. Therefore, the benefits reported, are evaluated through a cost-benefit approach by modeling the problem as a multi-attribute problem using several Decision-Aid (DA) techniques to capture different Decision Maker (DM) preference structures.

Abstract
This document reports the development of a technical and economical study related to the use of a renewable energy source - biomass for electricity and heat production. It is a hybrid and autonomous system with solar PV panels and environment friendly process aiming the reduction of energy demand, costs and emissions. This energy model is a new sustainable standard about efficiency consumption energy (electrical and thermal demands) of a small hotel building, with the biomass gasification cogeneration technology. This system is one relevant contribute to certify, the building agree to the new national legislation of building thermal behaviour.