Abstract
In this work we intend to advance towards a computational model to hold up a Group Decision Support System for VirtualECare, a system aimed at sustaining online healthcare services, where Extended Logic Programs (ELP) will be used for knowledge representation and reasoning. Under this scenario it is possible to evaluate the ELPs making in terms of the Quality-of-Information (QoI) that is assigned to them, along the several stages of the decision making process, which is given as a truth value in the interval 0 ... 1, i.e., it is possible to provide a measure of the value of the QoI that supports the decision making process, an end in itself. It will be also considered the problem of QoI evaluation in a multicriteria decision setting, being the criteria to be fulfilled that of a Clinical Guideline (CG) for Chronic Obstructive Pulmonary Disease.

Abstract
In critical areas such as decision making, the Collaborative Work has an uttermost importance. Being a complex problem, the collective decision taking is currently a popular form of taking decisions. In this work we present the VirtualECare project: an intelligent multi-agent system able to monitor, interact and serve its customers (in need of care services). In developed countries, recent census data report a sudden increase in the elderly community together with a decrease of child birth. This is a new reality that needs to be dealt by the health sector, particularly by the public one. In an early stage, this new situation appears mostly as a financial problem. The costs involved in the health care are considerable. Thus, alternative technological solutions that lead to straightforward solutions should be adopted. Recently, a growing interest in combining the advances in information society - computing, telecommunications and presentation - to create Group Decision Support Systems (GDSS), has been observed. It is our view that the use of the GDSS in the health care area will pursue the achievement of better results in terms of patients Electronically Clinical Profile (ECP). Additionally, we believe that the best way of managing health appointments is through the use of calendars - one application that can manage both the physicians and patients calendars and consequently their day schedule. Within this area, the approaches used in the VirtualECare and iGenda projects are presented. © 2010 IEEE.

Abstract
Healthcare projects that intend to decrease the economical and social costs of the real ageing population phenomenon, through the de-localisation of healthcare services delivery and management to the home, have been arising in the scientific community. The VirtualECare project is one of those, so called, Ambient Assisted Living environments, which we have taken a step forward with the introduction of proactive techniques for better adapting to its users, namely elderly or chronic patients, once it is able to learn with their interaction based in contexts. This learning, however, causes the system need to know with whom it is interacting, especially if we are dealing with multi-user environments. Basic detection techniques based in possible devices that users carries along with them (e.g. RFID tags, mobile phones, ...) arc not good enough, since they can lose/forgot/switch them. To obtain the expected results the technology used has to be more advanced and available in several platforms. One possible and already fairly developed technique is Facial Recognition, and it appears to be the most appropriate one to handle the problem. This document exposes the initial approach of the VirtualECare project to the Facial Recognition area.

Abstract
Memory is one of our most precious goods has it gives us the ability to store, retain and recall information thus giving a meaning to our past and help us to envision our future, dreams and expectations. However, ageing decreases the capacity of remembering and the capacity to store new memories, thus affecting our life quality. These presented problems configure a social and human dilemma. With the presented work we intend to address some of these problems, thru the use of the Personal Memory Assistant (PMA) concept in order to help its user to remember things and occurrences in a proactive manner. We will also address socialization and relaxation events that should be part of the user's life. With the use of a Multi-Agent System to implement the PMA, the objectives can be achieved in a ubiquitous and highly configurable manner. It is presented here the platform concept, scheme and the agent characteristics and their contribution to each and every agent.

Abstract

Abstract
The identification of patterns on large repositories of code can be of paramount importance to guide the design of new hardware accelerators, To acquire the suitability of a certain hardware accelerator and to generate application-specific architectures that maximize hardware reuse. This work intends to research and develop methods to both acquire the presence of a given pattern (map-suitability) and to identify common and highly similar patterns in code repositories (design-suggestions). The approach being proposed is based on a number of identification layers that refine the selections at each stage. We analyze two possible complementary options for a high-level layer. A first option is based on the representation of programs as a sequence of symbols and string matching and clustering algorithms are then used to expose similar patterns. A second option is based on tree matching techniques for identifying the presence of user's input patterns in the programs under inspection. We are evaluating our approach using the MiBench, Media-Bench, UTDSP, and SNU code repositories. The results show the potential of our approach to identify approximate patterns that can be implemented by merging highly similar structures. © 2010 IEEE.