Abstract
Memory is one's mental ability to store, to retain, and recall information, representing past and future, our dreams and/or expectations. However, as the human been ages, the capacity of remembering decreases as well the ability to pile up new memories, therefore affecting our quality-of-living and lowering our self- esteem. This configures a social and human dilemma. With the present work we intend to address some of these problems, in terms of a Personal Memory Assistant (PMA), in order to help the user to remember things and occurrences, making it in a proactive mode. It will also cater for some form of relaxation on the part of the user.

Abstract
In this work it is addressed the problem of knowledge evaluation in a VirtualECare Group Decision Supporting System (GDSS), in terms of an Multi-valued Extended Logic Programming language, which is aimed at sustaining online healthcare services. Indeed, reasoning with incomplete and uncertain knowledge have to be dealt with, due to the particular nature of the healthcare services, where the awful consequences of bad decisions, or lack of timely ones, demand for a responsible answer.

Abstract
Web growth has brought several problems to users. The large amount of information that exists nowadays in some particular Websites turns the task of finding useful information very difficult. Knowing users' visiting pattern is crucial to owners, so that they may transform or customize the Website. This problem originated the concept known as Adaptive Website: a Website that adapts itself for the purpose of improving the user's experience. This paper describes a proposal for a doctoral thesis. The main goal of this work is to follow a multi-agent approach for Web adaptation. The idea is that all knowledge administration about the Website and its users, and the use of that knowledge to adapt the site to fulfil user's needs, are made by an autonomous intelligent agent society in a negotiation environment. The complexity of the problem and the inherently distributed nature of the Web, which is an open, heterogeneous and decentralized network, are reasons that justify the multi-agent approach. It is expected that this approach enables real-time Web adaptation with a good level of benefit to the users.

Abstract
We propose an unsupervised method for propagating automatically extracted fine-grained topic labels among news items to improve their topic description for subsequent text classification procedure. This method compares vector representations of news items and assigns to each news item the label of its closest neighbour with a different topic label. Results obtained show that high precision can be achieved in propagating the top ranked topic label, and that 2-gram and 3-gram feature representations optimize the precision.

Abstract
Sorting is an important operation in a myriad of applications. It can contribute substantially to the overall execution time of an application. Dedicated sorting architectures can be used to accelerate applications and/or to reduce energy consumption. In this paper, we propose an efficient sorting unit aiming at acceleratin. The sort operation in FPGA-based embedded systems. The proposed sorting unit, named Unbalanced FIFO Merge Sorting Unit, is based on a FIFO merger implementation and is easily scalable to handle different data-set sizes. We show results oy the proposed sorting unit when isolated and when integrated in a software/hardware solution. When using a Xilinx Virtex-5 SX50T FPGA device. The logic resources for a 32 Kword machine is lower than 1%, an. The block RAM usage is about 22%. When compared to a quicksort pure software implementation, our Sorting Unit provides speed-ups from 1.2× to 50× and about 20× when isolated and when integrated in a software/hardware solution, respectively. © 2009 IEEE.

Abstract
Field-Programmable Gate Arrays (FPGAs) are becoming increasingly important in embedded and high-performance computing systems. They allow performance levels close to the ones obtained from Application-Specific Integrated Circuits (ASICs), while still keeping design and implementation flexibility. However to efficiently program FPGAs, one needs the expertise of hardware developers and to master hardware description languages (HDLs) such as VHDL or Verilog. The attempts to furnish a high-level compilation flow (e.g., front C programs) still have open issues before efficient and consistent results can be obtained. Bearing in mind the FPGA resources, we have developed LALP, a novel language to program FPGAs. A compilation framework including mapping capabilities supports the language. The main ideas behind LALP is to provide a higher abstraction level than HDLs, to exploit the intrinsic parallelism of hardware resources, and to permit the programmer to control execution stages whenever the compiler techniques are unable to generate efficient implementations. In this paper we describe LALP, and show how it can be used to achieve high-performance computing solutions.