Abstract
In this paper, a new multiband antenna consisting of a coplanar patch antenna over an active artificial magnetic conductor (AMC) ground plane is demonstrated. The AMC ground plane, which has been proven to be very effective in the design of low profile antennas, consists of 4x4 square shaped unit cells. By connecting RF switches between adjacent unit cells, a group of four unit cells can be aggregated to a larger size unit cell. In this proposed antenna, the coplanar patch is placed 2mm above the AMC ground plane. It is observed that it is possible to use the patch to excite the AMC ground plane to become another resonant element. Moreover, operation in two more resonant frequencies can be achieved by reconfiguring the unit size of the AMC ground plane. In this way, one coplanar antenna can operate at four different bands with a simple configuration while keeping a low profile. In this work, it is shown that using the actively tuned AMC ground plane, one coplanar patch antenna can operate at 5.8GHz, 5.2GHz, 4.5GHz and 2.4GHz with a good operation bandwidth (S11<-10dB), which includes the entire required bands for WLAN 802.11a/b/g applications. The experimental and simulated results for impedance and radiation performance characterization are presented. All of the design and optimization work have been conducted using the Ansoft HFSS, which is a 3D full-wave electromagnetic field simulation software.

Abstract
With the increase of Endoscopic Capsule (EC) exams, the amount of video data to be analyzed by automated image processing algorithms grows exponentially and standard desktop computers start to present limitations to complete that procedure in an acceptable "clinical time". This has motivated us to assess the potential of Grid computing paradigm to process and analyze EC data, using existing Grid infrastructures. We used our Automated Topografic Segmentation (ATS) algorithm as a case study to run experiments on the Ibergrid Grid infrastructure. As a result, we were able to port the existing ATS algorithm used in routine to run on the Grid seamlessly. A friendly portal environment was adopted, allowing for clinical end-users to harness from existing production Grids in a practical way. The processing time could be reduced in some cases but, when considering job processing overheads, the desktop version is preferable for small scale processing. These results show that Grid computing is a promising technology to process massive amounts of EC data, but current infrastructures present a high variability in jobs processing times, especially when compared with dedicated clusters.

Abstract
Machine Learning (ML) and Knowledge Discovery (KD) are research areas with several different applications but that share a common objective of acquiring more and new information from data. This paper presents an application of several ML techniques in the identification of the opponent team and also on the classification of robotic soccer formations in the context of RoboCup international robotic soccer competition. RoboCup international project includes several distinct leagues were teams composed by different types of real or simulated robots play soccer games following a set of pre-established rules. The simulated 2D league uses simulated robots encouraging research on artificial intelligence methodologies like high-level coordination and machine learning techniques. The experimental tests performed, using four distinct datasets, enabled us to conclude that the Support Vector Machines (SVM) technique has higher accuracy than the k-Nearest Neighbor, Neural Networks and Kernel Naïve Bayes in terms of adaptation to a new kind of data. Also, the experimental results enable to conclude that using the Principal Component Analysis SVM achieves worse results than using simpler methods that have as primary assumption the distance between samples, like k-NN. © 2010 IEEE.

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 introduction of interaction technology in museum settings requires special care in different aspects including the relations with the different participants (public, artists, and curators), and the ability of the technology to provide rewarding experiences over extended periods of time for a demanding audience. This paper describes a hardware and software multi-touch table deployed in a contemporary art exhibition with many visitors. The design requirements are discussed and presented along with the development process. The paper also focuses on the different interaction and navigation mechanisms available and how they are used by the visitors and participants. © 2010 ACM.