Abstract
Poker has been gradually gaining the attention of the scientific community, mostly in researchers on Artificial Intelligence. The main reason is concerned with the fact that Poker provides great challenges to the research in the area. Unlike many other games, poker is a stochastic game of imperfect information, which creates a high amount of possibilities to every state of the game. In this work a different line of thought is followed by trying to create an agent capable of reproducing the way a professional Poker human player plays for all stages in a Texas Hold'em Poker game. For this purpose, a high level data model able to comprehend the maximum of information relevant to every state of the game was built, loaded with data from a database containing millions of plays made by a professional poker players, by using Talend Data Integration. To execute Data mining techniques Weka software package was used. The final results show that it is possible to create a virtual poker player that make very similar decisions of a professional poker player.

Abstract
Social networks have an evolving characteristic because of continuous interaction between users. Existing event detection tasks do not consider the analysis under a user-centric perspective. In this paper we propose to detect node centrality events, that is the task of finding events based on the position and roles of the nodes. We present a naive algorithm for detecting such events in network streams. Moreover, we apply our proposal in a case study, showing how node centrality events can be used for tracking user preferences changes.

Abstract
In this paper an accessible Web application that uses icons instead of text to performed YouTube video search, called SAMi, is presented. With this iconic interaction Web application (SAMi), we aimed to develop universal access on the Web, by presenting an alternative way of Web search (without using text); to be a starting point for the definition of an accessible interaction metaphor, based on universal design iconography for digital environments; and ultimately, to contribute to the democratization of access to the Web for all users, regardless of the degree of literacy. The main results obtained with the user test evaluation were: first-rate performance, higher satisfaction and total autonomy in their interaction with SAMi.

Abstract
PhenoSat is a software tool that extracts phenological information from satellite based vegetation index time-series. This chapter presents PhenoSat and tests its main characteristics and functionalities using a multi-year experiment and different vegetation types – vineyard and semi-natural meadows. Three important features were analyzed: (1) the extraction of phenological information for the main growing season, (2) detection and estimation of double growth season parameters, and (3) the advantages of selecting a sub-temporal region of interest. Temporal NDVI satellite data from SPOT VEGETATION and NOAA AVHRR were used. Six fitting methods were applied to filter the satellite noise data: cubic splines, piecewise-logistic, Gaussian models, Fourier series, polynomial curve-fitting and Savitzky-Golay. PhenoSat showed to be capable to extract phenological information consistent with reference measurements, presenting in some cases correlations above 70% (n=10; p=0.012). The start of in-season regrowth in semi-natural meadows was detected with a precision lower than 10-days. The selection of a temporal region of interest, improve the fitting process (R-square increased from 0.596 to 0.997). This improvement detected more accurately the maximum vegetation development and provided more reliable results. PhenoSat showed to be capable to adapt to different vegetation types, and different satellite data sources, proving to be a useful tool to extract metrics related with vegetation dynamics. © Springer International Publishing AG 2016.

Abstract
In this document we outline a Ph. D. research plan and a summary of preliminary results on test automation for distributed and heterogeneous systems.

Abstract
This paper presents MicroFactory - a simplified version of the Robot@Factory competition. This version of the competition was conceived to be low-cost and easily implementable in a small space, be it a classroom or the school robotics club. The factory scenario size was originally 3.5m by 2.5m. The floor is now an A0 printed sheet and the warehouses and machines dimensions are so that they can be 3D printed or made out of LEGO (TM) bricks. Both machines and parts had active elements with leds; now they are passive. Robot@Factory is a Portuguese robotic competition whose first edition was held in 2011 in Lisbon. The scenario of the competition simulates a factory which has an Incoming Warehouse, an Outgoing Warehouse, and 8 processing machines. The robots must collect, transport and position the materials, self-localize and navigate while avoiding collisions with walls, obstacles and other robots. Participants' research contributes to improve AGVs (Automated Guided Vehicle systems) technology. Robot@Factory is now integrated in Festival Nacional de Robotica, a yearly event which attracts lots of public, contributing also to STEM (Science, Technology, Engineering and Mathematics) popularization. MicroFactory's main contribution is different - enhancing learning and the undergraduate experience in robotics. While Robot@Factory is intended for groups with high skills, MicroFactory is supposed to attract younger and less skilled people. So, the proposed challenges were simplified. It was also designed an official robot for the MicroFactory competition. It's a 3D printed robot, based on Arduino and low cost common electronic parts. CAD files for the mechanics (and every bit of the factory scenario), the hardware schematics and most of the software can be made available to the organizers or teachers trying to implement didactic experiences involving robotics. The challenge may then be reduced from developing a robot from scratch to implementing just a small part like programming the navigation algorithm. The presented work is part of a wider Open Source project, aiming to develop project-based collaborative didactic experiences involving robotics to foster STEM education, and low-cost 3D printed educational robots based on generic electronics to support those experiences.