Abstract

Abstract

Abstract
Managing a team of heterogeneous robots in a dynamic environment poses a challenging job. In this paper a model for a multi-purpose, real-time, adaptable, strategical coordination layer is presented. Based on previous work developed for the RoboCup Soccer simulation, small-size, middle-size and legged leagues, a generic coordination model was built. As both centralized and distributed environment are handled by the layer, communication was an important factor to consider only introducing a minor overhead. A multi-level hierarchical approach was followed with hybrid methods used to switch between concepts. The model was tested with two strategy instances, RoboCup Rescue Simulation and RoboCup Soccer. Strategies are designed with the help of a graphical tool. Results achieved by the team in RoboCup Rescue and Soccer Simulation competitions demonstrate the usefulness of this approach. Copyright © 2011-2012 ICST

Abstract
BioStories is the outcome of a four-year research project focused in uniting affective and ubiquitous computing with context aware multimedia environments real-time generation. Its initial premise was based in the possibility of performing real-time automatic emotion assessment trough online biometric channels monitoring and use this information to design on-the-fly dynamic multimedia storylines emotionally adapted, so that end users would unconsciously be determining the story graph. The emotion assessment process was based on biometric channels dynamic fusion such as EEG, GSR, respiration rate and volume, skin temperature and heart rate on top of Russell's circumplex model of affect. BioStories' broad scope also allowed for some spin-off projects namely mouse control through EMG that resulted in a tested technology for alternative/inclusive interfaces. Exhaustive experiments showed 86% of success rate for emotion assessment, IC(95%)(p)approximate to(0.81, 0.90), in a dynamic tridimensional virtual environment with an immersiveness user score of 4.3 out of 5. The success of the proposed approach allows the vision of its appliance in several domains such as virtual entertainment, videogames and cinema as well as direct marketing, digital TV and domotic appliances.

Abstract
The usage of data mining models has the main purpose of discovering new patterns from dataset analysis by extracting knowledge from data and converting it to information. The most challenging part of problem solving is not the generation of high number of instances in dataset, most often hard to understand, but the interpretation of all those instances to extrapolate information about it. Simulation of coastal ecosystems is used to replicate some real conditions related with physical, chemical and biological processes, and produces large datasets from which it could be deduced some information about attributes behaviors. This paper relates the use of Decision Tree models to analyze the growth of bivalve species in an ecosystem simulation. With a set of attributes that represents the water quality in certain modeled regions, the usage of Decision Tree is intended to identify the most significant attribute conditions, which could justify the growth behavior for each analyzed species. This approach aims the creation of new information about how water conditions should be to promote a healthy and fast growth of the analyzed species, being useful to know in which zones the bivalve should be seeded, and which are the conditions that aquaculture producers should afford to benefit the quality of its crops.

Abstract
This paper presents the architecture and algorithms developed for Dom Dinis, a simple compass-guided robot built by the authors. This includes environment exploration, task planning and task execution. Environment exploration, based on repeating a reactive goal search, enables a progressive construction of a grid-based map. Based on the (possibly incomplete) map, the robot is able to plan its tasks. The execution capabilities of the robot include exception handling. Essential to all these capabilities is the knowledge of the robot's position in the world. The position is computed based on tracking traversed distances and followed orientations. Orientation is given by a compass. Dom Dinis doesn't use wheel encoders at all.