Abstract
Our aim was to determine prototypical patterns of eating behaviour among Portuguese higher education students, and to relate these patterns with BMI. Data from 280 higher education students (63.2% females) aged between 18 and 27 years were analysed. Several eating behaviour dimensions (emotional and external eating, flexible and rigid restraint, binge eating, and eating self-efficacy) were assessed, and eating styles were derived through cluster analysis. BMI for current, desired and maximum self-reported weights and the differences between desired and current BMI and between maximum and current BMI were calculated. Women scored higher in emotional eating and restraint, whereas men showed higher eating self-efficacy. Men had higher current, desired and maximum BMI. Cluster analysis showed three eating styles in both male and female subsamples: "Overeating", "High self-efficacy" and "High restraint". High self-efficacy women showed lower BMI values than the others, and restrictive women had higher lost BMI. High self-efficacy men showed lower desired BMI than overeaters, and lower maximum and lost BMI than highly restrictive ones. Restrictive women and men differ on important eating behaviour features, which may be the cause of differences in the associations with BMI. Eating self-efficacy seems to be a central variable influencing the relationships between other eating behaviour dimensions and BMI.

Abstract
This work addresses the problem of traction control in mobile wheeled robots in the particular case of the RoboCup Middle Size League (MSL). The slip control problem is formulated using simple friction models for ISePorto Team Robots with a differential wheel configuration. Traction was also characterized experimentally in the MSL scenario for relevant game events. This work proposes a hierarchical traction control architecture which relies on local slip detection and control at each wheel, with relevant information being relayed to a higher level responsible for global robot motion control. A dedicated one axis control embedded hardware subsystem allowing complex local control, high frequency current sensing and odometric information procession was developed. This local axis control board is integrated in a distributed system using CAN bus communications. The slipping observer was implemented in the axis control hardware nodes integrated in the ISePorto Robots and was used to control and detect loss of traction. An external vision system was used to perform a qualitative analysis of the slip detection and observer performance results are presented.

Abstract
In recent years, computer vision has been widely used on industrial environments, allowing robots to perform important tasks like quality control, inspection and recognition. Vision systems are typically used to determine the position and orientation of objects in the workstation, enabling them to be transported and assembled by a robotic cell (e.g. industrial manipulator). These systems commonly resort to CCD (Charge-Coupled Device) Cameras fixed and located in a particular work area or attached directly to the robotic arm (eye-in-hand vision system). Although it is a valid approach, the performance of these vision systems is directly influenced by the industrial environment lighting. Taking all these into consideration, a new approach is proposed for eye-on-hand systems, where the use of cameras will be replaced by the 2D Laser Range Finder (LRF). The LRF will be attached to a robotic manipulator, which executes a pre-defined path to produce grayscale images of the workstation. With this technique the environment lighting interference is minimized resulting in a more reliable and robust computer vision system. After the grayscale image is created, this work focuses on the recognition and classification of different objects using inherent features (based on the invariant moments of Hu) with the most well-known machine learning models: k-Nearest Neighbor (kNN), Neural Networks (NNs) and Support Vector Machines (SVMs). In order to achieve a good performance for each classification model, a wrapper method is used to select one good subset of features, as well as an assessment model technique called K-fold cross-validation to adjust the parameters of the classifiers. The performance of the models is also compared, achieving performances of 83.5% for kNN, 95.5% for the NN and 98.9% for the SVM (generalized accuracy). These high performances are related with the feature selection algorithm based on the simulated annealing heuristic, and the model assessment (k-fold cross-validation). It makes possible to identify the most important features in the recognition process, as well as the adjustment of the best parameters for the machine learning models, increasing the classification ratio of the work objects present in the robot's environment.

Abstract

Abstract
This paper reports the development of a B2B platform for the personalization of the publicity transmitted during the program intervals. The platform as a whole must ensure that the intervals are filled with ads compatible with the profile, context and expressed interests of the viewers. The platform acts as an electronic marketplace for advertising agencies (content producer companies) and multimedia content providers (content distribution companies). The companies, once registered at the platform, are represented by agents who negotiate automatically the price of the interval timeslots according to the specified price range and adaptation behaviour. The candidate ads for a given viewer interval are selected through a matching mechanism between ad, viewer and the current context (program being watched) profiles. The overall architecture of the platform consists of a multiagent system organized into three layers consisting of: (i) interface agents that interact with companies; (ii) enterprise agents that model the companies, and (iii) delegate agents that negotiate a specific ad or interval. The negotiation follows a variant of the Iterated Contract Net Interaction Protocol (ICNIP) and is based on the price/s offered by the advertising agencies to occupy the viewer's interval. © Springer International Publishing Switzerland 2013.

Abstract