Abstract
The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.

Abstract
Intelligent Wheelchair (IW) is a new concept aiming to allow higher autonomy to people with lower mobility such as disabled or elderly individuals. Some of the more recent IWs have a multimodal interface, enabling multiple command modes such as joystick, voice commands, head movements, or even facial expressions. In these IW it may be very useful to provide the user with the best way of driving it through an adaptive interface. This paper describes the foundations for creating a simple methodology for extracting user profiles, which can be used to adequately select the best IW command mode for each user. The methodology is based on an interactive wizard composed by a flexible set of simple tasks presented to the user, and a method for extracting and analyzing the user's execution of those tasks. The results achieved showed that it is possible to extract simple user profiles, using the proposed method. Thus, the approach may be further used to extract more complete user profiles, just by extending the set of tasks used, enabling the adaptation of the IW interface to each user's characteristics.

Abstract
Studies on social representations already seem to be relatively common in the field of Social Sciences. However, the particular circumstances being experienced throughout Europe as a result of the international crisis seem to bring with it new possibilities for analysis. It is in this context that falls this present analysis in which are presented the preliminary results of a larger study on the perception and experience of Erasmus students in Portugal within the economic environment in which we live in. Thus, we intend to initially assess the extent the financial crisis has had impact on the motivations and expectations of those students, later to suggest an interpretative model of these results. From a conceptual standpoint, we supported this analysis in international studies and on migratory phenomena studies. In terms of methodology we chose to carry out a questionnaire then subjected to statistical analysis.

Abstract
New production control paradigms, such as holonic and multi-agent systems, allow the development of more flexible and adaptive factories. In these distributed approaches, autonomous entities possess a partial view of the environment, being the decisions taken from the cooperation among them. The introduction of self-organization mechanisms to enhance the system adaptation may cause the system instability when trying to constantly adapt their behaviours, which can drive the system to fall into a chaotic behaviour. This paper proposes a nervousness control mechanism based on the classical Proportional, Integral and Derivative feedback loop controllers to support the system self-organization. The validation of the proposed model is made through the simulation of a flexible manufacturing system.

Abstract
Nowadays location systems are used within a large variety of applications. The application of these systems within indoor environments is already provided by several solutions. However, the need for high accuracy within these environments to pursue such purpose implies the use of specific infrastructures designed towards it. Our project tries to meet the requirements for a simple, low-cost, and scalable location system through different approaches. The main idea of it is to re-construct topological maps of indoor spaces through location estimation, i.e. using off-the-shelf technologies. We try to perform location estimations and then re-create the indoor maps as topological maps as a means of reducing the precision requirements other systems have, and develop a scalable and highly applicable system using sensors featuring mobile devices.

Abstract
Recent research efforts in semantic representations and context modeling are based on the principle of task expansion: that vision problems such as object recognition, scene classification, or retrieval (RCR) cannot be solved in isolation. The extended principle of modality expansion (that RCR problems cannot be solved from visual information alone) is investigated in this work. A semantic image labeling system is augmented with text. Pairs of images and text are mapped to a semantic space, and the text features used to regularize their image counterparts. This is done with a new cross-modal regularizer, which learns the mapping of the image features that maximizes their average similarity to those derived from text. The proposed regularizer is class-sensitive, combining a set of class-specific denoising transformations and nearest neighbor interpolation of text-based class assignments. Regularization of a state-of-the-art approach to image retrieval is then shown to produce substantial gains in retrieval accuracy, outperforming recent image retrieval approaches. © 2012 IEEE.