Abstract

Abstract

Abstract
This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR).

Abstract
The ability to adjust itself to users' profile is imperative in modern system, given that many people interact with a lot of information in different ways. The creation of adaptive systems is a complex domain that requires very specific methods and the integration of several intelligent techniques, from an intelligent systems development perspective. Designing an adaptive system requires planning and training of user modelling techniques combined with existing system components. Based on the architecture for user modelling on Intelligent and Adaptive Scheduling Systems, this paper presents an analysis of using the mentioned architecture to characterize user's behaviours and a case study comparing the employment of different user classifiers. Bayesian and Artificial Neural Networks were selected as the elements of the computational study and this paper presents a description on how to prepare them to deal with user information.

Abstract
The restructuring of electricity markets brought many changes to markets operation. To overcome these new challenges, the study of electricity markets operation has been gaining an increasing importance. With the emergence of microgrids and smart grids, new business models able to cope with new opportunities are being developed. New types of players are also emerging, allowing aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers. The virtual power player (VPP) facilitates their participation in the electricity markets and provides a set of new services promoting generation and consumption efficiency, while improving players' benefits. The contribution of this paper is a customized normalization method that supports a clustering methodology for the remuneration and tariffs definition from VPPs. To implement fair and strategic remuneration and tariff methodologies, this model uses a clustering algorithm, applied on normalized load values, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision making process is found, according to players characteristics. The proposed clustering methodology has been tested in a real distribution network with 30 bus, including residential and commercial consumers, photovoltaic generation and storage.

Abstract
Angiogenesis, the formation of blood vessels from pre-existing ones, is a key event in pathology, including cancer progression, but also in homeostasis and regeneration. As the phenotype of endothelial cells (ECs) is continuously regulated by local biomechanical forces, studying endothelial behaviour in altered gravity might contribute to new insights towards angiogenesis modulation. This study aimed at characterizing EC behaviour after hypergravity exposure (more than 1g), with special focus on cytoskeleton architecture and capillary-like structure formation. Herein, human umbilical vein ECs (HUVECs) were cultured under two-dimensional and three-dimensional conditions at 3g and 10g for 4 and 16 h inside the large diameter centrifuge at the European Space Research and Technology Centre (ESTEC) of the European Space Agency. Although no significant tendency regarding cytoskeleton organization was observed for cells exposed to high g's, a slight loss of the perinuclear localization of beta-tubulin was observed for cells exposed to 3g with less pronounced peripheral bodies of actin when compared with 1g control cells. Additionally, hypergravity exposure decreased the assembly of HUVECs into capillary-like structures, with a 10g level significantly reducing their organization capacity. In conclusion, short-term hypergravity seems to affect EC phenotype and their angiogenic potential in a time and g-level-dependent manner.