Abstract

Abstract
The population ageing requires new approaches to optimize the available resources. In particular, it is urgent to evolve for an effective care integration, which requires toconsider aspects of people's daily lives that impact on their health conditions. Therefore, the information interoperability has an increasing importance, not only the interoperability of health related information, but also social context related information. In this paper, we propose a framework for the creation of applications for information recording, based on a generic and flexible information model, for the provision of integrated care.

Abstract

Abstract

Abstract
Pavement cracks involve important information to measure road quality. Crack classification is a challenging problem given the diversity of possible cracks, therefore, it is needed to retrieve good features in order to facilitate the learning of predictive models with as few samples as possible. In this paper, we propose a graph-based set of features to efficiently describe cracks. These features proved to have high degree of expressiveness and robustness when used for crack classification. We show that the proposed features succeed in the assessment of 525 images with different kinds of cracks. We proved the robustness of the approach applying different levels of noise to the images and evaluating the classification accuracy.

Abstract
This work presents a methodology to manage Electric Vehicles (EVs) charging in quasi-real-time, considering the participation of EV aggregators in electricity markets and the technical restrictions of the electricity grid components, controlled by the Distribution System Operator. Two methodologies are presented in this paper to manage EV charging, one to be used by the EV aggregators and the other by the Distribution System Operator (DSO). The methodology developed for the aggregator has as main objective the minimization of the deviation between the energy bought in the market and the energy consumed by EVs. The methodology developed for the DSO allows it to manage the grid and solve operational problems that may appear by controlling EVs charging. A method to generate a synthetic EV data set is used in this work, providing information about EV movement, including the periods when EVs are parked and their energy requirements. This data set is used afterwards to assess the performance of the algorithms developed to manage the EV charging in quasi-real-time.