Abstract
Due to the large amount of pages in Websites it is important to collect knowledge about users' previous visits in order to provide patterns that allow the customization of the Website. In previous work we proposed a multi-agent approach using agents with two different algorithms (associative rules and collaborative filtering) and showed the results of the offline tests. Both algorithms are incremental and work with binary data. In this paper we present the results of experiments held online. Results show that this multi-agent approach combining different algorithms is capable of improving user's satisfaction.

Abstract
The combination of the potentialities of the interactive technologies, like exergames and the emerging motion capture devices with the ability of 3D virtual worlds for socialisation and context, can produce a platform to promote the physical activity of its users, which leverages its potential. The OnlineGym is an exploratory project based on an online 3D virtual worlds platform that allows users to interact with the system through the use of a motion capture device. This paper discusses the chosen technological approaches and the preliminary results of the experiments performed with users.

Abstract
Serious games combine a ludic component with instructive and formative goals. They aim to educate and train through play. This paper explores the use of a development framework for dynamic virtual environments to develop serious games. The framework (APEX) was originally developed to prototype ubiquitous computing environments. Here it is used to develop a first person serious game: the Asthma Game. This game aims to teach children with asthma how to act to prevent attacks by drawing attention to asthma triggers in the home, and by providing information about how to avoid them. Besides the description of the game, results about the viability and utility of the approach are also discussed.

Abstract
Wind power is expected to deliver a significant part of power generation in future smart grid. However, many economic challenges have arisen from the intermittent nature of wind power. In this paper, a multi-stage stochastic model is proposed for self-scheduling problem of Wind Power Producers (WPPs) in competitive electricity markets. The proposed model includes three trading levels namely; forward, day-ahead, and balancing sessions. The problem uncertainties, such as wind power, market prices and quantity of activated reserve by ISO are considered by the Monte Carlo method. Moreover, Conditional Value-at-Risk (CVaR) is employed in the model as an appropriate risk measuring technique. The proposed model yields the optimal behavior of WPPs to participate in day-ahead energy and ancillary services markets (i.e. spinning reserve and regulation). Simulation results indicate that simultaneous participation of the WPPs in the mentioned markets not only augments their profit but also can significantly decrease the associated risks.

Abstract
We show a one-to-one correspondence between circle diffeomorphism sequences that are C1+ n-periodic points of renormalization and smooth Markov sequences. © Springer Science+Business Media New York 2014.

Abstract
This paper presents a study based on the application of cascade ANN prediction models to an earthwork construction database. Results show not only a good adjustment to the data, but also the influence of each earthwork construction process on the work rate of the global production line. Furthermore, the obtained results emphasize the importance of optimal resource allocation and management throughout earthwork construction phases. Following this framework, the study concludes with a demonstration of how the developed models can be integrated into a more complex system in order to pursue that purpose.