In this paper, an oscillating water column-based wave energy conversion plant is modeled and controlled by means of two complementary control strategies in order to improve the conversion of wave energy into electric power. This wave power generation system consists of a capture chamber, a Wells turbine, and an induction generator. The improvement relays on the implementation of a control scheme that combines two different control methods: a rotational speed control and an airflow control implemented by means of a throttle valve in series with the turbine. The use of rotational speed control provides a fast way to react to the abrupt and short changes in the turbine speed, ensuring that the average power of the generator is adequately adjusted according to the incident wave power level. Besides, a throttle-valve is used to control the flow through the turbine so as to increase the amount of energy produced, particularly at the higher incident wave power levels. These two control strategies complement each other, maximizing and improving the quality of supply by controlling and smoothing the generated power for different scenarios of wave oscillations, variations of wave grouping, and changes in the sea state.

Universities can offer eLearning 2.0 tools and services to learners while obtaining clear benefits from releasing the control over some learning content. This means a shift from the institution centred and monolithic model of traditional virtual learning environments (VLEs) to a more heterogeneous and open model. This article tries to plot an architecture to be put in practice by universities to give learners the control of their learning processes by using eLearning 2.0. We propose an institutionally powered personal learning environment (iPLE) that constitutes our vision of how Web 2.0 tools (blogs, wikis, starting pages), services (del.icio.us, Flickr, YouTube) and people arrangement and data sharing (social networking, learn-streaming) could be applied in an integrated manner to learning processes. First, this article justifies the suitability for a PLE in the context of eLearning 2.0 and European Higher Education Area. Second, an overview of the evolution from VLEs to PLEs is given, and different PLE approaches are reviewed. Third, the concept of an iPLE is presented, and a conceptual architecture for it is detailed. Finally, this article also describes the technological aspects of a prototype of iPLE Network designed for the University of the Basque Country, which will be used as a test-bed for a case study in the Faculty of Medicine.

To meet the demands of a rising population greenhouses must face the challenge of producing more in a more efficient and sustainable way. Innovative mobile robotic solutions with flexible navigation and manipulation strategies can help monitor the field in real-time. Guided by Integrated Pest Management strategies, robots can perform early pest detection and selective treatment tasks autonomously. However, combining the different robotic skills is an error prone work that requires experience in many robotic fields, usually deriving on ad-hoc solutions that are not reusable in other contexts. This work presents Robotframework, a generic ROS-based architecture which can easily integrate different navigation, manipulation, perception, and high-decision modules leading to a faster and simplified development of new robotic applications. The architecture includes generic real-time data collection tools, diagnosis and error handling modules, and user-friendly interfaces. To demonstrate the benefits of combining and easily integrating different robotic skills using the architecture, two flexible manipulation strategies have been developed to enhance the pest detection in its early state and to perform targeted spraying in simulated and field commercial greenhouses. Besides, an additional use-case has been included to demonstrate the applicability of the architecture in other industrial contexts.

The main objective of this paper is to analyse the effect of the affordances of a virtual learning environment and a personal learning environment (PLE) in the configuration of the students' personal networks in a higher education context. The results are discussed in light of the adaptation of the students to the learning network made up by two undergraduate, inter-university and online courses. Besides, we also examine the influence of this effect in the learning process. The findings reflect the effectiveness of a PLE for facilitating student participation and for assisting students in the creation of larger and more balanced personal networks with richer social capital. However, the findings do not provide evidences about a difference in the learning performance between the two environments. From a methodological point of view, this paper serves as an illustration of the analysis of personal networks on digital data collected from technology-enhanced learning environments.

The paradigm of the fourth industrial revolution poses the combined use of technologies that provide companies with adaptability to face uncertain market scenarios. Different institutions have presented their reference architectures to apply principles of the fourth industrial revolution in a standardized way, being the German proposal Industry 4.0 (I4.0) the most widespread. Nowadays most companies are still in the computerization and digitalization phases prior to being able to connect to I4.0. This situation highlights the need for solutions for the integration of physical assets in I4.0. However, most of the work in this area focuses on ad-hoc solutions, or at least technology-dependent ones. This paper presents a multi-layer approach for integrating physical assets in I4.0. The goal is to separate the different concerns related to the integration of physical assets into abstract layers. This approach allows addressing these concerns in a generic way, regardless of the type of asset and/or the technology used, as well as efficient, since it addresses each concern separately. This approach is complemented by a methodology that provides guidelines for integrating physical assets according to the multi-layer approach. The applicability of the multi-layer approach and the integration methodology is put to the test by integrating a robotic arm.

Cloud Computing is revolutionizing smart manufacturing by offering on-demand and scalable computer systems that facilitate plant data analysis and operational efficiency optimization. DevOps is a methodology, widely used for developing Cloud Computing systems, that streamlines software development by improving its integration, delivery, and deployment. Although cloud application designers within a DevOps team are assumed to have development and operational knowledge, this does not fall within the skills of experts that design analytics applications of plant data. The deployment environment is also relevant since, as such applications are often hosted in the Fog, the proliferation of application components may hinder their composition and validation. This work is aimed at embracing the Platform Engineering approach to provide a tailored toolkit that guides the design and development of OpenFog compliant applications for the experts in the Smart Manufacturing domain. The platform uses Model Driven Engineering techniques and a flow-based visual editor to allow application designers to graphically compose applications from components previously delivered by component developers, abstracting them from the underlying technologies. As a result, containerized applications, ready to be deployed and run by a container orchestrator, are obtained. The feasibility of the proposal is proved through an industrial case study.