Open University of Catalonia

About: Open University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Context (language use) & Higher education. The organization has 1943 authors who have published 4646 publications receiving 64200 citations. The organization is also known as: Universitat Oberta de Catalunya & UOC.

Older People and Mobile Communication in Two European Contexts

Abstract: We analyze the relationships seniors have with mobile communications in two different European contexts, Romania and Catalonia. By means of a qualitative approach, we describe the ways older individuals incorporate mobile phones in everyday life communication practices, and the motivations supporting these decisions. To understand motivations for using a given communication device –as the mobile phone– we took into account the channels individual has access to; individual’s personal interest on using available devices in everyday communications; the location of the members of the individual’s personal network; and the pricing system that determines the cost of mediated communication. The empirical analysis is based on two case studies conducted in Romania and in the metropolitan area of Barcelona (Catalonia) in different moments, between 2010 and 2012. Participants were 60 years old or over. Information was gathered by means of semi-structured interviews that were recorded and transcribed, while a common methodological design allows an enriched insight. Besides gender, we take into account heterogeneity of ageing for a more nuanced analysis. This paper constitutes the first step in the exploration of common trends in the relationship seniors have with mobile communication in different European countries.

Symbiotic simulation system: hybrid systems model meets big data analytics

Abstract: Symbiotic simulation is one of Industry 4.0 technologies that enables interaction between a physical system and the simulation model that represents it as its digital twin. Symbiotic simulation is designed to support decision making at the operational levels by making use of real- or near real- time data that is generated by the physical system, which is used as an input to the simulation model. From the modeling perspective, a symbiotic simulation system comprises a hybrid systems model that combines simulation, optimization and machine learning models as well as a data acquisition module and an actuator. The actuator is needed when the symbiotic simulation system is designed to directly control the physical system without human intervention. This paper reviews the components of a symbiotic simulation system from the perspective of hybrid systems modeling and highlights research questions needed to advance symbiotic simulation study.

User Navigational Behavior in e-Learning Virtual Environments

Abstract: In this paper we describe the navigational behavior of the students of a e-learning virtual environment, in order to determine whether such navigational patterns are related to the academic performance achieved by the students or not, and which behaviors can be identified as more successful. As an example, a subset of students taking a degree in Computer Science in a completely virtual online university are selected as the matter of study. Three levels of analysis are described: a session level, where students perform a few actions in a single session logged to the virtual campus; a course level, where all single sessions are joined to form a course navigational pattern; and a life-long learning level, where students enroll in several subjects each academic semester. A simple experiment is outlined for the course level to demonstrate the possibilities of such analysis in a virtual e-learning environment. This experiment shows that the information collected in this level is useful for understanding user behavior and the relationship with his or her academic achievements, and that some intuitive ideas about the relevance of specific user actions or particularities can be also better explained.

Current models underestimate future irrigated areas

Abstract: Predictions of global irrigated areas are widely used to guide strategies that aim to secure environmental welfare and manage climate change. Here we show that these predictions, which range between 240 and 450 million hectares (Mha), underestimate the potential extension of irrigation by ignoring basic parametric and model uncertainties. We found that the probability distribution of global irrigated areas in 2050 spans almost half an order of magnitude (∼300–800 Mha, P2.5,P97.5), with the right tail pushing values to up to ∼1,800 Mha. This uncertainty is mostly irreducible as it is largely caused by either population-related parameters or the assumptions behind the model design. Model end-users and policy makers should acknowledge that irrigated areas are likely to grow much more than previously thought in order to avoid underestimating potential environmental costs.