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Learning Analytics (LA) is currently the most effective way of achieving better information and in-depth insights of the learning processes. Specifications like Experience API (xAPI) have been defined as part of LA initiatives to add interoperability among LA-aware applications. Tools that validate the conformance of data to these specifications are key components to assure the interoperability among...
In this paper, we present a big data software architecture that uses an ontology, based on the Experience API specification, to semantically represent the data streams generated by the learners when they undertake the learning activities of a course, e.g., in a course. These data are stored in a RDF database to provide a high performance access so learning analytics services can process the large...
Capturing and storing learners' data is the first step to implement a learning analytics architecture. The Experience API (xAPI) specification is a de facto standard that describes (i) a REST-based API to store and retrieve the learners' activity data, and (ii) an RDF-based data model where the restrictions among data are specified in natural language. In this paper, we present an ontology that formally...
In this paper an approach for taking advantage of the information available in the social network tools of Learning Management Systems is presented. Specifically, our objective is to determine domain experts from their participation in the social networks. Our approach first integrates the different sources of information through an ontology based on the \textit{Dublin Core Metadata}, and then applies...
In this paper we present an approach for improving a specific class of semantic annotation, that relates a term of the document with a (sub)tree of the ontology, instead of linking a term with a single concept of the ontology. An important part of this class of annotation is filtering the relevant (sub)nodes and relations, because the returned graph should only contain relevant information, that is,...
Nowadays a greater number of domains require an improvement in the flexibility of its e-learning systems to so facilitate the adaptation of their course to their user needs. Some adaptive learning systems have been developed in recent years to cover part of these needs, and provide the ability to redirect the student learning flow based on the knowledge base (mainly rules) defined by the teacher....
Learning objects have arisen in response to the need of high-quality and reusable instructional materials. The repositories that hold learning objects allow educators to create and share their instructional contents in an organized infrastructure and where information should be easily searchable. Therefore, a key point of these repositories is the way learning objects are categorized. In this paper,...
At present no specific methodologies have been developed for the design of the anchoring systems of offshore moored platforms, individual and in farm configuration, for obtaining renewable energy. This paper presents a R&D project whose objective is to cover this lack of knowledge. The scope of the project involves several areas of scientific expertise such as Soil Mechanics, Hydrodynamics, Offshore...
Offshore wind power is nowadays the most promising marine renewable energy. In the North Sea, several wind farms have been constructed near the coastline. However the most interesting resource is located far from the coasts; where the wind is purely offshore wind, where turbulence and environmental impact are less important and winds are high and therefore more profitable. But working further from...
In this work, we make use of two wave databases, satellite measurements and numerical modeling, to develop a methodology to obtain reliable estimates of the spatial and temporal variability of global wave energy resources. As a result, the global distribution of wave energy resources has been evaluated (since 1948) at a global scale analyzing its variability in time (within seasons and months) and...
We present a simple and elegant method to incorporate user input in a template-based segmentation method for diseased organs. The user provides a partial segmentation of the organ of interest, which is used to guide the template towards its target. The user also highlights some elements of the background that should be excluded from the final segmentation. We derive by likelihood maximization a registration...
This paper presents some research results which assesses the problem of query expansion in search activities. We propose the use of domain ontologies, linguistic processing and validation based on a general dictionary. The work is focused on Learning Object's search in specialized repositories. It includes a review of query expansion methods that can be used in e-learning and a description of a prototype...
In this paper we propose a method for classifying the vegetation types in an aerial color infra-red (CIR) image. Different vegetation types do not only differ in color, but also in texture. We study the use of four Haralick features (energy, contrast, entropy, homogeneity) for texture analysis, and then perform the classification using the one-against-all (OAA) multi-class support vector machine (SVM),...
Many techniques have been proposed to segment organs from images, however the segmentation of diseased organs remains challenging and frequently requires lots of user interaction. The challenge consists of segmenting an organ while its appearance and its shape vary due to the presence of the disease in addition to individual variations. We propose a template registration technique that can be used...
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