1,720,991 research outputs found
Ambiente Venezia - Banca di Dati Ambientali su rete internet
No full textURL: http://www.istitutoveneto.it
Nowcasting of urban air pollutants by neural networks
Full text linkThe modelling of urban air quality prediction is a difficult task because: i) the processes are controlled by complex chemical and physical mechanisms; ii) its state is ascertained by measuring too few parameters for a sufficient chemical picture; iii) sampling measurements are generally collected at too few points without consideration of scaling (for example CO is a local phenomenon while O-3 is regional and both are often measured by the same monitoring network); iv) balances of chemical species are often forced to work far from "local equilibria". In order to overcome these problems, Artificial Neural Networks (ANNs) were used here because they are model free and require very little knowledge about the underlying system structure. CO, NO2, and O-3 concentrations at the time (t + Deltat) are variables that depend on their previous concentrations and of other external information, such as meteorological data, solar radiation, chemical precursors or vehicle traffic information. ANNs used in this work were able to explain over 90% of the variability of the pollutant concentrations considered at the next hour (CO, NO2, and O-3) and over 80% of that of the next three-hour O-3 concentration. The forecasting of CO peaks exceeding a given value has been successfully performed by transforming original concentration time series into a probability series and processing the transformed data by an ANN. Sensitivity analysis has provided useful insight into the most important forecasting variables and their relevant links
Towards the recommendation of resources in Coursera
Full text linkTechnology Enhanced Learning (TEL) largely focuses on the retrieval and reuse of educational resources from Web platforms like Coursera. Unfortunately, Coursera does not provide educational metadata of its content. To overcome this limitation, this study proposes a data mining approach for discovering Teaching Contexts (TC) where resources have been delivered in. Such TCs can facilitate the retrieval of resources for the teaching preferences and requirements of teachers
Enhancing categorization of learning resources in the DAtaset of joint educational entities
Full text linkThe DAtaset of Joint Educational Entities (DAJEE) is a repository which hosts more than 20,000 educational resources crawled from the MOOC platform Coursera. The resources are divided per category according to the MOOC categorization on Coursera, which is, however, very shallow. This contribution focuses on a more meaningful categorization of the resources in DAJEE, tailored to their content. To achieve such goal, our approach enriches the resources in DAJEE with semantic entities by applying state-of-the-art semantic techniques. The result is a significant improvement of the categorization of the resources in DAJEE than the previous version
A recommendation module to help teachers build courses through the Moodle Learning Management System
Full text linkIn traditional e-learning, teachers design sets of Learning Objects (LOs) and organize their sequencing; the material implementing the LOs could be either built anew or adopted from elsewhere (e.g. from standard-compliant repositories) and reused. This task is applicable also when the teacher works in a system for personalized e-learning. In this case, the burden actually increases: for instance, the LOs may need adaptation to the system, through additional metadata. This paper presents a module that gives some support to the operations of retrieving, analyzing, and importing LOs from a set of standard Learning Objects Repositories, acting as a recommending system. In particular, it is designed to support the teacher in the phases of (i) retrieval of LOs, through a keyword-based search mechanism applied to the selected repositories; (ii) analysis of the returned LOs, whose information is enriched by a concept of relevance metric, based on both the results of the searching operation and the data related to the previous use of the LOs in the courses managed by the Learning Management System; and (iii) LO importation into the course under construction
Hyperspectral remote sensing of salt marsh vegetation and morphology
No full textsupplement to Annales Geophysica
- …
