University of Córdoba (Spain)

About: University of Córdoba (Spain) is a education organization based out in Cordova, Spain. It is known for research contribution in the topics: Population & Catalysis. The organization has 12006 authors who have published 22998 publications receiving 537842 citations. The organization is also known as: University of Córdoba (Spain) & Universidad de Córdoba.

Data mining in education

Abstract: Applying data mining DM in education is an emerging interdisciplinary research field also known as educational data mining EDM. It is concerned with developing methods for exploring the unique types of data that come from educational environments. Its goal is to better understand how students learn and identify the settings in which they learn to improve educational outcomes and to gain insights into and explain educational phenomena. Educational information systems can store a huge amount of potential data from multiple sources coming in different formats and at different granularity levels. Each particular educational problem has a specific objective with special characteristics that require a different treatment of the mining problem. The issues mean that traditional DM techniques cannot be applied directly to these types of data and problems. As a consequence, the knowledge discovery process has to be adapted and some specific DM techniques are needed. This paper introduces and reviews key milestones and the current state of affairs in the field of EDM, together with specific applications, tools, and future insights. © 2012 Wiley Periodicals, Inc.

Food waste as a valuable resource for the production of chemicals, materials and fuels. Current situation and global perspective

Abstract: Increasing demand for fuels and chemicals, driven by factors including over-population, the threat of global warming and the scarcity of fossil resources, strains our resource system and necessitates the development of sustainable and innovative strategies for the chemical industry. Our society is currently experiencing constraints imposed by our resource system, which drives industry to increase its overall efficiency by improving existing processes or finding new uses for waste. Food supply chain waste emerged as a resource with a significant potential to be employed as a raw material for the production of fuels and chemicals given the abundant volumes globally generated, its contained diversity of functionalised chemical components and the opportunity to be utilised for higher value applications. The present manuscript is aimed to provide a general overview of the current and most innovative uses of food supply chain waste, providing a range of worldwide case-studies from around the globe. These studies will focus on examples illustrating the use of citrus peel, waste cooking oil and cashew shell nut liquid in countries such as China, the UK, Tanzania, Spain, Greece or Morocco. This work emphasises 2nd generation food waste valorisation and re-use strategies for the production of higher value and marketable products rather than conventional food waste processing (incineration for energy recovery, feed or composting) while highlighting issues linked to the use of food waste as a sustainable raw material. The influence of food regulations on food supply chain waste valorisation will also be addressed as well as our society's behavior towards food supply chain waste. “There was no ways of dealing with it that have not been known for thousands of years. These ways are essentially four: dumping it, burning it, converting it into something that can be used again, and minimizing the volume of material goods – future garbage – that is produced in the first place.” William Rathje on waste (1945–2012) – Director of the Tucson Garbage project.

Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms

Abstract: Local Indicators of Spatial Aggregation (LISA) can be used as objectives in a multicriteria framework when highly autocorrelated areas (hot-spots) must be identified and geographically located in complex areas. To do so, a Multi-Objective Evolutionary Algorithm (MOEA) based on SPEA2 (Strength Pareto Evolutionary Algorithm v.2) has been designed to evaluate three different fitness functions (fine-grained strength, the weighted sum of objectives and fuzzy evaluation of weighted objectives) and three LISA methods. MOEA makes it possible to achieve a compromise between spatial econometric methods as it highlights areas where a specific phenomenon shows significantly high autocorrelation. The spatial distribution of financially compromised olive-tree farms in Andalusia (Spain) was selected for analysis and two fuzzy hot-spots were statistically identified and spatially located. Hot-spots can be considered to be spatial fuzzy sets where the spatial units have a membership degree that can also be calculated.

2010 update of the ASAS/EULAR recommendations for the management of ankylosing spondylitis

Abstract: This fi rst up date of the ASAS/EULAR recommendations on the management of anky lo sing spondylitis (AS) is based on the original paper, a systematic review of existing recommendations and the literature since 2005 and the discussion and agreement among 21 international experts, 2 patients and 2 physiotherapists in a meeting in February 2010. Each original bullet point was discussed in de tail and rewor ded if necessary. Decisions on new re com men da tions were made — if necessary after voting. The strength of the recommen dations (SOR) was scored on an 11-point nume rical rating scale after the meeting by email. These recommendations apply to patients of all ages that fulfi ll the modifi ed NY criteria for AS, independent of extra-ar ticu lar manifestations, and they take into ac count all drug and non-drug interventions related to AS. Four overarching principles were introduced, implying that one bullet has been moved to this section. There are now 11 bullet points in clu ding 2 new ones, one related to extra-articular manife sta tions and one to changes in the disease course. With a mean score of 9.1 (range 8-10) the SOR was generally very good.

The impact of agricultural soil erosion on the global carbon cycle

Abstract: Agricultural soil erosion is thought to perturb the global carbon cycle, but estimates of its effect range from a source of 1 petagram per year(-1) to a sink of the same magnitude. By using caesium-137 and carbon inventory measurements from a large-scale survey, we found consistent evidence for an erosion-induced sink of atmospheric carbon equivalent to approximately 26% of the carbon transported by erosion. Based on this relationship, we estimated a global carbon sink of 0.12 (range 0.06 to 0.27) petagrams of carbon per year(-1) resulting from erosion in the world's agricultural landscapes. Our analysis directly challenges the view that agricultural erosion represents an important source or sink for atmospheric CO2.