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Publications
Publications (35)
At the dawn of a new era of intelligent applications in the music sector, the automatic genre-based classification of music tracks is a paramount task for the development of different services, such as music recommenders. In that sense, current solutions to uncover the genre of a song usually follow a multi-class approach revealing only a single ge...
Purpose
The authors will review the main concepts of graphs, present the implemented algorithm, as well as explain the different techniques applied to the graph, to achieve an efficient execution of the algorithm, both in terms of the use of multiple cores that the authors have available today, and the use of massive data parallelism through the pa...
The music industry is now more complex and competitive than ever before. In recent years, the search for collaborations with other artists has become a common strategy of musicians to maintain their presence in the sector. Besides, existing music streaming services such as Spotify have exposed large data feeds that can be used to develop innovative...
Air temperature records are acquired by networks of weather stations which may be several kilometres apart. In complex topographies the representativeness of a meteorological station may be diminished in relation to a flatter valley, and the nearest station may have no relation to a place located near it. The present study shows a simple method to...
Music listening choices are considered to be a factor capable of measuring people’s emotions. Thanks to the explosion of streaming music applications in recent years, it is possible to describe listening trends of the global population based on emotional features. In this paper we have analysed the most popular songs from 52 countries on Spotify th...
Clustering algorithms are one of the most widely used kernels to generate knowledge from large datasets. These algorithms group a set of data elements (i.e., images, points, patterns, etc.) into clusters to identify patterns or common features of a sample. However, these algorithms are very computationally expensive as they often involve the comput...
La presencia de contaminantes emergentes en aguas es cada vez mayor. Especialmente preocupan los antibióticos, debido a que pueden dar lugar a la aparición de bacterias resistentes, pero también a que dichos antibióticos pueden afectar negativamente a los ecosistemas y a los organismos que los habitan. Los antibióticos empleados para el consumo hum...
The Internet of Things (IoT) is pushing the next economic revolution in which the main players are data and immediacy. IoT is increasingly producing large amounts of data that are now classified as “dark data” because most are created but never analyzed. The efficient analysis of this data deluge is becoming mandatory in order to transform it into...
Portable mid-infrared (MIR) technology is well suited for the provision of detailed and inexpensive information on key soil properties for optimum soil management. This technology requires prior complex multivariate modelling. In this manuscript, we propose an intelligent system approach based on portable MIR spectroscopy data modelled by machine l...
Novel cooperative intelligent transportation systems (ITS) serve as the basis for the provision of a number of services for drivers, occupants, and third parties. The vast amount of information to be collected, especially in vehicle-to-infrastructure (V2I) communication services, requires new algorithms and hardware platforms to cope with real-time...
Air-pollution is one of the main threats for developed societies. According to the World Health Organization (WHO), pollution is the main cause of deaths among children aged under five. Smart cities are called to play a decisive role to improve such pollution by first collecting, in real-time, different parameters such as SO2, NOx, O3, NH3, CO, PM1...
One of the most important problems faced in hydrology is the estimation of flood magnitudes and frequencies in ungauged basins. Hydrological regionalisation is used to transfer information from gauged watersheds to ungauged watersheds. However, to obtain reliable results, the watersheds involved must have a similar hydrological behaviour. In this s...
El presente trabajo ofrece un análisis de las diferentes herramientas de tutorización más frecuentes en los Entornos Virtuales de Aprendizaje. Dicho análisis se basa tanto en las estadísticas de uso obtenidas por los sistemas que soportan dichos entornos como de la valoración que hacen los profesores y estudiantes. En base a dicho análisis descript...
Various methods are used to make the partition of data sets for QSAR development and model validation. In this work we used a fuzzy minimals partitioning and we compare this methodology with another rational partition methods like k-means clustering (KMS) and Minimal Test Set Dissimilarity (MTSD). For the development of QSAR models Ordinary Least S...
The Segura River Basin is one of the most water-stressed basins in Mediterranean Europe. If we add to the actual situation that most climate change projections forecast important decreases in water resource availability in the Mediterranean region, the situation will become totally unsustainable. This study assessed the impact of climate change in...
Spanish / English book.
Apride.es is a free access web-app based on a Doctoral thesis Project from the Catholic University of Murcia, Nursing Department to perfect and validate the APRIDE algorithm (Nursing Diagnoses Prioritization Algorithm). This system is designed to make the nursing assessment process easier through the use of a Standard Asses...
Abstract. ZINC database contains one of the biggest collection of pur- chasable compounds from the web, and it is freely accessible and widely used by tens of thousands of researchers all around the world. Users in the need for filtering compounds with certain molecular properties can use ZINC server for such purpose, being the main limitation that...
Clustering aims to classify different patterns into groups called clusters. Many algorithms for both hard and fuzzy clustering have been developed to deal with exploratory data analysis in many contexts such as image processing, pattern recognition, etc. However, we are witnessing the era of big data computing where computing resources are becoming...
El presente trabajo destaca los elementos más relevantes de los cursos masivos en línea y abiertos (MOOC) como recurso disponible para favorecer el desarrollo económico-social y afianzar los procesos de externalización de la Universidad en su entorno.Los cursos de este tipo ofrecen ventajas entre las que resalta la accesibilidad al conocimiento act...
This paper offers an agent-based mechanism in intelligent environments IE to recommend profiles to users according to their requirements. This mechanism is based on similarity among profiles as well as trust and reputation among agents. Our proposal is employed in an intelligent university campus where there are different activities that require us...
Clustering techniques are based upon a dissimilarity or distance measure between objects and clusters. This paper focuses on the simplex space, whose elements—compositions—are subject to non-negativity and constant-sum constraints. Any data analysis involving compositions should fulfill two main principles: scale invariance and subcompositional coh...
Fuzzy clustering procedures based on the FCM algorithm calculate group membership probabilities or degrees taking into account the distance between objects and group prototypes. This paper seeks to improve the computation of such membership probabilities by a new membership function which also reflects the relative position of an object with respec...
In recent years, fuzzy logic techniques have been successfully applied in geodesy problems, in particular to GPS. The aim of this work is to test a fuzzy-logic method with an enhanced probability function as a tool to provide a reliable criteria for weighting scheme for satellite-laser-ranging (SLR) station observations, seeking to optimize their c...
In fuzzy clustering literature usually the main task is to minimize the distance between the elements of a sample. In the formulation of the objective function some conditions, as a fuzzy partition degree equal to 2, are required to reach results in agreement with what is expected. In this paper we establish a formal framework to a different deduct...
Las técnicas de agrupación difusa trabajan, casi exclusivamente en la literatura existente, en la minimización de las distancias de los elementos de la muestra. La formulación de esta función objetivo se presenta exigiendo condiciones, como el grado difuso de la partición igual a 2, para que los resultados sean acordes con los esperados. En el pres...
In satellite-laser-ranging (SLR) data processing, oftentimes the weighting scheme of station observations is subjective or even quasi-arbitrary, and a somewhat arbitrary cutoff of say, 1m is applied prior to the data processing. This practice leaves something to be decided in terms of making optimal use of the available data. We intend to improve t...
