Categoría: investigación

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

Abstract 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

A graph-based algorithm is proposed for detecting song propagation patterns in Spotify. Nodes are countries and edges reflect the frequent flow of songs across them. The patterns are reflected in cultural components such as language or migration flows. Predictors of song propagation based on the discovered patterns are discussed.   Abstract Nowadays, music streaming services

Mental workload refers to the cognitive or intellectual requirements that a worker is subjected to in a workday. The objective of the present work was to discover the subjective mental workload of nursing staff at Hospital Emergency Units, and its relationship with sociodemographic, work, environmental factors at the workplace, and personality variables. Method: A quantitative,

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

Evolution of global music trends: An exploratory and predictive approach based on Spotify data. An exploratory analysis of worldwide music listening trends is put forward. A drop in the global danceability of songs has occurred since 2020. A predictor to anticipate listening behaviours has been developed. Music listening choices are considered to be a factor

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 computation of expensive

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 humano terminan llegando

Ya está disponible nuestro nueva publicación. Developing an intelligent system for the prediction of soil properties with a portable mid-infrared instrument. Highlights •Different machine learning techniques have been tested to predict soil properties. •The predicted soil properties are TC, TN, CEC, clay, silt and Na+. •The best predictive machine learning technique has been the Gaussian

Estamos de suerte, al final nos han aceptado el artículo que llevamos meses en revisión. Air-Pollution Prediction in Smart Cities through Machine Learning Methods: A Case of Study in Murcia, Spain Abstract: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