¿Potencia sonora? España en los Premios Grammy

Este documento trabajo analiza la presencia de España en los premios Grammy Latino, el principal galardón a los artistas hispanos en EEUU. Siguiendo a sociólogos como Pierre Bourdieu (1993, 2002) y Motti Regev (1993, 2007, 2011), el trabajo se enmarca en la configuración de una sociología de la música popular española como un campo de producción cultural. Como los Grammy Latino premian la producción discográfica, es posible comprender la música popular global como un nuevo campo mundial de producción cultural, cuyos estadios de consagración pueden reflejarse o apoyarse en el reconocimiento de los galardones de la Academia Latina de Grabación

Una sociología del cuerpo del rock

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Políticas y Sociología, Departamento de Sociología V (Teoría Sociológica), leída el 16-01-2015Depto. de Sociología: Metodología y TeoríaFac. de Ciencias Políticas y SociologíaTRUEunpu

El campo sonoro y el oído de la sociología: de la doxa sonora al oído sociológico, o los fundamentos teórico-analíticos para el estudio de la vida sonora

The aim of this article is to introduce the sound field concept through the sociological sounding perspective. Departing from sociology of music, urban ecology or sound studies, I try to introduce sociology’s aural ability as an unavoidable component of the sociological analysis. In a first moment there’s a brief search of this sociological ear/hearing trail and how it developed in the study of the sound field. Finally, I introduce a series of concepts coming from sociology, ethnomusicology or acustic ecology, with which to build a sociological ear/hearing perspective that enables to address the study of the sound field.El objetivo de este artículo es presentar el concepto de campo sonoro a través de la perspectiva sonora sociológica. Partiendo de la sociología de la música, la ecología urbana o los sound studies, se intenta presentar la capacidad auditiva de la sociología como elemento ineludible del análisis sociológico. En una primera parte se hace un breve rastreo de las pistas de este oído sociológico y cómo ha ido desarrollándose en el estudio del campo sonoro. Finalmente, se introducen una serie de conceptos provenientes de la sociología, la etnomusicología o la ecología acústica, con los que construir una mirada o perspectiva del oído sociológico que permita abordar el estudio del campo sonoro

Autonomy, Submission or Sound Hybridization? The Construction of the Aesthetic Canon of the Spanish Pop-Rock

This paper provides an approach to the aesthetic canon of Spanish pop-rock, which is understood as being the musicians, bands and works which have had the most infl uence on this musical genre in Spain. Using Bourdieu?s sociology of art and its application to popular music studies, surveys have been analysed that were carried out by both Spanish music critics and musicians. The hypothesis posed is whether an autochthonous aesthetic canon exists, and whether this is determined by an Anglo- American influence. From lists or rankings published whether in books or in general or specialist magazines, these data were combined to obtain a meta-ranking, which was tested by using certain statistical tests. From this, some characteristics particular to the Spanish aesthetic canon have been obtained, as well as some which are shared with the Englishspeaking canon

¿Autonomía, sumisión o hibridación sonora? La construcción del canon estético del pop-rock español

This paper provides an approach to the aesthetic canon of Spanish pop-rock, which is understood as being the musicians, bands and works which have had the most infl uence on this musical genre in Spain. Using Bourdieu?s sociology of art and its application to popular music studies, surveys have been analysed that were carried out by both Spanish music critics and musicians. The hypothesis posed is whether an autochthonous aesthetic canon exists, and whether this is determined by an Anglo- American influence. From lists or rankings published whether in books or in general or specialist magazines, these data were combined to obtain a meta-ranking, which was tested by using certain statistical tests. From this, some characteristics particular to the Spanish aesthetic canon have been obtained, as well as some which are shared with the Englishspeaking canonEn este trabajo nos acercamos al análisis del canon estético del pop-rock español, entendiendo por este a los músicos, grupos y obras que han tenido más influencia en el género en España. Partiendo de la sociología del arte de Bourdieu, y de su aplicación en los estudios de música popular, hemos analizado las encuestas realizadas entre la crítica musical española, pero también entre los músicos, planteándonos la hipótesis de si existe un canon estético autóctono, o si este está determinado por la influencia anglófona. A partir de los listados o rankings publicados, ya fuese en libros o en revistas generalistas o especializadas, hemos combinado estos datos para obtener un meta-ranking, que hemos contrastado con algunas pruebas estadísticas. De aquí se han obtenido algunos rasgos propios del canon estético español, y algunos compartidos con el canon anglosajó

Imágenes desconocidas : la modernidad en la encrucijada postmoderna

No es casual que los latinoamericanos, desde la dramática diversidad de sus entes constitutivos nos volvamos a preguntar, como en otros momentos de acecho y decisión, no sólo quiénes somos, sino qué estamos siendo o mejor aún qué seremos. ¿Seremos? Por eso, cuando el peligro acecha volvemos también a preguntas fundacionales. ¿desde dónde nos toca reflexionar a los latinoamericanos esta crisis de la modernidad y las ofertas postmodernas?, ¿por qué se discute aquí esto, cómo participamos en esa discusión y cómo nos afecta?, ¿cómo nosotros (si podemos) planteamos nuestras preguntas y nuestras respuestas? Las miradas latinoamericanas pueden ser tan divergentes unas de otras que no lleguen a mirarse nunca, pero también pueden ser tan congruentes como lo son las retinas izquierda y derecha que se miran en un espejo roto. Y quizás en estas imágenes desconocidas, silenciosas y solitarias, por fin el continente y los continentales asumamos la soledad, asumamos que nuestra respuesta no está en otra parte, ni en ilusiones ilustres, ni en fogatas que ya casi se apagaron, sino en nosotros mismos y esto quizás nos ayude a servir mejor los retos de estos tiempos. De la introducción de Fernando Calderó

5G-PPP Technology Board:AI and ML – Enablers for Beyond 5G Networks

This white paper on AI and ML as enablers of beyond 5G (B5G) networks is based on contributions from 5G PPP projects that research, implement and validate 5G and B5G network systems. The white paper introduces the main relevant mechanisms in Artificial Intelligence (AI) and Machine Learning (ML), currently investigated and exploited for 5G and B5G networks. A family of neural networks is presented which are, generally speaking, non-linear statistical data modelling and decision-making tools. They are typically used to model complex relationships between input and output parameters of a system or to find patterns in data. Feed-forward neural networks, deep neural networks, recurrent neural networks, and convolutional neural networks belong to this family. Reinforcement learning is concerned about how intelligent agents must take actions in order to maximize a collective reward, e.g., to improve a property of the system. Deep reinforcement learning combines deep neural networks and has the benefit that is can operate on non-structured data. Hybrid solutions are presented such as combined analytical and machine learning modelling as well as expert knowledge aided machine learning. Finally, other specific methods are presented, such as generative adversarial networks and unsupervised learning and clustering. In the sequel the white paper elaborates on use case and optimisation problems that are being tackled with AI/ML, partitioned in three major areas namely, i) Network Planning, ii) Network Diagnostics/Insights, and iii) Network Optimisation and Control. In Network Planning, attention is given to AI/ML assisted approaches to guide planning solutions. As B5G networks become increasingly complex and multi-dimensional, parallel layers of connectivity are considered a trend towards disaggregated deployments in which a base station is distributed over a set of separate physical network elements which ends up in the growing number of services and network slices that need to be operated. This climbing complexity renders traditional approaches in network planning obsolete and calls for their replacement with automated methods that can use AI/ML to guide planning decisions. In this respect two solutions are discussed, first the network element placement problem is introduced which aims at improvements in the identification of optimum constellation of base stations each located to provide best network performance taking into account various parameters, e.g. coverage, user equipment (UE) density and mobility patterns (estimates), required hardware and cabling, and overall cost. The second problem considered in this regard is the dimensioning considerations for C-RAN clusters, in which employing ML-based algorithms to provide optimal allocation of baseband unit (BBU) functions (to the appropriate servers hosted by the central unit (CU)) to provide the expected gains is addressed. In Network Diagnostics, attention is given to the tools that can autonomously inspect the network state and trigger alarms when necessary. The contributions are divided into network characteristics forecasts solutions, precise user localizations methods, and security incident identification and forecast. The application of AI/ML methods in high-resolution synthesising and efficient forecasting of mobile traffic; QoE inference and QoS improvement by forecasting techniques; service level agreement (SLA) prediction in multi-tenant environments; and complex event recognition and forecasting are among network characteristics forecasts methods discussed. On high-precision user localization, AI-assisted sensor fusion and line-of-sight (LoS)/non-line-of-sight (NLoS) discrimination, and 5G localization based on soft information and sequential autoencoding are introduced. And finally, on forecasting security incidents, after a short introduction on modern attacks in mobile networks, ML-based network traffic inspection and real-time detection of distributed denial-of-service (DDoS) attacks are briefly examined. In regard to the Network Optimisation and Control, attention is given to the different network segments, including radio access, transport/fronthaul (FH)/backhaul (BH), virtualisation infrastructure, end-to-end 5G PPP Technology Board AI/ML for Networks 3 (E2E) network slicing, security, and application functions. Among application of AI/ML in radio access, the slicing in multi-tenant networks, radio resource provisioning and traffic steering, user association, demand-driven power allocation, joint MAC scheduling (across several gNBs), and propagation channel estimation and modelling are discussed. Moreover, these solutions are categorised (based on the application time-scale) into real-time, near-real-time, and non-real-time groups. On transport and FH/BH networks, AI/ML algorithms on triggering path computations, traffic management (using programmable switches), dynamic load balancing, efficient per-flow scheduling, and optimal FH/BH functional splitting are introduced. Moreover, federated learning across MEC and NFV orchestrators, resource allocation for service function chaining, and dynamic resource allocation in NFV infrastructure are among introduced AI/ML applications for virtualisation infrastructure. In the context of E2E slicing, several applications such as automated E2E service assurance, resource reservation (proactively in E2E slice) and resource allocation (jointly with slice-based demand prediction), slice isolation, and slice optimisation are presented. In regard to the network security, the application of AI/ML techniques in responding to the attack incidents are discussed for two cases, i.e. in moving target defence for network slice protection, and in self-protection against app-layer DDoS attacks. And finally, on the AI/ML applications in optimisation of application functions, the dash prefetching optimization and Q-learning applications in federated scenarios are presented.The white paper continues with the discussions on the application of AI/ML in the 5G and B5G network architectures. In this context the AI/ML based solutions pertaining to autonomous slice management, control and orchestration, cross-layer optimisation framework, anomaly detection, and management analytics, as well as aspects in AI/ML-as-a-service in network management and orchestration, and enablement of ML for the verticals' domain are presented. This is followed by topics on management of ML models and functions, namely the ML model lifecycle management, e.g., training, monitoring, evaluation, configuration and interface management of ML models. Furthermore, the white paper investigates the standardisation activities on the enablement of AI/ML in networks, including the definition of network data analytics function (NDAF) by 3GPP, the definition of an architecture that helps address challenges in network automation and optimization using AI and the categories of use cases where AI may benefit network operation and management by ETSI ENI, and finally the O-RAN definition of non-real-time and near-real-time RAN controllers to support ML-based management and intelligent RAN optimisation. Additionally, the white paper identifies the challenges in view of privacy and trust in AI/ML-based networks and potential solutions by introducing privacy preserving mechanisms and the zero-trust management approach are introduced. The availability of reliable data-sets as a crucial prerequisite to efficiency of AI/ML algorithms is discussed and the white paper concludes with a brief overview of AI/ML-based KPI validation and system troubleshooting. In summary the findings of this white paper conclude with the identification of several areas (research and development work) for further attention in order to enhance future network return-on-investment (ROI): (a) building standardized interfaces to access relevant and actionable data, (b) exploring ways of using AI to optimize customer experience, (c) running early trials with new customer segments to identify AI opportunities, (d) examining use of AI and automation for network operations, including planning and optimization, (e) ensuring early adoption of new solutions for AI and automation to facilitate introduction of new use cases, and (f) establish/launch an open repository for network data-sets that can be used for training and benchmarking algorithms by all