Music production in times of monopoly : the example of Sweden

For several decades now, Sweden has been successful in the worldwide popular music arena. This article explores how Sweden, as an integral part of the global music industry, has been able to cope with the changed market conditions brought about by regulatory changes and digital technologies. The article reflects on the virtualization of music distribution, the decline of the long‐play album and the ageing popular music audience.

The enemy of music : modeling the behavior of a cultural industry in crisis

The purpose of this explorative study is to contribute to the understanding of current music industry dynamics. The situation is undeniably quite dramatic: Since the turn of the millennium, the global music industry has declined by $ US 6.2 billion in value—a fall of 16.3% in constant dollar terms. IFPI, the trade organization representing the international recording industry, identifies a number of exogenous factors as the main drivers of the downturn. This article suggests that other factors, in addition to those identified by IFPI, may have contributed to the current difficulties. A model is presented which indicates that business strategies which were designed to cope with the challenging business environment have reduced product diversity, damaged profitability, and contributed to the problem they were intended to solve.

The transformation of Sweden from a haven for online pirates to the hope of the digital music industry [Musikbranschens föregångsland]

1974 was the year when the Swedish pop group ABBA won the Eurovision Song Contest in Brighton and when Blue Swede reached number one on the Billboard Hot 100 in the US. Although Swedish pop music gained some international success even prior to 1974, this year is often considered as the beginning of an era in which Swedish pop music had great success around the world. With brands such as ABBA, Europe, Roxette, The Cardigans, Ace of Base, In Flames, Robyn, Avicii, Swedish House Mafia and music producers Stig Andersson, Ola Håkansson, Dag Volle, Max Martin, Andreas Carlsson, Jorgen Elofsson and several others have the myth of the Swedish music miracle kept alive for nearly more than four decades. Swedish music looks to continue reap success around the world, but since the millennium, Sweden's relationship with music has been more focused on relatively controversial Internet-based services for music distribution developed by Swedish entrepreneurs and engineers rather than on successful musicians and composers. This chapter focusses on the music industry in Sweden. The chapter will discuss the development of the Internet services mentioned above and their impact on the production, distribution and consumption of recorded music. Ample space will be given in particular to Spotify, the music service that quickly has fundamentally changed the music industry in Sweden. The chapter will also present how the music industry's three sectors - recorded music, music licensing and live music - interact and evolve in Sweden.

Development of an integrated GIS and land use planning course : impacts of hybrid instructional methods

This study reports an action research undertaken at Queensland University of Technology. It evaluates the effectiveness of the integration of GIS within the substantive domains of an existing land use planning course in 2011. Using student performance, learning experience survey, and questionnaire survey data, it also evaluates the impacts of incorporating hybrid instructional methods (e.g., in-class and online instructional videos) in 2012 and 2013. Results show that: students (re)iterated the importance of GIS in the course justifying the integration; the hybrid methods significantly increased student performance; and unlike replacement, the videos are more suitable as a complement to in-class activity.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Power sharing control with frequency droop in a hybrid microgrid

A microgrid may contain a large number of distributed generators (DGs). These DGs can be either inertial or non-inertial, either dispatchable or non-dispatchable. Moreover, the DGs may operate in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new control algorithm for converter interfaced (dispatchable) DG is proposed which facilitates smooth operation in a hybrid microgrid containing inertial and non-inertial DGs. The control algorithm works satisfactorily even when some of the DGs operate in plug and play mode. The proposed strategy is validated through PSCAD simulation studies.

Is there an app for that? A case study of the potentials and limitations of the participator turn and networked publics for classical music audience engagement

The participatory turn, fuelled by discourses and rhetoric regarding social media, and in the aftermath of the dot.com crash of the early 2000s, enrols to some extent an idea of being able to deploy networks to achieve institutional aims. The arts and cultural sector in the UK, in the face of funding cuts, has been keen to engage with such ideas in order to demonstrate value for money; by improving the efficiency of their operations, improving their respective audience experience and ultimately increasing audience size and engagement. Drawing on a case study compiled via a collaborative research project with a UK-based symphony orchestra (UKSO) we interrogate the potentials of social media engagement for audience development work through participatory media and networked publics. We argue that the literature related to mobile phones and applications (‘apps’) has focused primarily on marketing for engagement where institutional contexts are concerned. In contrast, our analysis elucidates the broader potentials and limitations of social-media-enabled apps for audience development and engagement beyond a marketing paradigm. In the case of UKSO, it appears that the technologically deterministic discourses often associated with institutional enrolment of participatory media and networked publics may not necessarily apply due to classical music culture. More generally, this work raises the contradictory nature of networked publics and argues for increased critical engagement with the concept.

Designing Web 2.0 ePortfolios for music postgraduate study : A practice-led enquiry

This article examines the design of ePortfolios for music postgraduate students utilizing a practice-led design iterative research process. It is suggested that the availability of Web 2.0 technologies such as blogs and social network software potentially provide creative artist with an opportunity to engage in a dialogue about art with artefacts of the artist products and processes present in that discussion. The design process applied Software Development as Research (SoDaR) methodology to simultaneously develop design and pedagogy. The approach to designing ePortfolio systems applied four theoretical protocols to examine the use of digitized artefacts to enable a dynamic and inclusive dialogue around representations of the students work. A negative case analysis identified a disjuncture between university access and control policy, and the relative openness of Web2.0 systems outside the institution that led to the design of an integrated model of ePortfolio.

Residential voltage dip and swell mitigation using Plug-in Hybrid Electric Vehicle in smart grid

Solutions to remedy the voltage disturbances have been mostly suggested only for industrial customers. However, not much research has been done on the impact of the voltage problems on residential facilities. This paper proposes a new method to reduce the effect of voltage dip and swell in smart grids equipped by communication systems. To reach this purpose, a voltage source inverter and the corresponding control system are employed. The behavior of a power system during voltage dip and swell are analyzed. The results demonstrate reasonable improvement in terms of voltage dip and swell mitigation. All simulations are implemented in MATLAB/Simulink environment.

A phase-locked-loop design for the smooth operation of a hybrid microgrid

A microgrid contains both distributed generators (DGs) and loads and can be viewed by a controllable load by utilities. The DGs can be either inertial synchronous generators or non-inertial converter interfaced. Moreover, some of them can come online or go offline in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new phase locked loop (PLL) algorithm is proposed for smooth synchronization of plug and play DGs. A frequency droop for power sharing is used and a pseudo inertia has been introduced to non-inertial DGs in order to match their response with inertial DGs. The proposed strategy is validated through PSCAD simulation studies.

Hybrid multi-channel cooperative spectrum sensing to satisfy channel target

Spectrum sensing of multiple primary user channels is a crucial function in cognitive radio networks. In this paper we propose an optimal, sensing resource allocation algorithm for multi-channel cooperative spectrum sensing. The channel target is implemented as an objective and constraint to ensure a pre-determined number of empty channels are detected for secondary user network operations. Based on primary user traffic parameters, we calculate the minimum number of primary user channels that must be sensed to satisfy the channel target. We implement a hybrid sensing structure by grouping secondary user nodes into clusters and assign each cluster to sense a different primary user channels. We then solve the resource allocation problem to find the optimal sensing configuration and node allocation to minimise sensing duration. Simulation results show that the proposed algorithm requires the shortest sensing duration to achieve the channel target compared to existing studies that require long sensing and cannot guarantee the target.

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K-means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley’s Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.

An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.