About this publication: What is the correlation among the creative industries, creative industry policies, new media paradigms and capitalism as colonial relations of dominance? What is the role of these industries in the prioritization of the interests of capital at the expense of those of society and how can these paradigms be criticized in the context of the actual, neoliberal, flexible regime of reproduction of capital? To what measure is this regime ‘flexible’ and to what measure it is just an extension of rigid, feudal and racial logics that underline (post)modern representational discourses? To what measure do the concepts of creativity, transparency, openness and flexibility conceal the hegemonic nature of modern hierarchies of exploitation?This publication brings together six essays that offer a critique of the relationship between the creative industries and capital. It treats ‘the networked world’ — its democracies, cognitivities, its attention and its paradigmatic cultural discourses — as one of the domains wherein and by which capitalism and its colonial relations of dominance are being reproduced, reorganized, perpetuated and ‘modernized’.The Gray Zones of Creativity and Capital (eds. Gordana Nikolić and Šefik Tatlić) consists of works from a diverse range of authors from around the globe: Jonathan Beller, Josephine Berry Slater, Marc James Léger, Ana Vilenica, Sandi Abram & Irmgard Emmelheinz. The book first appeared in Serbian in 2015.
MULTIFILE
As every new generation of civil aircraft creates more on-wing data and fleets gradually become more connected with the ground, an increased number of opportunities can be identified for more effective Maintenance, Repair and Overhaul (MRO) operations. Data are becoming a valuable asset for aircraft operators. Sensors measure and record thousands of parameters in increased sampling rates. However, data do not serve any purpose per se. It is the analysis that unleashes their value. Data analytics methods can be simple, making use of visualizations, or more complex, with the use of sophisticated statistics and Artificial Intelligence algorithms. Every problem needs to be approached with the most suitable and less complex method. In MRO operations, two major categories of on-wing data analytics problems can be identified. The first one requires the identification of patterns, which enable the classification and optimization of different maintenance and overhaul processes. The second category of problems requires the identification of rare events, such as the unexpected failure of parts. This cluster of problems relies on the detection of meaningful outliers in large data sets. Different Machine Learning methods can be suggested here, such as Isolation Forest and Logistic Regression. In general, the use of data analytics for maintenance or failure prediction is a scientific field with a great potentiality. Due to its complex nature, the opportunities for aviation Data Analytics in MRO operations are numerous. As MRO services focus increasingly in long term contracts, maintenance organizations with the right forecasting methods will have an advantage. Data accessibility and data quality are two key-factors. At the same time, numerous technical developments related to data transfer and data processing can be promising for the future.
