Statistical properties of acoustic emission signals from metal cutting processes

Acoustic Emission (AE) data from single point turning machining are analysed in this paper in order to gain a greater insight of the signal statistical properties for Tool Condition Monitoring (TCM) applications. A statistical analysis of the time series data amplitude and root mean square (RMS) value at various tool wear levels are performed, �nding that ageing features can be revealed in all cases from the observed experimental histograms. In particular, AE data amplitudes are shown to be distributed with a power-law behaviour above a cross-over value. An analytic model for the RMS values probability density function (pdf) is obtained resorting to the Jaynes' maximum entropy principle (MEp); novel technique of constraining the modelling function under few fractional moments, instead of a greater amount of ordinary moments, leads to well-tailored functions for experimental histograms.Comment: 16 pages, 7 figure

The moral technical imaginaries of internet convergence in an American television network

How emergent technologies are imagined, discussed, and implemented reveals social morality about how society, politics, and economics should be organized. For the television industry in the United States, for instance, the development of internet “convergence” provoked the rise of a new discourse about participatory democracy as well as the hopes for lucrative business opportunities. The simultaneity of technical, moral, and social ordering defines the “moral technical imaginary.” Populating this concept with ethnographic and historical detail, this article expands the theory of the moral technical imaginary with information from six years of participant observation, interviews, and employment with Current TV, an American-based television news network founded by Vice President Al Gore to democratize television production. This chapter explores the limits of political participation and morality when faced with neoliberal capitalism