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This work investigates computational musicology for the study of tape music works tackling the problems concerning stemmatics. These philological problems have been analyzed with an innovative approach considering the peculiarities of audio tape recordings. The paper presents a phylogenetic reconstruction strategy that relies on digitizing the analyzed tapes and the converting each audio track into a two-dimensional spectrogram. This conversion allows adopting a set of computer vision tools to align and equalize different tracks in order to infer the most likely transformation that converts one track into another. In the presented approach, the main editing techniques, intentional and unintentional alterations and different configurations of a tape recorded are estimated in phylogeny analysis. The proposed solution presents a satisfying robustness to the adoption of the wrong reading setup together with a good reconstruction accuracy of the phylogenetic tree. The reconstructed dependencies proved to be correct or plausible in 90% of the experimental cases. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) applications play a relevant role in today's industry in sharing diagnostic data with off-site service teams, as well as in enabling reliable predictive maintenance systems. Several interventions scenarios, however, require the physical presence of a human operator: Augmented Reality (AR), together with a broad-band connection, represents a major opportunity to integrate diagnostic data with real-time in-situ acquisitions. Diagnostic information can be shared with remote specialists that are able to monitor and guide maintenance operations from a control room as if they were in place. Furthermore, integrating heterogeneous sensors with AR visualization displays could largely improve operators' safety in complex and dangerous industrial plants. In this paper, we present a complete setup for a remote assistive maintenance intervention based on 5G networking and tested at a Vodafone Base Transceiver Station (BTS) within the Vodafone 5G Program. Technicians' safety was improved by means of a lightweight AR Head-Mounted Display (HDM) equipped with a thermal camera and a depth sensor to foresee possible collisions with hot surfaces and dangerous objects, by leveraging the processing power of remote computing paired with the low latency of 5G connection. Field testing confirmed that the proposed approach can be a viable solution for egocentric environment understanding and enables an immersive integration of the obtained augmented data within the real scene. [ABSTRACT FROM AUTHOR]