Room geometry estimation from stereo recordings using neural networks

Acoustic room geometry estimation is often performed in ad hoc settings, i.e., using multiple microphones and sources distributed around the room, or assuming control over the excitation signals. To facilitate practical applications, we propose a fully convolutional network (FCN) that localizes reflective surfaces under the relaxed assumptions that (i) a compact array of only two microphones is available, (ii) emitter and receivers are not synchronized, and (iii), both the excitation signals and the impulse responses of the enclosures are unknown.Our FCN is designed to extract spectral and temporal patterns from stereo recordings, aggregate the temporal information over time-frames, and predict the likelihood of virtual sources corresponding to reflective surfaces at specific locations. Whereas most source localization algorithms are limited to direction-of-arrival (DOA) estimation, the proposed method jointly estimates distances and DOAs. Numerical experiments confirm that the network is able to generalize to mismatched microphone array sizes, sensor directivity patterns, or audio signal types, while highlighting front-back ambiguity as a prominent source of uncertainty. When a single reflective surface is present, up to 80% of the sources are detected, while this figure approaches 50% in rectangular rooms.Further tests on real-world recordings report similar accuracy as with artificially reverberated speech signals, validating the generalization capabilities of the framework.Electrical Engineering | Circuits and System

An Integrated Model for Supporting Aware Decisions of Companies in a Circular and Sustainable Economy Transition

The world of business is rapidly changing, not only thanks to digitization and technological transformation, but also to address challenges related to the environment and climate change, and to reduce its impact in terms of waste, emissions, and raw materials. The COVID-19 crisis and the European Green New Deal have also accelerated this transformation process. In this context, companies must be able to evaluate their commitment and contribution to sustainable development, and to adopt lower impact business models. To achieve this aim, companies need easy and accessible measurement tools. The tools currently available are based on quantitative or statistical approaches and require the process of large amounts of data. This approach is easily accessible to large companies, while small companies or craft businesses may be scared off, as they may lack the structures and expertise. This study fills this gap by presenting an innovative and easy-to-access methodology for assessing sustainability in companies. Through a qualitative assessment of interdependence among nine categories grouping multiple environmental, social, and governance indicators, companies can evaluate their impact on the 17 SDGs and on the 3 ESG dimensions. The result can be used by the companies to design strategies for their businesses and plan future actions to improve circular models, thanks to the awareness and benefits gained from the analysis. The methodology has been applied to the case study of Ohoskin © 2021

De aeterna dei praedestinatione et reprobatione sententia Don Ioannis à Bononia...

Colofón en v. de 2E5Sign.: [calderón]6, A-Z6, 2A-2E6Portada con grab. xil. de escudo imperial y escudo xil. del autor en v. de ultima páginaErrores de pag.: repetidas las pags. 36 y 91 y salto de la 187 a la 189Ex-libris ms. en port.: "Es del Mº de la Compañía de Jesús de san Ambrosio de Valladolid, de la libreria"Enc. renacentista con restos de brochesAnt. sign.: 06894 en etiqueta impresa de la Biblioteca Universitaria en contraguarda anterio