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In response to the coronavirus disease (COVID-19) pandemic, public health scientists have produced a large and rapidly expanding body of literature that aims to answer critical questions, such as the proportion of the population in a geographic area that h ...
Efficiency is one of the key performance indexes in the design of electric motors. When considering fully active magnetic bearing machines, this aspect gain further relevance due to the necessity of actively controlling all the remaining degrees of freedom ...
Two low CO2 cement systems are investigated: one made with the use of supplementary cementitious materi-als (SCMs) (metakaolin and limestone) and the other an alternative binder, calcium sulfoaluminate cement (CSA). These two low CO2 cements contain a simi ...
Electronic-structure calculations based on hybrid functionals have emerged as a standard technique used in physics, chemistry, and material science.
Despite this success, hybrid functionals have the drawback of containing undetermined parameters.
To overc ...
The purpose of this paper is to consider a number of valuable architectural accomplishments from the beginning of the XX century, built in Vienna (1919-1933) and Frankfurt am Main (1925-1931), by means of Aldo Rossi’s theoretical thought and analytical app ...
Oscillator system (1) comprising:- a substantially planar frame (3);- a first sub-oscillator (5), a second sub-oscillator (7), a third sub-oscillator (9), and a fourth sub-oscillator (11), each sub-oscillator (5, 7, 9, 11) comprising a substantially rigid ...
This thesis focuses on developing efficient algorithmic tools for processing large datasets. In many modern data analysis tasks, the sheer volume of available datasets far outstrips our abilities to process them. This scenario commonly arises in tasks incl ...
The “Multivariate Ring Learning with Errors” problem was presented as a generalization of Ring Learning with Errors (RLWE), introducing efficiency improvements with respect to the RLWE counterpart thanks to its multivariate structure. Nevertheless, the rec ...
Speech-based degree of sleepiness estimation is an emerging research problem. This paper investigates an end-to-end approach, where given raw waveform as input, a convolutional neural network (CNN) estimates at its output the degree of sleepiness. Within t ...
Kernel methods are fundamental tools in machine learning that allow detection of non-linear dependencies between data without explicitly constructing feature vectors in high dimensional spaces. A major disadvantage of kernel methods is their poor scalabili ...