An accurate knowledge of the sound field distribution inside a room is required to identify and optimally locate corrective measures for room acoustics. However, the spatial recovery of the sound field would result in an impractically high number of microp ...
The Fourier-Galerkin method (in short FFTH) has gained popularity in numerical homogenisation because it can treat problems with a huge number of degrees of freedom. Because the method incorporates the fast Fourier transform (FFT) in the linear solver, it ...
Life cycle interpretation is the fourth and last phase of life cycle assessment (LCA). Being a "pivot" phase linking all other phases and the conclusions and recommendations from an LCA study, it represents a challenging task for practitioners, who miss ha ...
Data from animal-borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have b ...
Information regarding occupant flows inside buildings is beneficial for applications such as thermal-load control, market research and security enhancement. Existing methodologies for occupant tracking involve data-driven techniques that rely either on rad ...
Percolation, in its most general interpretation, refers to the “flow” of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction–diffusion s ...
The legacy of Joseph Fourier in science is vast, especially thanks to the essential tool that the Fourier transform is. The flexibility of this analysis, its computational efficiency and the physical interpretation it offers makes it a cornerstone in many ...
Far from nostalgically celebrate the 90th anniversary of the second CIAM, which indeed opened in October 1929 in Frankfurt, the present issue is intended as collective work, a springboard which aims to widen the debate over housing experiences beyond geogr ...
Biased decision making by machine learning systems is increasingly recognized as an important issue. Recently, techniques have been proposed to learn non-discriminatory classifiers by enforcing constraints in the training phase. Such constraints are either ...
