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Far-field perfect imaging with time-modulated gratings
(American Physical Society, 2022-06-22)
We study the capabilities of time-modulated diffraction gratings as imaging devices. It is shown that a time-dependent but transversally homogeneous slab can be used to make a perfect image of an object in the far-field, ...
Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes
(MDPI, 2021-08-31)
The doubly stochastic mechanism generating the realizations of spatial log-Gaussian
Cox processes is empirically assessed in terms of generalized entropy, divergence and complexity
measures. The aim is to characterize ...
A set of deep learning algorithms for air quality prediction applications
(Elsevier, 2023)
This paper presents a set of machine learning algorithms, including grid-based (Bidirectional Convolutional Long Short-Term Memory) and graph-based (Attention Temporal Graph Convolutional Network) algorithms to predict air ...
Modulating the Gameplay Challenge Through Simple Visual Computing Elements: A Cube Puzzle Case Study
(UNIR - Universidad Internacional de La Rioja, 2022-05-02)
Positive player’s experiences greatly rely on a balanced gameplay where the game difficulty is related to player’s
skill. Towards this goal, the gameplay can be modulated to make it easier or harder. In this work, a ...
Introducción a los conceptos del pensamiento computacional en educación infantil y primaria con programación tangible
(Asociación de Enseñantes Universitarios de la Informática (AENUI), 2023-07-05)
El programa Sucre tiene como objetivo el fomento del
pensamiento computacional y la programación en cada
etapa educativa. Tras una reestructuración del programa,
la iniciativa Sucre4Kids se reorienta a la educación
infantil ...
Transfer Deep Learning for Remote Sensing Datasets: A Comparison Study
(IEEE, 2022-07-17)
Remote sensing is also benefiting from the quick development of deep learning algorithms for image analysis and classification tasks. In this paper, we evaluate the classification performance of a well-known Convolutional ...
A stochastic Bayesian bootstrapping model for COVID-19 data
(Springer, 2022-01-11)
We provide a stochastic modeling framework for the incidence of COVID-19 in Castilla-Leon (Spain) for the period March 1, 2020 to February 12, 2021, which encompasses four waves. Each wave is appropriately described by a ...
A spatial randomness test based on the box-counting dimension
(Springer, 2022)
Statistical modelling of a spatial point pattern often begins by testing the hypothesis of spatial randomness. Classical tests are based on quadrat counts and distance-based methods. Alternatively, we propose a new statistical ...
A Spatially Correlated Model with Generalized Autoregressive Conditionally Heteroskedastic Structure for Counts of Crimes
(MDPI, 2022-06-29)
Crime is a negative phenomenon that affects the daily life of the population and its development. When modeling crime data, assumptions on either the spatial or the temporal relationship between observations are necessary ...
Time-expanded φOTDR using low-frequency electronics
(Optica Publishing Group, 2023-01)
Time expanded phase-sensitive optical time-domain reflectometry (TE-φOTDR) is a
recently reported technique for distributed optical fiber sensing based on the interference of two
mutually coherent optical frequency combs. ...