Browsing MAT_Articles by Title
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A Bayesian machine learning approach for spatio-temporal prediction of COVID-19 cases
Springer (2022)Modeling the spread of infectious diseases in space and time needs to take care of complex dependencies and uncertainties. Machine learning methods, and neural networks, in particular, are useful in modeling this sort of ... -
A Bayesian Spatial Analysis of the Heterogeneity in Human Mobility Changes During the First Wave of the COVID-19 Epidemic in the United States
American Statistician (2021)The spread of COVID-19 in the U.S. prompted nonpharmaceutical interventions which caused a reduction in mobility everywhere, although with large disparities between different counties. Using a Bayesian spatial modeling ... -
A case study of proving by students with different levels of mathematical giftedness
MTRJ (2024)We present a case study of proving by three 12–13-year-old students with different levels of mathematical giftedness. After analysing students’ proofs, we conclude that: there was a relation on the consistency and the ... -
A characterization of a local vector valued Bollobás Theorem
Springer Nature (2021-07-30)In this paper, we are interested in giving two characterizations for the so-called property Lo,o, a local vector valued Bollobás type theorem. We say that (X, Y) has this property whenever given ε>0 and an operador T:X→Y, ... -
A class of polynomial planar vector fields with polynomial first integral
Elsevier (2015-10)We give an algorithm for deciding whether a planar polynomial differential system has a first integral which factorizes as a product of defining polynomials of curves with only one place at infinity. In the affirmative ... -
A classification of the cofinal structures of precompacta
Elsevier (2020-08)We provide a complete classification of the possible cofinal structures of the families of precompact (totally bounded) sets in general metric spaces, and compact sets in general complete metric spaces. Using this ... -
A conditional machine learning classification approach for spatio-temporal risk assessment of crime data
Springer (2023)Crime data analysis is an essential source of information to aid social and political decisions makers regarding the allocation of public security resources. Computer-aided dispatch systems and technological advances in ... -
A coprime action version of a solubility criterion of Deskins
Springer Verlag (2019)Let A and G be finite groups of relatively prime orders and suppose that A acts on G via automorphisms. We demonstrate that if G has a maximal A-invariant subgroup M that is nilpotent and the Sylow 2-subgroup of M has ... -
A countable free closed non-reflexive subgroup of Zc
American Mathematical Society (2017)We prove that the group G = Hom(ZN, Z) of all homomorphisms from the Baer-Specker group ZN to the group Z of integer numbers endowed with the topology of pointwise convergence contains no infinite compact subsets. We ... -
A criterion for a normal subgroup to be hypercentral based on class sizes
Springer (2024)Let G be a finite group and N a normal subgroup of G. We prove that the knowledge of the sizes of the conjugacy classes of G that are contained in N and of their multiplicities provides information of N in relation to the ... -
A Data Science Analysis of Academic Staff Workload Profiles in Spanish Universities: Gender Gap Laid Bare
MDPI (2021-06-25)This paper presents a snapshot of the distribution of time that Spanish academic staff spend on different tasks. We carry out a statistical exploratory study by analyzing the responses provided in a survey of 703 Spanish ... -
A data-driven classification of 3D foot types by archetypal shapes based on landmarks
Costin Daniel Untaroiu (Virginia Tech, USA) (2020-01-30)The taxonomy of foot shapes or other parts of the body is important, especially for design purposes. We propose a methodology based on archetypoid analysis (ADA) that overcomes the weaknesses of previous methodologies used ... -
A deep learning object detection method to improve cluster analysis of two-dimensional data
Springer (2024-02-07)Clustering is an unsupervised machine learning method grouping data samples into clusters of similar objects, used as a system support tool in numerous applications such as banking customers profiling, document retrieval, ... -
A dichotomy property for locally compact groups
Elsevier (2018-08)We extend to metrizable locally compact groups Rosenthal's theorem describing those Banach spaces containing no copy of l1. For that purpose, we transfer to general locally compact groups the notion of interpolation (Io) ... -
A Distance-based Method for Spatial Prediction in the Presence of Trend
Springer (2020-06-01)A new method based on distances for modeling continuous random data in Gaussian random fields is presented. In non-stationary cases in which a trend or drift is present, dealing with information in regionalized mixed ... -
A distance-based model for spatial prediction using radial basis functions
Springer Berlin Heidelberg (2018)In the context of local interpolators, radial basis functions (RBFs) are known to reduce the computational time by using a subset of the data for prediction purposes. In this paper, we propose a new distance-based spatial ... -
A Dynamic Spatio-Temporal Stochastic Modeling Approach of Emergency Calls in an Urban Context
MDPI (2023)Emergency calls are defined by an ever-expanding utilisation of information and sensing technology, leading to extensive volumes of spatio-temporal high-resolution data. The spatial and temporal character of the emergency ... -
A dynamical mathematical model for crime evolution based on a compartmental system with interactions
Taylor & Francis (2024-01-11)We use data on imprisonment in Spain to fit a system of three ordinary differential equations that describes the temporal evolution of three different groups in the country: offenders that are not in prison, offenders that ... -
A family of Markov processes in maximal compact subgroups of a semisimple Lie groups
Elsevier (2017)We propose and define a family of marked point processes in noncompact semisimple Lie groups. We first generate Lévy processes via marked point processes by using jump–diffusion processes. Then we build a family of Markov ... -
A first‐order, ratio‐based nonparametric separability test for spatiotemporal point processes
(2018-02)Testing whether the intensity function of a spatiotemporal point process is sep- arable should be one of the first steps in the analysis of any observed pattern. Under separability, the risk of observing an event at time ...