Summary characteristics for multivariate function-valued spatial point process attributes

Prompted by modern technologies in data acquisition, the statistical analysis of spatially distributed function-valued quantities has attracted a lot of attention in recent years. In particular, combinations of functional variables and spatial point processes yield a highly challenging instance of such modern spatial data applications. Indeed, the analysis of spatial random point configurations, where the point attributes themselves are functions rather than scalar-valued quantities, is just in its infancy, and extensions to function-valued quantities still remain limited. In this view, we extend current existing first- and second-order summary characteristics for real-valued point attributes to the case where in addition to every spatial point location a set of distinct function-valued quantities are available. Providing a flexible treatment of more complex point process scenarios, we build a framework to consider points with multivariate function-valued marks, and develop sets of different cross-function (cross-type and also multi-function cross-type) versions of summary characteristics that allow for the analysis of highly demanding modern spatial point process scenarios. We consider estimators of the theoretical tools and analyse their behaviour through a simulation study and two real data applications.Comment: submitted for publicatio

Directional analysis for point patterns on linear networks

Statistical analysis of point processes often assumes that the underlying process is isotropic in the sense that its distribution is invariant under rotation. For point processes on R-2, some tests based on the K-function and nearest neighbour orientation function have been proposed to check such an assumption. However, anisotropy and directional analysis need proper caution when dealing with point processes on linear networks, as the implicit geometry of the network forces particular directions that the points of the pattern have to necessarily meet. In this paper, we adapt such tests to the case of linear networks and discuss how to use them to detect particular directional preferences, even at some angles that are different from the main angles imposed by the network. Through a simulation study, we check the performance of our proposals under different settings, over a linear network and a dendrite tree, showing that they are able to precisely detect the directional preferences of the points in the pattern, regardless the type of spatial interaction and the geometry of the network. We use our tests to highlight the directional preferences in the spatial distribution of traffic accidents in Barcelona (Spain), during 2019, and in Medellin (Colombia), during 2016.Generalitat Valenciana, Grant/Award Number: AICO/2019/198; Spanish Ministry of Science, Grant/Award Number: MTM2017-86767-R and PID2019-107392RB-I00; Universitat Jaume I, Grant/Award Number: UJI-B2018-0

INFOPràcticum: i després del grau, què?

Podeu consultar la Vuitena trobada de professorat de Ciències de la Salut completa a: http://hdl.handle.net/2445/66524L'INFOPràcticum és una jornada en que s'organitzen un conjunt d'activitats (xerrades, taula rodona, presentació de pòsters sobre les pràctiques realitzades, etc.), pensades per orientar a l'alumnat de 4t. curs sobre les sortides professionals, i les possibilitats que té de seguir-se formant a l'INEFC. És també el moment en que l'alumnat de 4t. de grau..

The Framework of a Life Support Simulation Application

AbstractIn this paper we present the framework of a LIfe Support Simulation Application (LISSA) designed to teach and learn cardiopulmonary resuscitation (CPR) skills. DLISSA exploits video game technology to link in a single framework computer-based simulations of CPR emergencies with the functionalities of e-learning platforms. DEmergency situations are presented as problems that the learner has to solve in a game mode. Learner actions are registered in a database. DThis information is used to present new problems to the learner in an adaptive learning mode.DLISSA can be used as a substitute or a complement for traditional CPR classroom-based instruction Dor to refresh and improve CPR skill retention over time

Statistical modelling of CSP solving algorithms performance

The goal of this work is to try to create a statistical model, based only on easily computable parameters from the CSP problem to predict runtime behaviour of the solving algorithms, and let us choose the best algorithm to solve the problem. Although it seems that the obvious choice should be MAC, experimental results obtained so far show, that with big numbers of variables, other algorithms perfom much better, specially for hard problems in the transition phase