Search results for "PC"
showing 10 items of 2805 documents
Long gaps in multivariate spatio-temporal data: an approach based on functional data analysis
2015
The main aim of this paper is to perform Functional Principal Component Analysis (FPCA) taking into account spatio-temporal correlation structures, in order to fill in missing values in spatio-temporal multivariate data set. A spatial and a spatio-temporal variant of the classical temporal FPCA is considered; in other words, FPCA is carried out after modeling data with respect to more than one dimension: space (long, lat) or space+time. Moreover, multidimensional FPCA is extended to multivariate context (more than one variable). Information on spatial or spatiotemporal structures are efficiently extracted by applying Generalized Additive Models (GAMs). Both simulation studies and some perfo…
Methods for Determining the Thermal Transfer in Phase-Changing Materials (PCMs).
2020
A very important issue that needs to be solved as simply and correctly as possible is how to establish the thermal performance of phase-changing materials (PCM). The undertaken researches have analyzed the values of the thermal performances of the PCM taking into account the method of finite elements and the experimental research, respectively, based on a modern measurement system that was designed and implemented. Butyl stearate which has been encapsulated through complex coacervation in polymethyl methacrylate has been used as a PCM. Samples were made containing 10%, 20%, 30% and 40% PCM, respectively, within their structure. The research has established that at both the hot plate and the…
Search for relativistic magnetic monopoles with the ANTARES neutrino telescope
2012
Magnetic monopoles are predicted in various unified gauge models and could be produced at intermediate mass scales. Their detection in a neutrino telescope is facilitated by the large amount of light emitted compared to that from muons. This paper reports on a search for upgoing relativistic magnetic monopoles with the ANTARES neutrino telescope using a data set of 116 days of live time taken from December 2007 to December 2008. The one observed event is consistent with the expected atmospheric neutrino and muon background, leading to a 90% C.L. upper limit on the monopole flux between 1.3 ¿ 10¿17 and 8.9 ¿ 10¿17 cm¿2 s¿1 sr¿1 for monopoles with velocity ß ¿ 0.625.
Bayesian classification for dating archaeological sites via projectile points
2021
Dating is a key element for archaeologists. We propose a Bayesian approach to provide chronology to sites that have neither radiocarbon dating nor clear stratigraphy and whose only information comes from lithic arrowheads. This classifier is based on the Dirichlet-multinomial inferential process and posterior predictive distributions. The procedure is applied to predict the period of a set of undated sites located in the east of the Iberian Peninsula during the IVth and IIIrd millennium cal. BC.
Lieb polariton topological insulators
2018
We predict that the interplay between the spin-orbit coupling, stemming from the TE-TM energy splitting, and the Zeeman effect in semiconductor microcavities supporting exci- ton-polariton quasi-particles results in the appearance of unidirectional linear topological edge states when the top microcavity mirror is patterned to form a truncated dislocated Lieb lattice of cylindrical pillars. Periodic nonlinear edge states are found to emerge from the linear ones. They are strongly localized across the interface and they are remarkably robust in comparison to their counterparts in hexagonal lattices. Such robustness makes possible the existence of nested unidirectional dark solitons that move …
Clustering of waveforms-data based on FPCA direction
2010
The necessity of nding similar features of waveforms data recorded for earthquakes at di erent time instants is here considered, since eventual similarity between these functions could suggest similar behavior of the source process of the corresponding earthquakes. In this paper we develop a clustering algorithm for curves based on directions de ned by an application of PCA to functional data.
Clustering of waveforms based on FPCA direction
2010
Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). Waveforms correlation techniques have been introduced to charac- terize the degree of seismic event similarity (Menke, 1999) and in facilitating more accurate relative locations within similar event clusters by providing more precise timing of seismic wave (P and S) arrivals (Phillips, 1997). In this paper functional analysis (Ramsey, and Silverman, 2006) is considered to highlight common characteristics of waveforms-data and to summarize these charac- teristics by few components, by applying a variant of a classical clust…
Space-time FPCA Algorithm for clustering of multidimensional curves.
2016
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.
Functional Principal components direction to cluster earthquake waveforms
2010
Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). In this paper we combine the aim of finding clusters from a set of individual curves to the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. We apply a classical clustering method to rotated data, according to the direction of maximum variance. A k-means clustering algorithm based on PCA rotation of data is proposed, as an alternative to methods that require previous interpolation of data based on splines or linear fitting (Garc´ıa- Escudero and Gordali…
FPCA Algorithm For Waveform Clustering
2011
Similar features between waveform data recorded for earthquakes at different time instants could suggest similar behavior of the source process of the corresponding source seismic process. In this paper we combine the aim of finding clusters from a set of individual waveform curves with the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. This approach overcome the limitation of the cross-correlation, and represents an alternative to methods based on the interpolation of data by splines or linear fitting.